Week_03_Python_Libraries(Friday).ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Week_03-Python_Libraries(Friday).ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2o4PI8WQ_jDt"
      },
      "source": [
        "# Week 03: Python libraries"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vtMRjvySFEyS"
      },
      "source": [
        "## Importing a module"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RhgztfkhFNEW"
      },
      "source": [
        "# import the modules\n",
        "\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "%matplotlib inline"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aOlrFGCWKEP5"
      },
      "source": [
        "## Getting started with Numpy\n",
        "\n",
        "The Numpy documentation can be found [here](https://numpy.org/)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pUYnvOuVJ9gO",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e97061c9-e568-4231-c560-fb32b901c6e0"
      },
      "source": [
        "# Create a simple array\n",
        "\n",
        "a = np.array([1,2,3])\n",
        "print('a: ', type(a))\n",
        "\n",
        "b = [1,2,3]\n",
        "print('b: ', type(b))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "a:  <class 'numpy.ndarray'>\n",
            "b:  <class 'list'>\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "s3zA4_97rK5T",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0aeb49ed-02ce-41f2-93a5-697b526552f2"
      },
      "source": [
        "# Creating an array of ones\n",
        "\n",
        "a = np.ones((3,4),dtype=np.int8)\n",
        "print(a)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[1 1 1 1]\n",
            " [1 1 1 1]\n",
            " [1 1 1 1]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NOeg0KTJrLH8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a595f086-45ea-4b7c-f67a-0ffa925b1407"
      },
      "source": [
        "# What if we want a matrix with the same values?\n",
        "\n",
        "a = np.full((3,4),0.63)\n",
        "print(a)\n",
        "\n",
        "b = 0.63*(np.ones((3,4), dtype=np.int8))\n",
        "print(b)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[0.63 0.63 0.63 0.63]\n",
            " [0.63 0.63 0.63 0.63]\n",
            " [0.63 0.63 0.63 0.63]]\n",
            "[[0.63 0.63 0.63 0.63]\n",
            " [0.63 0.63 0.63 0.63]\n",
            " [0.63 0.63 0.63 0.63]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lrxzUPzXrLVQ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b4474a39-27b7-402e-e769-5cb5fb7554cd"
      },
      "source": [
        "# Getting evenly spaced values within the range\n",
        "\n",
        "a = np.arange(10, 40, 5)\n",
        "print(a)\n",
        "\n",
        "print(type(a))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[10 15 20 25 30 35]\n",
            "<class 'numpy.ndarray'>\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0khdnsmkrLq0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e8037c32-27a1-488d-dfbd-06bde3025882"
      },
      "source": [
        "# Creating an evenly spaced array(?)\n",
        "\n",
        "a = np.linspace(10,40,7)\n",
        "print(a)\n",
        "\n",
        "b = np.linspace(0,5/3,6)\n",
        "print(b)\n",
        "\n",
        "# Question: How is it any different from arange?"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[10. 15. 20. 25. 30. 35. 40.]\n",
            "[0.         0.33333333 0.66666667 1.         1.33333333 1.66666667]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ss-1Zs7PrL43",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4e9ebc86-efc7-4c9a-8f2f-83001139e15b"
      },
      "source": [
        "# Generating random numbers\n",
        "\n",
        "a = np.random.rand(2,3)\n",
        "print(a)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[0.879907   0.2777585  0.64162537]\n",
            " [0.12718946 0.41874286 0.7510408 ]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wFJvqalBrMFW",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "93d42f0d-8fec-49ad-f023-79610ce902a6"
      },
      "source": [
        "# Empty?\n",
        "\n",
        "a = np.empty((2,3),dtype=np.float)\n",
        "print(a)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[0.879907   0.2777585  0.64162537]\n",
            " [0.12718946 0.41874286 0.7510408 ]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LbqCIQJHKZAV"
      },
      "source": [
        "## Why Numpy and Pandas over regular Python arrays?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "K9MNb_RDKp9R"
      },
      "source": [
        "### Easier to assign values over a slice of an array\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YJxo9HW6KgLe"
      },
      "source": [
        "# Numpy array\n",
        "\n",
        "a = np.array([1,2,5,7,8])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YytfM9WyK_wk"
      },
      "source": [
        "a[1:3] = -1"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rEvys0o0K6IT",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0133dfda-3077-4d69-cf39-7e9248866df0"
      },
      "source": [
        "a"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 1, -1, -1,  7,  8])"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "O4gMRK2SLGib"
      },
      "source": [
        "# Regular Python array\n",
        "\n",
        "b = [1,2,5,7,8]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "b9GKKynNLLYX",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 166
        },
        "outputId": "ffd7b951-d1b3-415f-ccd4-27e03aa866a3"
      },
      "source": [
        "b[1:3] = -1"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "TypeError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-27-3920840fcec8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mb\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mTypeError\u001b[0m: can only assign an iterable"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9g7JZMYW2tsh",
        "outputId": "939aa87b-46e5-467e-cceb-96e1226c2418"
      },
      "source": [
        "print(type(b))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'list'>\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zv7L5SxFLPvb"
      },
      "source": [
        "### ndarray slices, if modified will modify the original array as well"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PzAHP22QLbBP"
      },
      "source": [
        "# Numpy array slice\n",
        "\n",
        "a = np.array([1,2,5,7,8])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jZZl1iL1LdPX"
      },
      "source": [
        "a_slice = a[1:5]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FZuCY6Mk3K32",
        "outputId": "5a4dacd7-f7ae-4c24-916c-48136bd706b4"
      },
      "source": [
        "a_slice"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([2, 5, 7, 8])"
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0ztpflstLdjO"
      },
      "source": [
        "a_slice[1] = 1000"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LTl454BNLvV2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "62e90b4e-5653-416a-ba7f-a13f56c33a2f"
      },
      "source": [
        "a"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([   1,    2, 1000,    7,    8])"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Idsh6Eq8Ld5O"
      },
      "source": [
        "# Regular python array slice\n",
        "\n",
        "a = [1,2,5,7,8]\n",
        "b = a[1:5]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4UX5ka7a39Xa",
        "outputId": "957b864d-2c18-4490-f913-e0568a477edb"
      },
      "source": [
        "b"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[2, 5, 7, 8]"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6RPrkU5j8_T2"
      },
      "source": [
        "b[1] = 1000"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "V3mqMpoxLe1S",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f5f5abb4-75a9-4dfb-d8b0-b32e4fb6dfb7"
      },
      "source": [
        "print('a: ', a)\n",
        "print('b: ', b)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "a:  [1, 2, 5, 7, 8]\n",
            "b:  [2, 1000, 7, 8]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "u04NpfLKL81H"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fzdmEVvHKQd-"
      },
      "source": [
        "## Understanding Pandas with an Example\n",
        "\n",
        "The Pandas documentation can be found [here](https://pandas.pydata.org/)\n",
        "\n",
        "We will be understanding Pandas with the help of an example"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MsoPgsXaJ4HQ",
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": "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",
              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 111
        },
        "outputId": "c1735334-9131-4668-aa36-dcf385a3b1af"
      },
      "source": [
        "from google.colab import files\n",
        "files.upload()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-af34baba-f927-4c36-92a3-0e3b2392af8a\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-af34baba-f927-4c36-92a3-0e3b2392af8a\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saving pokemon_data.csv to pokemon_data.csv\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'pokemon_data.csv': b\"#,Name,Type 1,Type 2,HP,Attack,Defense,Sp. Atk,Sp. Def,Speed,Generation,Legendary\\n1,Bulbasaur,Grass,Poison,45,49,49,65,65,45,1,FALSE\\n2,Ivysaur,Grass,Poison,60,62,63,80,80,60,1,FALSE\\n3,Venusaur,Grass,Poison,80,82,83,100,100,80,1,FALSE\\n3,VenusaurMega Venusaur,Grass,Poison,80,100,123,122,120,80,1,FALSE\\n4,Charmander,Fire,,39,52,43,60,50,65,1,FALSE\\n5,Charmeleon,Fire,,58,64,58,80,65,80,1,FALSE\\n6,Charizard,Fire,Flying,78,84,78,109,85,100,1,FALSE\\n6,CharizardMega Charizard X,Fire,Dragon,78,130,111,130,85,100,1,FALSE\\n6,CharizardMega Charizard Y,Fire,Flying,78,104,78,159,115,100,1,FALSE\\n7,Squirtle,Water,,44,48,65,50,64,43,1,FALSE\\n8,Wartortle,Water,,59,63,80,65,80,58,1,FALSE\\n9,Blastoise,Water,,79,83,100,85,105,78,1,FALSE\\n9,BlastoiseMega Blastoise,Water,,79,103,120,135,115,78,1,FALSE\\n10,Caterpie,Bug,,45,30,35,20,20,45,1,FALSE\\n11,Metapod,Bug,,50,20,55,25,25,30,1,FALSE\\n12,Butterfree,Bug,Flying,60,45,50,90,80,70,1,FALSE\\n13,Weedle,Bug,Poison,40,35,30,20,20,50,1,FALSE\\n14,Kakuna,Bug,Poison,45,25,50,25,25,35,1,FALSE\\n15,Beedrill,Bug,Poison,65,90,40,45,80,75,1,FALSE\\n15,BeedrillMega Beedrill,Bug,Poison,65,150,40,15,80,145,1,FALSE\\n16,Pidgey,Normal,Flying,40,45,40,35,35,56,1,FALSE\\n17,Pidgeotto,Normal,Flying,63,60,55,50,50,71,1,FALSE\\n18,Pidgeot,Normal,Flying,83,80,75,70,70,101,1,FALSE\\n18,PidgeotMega Pidgeot,Normal,Flying,83,80,80,135,80,121,1,FALSE\\n19,Rattata,Normal,,30,56,35,25,35,72,1,FALSE\\n20,Raticate,Normal,,55,81,60,50,70,97,1,FALSE\\n21,Spearow,Normal,Flying,40,60,30,31,31,70,1,FALSE\\n22,Fearow,Normal,Flying,65,90,65,61,61,100,1,FALSE\\n23,Ekans,Poison,,35,60,44,40,54,55,1,FALSE\\n24,Arbok,Poison,,60,85,69,65,79,80,1,FALSE\\n25,Pikachu,Electric,,35,55,40,50,50,90,1,FALSE\\n26,Raichu,Electric,,60,90,55,90,80,110,1,FALSE\\n27,Sandshrew,Ground,,50,75,85,20,30,40,1,FALSE\\n28,Sandslash,Ground,,75,100,110,45,55,65,1,FALSE\\n29,Nidoran (Female),Poison,,55,47,52,40,40,41,1,FALSE\\n30,Nidorina,Poison,,70,62,67,55,55,56,1,FALSE\\n31,Nidoqueen,Poison,Ground,90,92,87,75,85,76,1,FALSE\\n32,Nidoran (Male),Poison,,46,57,40,40,40,50,1,FALSE\\n33,Nidorino,Poison,,61,72,57,55,55,65,1,FALSE\\n34,Nidoking,Poison,Ground,81,102,77,85,75,85,1,FALSE\\n35,Clefairy,Fairy,,70,45,48,60,65,35,1,FALSE\\n36,Clefable,Fairy,,95,70,73,95,90,60,1,FALSE\\n37,Vulpix,Fire,,38,41,40,50,65,65,1,FALSE\\n38,Ninetales,Fire,,73,76,75,81,100,100,1,FALSE\\n39,Jigglypuff,Normal,Fairy,115,45,20,45,25,20,1,FALSE\\n40,Wigglytuff,Normal,Fairy,140,70,45,85,50,45,1,FALSE\\n41,Zubat,Poison,Flying,40,45,35,30,40,55,1,FALSE\\n42,Golbat,Poison,Flying,75,80,70,65,75,90,1,FALSE\\n43,Oddish,Grass,Poison,45,50,55,75,65,30,1,FALSE\\n44,Gloom,Grass,Poison,60,65,70,85,75,40,1,FALSE\\n45,Vileplume,Grass,Poison,75,80,85,110,90,50,1,FALSE\\n46,Paras,Bug,Grass,35,70,55,45,55,25,1,FALSE\\n47,Parasect,Bug,Grass,60,95,80,60,80,30,1,FALSE\\n48,Venonat,Bug,Poison,60,55,50,40,55,45,1,FALSE\\n49,Venomoth,Bug,Poison,70,65,60,90,75,90,1,FALSE\\n50,Diglett,Ground,,10,55,25,35,45,95,1,FALSE\\n51,Dugtrio,Ground,,35,80,50,50,70,120,1,FALSE\\n52,Meowth,Normal,,40,45,35,40,40,90,1,FALSE\\n53,Persian,Normal,,65,70,60,65,65,115,1,FALSE\\n54,Psyduck,Water,,50,52,48,65,50,55,1,FALSE\\n55,Golduck,Water,,80,82,78,95,80,85,1,FALSE\\n56,Mankey,Fighting,,40,80,35,35,45,70,1,FALSE\\n57,Primeape,Fighting,,65,105,60,60,70,95,1,FALSE\\n58,Growlithe,Fire,,55,70,45,70,50,60,1,FALSE\\n59,Arcanine,Fire,,90,110,80,100,80,95,1,FALSE\\n60,Poliwag,Water,,40,50,40,40,40,90,1,FALSE\\n61,Poliwhirl,Water,,65,65,65,50,50,90,1,FALSE\\n62,Poliwrath,Water,Fighting,90,95,95,70,90,70,1,FALSE\\n63,Abra,Psychic,,25,20,15,105,55,90,1,FALSE\\n64,Kadabra,Psychic,,40,35,30,120,70,105,1,FALSE\\n65,Alakazam,Psychic,,55,50,45,135,95,120,1,FALSE\\n65,AlakazamMega Alakazam,Psychic,,55,50,65,175,95,150,1,FALSE\\n66,Machop,Fighting,,70,80,50,35,35,35,1,FALSE\\n67,Machoke,Fighting,,80,100,70,50,60,45,1,FALSE\\n68,Machamp,Fighting,,90,130,80,65,85,55,1,FALSE\\n69,Bellsprout,Grass,Poison,50,75,35,70,30,40,1,FALSE\\n70,Weepinbell,Grass,Poison,65,90,50,85,45,55,1,FALSE\\n71,Victreebel,Grass,Poison,80,105,65,100,70,70,1,FALSE\\n72,Tentacool,Water,Poison,40,40,35,50,100,70,1,FALSE\\n73,Tentacruel,Water,Poison,80,70,65,80,120,100,1,FALSE\\n74,Geodude,Rock,Ground,40,80,100,30,30,20,1,FALSE\\n75,Graveler,Rock,Ground,55,95,115,45,45,35,1,FALSE\\n76,Golem,Rock,Ground,80,120,130,55,65,45,1,FALSE\\n77,Ponyta,Fire,,50,85,55,65,65,90,1,FALSE\\n78,Rapidash,Fire,,65,100,70,80,80,105,1,FALSE\\n79,Slowpoke,Water,Psychic,90,65,65,40,40,15,1,FALSE\\n80,Slowbro,Water,Psychic,95,75,110,100,80,30,1,FALSE\\n80,SlowbroMega Slowbro,Water,Psychic,95,75,180,130,80,30,1,FALSE\\n81,Magnemite,Electric,Steel,25,35,70,95,55,45,1,FALSE\\n82,Magneton,Electric,Steel,50,60,95,120,70,70,1,FALSE\\n83,Farfetch'd,Normal,Flying,52,65,55,58,62,60,1,FALSE\\n84,Doduo,Normal,Flying,35,85,45,35,35,75,1,FALSE\\n85,Dodrio,Normal,Flying,60,110,70,60,60,100,1,FALSE\\n86,Seel,Water,,65,45,55,45,70,45,1,FALSE\\n87,Dewgong,Water,Ice,90,70,80,70,95,70,1,FALSE\\n88,Grimer,Poison,,80,80,50,40,50,25,1,FALSE\\n89,Muk,Poison,,105,105,75,65,100,50,1,FALSE\\n90,Shellder,Water,,30,65,100,45,25,40,1,FALSE\\n91,Cloyster,Water,Ice,50,95,180,85,45,70,1,FALSE\\n92,Gastly,Ghost,Poison,30,35,30,100,35,80,1,FALSE\\n93,Haunter,Ghost,Poison,45,50,45,115,55,95,1,FALSE\\n94,Gengar,Ghost,Poison,60,65,60,130,75,110,1,FALSE\\n94,GengarMega Gengar,Ghost,Poison,60,65,80,170,95,130,1,FALSE\\n95,Onix,Rock,Ground,35,45,160,30,45,70,1,FALSE\\n96,Drowzee,Psychic,,60,48,45,43,90,42,1,FALSE\\n97,Hypno,Psychic,,85,73,70,73,115,67,1,FALSE\\n98,Krabby,Water,,30,105,90,25,25,50,1,FALSE\\n99,Kingler,Water,,55,130,115,50,50,75,1,FALSE\\n100,Voltorb,Electric,,40,30,50,55,55,100,1,FALSE\\n101,Electrode,Electric,,60,50,70,80,80,140,1,FALSE\\n102,Exeggcute,Grass,Psychic,60,40,80,60,45,40,1,FALSE\\n103,Exeggutor,Grass,Psychic,95,95,85,125,65,55,1,FALSE\\n104,Cubone,Ground,,50,50,95,40,50,35,1,FALSE\\n105,Marowak,Ground,,60,80,110,50,80,45,1,FALSE\\n106,Hitmonlee,Fighting,,50,120,53,35,110,87,1,FALSE\\n107,Hitmonchan,Fighting,,50,105,79,35,110,76,1,FALSE\\n108,Lickitung,Normal,,90,55,75,60,75,30,1,FALSE\\n109,Koffing,Poison,,40,65,95,60,45,35,1,FALSE\\n110,Weezing,Poison,,65,90,120,85,70,60,1,FALSE\\n111,Rhyhorn,Ground,Rock,80,85,95,30,30,25,1,FALSE\\n112,Rhydon,Ground,Rock,105,130,120,45,45,40,1,FALSE\\n113,Chansey,Normal,,250,5,5,35,105,50,1,FALSE\\n114,Tangela,Grass,,65,55,115,100,40,60,1,FALSE\\n115,Kangaskhan,Normal,,105,95,80,40,80,90,1,FALSE\\n115,KangaskhanMega Kangaskhan,Normal,,105,125,100,60,100,100,1,FALSE\\n116,Horsea,Water,,30,40,70,70,25,60,1,FALSE\\n117,Seadra,Water,,55,65,95,95,45,85,1,FALSE\\n118,Goldeen,Water,,45,67,60,35,50,63,1,FALSE\\n119,Seaking,Water,,80,92,65,65,80,68,1,FALSE\\n120,Staryu,Water,,30,45,55,70,55,85,1,FALSE\\n121,Starmie,Water,Psychic,60,75,85,100,85,115,1,FALSE\\n122,Mr. Mime,Psychic,Fairy,40,45,65,100,120,90,1,FALSE\\n123,Scyther,Bug,Flying,70,110,80,55,80,105,1,FALSE\\n124,Jynx,Ice,Psychic,65,50,35,115,95,95,1,FALSE\\n125,Electabuzz,Electric,,65,83,57,95,85,105,1,FALSE\\n126,Magmar,Fire,,65,95,57,100,85,93,1,FALSE\\n127,Pinsir,Bug,,65,125,100,55,70,85,1,FALSE\\n127,PinsirMega Pinsir,Bug,Flying,65,155,120,65,90,105,1,FALSE\\n128,Tauros,Normal,,75,100,95,40,70,110,1,FALSE\\n129,Magikarp,Water,,20,10,55,15,20,80,1,FALSE\\n130,Gyarados,Water,Flying,95,125,79,60,100,81,1,FALSE\\n130,GyaradosMega Gyarados,Water,Dark,95,155,109,70,130,81,1,FALSE\\n131,Lapras,Water,Ice,130,85,80,85,95,60,1,FALSE\\n132,Ditto,Normal,,48,48,48,48,48,48,1,FALSE\\n133,Eevee,Normal,,55,55,50,45,65,55,1,FALSE\\n134,Vaporeon,Water,,130,65,60,110,95,65,1,FALSE\\n135,Jolteon,Electric,,65,65,60,110,95,130,1,FALSE\\n136,Flareon,Fire,,65,130,60,95,110,65,1,FALSE\\n137,Porygon,Normal,,65,60,70,85,75,40,1,FALSE\\n138,Omanyte,Rock,Water,35,40,100,90,55,35,1,FALSE\\n139,Omastar,Rock,Water,70,60,125,115,70,55,1,FALSE\\n140,Kabuto,Rock,Water,30,80,90,55,45,55,1,FALSE\\n141,Kabutops,Rock,Water,60,115,105,65,70,80,1,FALSE\\n142,Aerodactyl,Rock,Flying,80,105,65,60,75,130,1,FALSE\\n142,AerodactylMega Aerodactyl,Rock,Flying,80,135,85,70,95,150,1,FALSE\\n143,Snorlax,Normal,,160,110,65,65,110,30,1,FALSE\\n144,Articuno,Ice,Flying,90,85,100,95,125,85,1,TRUE\\n145,Zapdos,Electric,Flying,90,90,85,125,90,100,1,TRUE\\n146,Moltres,Fire,Flying,90,100,90,125,85,90,1,TRUE\\n147,Dratini,Dragon,,41,64,45,50,50,50,1,FALSE\\n148,Dragonair,Dragon,,61,84,65,70,70,70,1,FALSE\\n149,Dragonite,Dragon,Flying,91,134,95,100,100,80,1,FALSE\\n150,Mewtwo,Psychic,,106,110,90,154,90,130,1,TRUE\\n150,MewtwoMega Mewtwo X,Psychic,Fighting,106,190,100,154,100,130,1,TRUE\\n150,MewtwoMega Mewtwo Y,Psychic,,106,150,70,194,120,140,1,TRUE\\n151,Mew,Psychic,,100,100,100,100,100,100,1,FALSE\\n152,Chikorita,Grass,,45,49,65,49,65,45,2,FALSE\\n153,Bayleef,Grass,,60,62,80,63,80,60,2,FALSE\\n154,Meganium,Grass,,80,82,100,83,100,80,2,FALSE\\n155,Cyndaquil,Fire,,39,52,43,60,50,65,2,FALSE\\n156,Quilava,Fire,,58,64,58,80,65,80,2,FALSE\\n157,Typhlosion,Fire,,78,84,78,109,85,100,2,FALSE\\n158,Totodile,Water,,50,65,64,44,48,43,2,FALSE\\n159,Croconaw,Water,,65,80,80,59,63,58,2,FALSE\\n160,Feraligatr,Water,,85,105,100,79,83,78,2,FALSE\\n161,Sentret,Normal,,35,46,34,35,45,20,2,FALSE\\n162,Furret,Normal,,85,76,64,45,55,90,2,FALSE\\n163,Hoothoot,Normal,Flying,60,30,30,36,56,50,2,FALSE\\n164,Noctowl,Normal,Flying,100,50,50,76,96,70,2,FALSE\\n165,Ledyba,Bug,Flying,40,20,30,40,80,55,2,FALSE\\n166,Ledian,Bug,Flying,55,35,50,55,110,85,2,FALSE\\n167,Spinarak,Bug,Poison,40,60,40,40,40,30,2,FALSE\\n168,Ariados,Bug,Poison,70,90,70,60,60,40,2,FALSE\\n169,Crobat,Poison,Flying,85,90,80,70,80,130,2,FALSE\\n170,Chinchou,Water,Electric,75,38,38,56,56,67,2,FALSE\\n171,Lanturn,Water,Electric,125,58,58,76,76,67,2,FALSE\\n172,Pichu,Electric,,20,40,15,35,35,60,2,FALSE\\n173,Cleffa,Fairy,,50,25,28,45,55,15,2,FALSE\\n174,Igglybuff,Normal,Fairy,90,30,15,40,20,15,2,FALSE\\n175,Togepi,Fairy,,35,20,65,40,65,20,2,FALSE\\n176,Togetic,Fairy,Flying,55,40,85,80,105,40,2,FALSE\\n177,Natu,Psychic,Flying,40,50,45,70,45,70,2,FALSE\\n178,Xatu,Psychic,Flying,65,75,70,95,70,95,2,FALSE\\n179,Mareep,Electric,,55,40,40,65,45,35,2,FALSE\\n180,Flaaffy,Electric,,70,55,55,80,60,45,2,FALSE\\n181,Ampharos,Electric,,90,75,85,115,90,55,2,FALSE\\n181,AmpharosMega Ampharos,Electric,Dragon,90,95,105,165,110,45,2,FALSE\\n182,Bellossom,Grass,,75,80,95,90,100,50,2,FALSE\\n183,Marill,Water,Fairy,70,20,50,20,50,40,2,FALSE\\n184,Azumarill,Water,Fairy,100,50,80,60,80,50,2,FALSE\\n185,Sudowoodo,Rock,,70,100,115,30,65,30,2,FALSE\\n186,Politoed,Water,,90,75,75,90,100,70,2,FALSE\\n187,Hoppip,Grass,Flying,35,35,40,35,55,50,2,FALSE\\n188,Skiploom,Grass,Flying,55,45,50,45,65,80,2,FALSE\\n189,Jumpluff,Grass,Flying,75,55,70,55,95,110,2,FALSE\\n190,Aipom,Normal,,55,70,55,40,55,85,2,FALSE\\n191,Sunkern,Grass,,30,30,30,30,30,30,2,FALSE\\n192,Sunflora,Grass,,75,75,55,105,85,30,2,FALSE\\n193,Yanma,Bug,Flying,65,65,45,75,45,95,2,FALSE\\n194,Wooper,Water,Ground,55,45,45,25,25,15,2,FALSE\\n195,Quagsire,Water,Ground,95,85,85,65,65,35,2,FALSE\\n196,Espeon,Psychic,,65,65,60,130,95,110,2,FALSE\\n197,Umbreon,Dark,,95,65,110,60,130,65,2,FALSE\\n198,Murkrow,Dark,Flying,60,85,42,85,42,91,2,FALSE\\n199,Slowking,Water,Psychic,95,75,80,100,110,30,2,FALSE\\n200,Misdreavus,Ghost,,60,60,60,85,85,85,2,FALSE\\n201,Unown,Psychic,,48,72,48,72,48,48,2,FALSE\\n202,Wobbuffet,Psychic,,190,33,58,33,58,33,2,FALSE\\n203,Girafarig,Normal,Psychic,70,80,65,90,65,85,2,FALSE\\n204,Pineco,Bug,,50,65,90,35,35,15,2,FALSE\\n205,Forretress,Bug,Steel,75,90,140,60,60,40,2,FALSE\\n206,Dunsparce,Normal,,100,70,70,65,65,45,2,FALSE\\n207,Gligar,Ground,Flying,65,75,105,35,65,85,2,FALSE\\n208,Steelix,Steel,Ground,75,85,200,55,65,30,2,FALSE\\n208,SteelixMega Steelix,Steel,Ground,75,125,230,55,95,30,2,FALSE\\n209,Snubbull,Fairy,,60,80,50,40,40,30,2,FALSE\\n210,Granbull,Fairy,,90,120,75,60,60,45,2,FALSE\\n211,Qwilfish,Water,Poison,65,95,75,55,55,85,2,FALSE\\n212,Scizor,Bug,Steel,70,130,100,55,80,65,2,FALSE\\n212,ScizorMega Scizor,Bug,Steel,70,150,140,65,100,75,2,FALSE\\n213,Shuckle,Bug,Rock,20,10,230,10,230,5,2,FALSE\\n214,Heracross,Bug,Fighting,80,125,75,40,95,85,2,FALSE\\n214,HeracrossMega Heracross,Bug,Fighting,80,185,115,40,105,75,2,FALSE\\n215,Sneasel,Dark,Ice,55,95,55,35,75,115,2,FALSE\\n216,Teddiursa,Normal,,60,80,50,50,50,40,2,FALSE\\n217,Ursaring,Normal,,90,130,75,75,75,55,2,FALSE\\n218,Slugma,Fire,,40,40,40,70,40,20,2,FALSE\\n219,Magcargo,Fire,Rock,50,50,120,80,80,30,2,FALSE\\n220,Swinub,Ice,Ground,50,50,40,30,30,50,2,FALSE\\n221,Piloswine,Ice,Ground,100,100,80,60,60,50,2,FALSE\\n222,Corsola,Water,Rock,55,55,85,65,85,35,2,FALSE\\n223,Remoraid,Water,,35,65,35,65,35,65,2,FALSE\\n224,Octillery,Water,,75,105,75,105,75,45,2,FALSE\\n225,Delibird,Ice,Flying,45,55,45,65,45,75,2,FALSE\\n226,Mantine,Water,Flying,65,40,70,80,140,70,2,FALSE\\n227,Skarmory,Steel,Flying,65,80,140,40,70,70,2,FALSE\\n228,Houndour,Dark,Fire,45,60,30,80,50,65,2,FALSE\\n229,Houndoom,Dark,Fire,75,90,50,110,80,95,2,FALSE\\n229,HoundoomMega Houndoom,Dark,Fire,75,90,90,140,90,115,2,FALSE\\n230,Kingdra,Water,Dragon,75,95,95,95,95,85,2,FALSE\\n231,Phanpy,Ground,,90,60,60,40,40,40,2,FALSE\\n232,Donphan,Ground,,90,120,120,60,60,50,2,FALSE\\n233,Porygon2,Normal,,85,80,90,105,95,60,2,FALSE\\n234,Stantler,Normal,,73,95,62,85,65,85,2,FALSE\\n235,Smeargle,Normal,,55,20,35,20,45,75,2,FALSE\\n236,Tyrogue,Fighting,,35,35,35,35,35,35,2,FALSE\\n237,Hitmontop,Fighting,,50,95,95,35,110,70,2,FALSE\\n238,Smoochum,Ice,Psychic,45,30,15,85,65,65,2,FALSE\\n239,Elekid,Electric,,45,63,37,65,55,95,2,FALSE\\n240,Magby,Fire,,45,75,37,70,55,83,2,FALSE\\n241,Miltank,Normal,,95,80,105,40,70,100,2,FALSE\\n242,Blissey,Normal,,255,10,10,75,135,55,2,FALSE\\n243,Raikou,Electric,,90,85,75,115,100,115,2,TRUE\\n244,Entei,Fire,,115,115,85,90,75,100,2,TRUE\\n245,Suicune,Water,,100,75,115,90,115,85,2,TRUE\\n246,Larvitar,Rock,Ground,50,64,50,45,50,41,2,FALSE\\n247,Pupitar,Rock,Ground,70,84,70,65,70,51,2,FALSE\\n248,Tyranitar,Rock,Dark,100,134,110,95,100,61,2,FALSE\\n248,TyranitarMega Tyranitar,Rock,Dark,100,164,150,95,120,71,2,FALSE\\n249,Lugia,Psychic,Flying,106,90,130,90,154,110,2,TRUE\\n250,Ho-oh,Fire,Flying,106,130,90,110,154,90,2,TRUE\\n251,Celebi,Psychic,Grass,100,100,100,100,100,100,2,FALSE\\n252,Treecko,Grass,,40,45,35,65,55,70,3,FALSE\\n253,Grovyle,Grass,,50,65,45,85,65,95,3,FALSE\\n254,Sceptile,Grass,,70,85,65,105,85,120,3,FALSE\\n254,SceptileMega Sceptile,Grass,Dragon,70,110,75,145,85,145,3,FALSE\\n255,Torchic,Fire,,45,60,40,70,50,45,3,FALSE\\n256,Combusken,Fire,Fighting,60,85,60,85,60,55,3,FALSE\\n257,Blaziken,Fire,Fighting,80,120,70,110,70,80,3,FALSE\\n257,BlazikenMega Blaziken,Fire,Fighting,80,160,80,130,80,100,3,FALSE\\n258,Mudkip,Water,,50,70,50,50,50,40,3,FALSE\\n259,Marshtomp,Water,Ground,70,85,70,60,70,50,3,FALSE\\n260,Swampert,Water,Ground,100,110,90,85,90,60,3,FALSE\\n260,SwampertMega Swampert,Water,Ground,100,150,110,95,110,70,3,FALSE\\n261,Poochyena,Dark,,35,55,35,30,30,35,3,FALSE\\n262,Mightyena,Dark,,70,90,70,60,60,70,3,FALSE\\n263,Zigzagoon,Normal,,38,30,41,30,41,60,3,FALSE\\n264,Linoone,Normal,,78,70,61,50,61,100,3,FALSE\\n265,Wurmple,Bug,,45,45,35,20,30,20,3,FALSE\\n266,Silcoon,Bug,,50,35,55,25,25,15,3,FALSE\\n267,Beautifly,Bug,Flying,60,70,50,100,50,65,3,FALSE\\n268,Cascoon,Bug,,50,35,55,25,25,15,3,FALSE\\n269,Dustox,Bug,Poison,60,50,70,50,90,65,3,FALSE\\n270,Lotad,Water,Grass,40,30,30,40,50,30,3,FALSE\\n271,Lombre,Water,Grass,60,50,50,60,70,50,3,FALSE\\n272,Ludicolo,Water,Grass,80,70,70,90,100,70,3,FALSE\\n273,Seedot,Grass,,40,40,50,30,30,30,3,FALSE\\n274,Nuzleaf,Grass,Dark,70,70,40,60,40,60,3,FALSE\\n275,Shiftry,Grass,Dark,90,100,60,90,60,80,3,FALSE\\n276,Taillow,Normal,Flying,40,55,30,30,30,85,3,FALSE\\n277,Swellow,Normal,Flying,60,85,60,50,50,125,3,FALSE\\n278,Wingull,Water,Flying,40,30,30,55,30,85,3,FALSE\\n279,Pelipper,Water,Flying,60,50,100,85,70,65,3,FALSE\\n280,Ralts,Psychic,Fairy,28,25,25,45,35,40,3,FALSE\\n281,Kirlia,Psychic,Fairy,38,35,35,65,55,50,3,FALSE\\n282,Gardevoir,Psychic,Fairy,68,65,65,125,115,80,3,FALSE\\n282,GardevoirMega Gardevoir,Psychic,Fairy,68,85,65,165,135,100,3,FALSE\\n283,Surskit,Bug,Water,40,30,32,50,52,65,3,FALSE\\n284,Masquerain,Bug,Flying,70,60,62,80,82,60,3,FALSE\\n285,Shroomish,Grass,,60,40,60,40,60,35,3,FALSE\\n286,Breloom,Grass,Fighting,60,130,80,60,60,70,3,FALSE\\n287,Slakoth,Normal,,60,60,60,35,35,30,3,FALSE\\n288,Vigoroth,Normal,,80,80,80,55,55,90,3,FALSE\\n289,Slaking,Normal,,150,160,100,95,65,100,3,FALSE\\n290,Nincada,Bug,Ground,31,45,90,30,30,40,3,FALSE\\n291,Ninjask,Bug,Flying,61,90,45,50,50,160,3,FALSE\\n292,Shedinja,Bug,Ghost,1,90,45,30,30,40,3,FALSE\\n293,Whismur,Normal,,64,51,23,51,23,28,3,FALSE\\n294,Loudred,Normal,,84,71,43,71,43,48,3,FALSE\\n295,Exploud,Normal,,104,91,63,91,73,68,3,FALSE\\n296,Makuhita,Fighting,,72,60,30,20,30,25,3,FALSE\\n297,Hariyama,Fighting,,144,120,60,40,60,50,3,FALSE\\n298,Azurill,Normal,Fairy,50,20,40,20,40,20,3,FALSE\\n299,Nosepass,Rock,,30,45,135,45,90,30,3,FALSE\\n300,Skitty,Normal,,50,45,45,35,35,50,3,FALSE\\n301,Delcatty,Normal,,70,65,65,55,55,70,3,FALSE\\n302,Sableye,Dark,Ghost,50,75,75,65,65,50,3,FALSE\\n302,SableyeMega Sableye,Dark,Ghost,50,85,125,85,115,20,3,FALSE\\n303,Mawile,Steel,Fairy,50,85,85,55,55,50,3,FALSE\\n303,MawileMega Mawile,Steel,Fairy,50,105,125,55,95,50,3,FALSE\\n304,Aron,Steel,Rock,50,70,100,40,40,30,3,FALSE\\n305,Lairon,Steel,Rock,60,90,140,50,50,40,3,FALSE\\n306,Aggron,Steel,Rock,70,110,180,60,60,50,3,FALSE\\n306,AggronMega Aggron,Steel,,70,140,230,60,80,50,3,FALSE\\n307,Meditite,Fighting,Psychic,30,40,55,40,55,60,3,FALSE\\n308,Medicham,Fighting,Psychic,60,60,75,60,75,80,3,FALSE\\n308,MedichamMega Medicham,Fighting,Psychic,60,100,85,80,85,100,3,FALSE\\n309,Electrike,Electric,,40,45,40,65,40,65,3,FALSE\\n310,Manectric,Electric,,70,75,60,105,60,105,3,FALSE\\n310,ManectricMega Manectric,Electric,,70,75,80,135,80,135,3,FALSE\\n311,Plusle,Electric,,60,50,40,85,75,95,3,FALSE\\n312,Minun,Electric,,60,40,50,75,85,95,3,FALSE\\n313,Volbeat,Bug,,65,73,55,47,75,85,3,FALSE\\n314,Illumise,Bug,,65,47,55,73,75,85,3,FALSE\\n315,Roselia,Grass,Poison,50,60,45,100,80,65,3,FALSE\\n316,Gulpin,Poison,,70,43,53,43,53,40,3,FALSE\\n317,Swalot,Poison,,100,73,83,73,83,55,3,FALSE\\n318,Carvanha,Water,Dark,45,90,20,65,20,65,3,FALSE\\n319,Sharpedo,Water,Dark,70,120,40,95,40,95,3,FALSE\\n319,SharpedoMega Sharpedo,Water,Dark,70,140,70,110,65,105,3,FALSE\\n320,Wailmer,Water,,130,70,35,70,35,60,3,FALSE\\n321,Wailord,Water,,170,90,45,90,45,60,3,FALSE\\n322,Numel,Fire,Ground,60,60,40,65,45,35,3,FALSE\\n323,Camerupt,Fire,Ground,70,100,70,105,75,40,3,FALSE\\n323,CameruptMega Camerupt,Fire,Ground,70,120,100,145,105,20,3,FALSE\\n324,Torkoal,Fire,,70,85,140,85,70,20,3,FALSE\\n325,Spoink,Psychic,,60,25,35,70,80,60,3,FALSE\\n326,Grumpig,Psychic,,80,45,65,90,110,80,3,FALSE\\n327,Spinda,Normal,,60,60,60,60,60,60,3,FALSE\\n328,Trapinch,Ground,,45,100,45,45,45,10,3,FALSE\\n329,Vibrava,Ground,Dragon,50,70,50,50,50,70,3,FALSE\\n330,Flygon,Ground,Dragon,80,100,80,80,80,100,3,FALSE\\n331,Cacnea,Grass,,50,85,40,85,40,35,3,FALSE\\n332,Cacturne,Grass,Dark,70,115,60,115,60,55,3,FALSE\\n333,Swablu,Normal,Flying,45,40,60,40,75,50,3,FALSE\\n334,Altaria,Dragon,Flying,75,70,90,70,105,80,3,FALSE\\n334,AltariaMega Altaria,Dragon,Fairy,75,110,110,110,105,80,3,FALSE\\n335,Zangoose,Normal,,73,115,60,60,60,90,3,FALSE\\n336,Seviper,Poison,,73,100,60,100,60,65,3,FALSE\\n337,Lunatone,Rock,Psychic,70,55,65,95,85,70,3,FALSE\\n338,Solrock,Rock,Psychic,70,95,85,55,65,70,3,FALSE\\n339,Barboach,Water,Ground,50,48,43,46,41,60,3,FALSE\\n340,Whiscash,Water,Ground,110,78,73,76,71,60,3,FALSE\\n341,Corphish,Water,,43,80,65,50,35,35,3,FALSE\\n342,Crawdaunt,Water,Dark,63,120,85,90,55,55,3,FALSE\\n343,Baltoy,Ground,Psychic,40,40,55,40,70,55,3,FALSE\\n344,Claydol,Ground,Psychic,60,70,105,70,120,75,3,FALSE\\n345,Lileep,Rock,Grass,66,41,77,61,87,23,3,FALSE\\n346,Cradily,Rock,Grass,86,81,97,81,107,43,3,FALSE\\n347,Anorith,Rock,Bug,45,95,50,40,50,75,3,FALSE\\n348,Armaldo,Rock,Bug,75,125,100,70,80,45,3,FALSE\\n349,Feebas,Water,,20,15,20,10,55,80,3,FALSE\\n350,Milotic,Water,,95,60,79,100,125,81,3,FALSE\\n351,Castform,Normal,,70,70,70,70,70,70,3,FALSE\\n352,Kecleon,Normal,,60,90,70,60,120,40,3,FALSE\\n353,Shuppet,Ghost,,44,75,35,63,33,45,3,FALSE\\n354,Banette,Ghost,,64,115,65,83,63,65,3,FALSE\\n354,BanetteMega Banette,Ghost,,64,165,75,93,83,75,3,FALSE\\n355,Duskull,Ghost,,20,40,90,30,90,25,3,FALSE\\n356,Dusclops,Ghost,,40,70,130,60,130,25,3,FALSE\\n357,Tropius,Grass,Flying,99,68,83,72,87,51,3,FALSE\\n358,Chimecho,Psychic,,65,50,70,95,80,65,3,FALSE\\n359,Absol,Dark,,65,130,60,75,60,75,3,FALSE\\n359,AbsolMega Absol,Dark,,65,150,60,115,60,115,3,FALSE\\n360,Wynaut,Psychic,,95,23,48,23,48,23,3,FALSE\\n361,Snorunt,Ice,,50,50,50,50,50,50,3,FALSE\\n362,Glalie,Ice,,80,80,80,80,80,80,3,FALSE\\n362,GlalieMega Glalie,Ice,,80,120,80,120,80,100,3,FALSE\\n363,Spheal,Ice,Water,70,40,50,55,50,25,3,FALSE\\n364,Sealeo,Ice,Water,90,60,70,75,70,45,3,FALSE\\n365,Walrein,Ice,Water,110,80,90,95,90,65,3,FALSE\\n366,Clamperl,Water,,35,64,85,74,55,32,3,FALSE\\n367,Huntail,Water,,55,104,105,94,75,52,3,FALSE\\n368,Gorebyss,Water,,55,84,105,114,75,52,3,FALSE\\n369,Relicanth,Water,Rock,100,90,130,45,65,55,3,FALSE\\n370,Luvdisc,Water,,43,30,55,40,65,97,3,FALSE\\n371,Bagon,Dragon,,45,75,60,40,30,50,3,FALSE\\n372,Shelgon,Dragon,,65,95,100,60,50,50,3,FALSE\\n373,Salamence,Dragon,Flying,95,135,80,110,80,100,3,FALSE\\n373,SalamenceMega Salamence,Dragon,Flying,95,145,130,120,90,120,3,FALSE\\n374,Beldum,Steel,Psychic,40,55,80,35,60,30,3,FALSE\\n375,Metang,Steel,Psychic,60,75,100,55,80,50,3,FALSE\\n376,Metagross,Steel,Psychic,80,135,130,95,90,70,3,FALSE\\n376,MetagrossMega Metagross,Steel,Psychic,80,145,150,105,110,110,3,FALSE\\n377,Regirock,Rock,,80,100,200,50,100,50,3,TRUE\\n378,Regice,Ice,,80,50,100,100,200,50,3,TRUE\\n379,Registeel,Steel,,80,75,150,75,150,50,3,TRUE\\n380,Latias,Dragon,Psychic,80,80,90,110,130,110,3,TRUE\\n380,LatiasMega Latias,Dragon,Psychic,80,100,120,140,150,110,3,TRUE\\n381,Latios,Dragon,Psychic,80,90,80,130,110,110,3,TRUE\\n381,LatiosMega Latios,Dragon,Psychic,80,130,100,160,120,110,3,TRUE\\n382,Kyogre,Water,,100,100,90,150,140,90,3,TRUE\\n382,KyogrePrimal Kyogre,Water,,100,150,90,180,160,90,3,TRUE\\n383,Groudon,Ground,,100,150,140,100,90,90,3,TRUE\\n383,GroudonPrimal Groudon,Ground,Fire,100,180,160,150,90,90,3,TRUE\\n384,Rayquaza,Dragon,Flying,105,150,90,150,90,95,3,TRUE\\n384,RayquazaMega Rayquaza,Dragon,Flying,105,180,100,180,100,115,3,TRUE\\n385,Jirachi,Steel,Psychic,100,100,100,100,100,100,3,TRUE\\n386,DeoxysNormal Forme,Psychic,,50,150,50,150,50,150,3,TRUE\\n386,DeoxysAttack Forme,Psychic,,50,180,20,180,20,150,3,TRUE\\n386,DeoxysDefense Forme,Psychic,,50,70,160,70,160,90,3,TRUE\\n386,DeoxysSpeed Forme,Psychic,,50,95,90,95,90,180,3,TRUE\\n387,Turtwig,Grass,,55,68,64,45,55,31,4,FALSE\\n388,Grotle,Grass,,75,89,85,55,65,36,4,FALSE\\n389,Torterra,Grass,Ground,95,109,105,75,85,56,4,FALSE\\n390,Chimchar,Fire,,44,58,44,58,44,61,4,FALSE\\n391,Monferno,Fire,Fighting,64,78,52,78,52,81,4,FALSE\\n392,Infernape,Fire,Fighting,76,104,71,104,71,108,4,FALSE\\n393,Piplup,Water,,53,51,53,61,56,40,4,FALSE\\n394,Prinplup,Water,,64,66,68,81,76,50,4,FALSE\\n395,Empoleon,Water,Steel,84,86,88,111,101,60,4,FALSE\\n396,Starly,Normal,Flying,40,55,30,30,30,60,4,FALSE\\n397,Staravia,Normal,Flying,55,75,50,40,40,80,4,FALSE\\n398,Staraptor,Normal,Flying,85,120,70,50,60,100,4,FALSE\\n399,Bidoof,Normal,,59,45,40,35,40,31,4,FALSE\\n400,Bibarel,Normal,Water,79,85,60,55,60,71,4,FALSE\\n401,Kricketot,Bug,,37,25,41,25,41,25,4,FALSE\\n402,Kricketune,Bug,,77,85,51,55,51,65,4,FALSE\\n403,Shinx,Electric,,45,65,34,40,34,45,4,FALSE\\n404,Luxio,Electric,,60,85,49,60,49,60,4,FALSE\\n405,Luxray,Electric,,80,120,79,95,79,70,4,FALSE\\n406,Budew,Grass,Poison,40,30,35,50,70,55,4,FALSE\\n407,Roserade,Grass,Poison,60,70,65,125,105,90,4,FALSE\\n408,Cranidos,Rock,,67,125,40,30,30,58,4,FALSE\\n409,Rampardos,Rock,,97,165,60,65,50,58,4,FALSE\\n410,Shieldon,Rock,Steel,30,42,118,42,88,30,4,FALSE\\n411,Bastiodon,Rock,Steel,60,52,168,47,138,30,4,FALSE\\n412,Burmy,Bug,,40,29,45,29,45,36,4,FALSE\\n413,WormadamPlant Cloak,Bug,Grass,60,59,85,79,105,36,4,FALSE\\n413,WormadamSandy Cloak,Bug,Ground,60,79,105,59,85,36,4,FALSE\\n413,WormadamTrash Cloak,Bug,Steel,60,69,95,69,95,36,4,FALSE\\n414,Mothim,Bug,Flying,70,94,50,94,50,66,4,FALSE\\n415,Combee,Bug,Flying,30,30,42,30,42,70,4,FALSE\\n416,Vespiquen,Bug,Flying,70,80,102,80,102,40,4,FALSE\\n417,Pachirisu,Electric,,60,45,70,45,90,95,4,FALSE\\n418,Buizel,Water,,55,65,35,60,30,85,4,FALSE\\n419,Floatzel,Water,,85,105,55,85,50,115,4,FALSE\\n420,Cherubi,Grass,,45,35,45,62,53,35,4,FALSE\\n421,Cherrim,Grass,,70,60,70,87,78,85,4,FALSE\\n422,Shellos,Water,,76,48,48,57,62,34,4,FALSE\\n423,Gastrodon,Water,Ground,111,83,68,92,82,39,4,FALSE\\n424,Ambipom,Normal,,75,100,66,60,66,115,4,FALSE\\n425,Drifloon,Ghost,Flying,90,50,34,60,44,70,4,FALSE\\n426,Drifblim,Ghost,Flying,150,80,44,90,54,80,4,FALSE\\n427,Buneary,Normal,,55,66,44,44,56,85,4,FALSE\\n428,Lopunny,Normal,,65,76,84,54,96,105,4,FALSE\\n428,LopunnyMega Lopunny,Normal,Fighting,65,136,94,54,96,135,4,FALSE\\n429,Mismagius,Ghost,,60,60,60,105,105,105,4,FALSE\\n430,Honchkrow,Dark,Flying,100,125,52,105,52,71,4,FALSE\\n431,Glameow,Normal,,49,55,42,42,37,85,4,FALSE\\n432,Purugly,Normal,,71,82,64,64,59,112,4,FALSE\\n433,Chingling,Psychic,,45,30,50,65,50,45,4,FALSE\\n434,Stunky,Poison,Dark,63,63,47,41,41,74,4,FALSE\\n435,Skuntank,Poison,Dark,103,93,67,71,61,84,4,FALSE\\n436,Bronzor,Steel,Psychic,57,24,86,24,86,23,4,FALSE\\n437,Bronzong,Steel,Psychic,67,89,116,79,116,33,4,FALSE\\n438,Bonsly,Rock,,50,80,95,10,45,10,4,FALSE\\n439,Mime Jr.,Psychic,Fairy,20,25,45,70,90,60,4,FALSE\\n440,Happiny,Normal,,100,5,5,15,65,30,4,FALSE\\n441,Chatot,Normal,Flying,76,65,45,92,42,91,4,FALSE\\n442,Spiritomb,Ghost,Dark,50,92,108,92,108,35,4,FALSE\\n443,Gible,Dragon,Ground,58,70,45,40,45,42,4,FALSE\\n444,Gabite,Dragon,Ground,68,90,65,50,55,82,4,FALSE\\n445,Garchomp,Dragon,Ground,108,130,95,80,85,102,4,FALSE\\n445,GarchompMega Garchomp,Dragon,Ground,108,170,115,120,95,92,4,FALSE\\n446,Munchlax,Normal,,135,85,40,40,85,5,4,FALSE\\n447,Riolu,Fighting,,40,70,40,35,40,60,4,FALSE\\n448,Lucario,Fighting,Steel,70,110,70,115,70,90,4,FALSE\\n448,LucarioMega Lucario,Fighting,Steel,70,145,88,140,70,112,4,FALSE\\n449,Hippopotas,Ground,,68,72,78,38,42,32,4,FALSE\\n450,Hippowdon,Ground,,108,112,118,68,72,47,4,FALSE\\n451,Skorupi,Poison,Bug,40,50,90,30,55,65,4,FALSE\\n452,Drapion,Poison,Dark,70,90,110,60,75,95,4,FALSE\\n453,Croagunk,Poison,Fighting,48,61,40,61,40,50,4,FALSE\\n454,Toxicroak,Poison,Fighting,83,106,65,86,65,85,4,FALSE\\n455,Carnivine,Grass,,74,100,72,90,72,46,4,FALSE\\n456,Finneon,Water,,49,49,56,49,61,66,4,FALSE\\n457,Lumineon,Water,,69,69,76,69,86,91,4,FALSE\\n458,Mantyke,Water,Flying,45,20,50,60,120,50,4,FALSE\\n459,Snover,Grass,Ice,60,62,50,62,60,40,4,FALSE\\n460,Abomasnow,Grass,Ice,90,92,75,92,85,60,4,FALSE\\n460,AbomasnowMega Abomasnow,Grass,Ice,90,132,105,132,105,30,4,FALSE\\n461,Weavile,Dark,Ice,70,120,65,45,85,125,4,FALSE\\n462,Magnezone,Electric,Steel,70,70,115,130,90,60,4,FALSE\\n463,Lickilicky,Normal,,110,85,95,80,95,50,4,FALSE\\n464,Rhyperior,Ground,Rock,115,140,130,55,55,40,4,FALSE\\n465,Tangrowth,Grass,,100,100,125,110,50,50,4,FALSE\\n466,Electivire,Electric,,75,123,67,95,85,95,4,FALSE\\n467,Magmortar,Fire,,75,95,67,125,95,83,4,FALSE\\n468,Togekiss,Fairy,Flying,85,50,95,120,115,80,4,FALSE\\n469,Yanmega,Bug,Flying,86,76,86,116,56,95,4,FALSE\\n470,Leafeon,Grass,,65,110,130,60,65,95,4,FALSE\\n471,Glaceon,Ice,,65,60,110,130,95,65,4,FALSE\\n472,Gliscor,Ground,Flying,75,95,125,45,75,95,4,FALSE\\n473,Mamoswine,Ice,Ground,110,130,80,70,60,80,4,FALSE\\n474,Porygon-Z,Normal,,85,80,70,135,75,90,4,FALSE\\n475,Gallade,Psychic,Fighting,68,125,65,65,115,80,4,FALSE\\n475,GalladeMega Gallade,Psychic,Fighting,68,165,95,65,115,110,4,FALSE\\n476,Probopass,Rock,Steel,60,55,145,75,150,40,4,FALSE\\n477,Dusknoir,Ghost,,45,100,135,65,135,45,4,FALSE\\n478,Froslass,Ice,Ghost,70,80,70,80,70,110,4,FALSE\\n479,Rotom,Electric,Ghost,50,50,77,95,77,91,4,FALSE\\n479,RotomHeat Rotom,Electric,Fire,50,65,107,105,107,86,4,FALSE\\n479,RotomWash Rotom,Electric,Water,50,65,107,105,107,86,4,FALSE\\n479,RotomFrost Rotom,Electric,Ice,50,65,107,105,107,86,4,FALSE\\n479,RotomFan Rotom,Electric,Flying,50,65,107,105,107,86,4,FALSE\\n479,RotomMow Rotom,Electric,Grass,50,65,107,105,107,86,4,FALSE\\n480,Uxie,Psychic,,75,75,130,75,130,95,4,TRUE\\n481,Mesprit,Psychic,,80,105,105,105,105,80,4,TRUE\\n482,Azelf,Psychic,,75,125,70,125,70,115,4,TRUE\\n483,Dialga,Steel,Dragon,100,120,120,150,100,90,4,TRUE\\n484,Palkia,Water,Dragon,90,120,100,150,120,100,4,TRUE\\n485,Heatran,Fire,Steel,91,90,106,130,106,77,4,TRUE\\n486,Regigigas,Normal,,110,160,110,80,110,100,4,TRUE\\n487,GiratinaAltered Forme,Ghost,Dragon,150,100,120,100,120,90,4,TRUE\\n487,GiratinaOrigin Forme,Ghost,Dragon,150,120,100,120,100,90,4,TRUE\\n488,Cresselia,Psychic,,120,70,120,75,130,85,4,FALSE\\n489,Phione,Water,,80,80,80,80,80,80,4,FALSE\\n490,Manaphy,Water,,100,100,100,100,100,100,4,FALSE\\n491,Darkrai,Dark,,70,90,90,135,90,125,4,TRUE\\n492,ShayminLand Forme,Grass,,100,100,100,100,100,100,4,TRUE\\n492,ShayminSky Forme,Grass,Flying,100,103,75,120,75,127,4,TRUE\\n493,Arceus,Normal,,120,120,120,120,120,120,4,TRUE\\n494,Victini,Psychic,Fire,100,100,100,100,100,100,5,TRUE\\n495,Snivy,Grass,,45,45,55,45,55,63,5,FALSE\\n496,Servine,Grass,,60,60,75,60,75,83,5,FALSE\\n497,Serperior,Grass,,75,75,95,75,95,113,5,FALSE\\n498,Tepig,Fire,,65,63,45,45,45,45,5,FALSE\\n499,Pignite,Fire,Fighting,90,93,55,70,55,55,5,FALSE\\n500,Emboar,Fire,Fighting,110,123,65,100,65,65,5,FALSE\\n501,Oshawott,Water,,55,55,45,63,45,45,5,FALSE\\n502,Dewott,Water,,75,75,60,83,60,60,5,FALSE\\n503,Samurott,Water,,95,100,85,108,70,70,5,FALSE\\n504,Patrat,Normal,,45,55,39,35,39,42,5,FALSE\\n505,Watchog,Normal,,60,85,69,60,69,77,5,FALSE\\n506,Lillipup,Normal,,45,60,45,25,45,55,5,FALSE\\n507,Herdier,Normal,,65,80,65,35,65,60,5,FALSE\\n508,Stoutland,Normal,,85,110,90,45,90,80,5,FALSE\\n509,Purrloin,Dark,,41,50,37,50,37,66,5,FALSE\\n510,Liepard,Dark,,64,88,50,88,50,106,5,FALSE\\n511,Pansage,Grass,,50,53,48,53,48,64,5,FALSE\\n512,Simisage,Grass,,75,98,63,98,63,101,5,FALSE\\n513,Pansear,Fire,,50,53,48,53,48,64,5,FALSE\\n514,Simisear,Fire,,75,98,63,98,63,101,5,FALSE\\n515,Panpour,Water,,50,53,48,53,48,64,5,FALSE\\n516,Simipour,Water,,75,98,63,98,63,101,5,FALSE\\n517,Munna,Psychic,,76,25,45,67,55,24,5,FALSE\\n518,Musharna,Psychic,,116,55,85,107,95,29,5,FALSE\\n519,Pidove,Normal,Flying,50,55,50,36,30,43,5,FALSE\\n520,Tranquill,Normal,Flying,62,77,62,50,42,65,5,FALSE\\n521,Unfezant,Normal,Flying,80,115,80,65,55,93,5,FALSE\\n522,Blitzle,Electric,,45,60,32,50,32,76,5,FALSE\\n523,Zebstrika,Electric,,75,100,63,80,63,116,5,FALSE\\n524,Roggenrola,Rock,,55,75,85,25,25,15,5,FALSE\\n525,Boldore,Rock,,70,105,105,50,40,20,5,FALSE\\n526,Gigalith,Rock,,85,135,130,60,80,25,5,FALSE\\n527,Woobat,Psychic,Flying,55,45,43,55,43,72,5,FALSE\\n528,Swoobat,Psychic,Flying,67,57,55,77,55,114,5,FALSE\\n529,Drilbur,Ground,,60,85,40,30,45,68,5,FALSE\\n530,Excadrill,Ground,Steel,110,135,60,50,65,88,5,FALSE\\n531,Audino,Normal,,103,60,86,60,86,50,5,FALSE\\n531,AudinoMega Audino,Normal,Fairy,103,60,126,80,126,50,5,FALSE\\n532,Timburr,Fighting,,75,80,55,25,35,35,5,FALSE\\n533,Gurdurr,Fighting,,85,105,85,40,50,40,5,FALSE\\n534,Conkeldurr,Fighting,,105,140,95,55,65,45,5,FALSE\\n535,Tympole,Water,,50,50,40,50,40,64,5,FALSE\\n536,Palpitoad,Water,Ground,75,65,55,65,55,69,5,FALSE\\n537,Seismitoad,Water,Ground,105,95,75,85,75,74,5,FALSE\\n538,Throh,Fighting,,120,100,85,30,85,45,5,FALSE\\n539,Sawk,Fighting,,75,125,75,30,75,85,5,FALSE\\n540,Sewaddle,Bug,Grass,45,53,70,40,60,42,5,FALSE\\n541,Swadloon,Bug,Grass,55,63,90,50,80,42,5,FALSE\\n542,Leavanny,Bug,Grass,75,103,80,70,80,92,5,FALSE\\n543,Venipede,Bug,Poison,30,45,59,30,39,57,5,FALSE\\n544,Whirlipede,Bug,Poison,40,55,99,40,79,47,5,FALSE\\n545,Scolipede,Bug,Poison,60,100,89,55,69,112,5,FALSE\\n546,Cottonee,Grass,Fairy,40,27,60,37,50,66,5,FALSE\\n547,Whimsicott,Grass,Fairy,60,67,85,77,75,116,5,FALSE\\n548,Petilil,Grass,,45,35,50,70,50,30,5,FALSE\\n549,Lilligant,Grass,,70,60,75,110,75,90,5,FALSE\\n550,Basculin,Water,,70,92,65,80,55,98,5,FALSE\\n551,Sandile,Ground,Dark,50,72,35,35,35,65,5,FALSE\\n552,Krokorok,Ground,Dark,60,82,45,45,45,74,5,FALSE\\n553,Krookodile,Ground,Dark,95,117,80,65,70,92,5,FALSE\\n554,Darumaka,Fire,,70,90,45,15,45,50,5,FALSE\\n555,DarmanitanStandard Mode,Fire,,105,140,55,30,55,95,5,FALSE\\n555,DarmanitanZen Mode,Fire,Psychic,105,30,105,140,105,55,5,FALSE\\n556,Maractus,Grass,,75,86,67,106,67,60,5,FALSE\\n557,Dwebble,Bug,Rock,50,65,85,35,35,55,5,FALSE\\n558,Crustle,Bug,Rock,70,95,125,65,75,45,5,FALSE\\n559,Scraggy,Dark,Fighting,50,75,70,35,70,48,5,FALSE\\n560,Scrafty,Dark,Fighting,65,90,115,45,115,58,5,FALSE\\n561,Sigilyph,Psychic,Flying,72,58,80,103,80,97,5,FALSE\\n562,Yamask,Ghost,,38,30,85,55,65,30,5,FALSE\\n563,Cofagrigus,Ghost,,58,50,145,95,105,30,5,FALSE\\n564,Tirtouga,Water,Rock,54,78,103,53,45,22,5,FALSE\\n565,Carracosta,Water,Rock,74,108,133,83,65,32,5,FALSE\\n566,Archen,Rock,Flying,55,112,45,74,45,70,5,FALSE\\n567,Archeops,Rock,Flying,75,140,65,112,65,110,5,FALSE\\n568,Trubbish,Poison,,50,50,62,40,62,65,5,FALSE\\n569,Garbodor,Poison,,80,95,82,60,82,75,5,FALSE\\n570,Zorua,Dark,,40,65,40,80,40,65,5,FALSE\\n571,Zoroark,Dark,,60,105,60,120,60,105,5,FALSE\\n572,Minccino,Normal,,55,50,40,40,40,75,5,FALSE\\n573,Cinccino,Normal,,75,95,60,65,60,115,5,FALSE\\n574,Gothita,Psychic,,45,30,50,55,65,45,5,FALSE\\n575,Gothorita,Psychic,,60,45,70,75,85,55,5,FALSE\\n576,Gothitelle,Psychic,,70,55,95,95,110,65,5,FALSE\\n577,Solosis,Psychic,,45,30,40,105,50,20,5,FALSE\\n578,Duosion,Psychic,,65,40,50,125,60,30,5,FALSE\\n579,Reuniclus,Psychic,,110,65,75,125,85,30,5,FALSE\\n580,Ducklett,Water,Flying,62,44,50,44,50,55,5,FALSE\\n581,Swanna,Water,Flying,75,87,63,87,63,98,5,FALSE\\n582,Vanillite,Ice,,36,50,50,65,60,44,5,FALSE\\n583,Vanillish,Ice,,51,65,65,80,75,59,5,FALSE\\n584,Vanilluxe,Ice,,71,95,85,110,95,79,5,FALSE\\n585,Deerling,Normal,Grass,60,60,50,40,50,75,5,FALSE\\n586,Sawsbuck,Normal,Grass,80,100,70,60,70,95,5,FALSE\\n587,Emolga,Electric,Flying,55,75,60,75,60,103,5,FALSE\\n588,Karrablast,Bug,,50,75,45,40,45,60,5,FALSE\\n589,Escavalier,Bug,Steel,70,135,105,60,105,20,5,FALSE\\n590,Foongus,Grass,Poison,69,55,45,55,55,15,5,FALSE\\n591,Amoonguss,Grass,Poison,114,85,70,85,80,30,5,FALSE\\n592,Frillish,Water,Ghost,55,40,50,65,85,40,5,FALSE\\n593,Jellicent,Water,Ghost,100,60,70,85,105,60,5,FALSE\\n594,Alomomola,Water,,165,75,80,40,45,65,5,FALSE\\n595,Joltik,Bug,Electric,50,47,50,57,50,65,5,FALSE\\n596,Galvantula,Bug,Electric,70,77,60,97,60,108,5,FALSE\\n597,Ferroseed,Grass,Steel,44,50,91,24,86,10,5,FALSE\\n598,Ferrothorn,Grass,Steel,74,94,131,54,116,20,5,FALSE\\n599,Klink,Steel,,40,55,70,45,60,30,5,FALSE\\n600,Klang,Steel,,60,80,95,70,85,50,5,FALSE\\n601,Klinklang,Steel,,60,100,115,70,85,90,5,FALSE\\n602,Tynamo,Electric,,35,55,40,45,40,60,5,FALSE\\n603,Eelektrik,Electric,,65,85,70,75,70,40,5,FALSE\\n604,Eelektross,Electric,,85,115,80,105,80,50,5,FALSE\\n605,Elgyem,Psychic,,55,55,55,85,55,30,5,FALSE\\n606,Beheeyem,Psychic,,75,75,75,125,95,40,5,FALSE\\n607,Litwick,Ghost,Fire,50,30,55,65,55,20,5,FALSE\\n608,Lampent,Ghost,Fire,60,40,60,95,60,55,5,FALSE\\n609,Chandelure,Ghost,Fire,60,55,90,145,90,80,5,FALSE\\n610,Axew,Dragon,,46,87,60,30,40,57,5,FALSE\\n611,Fraxure,Dragon,,66,117,70,40,50,67,5,FALSE\\n612,Haxorus,Dragon,,76,147,90,60,70,97,5,FALSE\\n613,Cubchoo,Ice,,55,70,40,60,40,40,5,FALSE\\n614,Beartic,Ice,,95,110,80,70,80,50,5,FALSE\\n615,Cryogonal,Ice,,70,50,30,95,135,105,5,FALSE\\n616,Shelmet,Bug,,50,40,85,40,65,25,5,FALSE\\n617,Accelgor,Bug,,80,70,40,100,60,145,5,FALSE\\n618,Stunfisk,Ground,Electric,109,66,84,81,99,32,5,FALSE\\n619,Mienfoo,Fighting,,45,85,50,55,50,65,5,FALSE\\n620,Mienshao,Fighting,,65,125,60,95,60,105,5,FALSE\\n621,Druddigon,Dragon,,77,120,90,60,90,48,5,FALSE\\n622,Golett,Ground,Ghost,59,74,50,35,50,35,5,FALSE\\n623,Golurk,Ground,Ghost,89,124,80,55,80,55,5,FALSE\\n624,Pawniard,Dark,Steel,45,85,70,40,40,60,5,FALSE\\n625,Bisharp,Dark,Steel,65,125,100,60,70,70,5,FALSE\\n626,Bouffalant,Normal,,95,110,95,40,95,55,5,FALSE\\n627,Rufflet,Normal,Flying,70,83,50,37,50,60,5,FALSE\\n628,Braviary,Normal,Flying,100,123,75,57,75,80,5,FALSE\\n629,Vullaby,Dark,Flying,70,55,75,45,65,60,5,FALSE\\n630,Mandibuzz,Dark,Flying,110,65,105,55,95,80,5,FALSE\\n631,Heatmor,Fire,,85,97,66,105,66,65,5,FALSE\\n632,Durant,Bug,Steel,58,109,112,48,48,109,5,FALSE\\n633,Deino,Dark,Dragon,52,65,50,45,50,38,5,FALSE\\n634,Zweilous,Dark,Dragon,72,85,70,65,70,58,5,FALSE\\n635,Hydreigon,Dark,Dragon,92,105,90,125,90,98,5,FALSE\\n636,Larvesta,Bug,Fire,55,85,55,50,55,60,5,FALSE\\n637,Volcarona,Bug,Fire,85,60,65,135,105,100,5,FALSE\\n638,Cobalion,Steel,Fighting,91,90,129,90,72,108,5,TRUE\\n639,Terrakion,Rock,Fighting,91,129,90,72,90,108,5,TRUE\\n640,Virizion,Grass,Fighting,91,90,72,90,129,108,5,TRUE\\n641,TornadusIncarnate Forme,Flying,,79,115,70,125,80,111,5,TRUE\\n641,TornadusTherian Forme,Flying,,79,100,80,110,90,121,5,TRUE\\n642,ThundurusIncarnate Forme,Electric,Flying,79,115,70,125,80,111,5,TRUE\\n642,ThundurusTherian Forme,Electric,Flying,79,105,70,145,80,101,5,TRUE\\n643,Reshiram,Dragon,Fire,100,120,100,150,120,90,5,TRUE\\n644,Zekrom,Dragon,Electric,100,150,120,120,100,90,5,TRUE\\n645,LandorusIncarnate Forme,Ground,Flying,89,125,90,115,80,101,5,TRUE\\n645,LandorusTherian Forme,Ground,Flying,89,145,90,105,80,91,5,TRUE\\n646,Kyurem,Dragon,Ice,125,130,90,130,90,95,5,TRUE\\n646,KyuremBlack Kyurem,Dragon,Ice,125,170,100,120,90,95,5,TRUE\\n646,KyuremWhite Kyurem,Dragon,Ice,125,120,90,170,100,95,5,TRUE\\n647,KeldeoOrdinary Forme,Water,Fighting,91,72,90,129,90,108,5,FALSE\\n647,KeldeoResolute Forme,Water,Fighting,91,72,90,129,90,108,5,FALSE\\n648,MeloettaAria Forme,Normal,Psychic,100,77,77,128,128,90,5,FALSE\\n648,MeloettaPirouette Forme,Normal,Fighting,100,128,90,77,77,128,5,FALSE\\n649,Genesect,Bug,Steel,71,120,95,120,95,99,5,FALSE\\n650,Chespin,Grass,,56,61,65,48,45,38,6,FALSE\\n651,Quilladin,Grass,,61,78,95,56,58,57,6,FALSE\\n652,Chesnaught,Grass,Fighting,88,107,122,74,75,64,6,FALSE\\n653,Fennekin,Fire,,40,45,40,62,60,60,6,FALSE\\n654,Braixen,Fire,,59,59,58,90,70,73,6,FALSE\\n655,Delphox,Fire,Psychic,75,69,72,114,100,104,6,FALSE\\n656,Froakie,Water,,41,56,40,62,44,71,6,FALSE\\n657,Frogadier,Water,,54,63,52,83,56,97,6,FALSE\\n658,Greninja,Water,Dark,72,95,67,103,71,122,6,FALSE\\n659,Bunnelby,Normal,,38,36,38,32,36,57,6,FALSE\\n660,Diggersby,Normal,Ground,85,56,77,50,77,78,6,FALSE\\n661,Fletchling,Normal,Flying,45,50,43,40,38,62,6,FALSE\\n662,Fletchinder,Fire,Flying,62,73,55,56,52,84,6,FALSE\\n663,Talonflame,Fire,Flying,78,81,71,74,69,126,6,FALSE\\n664,Scatterbug,Bug,,38,35,40,27,25,35,6,FALSE\\n665,Spewpa,Bug,,45,22,60,27,30,29,6,FALSE\\n666,Vivillon,Bug,Flying,80,52,50,90,50,89,6,FALSE\\n667,Litleo,Fire,Normal,62,50,58,73,54,72,6,FALSE\\n668,Pyroar,Fire,Normal,86,68,72,109,66,106,6,FALSE\\n669,Flab\\xc3\\xa9b\\xc3\\xa9,Fairy,,44,38,39,61,79,42,6,FALSE\\n670,Floette,Fairy,,54,45,47,75,98,52,6,FALSE\\n671,Florges,Fairy,,78,65,68,112,154,75,6,FALSE\\n672,Skiddo,Grass,,66,65,48,62,57,52,6,FALSE\\n673,Gogoat,Grass,,123,100,62,97,81,68,6,FALSE\\n674,Pancham,Fighting,,67,82,62,46,48,43,6,FALSE\\n675,Pangoro,Fighting,Dark,95,124,78,69,71,58,6,FALSE\\n676,Furfrou,Normal,,75,80,60,65,90,102,6,FALSE\\n677,Espurr,Psychic,,62,48,54,63,60,68,6,FALSE\\n678,MeowsticMale,Psychic,,74,48,76,83,81,104,6,FALSE\\n678,MeowsticFemale,Psychic,,74,48,76,83,81,104,6,FALSE\\n679,Honedge,Steel,Ghost,45,80,100,35,37,28,6,FALSE\\n680,Doublade,Steel,Ghost,59,110,150,45,49,35,6,FALSE\\n681,AegislashBlade Forme,Steel,Ghost,60,150,50,150,50,60,6,FALSE\\n681,AegislashShield Forme,Steel,Ghost,60,50,150,50,150,60,6,FALSE\\n682,Spritzee,Fairy,,78,52,60,63,65,23,6,FALSE\\n683,Aromatisse,Fairy,,101,72,72,99,89,29,6,FALSE\\n684,Swirlix,Fairy,,62,48,66,59,57,49,6,FALSE\\n685,Slurpuff,Fairy,,82,80,86,85,75,72,6,FALSE\\n686,Inkay,Dark,Psychic,53,54,53,37,46,45,6,FALSE\\n687,Malamar,Dark,Psychic,86,92,88,68,75,73,6,FALSE\\n688,Binacle,Rock,Water,42,52,67,39,56,50,6,FALSE\\n689,Barbaracle,Rock,Water,72,105,115,54,86,68,6,FALSE\\n690,Skrelp,Poison,Water,50,60,60,60,60,30,6,FALSE\\n691,Dragalge,Poison,Dragon,65,75,90,97,123,44,6,FALSE\\n692,Clauncher,Water,,50,53,62,58,63,44,6,FALSE\\n693,Clawitzer,Water,,71,73,88,120,89,59,6,FALSE\\n694,Helioptile,Electric,Normal,44,38,33,61,43,70,6,FALSE\\n695,Heliolisk,Electric,Normal,62,55,52,109,94,109,6,FALSE\\n696,Tyrunt,Rock,Dragon,58,89,77,45,45,48,6,FALSE\\n697,Tyrantrum,Rock,Dragon,82,121,119,69,59,71,6,FALSE\\n698,Amaura,Rock,Ice,77,59,50,67,63,46,6,FALSE\\n699,Aurorus,Rock,Ice,123,77,72,99,92,58,6,FALSE\\n700,Sylveon,Fairy,,95,65,65,110,130,60,6,FALSE\\n701,Hawlucha,Fighting,Flying,78,92,75,74,63,118,6,FALSE\\n702,Dedenne,Electric,Fairy,67,58,57,81,67,101,6,FALSE\\n703,Carbink,Rock,Fairy,50,50,150,50,150,50,6,FALSE\\n704,Goomy,Dragon,,45,50,35,55,75,40,6,FALSE\\n705,Sliggoo,Dragon,,68,75,53,83,113,60,6,FALSE\\n706,Goodra,Dragon,,90,100,70,110,150,80,6,FALSE\\n707,Klefki,Steel,Fairy,57,80,91,80,87,75,6,FALSE\\n708,Phantump,Ghost,Grass,43,70,48,50,60,38,6,FALSE\\n709,Trevenant,Ghost,Grass,85,110,76,65,82,56,6,FALSE\\n710,PumpkabooAverage Size,Ghost,Grass,49,66,70,44,55,51,6,FALSE\\n710,PumpkabooSmall Size,Ghost,Grass,44,66,70,44,55,56,6,FALSE\\n710,PumpkabooLarge Size,Ghost,Grass,54,66,70,44,55,46,6,FALSE\\n710,PumpkabooSuper Size,Ghost,Grass,59,66,70,44,55,41,6,FALSE\\n711,GourgeistAverage Size,Ghost,Grass,65,90,122,58,75,84,6,FALSE\\n711,GourgeistSmall Size,Ghost,Grass,55,85,122,58,75,99,6,FALSE\\n711,GourgeistLarge Size,Ghost,Grass,75,95,122,58,75,69,6,FALSE\\n711,GourgeistSuper Size,Ghost,Grass,85,100,122,58,75,54,6,FALSE\\n712,Bergmite,Ice,,55,69,85,32,35,28,6,FALSE\\n713,Avalugg,Ice,,95,117,184,44,46,28,6,FALSE\\n714,Noibat,Flying,Dragon,40,30,35,45,40,55,6,FALSE\\n715,Noivern,Flying,Dragon,85,70,80,97,80,123,6,FALSE\\n716,Xerneas,Fairy,,126,131,95,131,98,99,6,TRUE\\n717,Yveltal,Dark,Flying,126,131,95,131,98,99,6,TRUE\\n718,Zygarde50% Forme,Dragon,Ground,108,100,121,81,95,95,6,TRUE\\n719,Diancie,Rock,Fairy,50,100,150,100,150,50,6,TRUE\\n719,DiancieMega Diancie,Rock,Fairy,50,160,110,160,110,110,6,TRUE\\n720,HoopaHoopa Confined,Psychic,Ghost,80,110,60,150,130,70,6,TRUE\\n720,HoopaHoopa Unbound,Psychic,Dark,80,160,60,170,130,80,6,TRUE\\n721,Volcanion,Fire,Water,80,110,120,130,90,70,6,TRUE\\n\"}"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fDTSn0yXZHQ1"
      },
      "source": [
        "### Initialization"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eaXRWc6EKS6Z",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "494a4d46-e20f-4030-952d-9c702095db96"
      },
      "source": [
        "# Use pd.Series()\n",
        "\n",
        "a = pd.Series([1,2,3])\n",
        "a"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    1\n",
              "1    2\n",
              "2    3\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g3kPYbEQZjJq",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9d7a305e-34cd-43a8-9ca7-673518d1340b"
      },
      "source": [
        "print('Data passed as a list')\n",
        "df_list = pd.DataFrame([['May1', 32], ['May2', 35], ['May3', 40], ['May4', 50]])\n",
        "print(df_list)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Data passed as a list\n",
            "      0   1\n",
            "0  May1  32\n",
            "1  May2  35\n",
            "2  May3  40\n",
            "3  May4  50\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nFfp5JQ25kdT"
      },
      "source": [
        "# df = pd.DataFrame([1,2,34], index=, columns=)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Mu1gVthqZkF2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "450a6f8e-c4be-4724-84db-7fa8227fdaf7"
      },
      "source": [
        "print('Data passed as dictionary')\n",
        "df_dict = pd.DataFrame({\"A\": [1, 2, 3], \"B\": [4, 5, 6]},dtype = float)\n",
        "print(df_dict)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Data passed as dictionary\n",
            "     A    B\n",
            "0  1.0  4.0\n",
            "1  2.0  5.0\n",
            "2  3.0  6.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dA4DjbDjaWZb"
      },
      "source": [
        "### Column and Indexes\n",
        "\n",
        "In case of dictionary the keys would act as columns but in lists, the column names if not specified will start as '0' as the 1st column, '1' as the 2nd Column and so on.</br>\n",
        "The left most part of the dataframe is called as index, it's starts default with index 0."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Oq-vc7leZkUh",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c5d61c49-675e-4220-fc17-2ca32e9ceb40"
      },
      "source": [
        "# Listing the columns\n",
        "\n",
        "print(df_dict.columns)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Index(['A', 'B'], dtype='object')\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WT-IymKsbKhF",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "aaf52a98-a4b0-4d93-b658-f7a2cb070cc4"
      },
      "source": [
        "# Rename columns\n",
        "\n",
        "df_dict.rename(columns={'A': 'a'})\n",
        "\n",
        "# inplace by default is false\n",
        "# if inplace = True is not set then the changes are not made on the original df but only a temp df is made with changes\n",
        "df_dict"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>A</th>\n",
              "      <th>B</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3.0</td>\n",
              "      <td>6.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     A    B\n",
              "0  1.0  4.0\n",
              "1  2.0  5.0\n",
              "2  3.0  6.0"
            ]
          },
          "metadata": {},
          "execution_count": 56
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ObK8r59dbK76"
      },
      "source": [
        "# changes made for original df\n",
        "\n",
        "df_dict.rename(columns={'A': 'a'}, inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "nTJW48TG6OPB",
        "outputId": "5d3bd84c-c8b6-45a7-d227-ccf891f11102"
      },
      "source": [
        "df_dict"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>a</th>\n",
              "      <th>B</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3.0</td>\n",
              "      <td>6.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     a    B\n",
              "0  1.0  4.0\n",
              "1  2.0  5.0\n",
              "2  3.0  6.0"
            ]
          },
          "metadata": {},
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SpaeNkcAbLLx",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "64ea7180-5eed-4d85-f9a3-258131b45f53"
      },
      "source": [
        "# Reset column names\n",
        "# Tip: remember to pass the entire list in this case\n",
        "\n",
        "df_dict.columns = ['a', 'b']\n",
        "df_dict.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>a</th>\n",
              "      <th>b</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3.0</td>\n",
              "      <td>6.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     a    b\n",
              "0  1.0  4.0\n",
              "1  2.0  5.0\n",
              "2  3.0  6.0"
            ]
          },
          "metadata": {},
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QoAh13umbLcE",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "bad80d1c-4317-4915-b245-bd80a7425185"
      },
      "source": [
        "# Defining columns, index during dataframe creation\n",
        "\n",
        "df_temp = pd.DataFrame([['October 1', 67], ['October 2', 72], ['October 3', 58], ['October 4', 69], ['October 5', 77]], index = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5'], columns = ['Month', 'Temperature'])\n",
        "df_temp"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Month</th>\n",
              "      <th>Temperature</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Day 1</th>\n",
              "      <td>October 1</td>\n",
              "      <td>67</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day 2</th>\n",
              "      <td>October 2</td>\n",
              "      <td>72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day 3</th>\n",
              "      <td>October 3</td>\n",
              "      <td>58</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day 4</th>\n",
              "      <td>October 4</td>\n",
              "      <td>69</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day 5</th>\n",
              "      <td>October 5</td>\n",
              "      <td>77</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           Month  Temperature\n",
              "Day 1  October 1           67\n",
              "Day 2  October 2           72\n",
              "Day 3  October 3           58\n",
              "Day 4  October 4           69\n",
              "Day 5  October 5           77"
            ]
          },
          "metadata": {},
          "execution_count": 62
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MNLqFd0vblkP"
      },
      "source": [
        "`reset_index`: To drop index and bring pandas default sequential form of 0, 1, ..."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_ZwIM_UzbmB3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "f353040c-0181-4441-d9b8-428534998c46"
      },
      "source": [
        "# Here drop=True means we want to drop the original index we have and reset to default value\n",
        "\n",
        "df_temp.reset_index(drop=True, inplace=False)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Month</th>\n",
              "      <th>Temperature</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>October 1</td>\n",
              "      <td>67</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>October 2</td>\n",
              "      <td>72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>October 3</td>\n",
              "      <td>58</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>October 4</td>\n",
              "      <td>69</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>October 5</td>\n",
              "      <td>77</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       Month  Temperature\n",
              "0  October 1           67\n",
              "1  October 2           72\n",
              "2  October 3           58\n",
              "3  October 4           69\n",
              "4  October 5           77"
            ]
          },
          "metadata": {},
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "v667rvBkbmv1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "outputId": "fd7ae2b3-8de9-48dd-8f01-4883532ae493"
      },
      "source": [
        "# We can also make a column as index\n",
        "\n",
        "df_temp = pd.DataFrame([['October 1', 67], ['October 2', 72], ['October 3', 58], ['October 4', 69], ['October 5', 77]], columns = ['Month', 'Temperature'])\n",
        "df_temp.set_index('Month')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Temperature</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Month</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>October 1</th>\n",
              "      <td>67</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>October 2</th>\n",
              "      <td>72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>October 3</th>\n",
              "      <td>58</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>October 4</th>\n",
              "      <td>69</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>October 5</th>\n",
              "      <td>77</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           Temperature\n",
              "Month                 \n",
              "October 1           67\n",
              "October 2           72\n",
              "October 3           58\n",
              "October 4           69\n",
              "October 5           77"
            ]
          },
          "metadata": {},
          "execution_count": 64
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jtDOQmptcoGH",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "outputId": "df854916-7fc2-41d0-8532-da9c4aecad59"
      },
      "source": [
        "# Reading data from a csv file\n",
        "# index_col describes which column we want to set as the index\n",
        "# head function is used to print first n rows of the dataframe, here n=10 in our case\n",
        "\n",
        "pokemon_data = pd.read_csv('pokemon_data.csv', index_col = 0)\n",
        "pokemon_data.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Name</th>\n",
              "      <th>Type 1</th>\n",
              "      <th>Type 2</th>\n",
              "      <th>HP</th>\n",
              "      <th>Attack</th>\n",
              "      <th>Defense</th>\n",
              "      <th>Sp. Atk</th>\n",
              "      <th>Sp. Def</th>\n",
              "      <th>Speed</th>\n",
              "      <th>Generation</th>\n",
              "      <th>Legendary</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>#</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Bulbasaur</td>\n",
              "      <td>Grass</td>\n",
              "      <td>Poison</td>\n",
              "      <td>45</td>\n",
              "      <td>49</td>\n",
              "      <td>49</td>\n",
              "      <td>65</td>\n",
              "      <td>65</td>\n",
              "      <td>45</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Ivysaur</td>\n",
              "      <td>Grass</td>\n",
              "      <td>Poison</td>\n",
              "      <td>60</td>\n",
              "      <td>62</td>\n",
              "      <td>63</td>\n",
              "      <td>80</td>\n",
              "      <td>80</td>\n",
              "      <td>60</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Venusaur</td>\n",
              "      <td>Grass</td>\n",
              "      <td>Poison</td>\n",
              "      <td>80</td>\n",
              "      <td>82</td>\n",
              "      <td>83</td>\n",
              "      <td>100</td>\n",
              "      <td>100</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>VenusaurMega Venusaur</td>\n",
              "      <td>Grass</td>\n",
              "      <td>Poison</td>\n",
              "      <td>80</td>\n",
              "      <td>100</td>\n",
              "      <td>123</td>\n",
              "      <td>122</td>\n",
              "      <td>120</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Charmander</td>\n",
              "      <td>Fire</td>\n",
              "      <td>NaN</td>\n",
              "      <td>39</td>\n",
              "      <td>52</td>\n",
              "      <td>43</td>\n",
              "      <td>60</td>\n",
              "      <td>50</td>\n",
              "      <td>65</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                    Name Type 1  Type 2  ...  Speed  Generation  Legendary\n",
              "#                                        ...                              \n",
              "1              Bulbasaur  Grass  Poison  ...     45           1      False\n",
              "2                Ivysaur  Grass  Poison  ...     60           1      False\n",
              "3               Venusaur  Grass  Poison  ...     80           1      False\n",
              "3  VenusaurMega Venusaur  Grass  Poison  ...     80           1      False\n",
              "4             Charmander   Fire     NaN  ...     65           1      False\n",
              "\n",
              "[5 rows x 11 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XhTjKGEic-eu"
      },
      "source": [
        "### Basic Data Statistics"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IDExAI99coX3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "outputId": "48f2a581-8fe2-42fc-9eec-38fe57026481"
      },
      "source": [
        "#describe function will compute basic statistics as shown below as for each column\n",
        "\n",
        "pokemon_data.describe()\n",
        "\n",
        "\n",
        "#Note: Stats are not calculated for object or string dtype"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>HP</th>\n",
              "      <th>Attack</th>\n",
              "      <th>Defense</th>\n",
              "      <th>Sp. Atk</th>\n",
              "      <th>Sp. Def</th>\n",
              "      <th>Speed</th>\n",
              "      <th>Generation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>800.000000</td>\n",
              "      <td>800.000000</td>\n",
              "      <td>800.000000</td>\n",
              "      <td>800.000000</td>\n",
              "      <td>800.000000</td>\n",
              "      <td>800.000000</td>\n",
              "      <td>800.00000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>69.258750</td>\n",
              "      <td>79.001250</td>\n",
              "      <td>73.842500</td>\n",
              "      <td>72.820000</td>\n",
              "      <td>71.902500</td>\n",
              "      <td>68.277500</td>\n",
              "      <td>3.32375</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>25.534669</td>\n",
              "      <td>32.457366</td>\n",
              "      <td>31.183501</td>\n",
              "      <td>32.722294</td>\n",
              "      <td>27.828916</td>\n",
              "      <td>29.060474</td>\n",
              "      <td>1.66129</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>20.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>1.00000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>50.000000</td>\n",
              "      <td>55.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>49.750000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>45.000000</td>\n",
              "      <td>2.00000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>65.000000</td>\n",
              "      <td>75.000000</td>\n",
              "      <td>70.000000</td>\n",
              "      <td>65.000000</td>\n",
              "      <td>70.000000</td>\n",
              "      <td>65.000000</td>\n",
              "      <td>3.00000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>80.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>90.000000</td>\n",
              "      <td>95.000000</td>\n",
              "      <td>90.000000</td>\n",
              "      <td>90.000000</td>\n",
              "      <td>5.00000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>255.000000</td>\n",
              "      <td>190.000000</td>\n",
              "      <td>230.000000</td>\n",
              "      <td>194.000000</td>\n",
              "      <td>230.000000</td>\n",
              "      <td>180.000000</td>\n",
              "      <td>6.00000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               HP      Attack     Defense  ...     Sp. Def       Speed  Generation\n",
              "count  800.000000  800.000000  800.000000  ...  800.000000  800.000000   800.00000\n",
              "mean    69.258750   79.001250   73.842500  ...   71.902500   68.277500     3.32375\n",
              "std     25.534669   32.457366   31.183501  ...   27.828916   29.060474     1.66129\n",
              "min      1.000000    5.000000    5.000000  ...   20.000000    5.000000     1.00000\n",
              "25%     50.000000   55.000000   50.000000  ...   50.000000   45.000000     2.00000\n",
              "50%     65.000000   75.000000   70.000000  ...   70.000000   65.000000     3.00000\n",
              "75%     80.000000  100.000000   90.000000  ...   90.000000   90.000000     5.00000\n",
              "max    255.000000  190.000000  230.000000  ...  230.000000  180.000000     6.00000\n",
              "\n",
              "[8 rows x 7 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Js2sjLuVconw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f41ee7bc-6ecf-46ce-a528-f6511fcc8fd5"
      },
      "source": [
        "#Check the type of each column it will be Series datatype\n",
        "\n",
        "print(pokemon_data.dtypes)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Name          object\n",
            "Type 1        object\n",
            "Type 2        object\n",
            "HP             int64\n",
            "Attack         int64\n",
            "Defense        int64\n",
            "Sp. Atk        int64\n",
            "Sp. Def        int64\n",
            "Speed          int64\n",
            "Generation     int64\n",
            "Legendary       bool\n",
            "dtype: object\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cttQ3XXadYJ8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "520a3a23-f798-4b3c-9560-e958af2d8913"
      },
      "source": [
        "# Value counts for type 1\n",
        "\n",
        "pokemon_data['Type 1'].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Water       112\n",
              "Normal       98\n",
              "Grass        70\n",
              "Bug          69\n",
              "Psychic      57\n",
              "Fire         52\n",
              "Electric     44\n",
              "Rock         44\n",
              "Ground       32\n",
              "Ghost        32\n",
              "Dragon       32\n",
              "Dark         31\n",
              "Poison       28\n",
              "Steel        27\n",
              "Fighting     27\n",
              "Ice          24\n",
              "Fairy        17\n",
              "Flying        4\n",
              "Name: Type 1, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 68
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PTnYYnPUdYdM",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9cedf859-eba8-444d-8082-f75d9ac17331"
      },
      "source": [
        "# Calculate mean, max, min, std, sum of the HP\n",
        "\n",
        "print(pokemon_data['HP'].describe())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "count    800.000000\n",
            "mean      69.258750\n",
            "std       25.534669\n",
            "min        1.000000\n",
            "25%       50.000000\n",
            "50%       65.000000\n",
            "75%       80.000000\n",
            "max      255.000000\n",
            "Name: HP, dtype: float64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "d-XQGwDiC5Ps"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Bk1EhCRddmA3"
      },
      "source": [
        "### Axis management\n",
        "\n",
        "axis denotes the dimension of dataframe. </br>\n",
        "axis = 0, also the axis of index/rows. Thus calculations are done at column level. </br>\n",
        "axis = 1, also axis of columns. Calculations are done for each row </br>\n",
        "For added clarity, you can specify axis='index' (instead of axis=0) or axis='columns' (instead of axis=1)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EF8yk2j_dYq6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "outputId": "e42f16e1-6a25-4627-d4a3-b77496bb1aaf"
      },
      "source": [
        "df_dummy = pd.DataFrame([[2,-2],[1,-1]])\n",
        "df_dummy"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2</td>\n",
              "      <td>-2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   0  1\n",
              "0  2 -2\n",
              "1  1 -1"
            ]
          },
          "metadata": {},
          "execution_count": 70
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WzYAhEcbd_mY",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6688857d-48aa-40cb-c053-a2be18eab95a"
      },
      "source": [
        "# summation on axis 0 or for each row\n",
        "\n",
        "df_dummy.sum(axis=0)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    3\n",
              "1   -3\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 71
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bsShN686eADE",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c556dcf5-4a92-4e4f-c120-0817441b1059"
      },
      "source": [
        "# summation on axis 1 or for each column\n",
        "\n",
        "df_dummy.sum(axis=1)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    0\n",
              "1    0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 72
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iozcRmnCfIHL"
      },
      "source": [
        "### NaN\n",
        "\n",
        "NaN (Not a Number) is a special floating point number (like infinity) and is an indication of no data."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "P4h9ltBZeAY7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "78491dde-bc2f-4355-bade-f28516126c7b"
      },
      "source": [
        "df_nan = pd.DataFrame([{'a': 1, 'b': 2}, {'a':5, 'b':6, 'c':7}])\n",
        "print(df_nan)\n",
        "\n",
        "# Notice that column c is of type float due to NaN"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "   a  b    c\n",
            "0  1  2  NaN\n",
            "1  5  6  7.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dp_yybCcfbqA",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b4e62f61-3a3c-4061-d1a5-25df9bae9d5f"
      },
      "source": [
        "# isnull working - assigns each data point in the dataframe with True or False\n",
        "# return dataframe filled with True or False\n",
        "\n",
        "print(df_nan.isnull())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "       a      b      c\n",
            "0  False  False   True\n",
            "1  False  False  False\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-tWv56HBfb8q",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e58ce825-fc58-4806-f5db-c6887f4e2ced"
      },
      "source": [
        "# To count how many NaN, use sum function on the result of isnull\n",
        "\n",
        "print(df_nan.isnull().sum())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "a    0\n",
            "b    0\n",
            "c    1\n",
            "dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MkNIDwaigfsP"
      },
      "source": [
        "# Question: Which columns in the Pokemon data set have null values?\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iRCV0A74gvO5"
      },
      "source": [
        "### Data Manipulation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5TrcWjvEgzVe",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 174
        },
        "outputId": "eb800955-1a12-4267-e4ab-88edc197a144"
      },
      "source": [
        "df = pd.DataFrame([['May1',32],['May2',35],['May3',40],['May4',50]],index = ['Day1','Day2','Day3','Day4'],columns = ['Month','Temperature'])\n",
        "\n",
        "df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Month</th>\n",
              "      <th>Temperature</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Day1</th>\n",
              "      <td>May1</td>\n",
              "      <td>32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day2</th>\n",
              "      <td>May2</td>\n",
              "      <td>35</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day3</th>\n",
              "      <td>May3</td>\n",
              "      <td>40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day4</th>\n",
              "      <td>May4</td>\n",
              "      <td>50</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Month  Temperature\n",
              "Day1  May1           32\n",
              "Day2  May2           35\n",
              "Day3  May3           40\n",
              "Day4  May4           50"
            ]
          },
          "metadata": {},
          "execution_count": 76
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Bve0XaUigzlh",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c108d1b8-3af3-4ac9-f113-7668a0c813eb"
      },
      "source": [
        "# Access column by name\n",
        "\n",
        "df['Temperature']"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Day1    32\n",
              "Day2    35\n",
              "Day3    40\n",
              "Day4    50\n",
              "Name: Temperature, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 77
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GMFSKpAHgz1K",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 174
        },
        "outputId": "226e4aa2-343e-4dcf-9431-006486128b00"
      },
      "source": [
        "# Multiple column access\n",
        "\n",
        "df[['Temperature', 'Month']]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Temperature</th>\n",
              "      <th>Month</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Day1</th>\n",
              "      <td>32</td>\n",
              "      <td>May1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day2</th>\n",
              "      <td>35</td>\n",
              "      <td>May2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day3</th>\n",
              "      <td>40</td>\n",
              "      <td>May3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day4</th>\n",
              "      <td>50</td>\n",
              "      <td>May4</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      Temperature Month\n",
              "Day1           32  May1\n",
              "Day2           35  May2\n",
              "Day3           40  May3\n",
              "Day4           50  May4"
            ]
          },
          "metadata": {},
          "execution_count": 78
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_zLGu-PMg0kF",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "750f44c5-9abe-401a-a16e-ac494cc3e29b"
      },
      "source": [
        "print(type(df.iloc[1]))\n",
        "print(df.iloc[1])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.series.Series'>\n",
            "Month          May2\n",
            "Temperature      35\n",
            "Name: Day2, dtype: object\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WL9eLWkfidjZ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "12dd6565-3c69-47df-9c00-7487757d9a6f"
      },
      "source": [
        "print('range of index wise selection in discrete manner')\n",
        "print(df.iloc[[1,2,3]])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "range of index wise selection in discrete manner\n",
            "     Month  Temperature\n",
            "Day2  May2           35\n",
            "Day3  May3           40\n",
            "Day4  May4           50\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MW7z84ziid2r",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1214563f-8c7c-4200-d7e4-a0c097084f92"
      },
      "source": [
        "print('Get single value')\n",
        "print()\n",
        "print(df.iloc[0])\n",
        "print()\n",
        "\n",
        "print(df.iloc[0,0])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Get single value\n",
            "\n",
            "Month          May1\n",
            "Temperature      32\n",
            "Name: Day1, dtype: object\n",
            "\n",
            "May1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_VGJZ2M9ieHv"
      },
      "source": [
        "# Question: Select the first five columns of the Pokemon dataset\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zyIoRzhoiwD4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ba225e64-39d3-411f-f921-43795a0fcf11"
      },
      "source": [
        "# Adding columns\n",
        "# Notice the difference\n",
        "\n",
        "add_column = pd.Series(['St. Marks Ave', 'Carlton Ave', 'Jay Street', 'Nevins Street'], index=['Day1', 'Day2', 'Day4', 'Day3'])\n",
        "df['Stations'] = add_column\n",
        "df['Stations 2'] = pd.Series(['St. Marks Ave', 'Carlton Ave', 'Jay Street', 'Nevins Street'])\n",
        "print(df)\n",
        "\n",
        "# either specify index or add as python list instead of series\n",
        "df['Stations 2'] = ['St. Marks Ave', 'Carlton Ave', 'Jay Street', 'Nevins Street']\n",
        "print(df)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "     Month  Temperature       Stations Stations 2\n",
            "Day1  May1           32  St. Marks Ave        NaN\n",
            "Day2  May2           35    Carlton Ave        NaN\n",
            "Day3  May3           40  Nevins Street        NaN\n",
            "Day4  May4           50     Jay Street        NaN\n",
            "     Month  Temperature       Stations     Stations 2\n",
            "Day1  May1           32  St. Marks Ave  St. Marks Ave\n",
            "Day2  May2           35    Carlton Ave    Carlton Ave\n",
            "Day3  May3           40  Nevins Street     Jay Street\n",
            "Day4  May4           50     Jay Street  Nevins Street\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "c-mIXtUbiwU7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "09f28dca-640f-4321-bf07-fd3ed3c092b2"
      },
      "source": [
        "# New column using existing column\n",
        "\n",
        "df['Wind Speed'] = df['Temperature'] * 0.414\n",
        "print(df)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "     Month  Temperature       Stations     Stations 2  Wind Speed\n",
            "Day1  May1           32  St. Marks Ave  St. Marks Ave      13.248\n",
            "Day2  May2           35    Carlton Ave    Carlton Ave      14.490\n",
            "Day3  May3           40  Nevins Street     Jay Street      16.560\n",
            "Day4  May4           50     Jay Street  Nevins Street      20.700\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "00pdSSVbiwh_",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 174
        },
        "outputId": "b80beb58-5c86-4b0e-e1bf-f91942018b5e"
      },
      "source": [
        "# Column addition (with same data type)\n",
        "\n",
        "df['Add Wind Temp'] = df['Temperature'] + df['Wind Speed']\n",
        "df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Month</th>\n",
              "      <th>Temperature</th>\n",
              "      <th>Stations</th>\n",
              "      <th>Stations 2</th>\n",
              "      <th>Wind Speed</th>\n",
              "      <th>Add Wind Temp</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Day1</th>\n",
              "      <td>October 8</td>\n",
              "      <td>32</td>\n",
              "      <td>St. Marks Ave</td>\n",
              "      <td>St. Marks Ave</td>\n",
              "      <td>13.248</td>\n",
              "      <td>45.248</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day2</th>\n",
              "      <td>May2</td>\n",
              "      <td>35</td>\n",
              "      <td>Carlton Ave</td>\n",
              "      <td>Carlton Ave</td>\n",
              "      <td>14.490</td>\n",
              "      <td>49.490</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day3</th>\n",
              "      <td>May3</td>\n",
              "      <td>40</td>\n",
              "      <td>Nevins Street</td>\n",
              "      <td>Jay Street</td>\n",
              "      <td>16.560</td>\n",
              "      <td>56.560</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day4</th>\n",
              "      <td>May4</td>\n",
              "      <td>50</td>\n",
              "      <td>Jay Street</td>\n",
              "      <td>Nevins Street</td>\n",
              "      <td>20.700</td>\n",
              "      <td>70.700</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Month  Temperature  ... Wind Speed Add Wind Temp\n",
              "Day1  October 8           32  ...     13.248        45.248\n",
              "Day2       May2           35  ...     14.490        49.490\n",
              "Day3       May3           40  ...     16.560        56.560\n",
              "Day4       May4           50  ...     20.700        70.700\n",
              "\n",
              "[4 rows x 6 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 91
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ks6aL0ILiw67",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 174
        },
        "outputId": "3b34704a-5bab-41e6-e26c-5b638c1e216d"
      },
      "source": [
        "# Changing values using loc/iloc\n",
        "\n",
        "df.iloc[0,0] = 'October 8'\n",
        "df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Month</th>\n",
              "      <th>Temperature</th>\n",
              "      <th>Stations</th>\n",
              "      <th>Stations 2</th>\n",
              "      <th>Wind Speed</th>\n",
              "      <th>Add Wind Temp</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Day1</th>\n",
              "      <td>October 8</td>\n",
              "      <td>32</td>\n",
              "      <td>St. Marks Ave</td>\n",
              "      <td>St. Marks Ave</td>\n",
              "      <td>13.248</td>\n",
              "      <td>45.248</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day2</th>\n",
              "      <td>May2</td>\n",
              "      <td>35</td>\n",
              "      <td>Carlton Ave</td>\n",
              "      <td>Carlton Ave</td>\n",
              "      <td>14.490</td>\n",
              "      <td>49.490</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day3</th>\n",
              "      <td>May3</td>\n",
              "      <td>40</td>\n",
              "      <td>Nevins Street</td>\n",
              "      <td>Jay Street</td>\n",
              "      <td>16.560</td>\n",
              "      <td>56.560</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day4</th>\n",
              "      <td>May4</td>\n",
              "      <td>50</td>\n",
              "      <td>Jay Street</td>\n",
              "      <td>Nevins Street</td>\n",
              "      <td>20.700</td>\n",
              "      <td>70.700</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Month  Temperature  ... Wind Speed Add Wind Temp\n",
              "Day1  October 8           32  ...     13.248        45.248\n",
              "Day2       May2           35  ...     14.490        49.490\n",
              "Day3       May3           40  ...     16.560        56.560\n",
              "Day4       May4           50  ...     20.700        70.700\n",
              "\n",
              "[4 rows x 6 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 92
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qiFji4shjUeM"
      },
      "source": [
        "# drop function can be used to drop based on column or index \n",
        "\n",
        "df.drop('Add Wind Temp', axis=1, inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 174
        },
        "id": "Sntz3Bn1_D9b",
        "outputId": "1723e147-86c6-420a-ea30-4e0dc4ec95e0"
      },
      "source": [
        "df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Month</th>\n",
              "      <th>Temperature</th>\n",
              "      <th>Stations</th>\n",
              "      <th>Stations 2</th>\n",
              "      <th>Wind Speed</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Day1</th>\n",
              "      <td>October 8</td>\n",
              "      <td>32</td>\n",
              "      <td>St. Marks Ave</td>\n",
              "      <td>St. Marks Ave</td>\n",
              "      <td>13.248</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day2</th>\n",
              "      <td>May2</td>\n",
              "      <td>35</td>\n",
              "      <td>Carlton Ave</td>\n",
              "      <td>Carlton Ave</td>\n",
              "      <td>14.490</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day3</th>\n",
              "      <td>May3</td>\n",
              "      <td>40</td>\n",
              "      <td>Nevins Street</td>\n",
              "      <td>Jay Street</td>\n",
              "      <td>16.560</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day4</th>\n",
              "      <td>May4</td>\n",
              "      <td>50</td>\n",
              "      <td>Jay Street</td>\n",
              "      <td>Nevins Street</td>\n",
              "      <td>20.700</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Month  Temperature       Stations     Stations 2  Wind Speed\n",
              "Day1  October 8           32  St. Marks Ave  St. Marks Ave      13.248\n",
              "Day2       May2           35    Carlton Ave    Carlton Ave      14.490\n",
              "Day3       May3           40  Nevins Street     Jay Street      16.560\n",
              "Day4       May4           50     Jay Street  Nevins Street      20.700"
            ]
          },
          "metadata": {},
          "execution_count": 94
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "llW9g5aYjVNZ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "3d2617e6-c3f6-4916-fa93-fe4673ea1460"
      },
      "source": [
        "# Drop row of a dataframe use drop function and pass the indexed index or name of that index\n",
        "\n",
        "df.drop(df.index[0])\n",
        "\n",
        "# inplace=False"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Month</th>\n",
              "      <th>Temperature</th>\n",
              "      <th>Stations</th>\n",
              "      <th>Stations 2</th>\n",
              "      <th>Wind Speed</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Day2</th>\n",
              "      <td>May2</td>\n",
              "      <td>35</td>\n",
              "      <td>Carlton Ave</td>\n",
              "      <td>Carlton Ave</td>\n",
              "      <td>14.49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day3</th>\n",
              "      <td>May3</td>\n",
              "      <td>40</td>\n",
              "      <td>Nevins Street</td>\n",
              "      <td>Jay Street</td>\n",
              "      <td>16.56</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day4</th>\n",
              "      <td>May4</td>\n",
              "      <td>50</td>\n",
              "      <td>Jay Street</td>\n",
              "      <td>Nevins Street</td>\n",
              "      <td>20.70</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Month  Temperature       Stations     Stations 2  Wind Speed\n",
              "Day2  May2           35    Carlton Ave    Carlton Ave       14.49\n",
              "Day3  May3           40  Nevins Street     Jay Street       16.56\n",
              "Day4  May4           50     Jay Street  Nevins Street       20.70"
            ]
          },
          "metadata": {},
          "execution_count": 95
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0kMGuVZbjVaL",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "b8b37aca-dc6f-4432-a1e9-78059ae9d67a"
      },
      "source": [
        "# By index name\n",
        "\n",
        "df.drop('Day2', axis=0)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Month</th>\n",
              "      <th>Temperature</th>\n",
              "      <th>Stations</th>\n",
              "      <th>Stations 2</th>\n",
              "      <th>Wind Speed</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Day1</th>\n",
              "      <td>October 8</td>\n",
              "      <td>32</td>\n",
              "      <td>St. Marks Ave</td>\n",
              "      <td>St. Marks Ave</td>\n",
              "      <td>13.248</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day3</th>\n",
              "      <td>May3</td>\n",
              "      <td>40</td>\n",
              "      <td>Nevins Street</td>\n",
              "      <td>Jay Street</td>\n",
              "      <td>16.560</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day4</th>\n",
              "      <td>May4</td>\n",
              "      <td>50</td>\n",
              "      <td>Jay Street</td>\n",
              "      <td>Nevins Street</td>\n",
              "      <td>20.700</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Month  Temperature       Stations     Stations 2  Wind Speed\n",
              "Day1  October 8           32  St. Marks Ave  St. Marks Ave      13.248\n",
              "Day3       May3           40  Nevins Street     Jay Street      16.560\n",
              "Day4       May4           50     Jay Street  Nevins Street      20.700"
            ]
          },
          "metadata": {},
          "execution_count": 96
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CF_96XYeG-HB"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qSOYkDr3jklK"
      },
      "source": [
        "# Question: Select data for temperature and wind speed column by using the loc method\n",
        "# Hint: data.loc['Condition(s)']\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dT5o8WgCjr23",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9b2cf3a7-3818-48b9-8893-b9f0463d2791"
      },
      "source": [
        "# Condition based filtering\n",
        "\n",
        "# Conditions generate a mask df of booleans which is used to select relevant rows from original dataframe\n",
        "\n",
        "df['Temperature'] >= 40"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Day1    False\n",
              "Day2    False\n",
              "Day3     True\n",
              "Day4     True\n",
              "Name: Temperature, dtype: bool"
            ]
          },
          "metadata": {},
          "execution_count": 98
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KmSQhsLEjtFt",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "outputId": "5502aec8-991c-4fb3-c8ac-18512fb12e00"
      },
      "source": [
        "# Selection part\n",
        "\n",
        "df[df['Temperature'] >=40]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Month</th>\n",
              "      <th>Temperature</th>\n",
              "      <th>Stations</th>\n",
              "      <th>Stations 2</th>\n",
              "      <th>Wind Speed</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Day3</th>\n",
              "      <td>May3</td>\n",
              "      <td>40</td>\n",
              "      <td>Nevins Street</td>\n",
              "      <td>Jay Street</td>\n",
              "      <td>16.56</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day4</th>\n",
              "      <td>May4</td>\n",
              "      <td>50</td>\n",
              "      <td>Jay Street</td>\n",
              "      <td>Nevins Street</td>\n",
              "      <td>20.70</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Month  Temperature       Stations     Stations 2  Wind Speed\n",
              "Day3  May3           40  Nevins Street     Jay Street       16.56\n",
              "Day4  May4           50     Jay Street  Nevins Street       20.70"
            ]
          },
          "metadata": {},
          "execution_count": 99
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ejbRhw8JjtcT",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "outputId": "273620e3-7e15-4fc9-b02c-63e98eafe09b"
      },
      "source": [
        "# Complex selection\n",
        "\n",
        "df[(df['Temperature'] > 32) & (df['Wind Speed'] < 20)]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Month</th>\n",
              "      <th>Temperature</th>\n",
              "      <th>Stations</th>\n",
              "      <th>Stations 2</th>\n",
              "      <th>Wind Speed</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Day2</th>\n",
              "      <td>May2</td>\n",
              "      <td>35</td>\n",
              "      <td>Carlton Ave</td>\n",
              "      <td>Carlton Ave</td>\n",
              "      <td>14.49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Day3</th>\n",
              "      <td>May3</td>\n",
              "      <td>40</td>\n",
              "      <td>Nevins Street</td>\n",
              "      <td>Jay Street</td>\n",
              "      <td>16.56</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Month  Temperature       Stations   Stations 2  Wind Speed\n",
              "Day2  May2           35    Carlton Ave  Carlton Ave       14.49\n",
              "Day3  May3           40  Nevins Street   Jay Street       16.56"
            ]
          },
          "metadata": {},
          "execution_count": 100
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VV5ToWoyjt3h"
      },
      "source": [
        "# Question: What is the count of pokemon that have 'null' in type 2?\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6xlFkhb5juWa",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "139cef32-92c8-4d32-f9ca-0d677aa6018b"
      },
      "source": [
        "# Getting unique values for column 'Type 1' with help of unique function\n",
        "# The return type is ndarray which consist of n rows and columns \n",
        "# (18,) - Represents 18 rows and 1 column \n",
        "\n",
        "print(pokemon_data['Type 1'].unique())\n",
        "print(pokemon_data['Type 1'].unique().size)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['Grass' 'Fire' 'Water' 'Bug' 'Normal' 'Poison' 'Electric' 'Ground'\n",
            " 'Fairy' 'Fighting' 'Psychic' 'Rock' 'Ghost' 'Ice' 'Dragon' 'Dark' 'Steel'\n",
            " 'Flying']\n",
            "18\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pZ3EPhlMlKgX"
      },
      "source": [
        "### Data cleanup"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vZcHOWr9lMys",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "outputId": "ec96c7fc-0003-48c3-e0d8-2fa13945043b"
      },
      "source": [
        "# removing null containing rows\n",
        "\n",
        "pokemon_data.dropna()\n",
        "\n",
        "# since inplace is not set, values/rows will not be removed"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Name</th>\n",
              "      <th>Type 1</th>\n",
              "      <th>Type 2</th>\n",
              "      <th>HP</th>\n",
              "      <th>Attack</th>\n",
              "      <th>Defense</th>\n",
              "      <th>Sp. Atk</th>\n",
              "      <th>Sp. Def</th>\n",
              "      <th>Speed</th>\n",
              "      <th>Generation</th>\n",
              "      <th>Legendary</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>#</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Bulbasaur</td>\n",
              "      <td>Grass</td>\n",
              "      <td>Poison</td>\n",
              "      <td>45</td>\n",
              "      <td>49</td>\n",
              "      <td>49</td>\n",
              "      <td>65</td>\n",
              "      <td>65</td>\n",
              "      <td>45</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Ivysaur</td>\n",
              "      <td>Grass</td>\n",
              "      <td>Poison</td>\n",
              "      <td>60</td>\n",
              "      <td>62</td>\n",
              "      <td>63</td>\n",
              "      <td>80</td>\n",
              "      <td>80</td>\n",
              "      <td>60</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Venusaur</td>\n",
              "      <td>Grass</td>\n",
              "      <td>Poison</td>\n",
              "      <td>80</td>\n",
              "      <td>82</td>\n",
              "      <td>83</td>\n",
              "      <td>100</td>\n",
              "      <td>100</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>VenusaurMega Venusaur</td>\n",
              "      <td>Grass</td>\n",
              "      <td>Poison</td>\n",
              "      <td>80</td>\n",
              "      <td>100</td>\n",
              "      <td>123</td>\n",
              "      <td>122</td>\n",
              "      <td>120</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Charizard</td>\n",
              "      <td>Fire</td>\n",
              "      <td>Flying</td>\n",
              "      <td>78</td>\n",
              "      <td>84</td>\n",
              "      <td>78</td>\n",
              "      <td>109</td>\n",
              "      <td>85</td>\n",
              "      <td>100</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>719</th>\n",
              "      <td>Diancie</td>\n",
              "      <td>Rock</td>\n",
              "      <td>Fairy</td>\n",
              "      <td>50</td>\n",
              "      <td>100</td>\n",
              "      <td>150</td>\n",
              "      <td>100</td>\n",
              "      <td>150</td>\n",
              "      <td>50</td>\n",
              "      <td>6</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>719</th>\n",
              "      <td>DiancieMega Diancie</td>\n",
              "      <td>Rock</td>\n",
              "      <td>Fairy</td>\n",
              "      <td>50</td>\n",
              "      <td>160</td>\n",
              "      <td>110</td>\n",
              "      <td>160</td>\n",
              "      <td>110</td>\n",
              "      <td>110</td>\n",
              "      <td>6</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>720</th>\n",
              "      <td>HoopaHoopa Confined</td>\n",
              "      <td>Psychic</td>\n",
              "      <td>Ghost</td>\n",
              "      <td>80</td>\n",
              "      <td>110</td>\n",
              "      <td>60</td>\n",
              "      <td>150</td>\n",
              "      <td>130</td>\n",
              "      <td>70</td>\n",
              "      <td>6</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>720</th>\n",
              "      <td>HoopaHoopa Unbound</td>\n",
              "      <td>Psychic</td>\n",
              "      <td>Dark</td>\n",
              "      <td>80</td>\n",
              "      <td>160</td>\n",
              "      <td>60</td>\n",
              "      <td>170</td>\n",
              "      <td>130</td>\n",
              "      <td>80</td>\n",
              "      <td>6</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>721</th>\n",
              "      <td>Volcanion</td>\n",
              "      <td>Fire</td>\n",
              "      <td>Water</td>\n",
              "      <td>80</td>\n",
              "      <td>110</td>\n",
              "      <td>120</td>\n",
              "      <td>130</td>\n",
              "      <td>90</td>\n",
              "      <td>70</td>\n",
              "      <td>6</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>414 rows × 11 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                      Name   Type 1  Type 2  ...  Speed  Generation  Legendary\n",
              "#                                            ...                              \n",
              "1                Bulbasaur    Grass  Poison  ...     45           1      False\n",
              "2                  Ivysaur    Grass  Poison  ...     60           1      False\n",
              "3                 Venusaur    Grass  Poison  ...     80           1      False\n",
              "3    VenusaurMega Venusaur    Grass  Poison  ...     80           1      False\n",
              "6                Charizard     Fire  Flying  ...    100           1      False\n",
              "..                     ...      ...     ...  ...    ...         ...        ...\n",
              "719                Diancie     Rock   Fairy  ...     50           6       True\n",
              "719    DiancieMega Diancie     Rock   Fairy  ...    110           6       True\n",
              "720    HoopaHoopa Confined  Psychic   Ghost  ...     70           6       True\n",
              "720     HoopaHoopa Unbound  Psychic    Dark  ...     80           6       True\n",
              "721              Volcanion     Fire   Water  ...     70           6       True\n",
              "\n",
              "[414 rows x 11 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 104
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aD8H5957lNDs",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "outputId": "87242c73-7f94-4a87-ed57-8d9932dfc6ad"
      },
      "source": [
        "# Masking and use of loc\n",
        "# Converting to string datatype with astype\n",
        "\n",
        "pokemon_data['Type 2'] = pokemon_data['Type 2'].astype(str)\n",
        "mask = (pokemon_data['Type 2']!='nan')\n",
        "\n",
        "pk_data = pokemon_data.loc[mask]\n",
        "pk_data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Name</th>\n",
              "      <th>Type 1</th>\n",
              "      <th>Type 2</th>\n",
              "      <th>HP</th>\n",
              "      <th>Attack</th>\n",
              "      <th>Defense</th>\n",
              "      <th>Sp. Atk</th>\n",
              "      <th>Sp. Def</th>\n",
              "      <th>Speed</th>\n",
              "      <th>Generation</th>\n",
              "      <th>Legendary</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>#</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Bulbasaur</td>\n",
              "      <td>Grass</td>\n",
              "      <td>Poison</td>\n",
              "      <td>45</td>\n",
              "      <td>49</td>\n",
              "      <td>49</td>\n",
              "      <td>65</td>\n",
              "      <td>65</td>\n",
              "      <td>45</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Ivysaur</td>\n",
              "      <td>Grass</td>\n",
              "      <td>Poison</td>\n",
              "      <td>60</td>\n",
              "      <td>62</td>\n",
              "      <td>63</td>\n",
              "      <td>80</td>\n",
              "      <td>80</td>\n",
              "      <td>60</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Venusaur</td>\n",
              "      <td>Grass</td>\n",
              "      <td>Poison</td>\n",
              "      <td>80</td>\n",
              "      <td>82</td>\n",
              "      <td>83</td>\n",
              "      <td>100</td>\n",
              "      <td>100</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>VenusaurMega Venusaur</td>\n",
              "      <td>Grass</td>\n",
              "      <td>Poison</td>\n",
              "      <td>80</td>\n",
              "      <td>100</td>\n",
              "      <td>123</td>\n",
              "      <td>122</td>\n",
              "      <td>120</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Charizard</td>\n",
              "      <td>Fire</td>\n",
              "      <td>Flying</td>\n",
              "      <td>78</td>\n",
              "      <td>84</td>\n",
              "      <td>78</td>\n",
              "      <td>109</td>\n",
              "      <td>85</td>\n",
              "      <td>100</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>719</th>\n",
              "      <td>Diancie</td>\n",
              "      <td>Rock</td>\n",
              "      <td>Fairy</td>\n",
              "      <td>50</td>\n",
              "      <td>100</td>\n",
              "      <td>150</td>\n",
              "      <td>100</td>\n",
              "      <td>150</td>\n",
              "      <td>50</td>\n",
              "      <td>6</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>719</th>\n",
              "      <td>DiancieMega Diancie</td>\n",
              "      <td>Rock</td>\n",
              "      <td>Fairy</td>\n",
              "      <td>50</td>\n",
              "      <td>160</td>\n",
              "      <td>110</td>\n",
              "      <td>160</td>\n",
              "      <td>110</td>\n",
              "      <td>110</td>\n",
              "      <td>6</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>720</th>\n",
              "      <td>HoopaHoopa Confined</td>\n",
              "      <td>Psychic</td>\n",
              "      <td>Ghost</td>\n",
              "      <td>80</td>\n",
              "      <td>110</td>\n",
              "      <td>60</td>\n",
              "      <td>150</td>\n",
              "      <td>130</td>\n",
              "      <td>70</td>\n",
              "      <td>6</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>720</th>\n",
              "      <td>HoopaHoopa Unbound</td>\n",
              "      <td>Psychic</td>\n",
              "      <td>Dark</td>\n",
              "      <td>80</td>\n",
              "      <td>160</td>\n",
              "      <td>60</td>\n",
              "      <td>170</td>\n",
              "      <td>130</td>\n",
              "      <td>80</td>\n",
              "      <td>6</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>721</th>\n",
              "      <td>Volcanion</td>\n",
              "      <td>Fire</td>\n",
              "      <td>Water</td>\n",
              "      <td>80</td>\n",
              "      <td>110</td>\n",
              "      <td>120</td>\n",
              "      <td>130</td>\n",
              "      <td>90</td>\n",
              "      <td>70</td>\n",
              "      <td>6</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>414 rows × 11 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                      Name   Type 1  Type 2  ...  Speed  Generation  Legendary\n",
              "#                                            ...                              \n",
              "1                Bulbasaur    Grass  Poison  ...     45           1      False\n",
              "2                  Ivysaur    Grass  Poison  ...     60           1      False\n",
              "3                 Venusaur    Grass  Poison  ...     80           1      False\n",
              "3    VenusaurMega Venusaur    Grass  Poison  ...     80           1      False\n",
              "6                Charizard     Fire  Flying  ...    100           1      False\n",
              "..                     ...      ...     ...  ...    ...         ...        ...\n",
              "719                Diancie     Rock   Fairy  ...     50           6       True\n",
              "719    DiancieMega Diancie     Rock   Fairy  ...    110           6       True\n",
              "720    HoopaHoopa Confined  Psychic   Ghost  ...     70           6       True\n",
              "720     HoopaHoopa Unbound  Psychic    Dark  ...     80           6       True\n",
              "721              Volcanion     Fire   Water  ...     70           6       True\n",
              "\n",
              "[414 rows x 11 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 105
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kHLBHiyplefI"
      },
      "source": [
        "### Sort"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "d98w6vfTlNRy",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "outputId": "23dbd242-706b-4a0d-b8cb-145580d1aab7"
      },
      "source": [
        "# Can assign one or more column for sorting\n",
        "# Return type is dataframe object\n",
        "\n",
        "pokemon_data.sort_values(by=['HP', 'Attack', 'Defense', 'Speed'], ascending = [False, True, False, True], inplace=True)\n",
        "pokemon_data.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Name</th>\n",
              "      <th>Type 1</th>\n",
              "      <th>Type 2</th>\n",
              "      <th>HP</th>\n",
              "      <th>Attack</th>\n",
              "      <th>Defense</th>\n",
              "      <th>Sp. Atk</th>\n",
              "      <th>Sp. Def</th>\n",
              "      <th>Speed</th>\n",
              "      <th>Generation</th>\n",
              "      <th>Legendary</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>#</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>242</th>\n",
              "      <td>Blissey</td>\n",
              "      <td>Normal</td>\n",
              "      <td>nan</td>\n",
              "      <td>255</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>75</td>\n",
              "      <td>135</td>\n",
              "      <td>55</td>\n",
              "      <td>2</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>113</th>\n",
              "      <td>Chansey</td>\n",
              "      <td>Normal</td>\n",
              "      <td>nan</td>\n",
              "      <td>250</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>35</td>\n",
              "      <td>105</td>\n",
              "      <td>50</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>202</th>\n",
              "      <td>Wobbuffet</td>\n",
              "      <td>Psychic</td>\n",
              "      <td>nan</td>\n",
              "      <td>190</td>\n",
              "      <td>33</td>\n",
              "      <td>58</td>\n",
              "      <td>33</td>\n",
              "      <td>58</td>\n",
              "      <td>33</td>\n",
              "      <td>2</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>321</th>\n",
              "      <td>Wailord</td>\n",
              "      <td>Water</td>\n",
              "      <td>nan</td>\n",
              "      <td>170</td>\n",
              "      <td>90</td>\n",
              "      <td>45</td>\n",
              "      <td>90</td>\n",
              "      <td>45</td>\n",
              "      <td>60</td>\n",
              "      <td>3</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>594</th>\n",
              "      <td>Alomomola</td>\n",
              "      <td>Water</td>\n",
              "      <td>nan</td>\n",
              "      <td>165</td>\n",
              "      <td>75</td>\n",
              "      <td>80</td>\n",
              "      <td>40</td>\n",
              "      <td>45</td>\n",
              "      <td>65</td>\n",
              "      <td>5</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Name   Type 1 Type 2   HP  ...  Sp. Def  Speed  Generation  Legendary\n",
              "#                                    ...                                       \n",
              "242    Blissey   Normal    nan  255  ...      135     55           2      False\n",
              "113    Chansey   Normal    nan  250  ...      105     50           1      False\n",
              "202  Wobbuffet  Psychic    nan  190  ...       58     33           2      False\n",
              "321    Wailord    Water    nan  170  ...       45     60           3      False\n",
              "594  Alomomola    Water    nan  165  ...       45     65           5      False\n",
              "\n",
              "[5 rows x 11 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 106
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XELbuy2blrZX"
      },
      "source": [
        "### Groupby"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZI740Q70l987",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 645
        },
        "outputId": "a073b194-64be-419d-e31b-2b1f12622c0e"
      },
      "source": [
        "# Normal Group by\n",
        "\n",
        "pokemon_data.groupby('Type 1').head(1)\n",
        "\n",
        "# The above code displays the top row within each group."
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Name</th>\n",
              "      <th>Type 1</th>\n",
              "      <th>Type 2</th>\n",
              "      <th>HP</th>\n",
              "      <th>Attack</th>\n",
              "      <th>Defense</th>\n",
              "      <th>Sp. Atk</th>\n",
              "      <th>Sp. Def</th>\n",
              "      <th>Speed</th>\n",
              "      <th>Generation</th>\n",
              "      <th>Legendary</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>#</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>242</th>\n",
              "      <td>Blissey</td>\n",
              "      <td>Normal</td>\n",
              "      <td>nan</td>\n",
              "      <td>255</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>75</td>\n",
              "      <td>135</td>\n",
              "      <td>55</td>\n",
              "      <td>2</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>202</th>\n",
              "      <td>Wobbuffet</td>\n",
              "      <td>Psychic</td>\n",
              "      <td>nan</td>\n",
              "      <td>190</td>\n",
              "      <td>33</td>\n",
              "      <td>58</td>\n",
              "      <td>33</td>\n",
              "      <td>58</td>\n",
              "      <td>33</td>\n",
              "      <td>2</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>321</th>\n",
              "      <td>Wailord</td>\n",
              "      <td>Water</td>\n",
              "      <td>nan</td>\n",
              "      <td>170</td>\n",
              "      <td>90</td>\n",
              "      <td>45</td>\n",
              "      <td>90</td>\n",
              "      <td>45</td>\n",
              "      <td>60</td>\n",
              "      <td>3</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>426</th>\n",
              "      <td>Drifblim</td>\n",
              "      <td>Ghost</td>\n",
              "      <td>Flying</td>\n",
              "      <td>150</td>\n",
              "      <td>80</td>\n",
              "      <td>44</td>\n",
              "      <td>90</td>\n",
              "      <td>54</td>\n",
              "      <td>80</td>\n",
              "      <td>4</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>297</th>\n",
              "      <td>Hariyama</td>\n",
              "      <td>Fighting</td>\n",
              "      <td>nan</td>\n",
              "      <td>144</td>\n",
              "      <td>120</td>\n",
              "      <td>60</td>\n",
              "      <td>40</td>\n",
              "      <td>60</td>\n",
              "      <td>50</td>\n",
              "      <td>3</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>716</th>\n",
              "      <td>Xerneas</td>\n",
              "      <td>Fairy</td>\n",
              "      <td>nan</td>\n",
              "      <td>126</td>\n",
              "      <td>131</td>\n",
              "      <td>95</td>\n",
              "      <td>131</td>\n",
              "      <td>98</td>\n",
              "      <td>99</td>\n",
              "      <td>6</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>717</th>\n",
              "      <td>Yveltal</td>\n",
              "      <td>Dark</td>\n",
              "      <td>Flying</td>\n",
              "      <td>126</td>\n",
              "      <td>131</td>\n",
              "      <td>95</td>\n",
              "      <td>131</td>\n",
              "      <td>98</td>\n",
              "      <td>99</td>\n",
              "      <td>6</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>646</th>\n",
              "      <td>KyuremWhite Kyurem</td>\n",
              "      <td>Dragon</td>\n",
              "      <td>Ice</td>\n",
              "      <td>125</td>\n",
              "      <td>120</td>\n",
              "      <td>90</td>\n",
              "      <td>170</td>\n",
              "      <td>100</td>\n",
              "      <td>95</td>\n",
              "      <td>5</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>699</th>\n",
              "      <td>Aurorus</td>\n",
              "      <td>Rock</td>\n",
              "      <td>Ice</td>\n",
              "      <td>123</td>\n",
              "      <td>77</td>\n",
              "      <td>72</td>\n",
              "      <td>99</td>\n",
              "      <td>92</td>\n",
              "      <td>58</td>\n",
              "      <td>6</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>673</th>\n",
              "      <td>Gogoat</td>\n",
              "      <td>Grass</td>\n",
              "      <td>nan</td>\n",
              "      <td>123</td>\n",
              "      <td>100</td>\n",
              "      <td>62</td>\n",
              "      <td>97</td>\n",
              "      <td>81</td>\n",
              "      <td>68</td>\n",
              "      <td>6</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>244</th>\n",
              "      <td>Entei</td>\n",
              "      <td>Fire</td>\n",
              "      <td>nan</td>\n",
              "      <td>115</td>\n",
              "      <td>115</td>\n",
              "      <td>85</td>\n",
              "      <td>90</td>\n",
              "      <td>75</td>\n",
              "      <td>100</td>\n",
              "      <td>2</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>464</th>\n",
              "      <td>Rhyperior</td>\n",
              "      <td>Ground</td>\n",
              "      <td>Rock</td>\n",
              "      <td>115</td>\n",
              "      <td>140</td>\n",
              "      <td>130</td>\n",
              "      <td>55</td>\n",
              "      <td>55</td>\n",
              "      <td>40</td>\n",
              "      <td>4</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>365</th>\n",
              "      <td>Walrein</td>\n",
              "      <td>Ice</td>\n",
              "      <td>Water</td>\n",
              "      <td>110</td>\n",
              "      <td>80</td>\n",
              "      <td>90</td>\n",
              "      <td>95</td>\n",
              "      <td>90</td>\n",
              "      <td>65</td>\n",
              "      <td>3</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>89</th>\n",
              "      <td>Muk</td>\n",
              "      <td>Poison</td>\n",
              "      <td>nan</td>\n",
              "      <td>105</td>\n",
              "      <td>105</td>\n",
              "      <td>75</td>\n",
              "      <td>65</td>\n",
              "      <td>100</td>\n",
              "      <td>50</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>385</th>\n",
              "      <td>Jirachi</td>\n",
              "      <td>Steel</td>\n",
              "      <td>Psychic</td>\n",
              "      <td>100</td>\n",
              "      <td>100</td>\n",
              "      <td>100</td>\n",
              "      <td>100</td>\n",
              "      <td>100</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>True</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>181</th>\n",
              "      <td>Ampharos</td>\n",
              "      <td>Electric</td>\n",
              "      <td>nan</td>\n",
              "      <td>90</td>\n",
              "      <td>75</td>\n",
              "      <td>85</td>\n",
              "      <td>115</td>\n",
              "      <td>90</td>\n",
              "      <td>55</td>\n",
              "      <td>2</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>469</th>\n",
              "      <td>Yanmega</td>\n",
              "      <td>Bug</td>\n",
              "      <td>Flying</td>\n",
              "      <td>86</td>\n",
              "      <td>76</td>\n",
              "      <td>86</td>\n",
              "      <td>116</td>\n",
              "      <td>56</td>\n",
              "      <td>95</td>\n",
              "      <td>4</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>715</th>\n",
              "      <td>Noivern</td>\n",
              "      <td>Flying</td>\n",
              "      <td>Dragon</td>\n",
              "      <td>85</td>\n",
              "      <td>70</td>\n",
              "      <td>80</td>\n",
              "      <td>97</td>\n",
              "      <td>80</td>\n",
              "      <td>123</td>\n",
              "      <td>6</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                   Name    Type 1   Type 2  ...  Speed  Generation  Legendary\n",
              "#                                           ...                              \n",
              "242             Blissey    Normal      nan  ...     55           2      False\n",
              "202           Wobbuffet   Psychic      nan  ...     33           2      False\n",
              "321             Wailord     Water      nan  ...     60           3      False\n",
              "426            Drifblim     Ghost   Flying  ...     80           4      False\n",
              "297            Hariyama  Fighting      nan  ...     50           3      False\n",
              "716             Xerneas     Fairy      nan  ...     99           6       True\n",
              "717             Yveltal      Dark   Flying  ...     99           6       True\n",
              "646  KyuremWhite Kyurem    Dragon      Ice  ...     95           5       True\n",
              "699             Aurorus      Rock      Ice  ...     58           6      False\n",
              "673              Gogoat     Grass      nan  ...     68           6      False\n",
              "244               Entei      Fire      nan  ...    100           2       True\n",
              "464           Rhyperior    Ground     Rock  ...     40           4      False\n",
              "365             Walrein       Ice    Water  ...     65           3      False\n",
              "89                  Muk    Poison      nan  ...     50           1      False\n",
              "385             Jirachi     Steel  Psychic  ...    100           3       True\n",
              "181            Ampharos  Electric      nan  ...     55           2      False\n",
              "469             Yanmega       Bug   Flying  ...     95           4      False\n",
              "715             Noivern    Flying   Dragon  ...    123           6      False\n",
              "\n",
              "[18 rows x 11 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 107
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_hxuBcWYlucC",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 645
        },
        "outputId": "737dbeed-0f50-4f7a-9809-184afb7bda2f"
      },
      "source": [
        "# Aggregate Functions on groups\n",
        "\n",
        "pokemon_data.groupby('Type 1').mean()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>HP</th>\n",
              "      <th>Attack</th>\n",
              "      <th>Defense</th>\n",
              "      <th>Sp. Atk</th>\n",
              "      <th>Sp. Def</th>\n",
              "      <th>Speed</th>\n",
              "      <th>Generation</th>\n",
              "      <th>Legendary</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Type 1</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Bug</th>\n",
              "      <td>56.884058</td>\n",
              "      <td>70.971014</td>\n",
              "      <td>70.724638</td>\n",
              "      <td>53.869565</td>\n",
              "      <td>64.797101</td>\n",
              "      <td>61.681159</td>\n",
              "      <td>3.217391</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dark</th>\n",
              "      <td>66.806452</td>\n",
              "      <td>88.387097</td>\n",
              "      <td>70.225806</td>\n",
              "      <td>74.645161</td>\n",
              "      <td>69.516129</td>\n",
              "      <td>76.161290</td>\n",
              "      <td>4.032258</td>\n",
              "      <td>0.064516</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dragon</th>\n",
              "      <td>83.312500</td>\n",
              "      <td>112.125000</td>\n",
              "      <td>86.375000</td>\n",
              "      <td>96.843750</td>\n",
              "      <td>88.843750</td>\n",
              "      <td>83.031250</td>\n",
              "      <td>3.875000</td>\n",
              "      <td>0.375000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Electric</th>\n",
              "      <td>59.795455</td>\n",
              "      <td>69.090909</td>\n",
              "      <td>66.295455</td>\n",
              "      <td>90.022727</td>\n",
              "      <td>73.704545</td>\n",
              "      <td>84.500000</td>\n",
              "      <td>3.272727</td>\n",
              "      <td>0.090909</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Fairy</th>\n",
              "      <td>74.117647</td>\n",
              "      <td>61.529412</td>\n",
              "      <td>65.705882</td>\n",
              "      <td>78.529412</td>\n",
              "      <td>84.705882</td>\n",
              "      <td>48.588235</td>\n",
              "      <td>4.117647</td>\n",
              "      <td>0.058824</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Fighting</th>\n",
              "      <td>69.851852</td>\n",
              "      <td>96.777778</td>\n",
              "      <td>65.925926</td>\n",
              "      <td>53.111111</td>\n",
              "      <td>64.703704</td>\n",
              "      <td>66.074074</td>\n",
              "      <td>3.370370</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Fire</th>\n",
              "      <td>69.903846</td>\n",
              "      <td>84.769231</td>\n",
              "      <td>67.769231</td>\n",
              "      <td>88.980769</td>\n",
              "      <td>72.211538</td>\n",
              "      <td>74.442308</td>\n",
              "      <td>3.211538</td>\n",
              "      <td>0.096154</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Flying</th>\n",
              "      <td>70.750000</td>\n",
              "      <td>78.750000</td>\n",
              "      <td>66.250000</td>\n",
              "      <td>94.250000</td>\n",
              "      <td>72.500000</td>\n",
              "      <td>102.500000</td>\n",
              "      <td>5.500000</td>\n",
              "      <td>0.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Ghost</th>\n",
              "      <td>64.437500</td>\n",
              "      <td>73.781250</td>\n",
              "      <td>81.187500</td>\n",
              "      <td>79.343750</td>\n",
              "      <td>76.468750</td>\n",
              "      <td>64.343750</td>\n",
              "      <td>4.187500</td>\n",
              "      <td>0.062500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Grass</th>\n",
              "      <td>67.271429</td>\n",
              "      <td>73.214286</td>\n",
              "      <td>70.800000</td>\n",
              "      <td>77.500000</td>\n",
              "      <td>70.428571</td>\n",
              "      <td>61.928571</td>\n",
              "      <td>3.357143</td>\n",
              "      <td>0.042857</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Ground</th>\n",
              "      <td>73.781250</td>\n",
              "      <td>95.750000</td>\n",
              "      <td>84.843750</td>\n",
              "      <td>56.468750</td>\n",
              "      <td>62.750000</td>\n",
              "      <td>63.906250</td>\n",
              "      <td>3.156250</td>\n",
              "      <td>0.125000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Ice</th>\n",
              "      <td>72.000000</td>\n",
              "      <td>72.750000</td>\n",
              "      <td>71.416667</td>\n",
              "      <td>77.541667</td>\n",
              "      <td>76.291667</td>\n",
              "      <td>63.458333</td>\n",
              "      <td>3.541667</td>\n",
              "      <td>0.083333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Normal</th>\n",
              "      <td>77.275510</td>\n",
              "      <td>73.469388</td>\n",
              "      <td>59.846939</td>\n",
              "      <td>55.816327</td>\n",
              "      <td>63.724490</td>\n",
              "      <td>71.551020</td>\n",
              "      <td>3.051020</td>\n",
              "      <td>0.020408</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Poison</th>\n",
              "      <td>67.250000</td>\n",
              "      <td>74.678571</td>\n",
              "      <td>68.821429</td>\n",
              "      <td>60.428571</td>\n",
              "      <td>64.392857</td>\n",
              "      <td>63.571429</td>\n",
              "      <td>2.535714</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Psychic</th>\n",
              "      <td>70.631579</td>\n",
              "      <td>71.456140</td>\n",
              "      <td>67.684211</td>\n",
              "      <td>98.403509</td>\n",
              "      <td>86.280702</td>\n",
              "      <td>81.491228</td>\n",
              "      <td>3.385965</td>\n",
              "      <td>0.245614</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Rock</th>\n",
              "      <td>65.363636</td>\n",
              "      <td>92.863636</td>\n",
              "      <td>100.795455</td>\n",
              "      <td>63.340909</td>\n",
              "      <td>75.477273</td>\n",
              "      <td>55.909091</td>\n",
              "      <td>3.454545</td>\n",
              "      <td>0.090909</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Steel</th>\n",
              "      <td>65.222222</td>\n",
              "      <td>92.703704</td>\n",
              "      <td>126.370370</td>\n",
              "      <td>67.518519</td>\n",
              "      <td>80.629630</td>\n",
              "      <td>55.259259</td>\n",
              "      <td>3.851852</td>\n",
              "      <td>0.148148</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Water</th>\n",
              "      <td>72.062500</td>\n",
              "      <td>74.151786</td>\n",
              "      <td>72.946429</td>\n",
              "      <td>74.812500</td>\n",
              "      <td>70.517857</td>\n",
              "      <td>65.964286</td>\n",
              "      <td>2.857143</td>\n",
              "      <td>0.035714</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 HP      Attack     Defense  ...       Speed  Generation  Legendary\n",
              "Type 1                                       ...                                   \n",
              "Bug       56.884058   70.971014   70.724638  ...   61.681159    3.217391   0.000000\n",
              "Dark      66.806452   88.387097   70.225806  ...   76.161290    4.032258   0.064516\n",
              "Dragon    83.312500  112.125000   86.375000  ...   83.031250    3.875000   0.375000\n",
              "Electric  59.795455   69.090909   66.295455  ...   84.500000    3.272727   0.090909\n",
              "Fairy     74.117647   61.529412   65.705882  ...   48.588235    4.117647   0.058824\n",
              "Fighting  69.851852   96.777778   65.925926  ...   66.074074    3.370370   0.000000\n",
              "Fire      69.903846   84.769231   67.769231  ...   74.442308    3.211538   0.096154\n",
              "Flying    70.750000   78.750000   66.250000  ...  102.500000    5.500000   0.500000\n",
              "Ghost     64.437500   73.781250   81.187500  ...   64.343750    4.187500   0.062500\n",
              "Grass     67.271429   73.214286   70.800000  ...   61.928571    3.357143   0.042857\n",
              "Ground    73.781250   95.750000   84.843750  ...   63.906250    3.156250   0.125000\n",
              "Ice       72.000000   72.750000   71.416667  ...   63.458333    3.541667   0.083333\n",
              "Normal    77.275510   73.469388   59.846939  ...   71.551020    3.051020   0.020408\n",
              "Poison    67.250000   74.678571   68.821429  ...   63.571429    2.535714   0.000000\n",
              "Psychic   70.631579   71.456140   67.684211  ...   81.491228    3.385965   0.245614\n",
              "Rock      65.363636   92.863636  100.795455  ...   55.909091    3.454545   0.090909\n",
              "Steel     65.222222   92.703704  126.370370  ...   55.259259    3.851852   0.148148\n",
              "Water     72.062500   74.151786   72.946429  ...   65.964286    2.857143   0.035714\n",
              "\n",
              "[18 rows x 8 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 108
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n0madfCqluro"
      },
      "source": [
        "# groupby with more than 1 column order in which columns are specified is important\n",
        "# Question: Group by on Type 1 and Type 2 pokemon and display them\n",
        "\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Hcm9YcYQKTl7"
      },
      "source": [
        "## Data Visualization\n",
        "\n",
        "Access the Matplotlib documentation from [here](https://matplotlib.org/) and Seaborn documentation from [here](https://seaborn.pydata.org/)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "F6CIQst1nfQH",
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": "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",
              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 111
        },
        "outputId": "dafffac1-9bce-413d-c67a-dd021ce5dc4d"
      },
      "source": [
        "from google.colab import files\n",
        "files.upload()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-e739ede4-3538-412f-ac4e-c3d1650dbe8a\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-e739ede4-3538-412f-ac4e-c3d1650dbe8a\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saving pokemon_data.csv to pokemon_data (1).csv\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'pokemon_data.csv': b\"#,Name,Type 1,Type 2,HP,Attack,Defense,Sp. Atk,Sp. Def,Speed,Generation,Legendary\\n1,Bulbasaur,Grass,Poison,45,49,49,65,65,45,1,FALSE\\n2,Ivysaur,Grass,Poison,60,62,63,80,80,60,1,FALSE\\n3,Venusaur,Grass,Poison,80,82,83,100,100,80,1,FALSE\\n3,VenusaurMega Venusaur,Grass,Poison,80,100,123,122,120,80,1,FALSE\\n4,Charmander,Fire,,39,52,43,60,50,65,1,FALSE\\n5,Charmeleon,Fire,,58,64,58,80,65,80,1,FALSE\\n6,Charizard,Fire,Flying,78,84,78,109,85,100,1,FALSE\\n6,CharizardMega Charizard X,Fire,Dragon,78,130,111,130,85,100,1,FALSE\\n6,CharizardMega Charizard Y,Fire,Flying,78,104,78,159,115,100,1,FALSE\\n7,Squirtle,Water,,44,48,65,50,64,43,1,FALSE\\n8,Wartortle,Water,,59,63,80,65,80,58,1,FALSE\\n9,Blastoise,Water,,79,83,100,85,105,78,1,FALSE\\n9,BlastoiseMega Blastoise,Water,,79,103,120,135,115,78,1,FALSE\\n10,Caterpie,Bug,,45,30,35,20,20,45,1,FALSE\\n11,Metapod,Bug,,50,20,55,25,25,30,1,FALSE\\n12,Butterfree,Bug,Flying,60,45,50,90,80,70,1,FALSE\\n13,Weedle,Bug,Poison,40,35,30,20,20,50,1,FALSE\\n14,Kakuna,Bug,Poison,45,25,50,25,25,35,1,FALSE\\n15,Beedrill,Bug,Poison,65,90,40,45,80,75,1,FALSE\\n15,BeedrillMega Beedrill,Bug,Poison,65,150,40,15,80,145,1,FALSE\\n16,Pidgey,Normal,Flying,40,45,40,35,35,56,1,FALSE\\n17,Pidgeotto,Normal,Flying,63,60,55,50,50,71,1,FALSE\\n18,Pidgeot,Normal,Flying,83,80,75,70,70,101,1,FALSE\\n18,PidgeotMega Pidgeot,Normal,Flying,83,80,80,135,80,121,1,FALSE\\n19,Rattata,Normal,,30,56,35,25,35,72,1,FALSE\\n20,Raticate,Normal,,55,81,60,50,70,97,1,FALSE\\n21,Spearow,Normal,Flying,40,60,30,31,31,70,1,FALSE\\n22,Fearow,Normal,Flying,65,90,65,61,61,100,1,FALSE\\n23,Ekans,Poison,,35,60,44,40,54,55,1,FALSE\\n24,Arbok,Poison,,60,85,69,65,79,80,1,FALSE\\n25,Pikachu,Electric,,35,55,40,50,50,90,1,FALSE\\n26,Raichu,Electric,,60,90,55,90,80,110,1,FALSE\\n27,Sandshrew,Ground,,50,75,85,20,30,40,1,FALSE\\n28,Sandslash,Ground,,75,100,110,45,55,65,1,FALSE\\n29,Nidoran (Female),Poison,,55,47,52,40,40,41,1,FALSE\\n30,Nidorina,Poison,,70,62,67,55,55,56,1,FALSE\\n31,Nidoqueen,Poison,Ground,90,92,87,75,85,76,1,FALSE\\n32,Nidoran (Male),Poison,,46,57,40,40,40,50,1,FALSE\\n33,Nidorino,Poison,,61,72,57,55,55,65,1,FALSE\\n34,Nidoking,Poison,Ground,81,102,77,85,75,85,1,FALSE\\n35,Clefairy,Fairy,,70,45,48,60,65,35,1,FALSE\\n36,Clefable,Fairy,,95,70,73,95,90,60,1,FALSE\\n37,Vulpix,Fire,,38,41,40,50,65,65,1,FALSE\\n38,Ninetales,Fire,,73,76,75,81,100,100,1,FALSE\\n39,Jigglypuff,Normal,Fairy,115,45,20,45,25,20,1,FALSE\\n40,Wigglytuff,Normal,Fairy,140,70,45,85,50,45,1,FALSE\\n41,Zubat,Poison,Flying,40,45,35,30,40,55,1,FALSE\\n42,Golbat,Poison,Flying,75,80,70,65,75,90,1,FALSE\\n43,Oddish,Grass,Poison,45,50,55,75,65,30,1,FALSE\\n44,Gloom,Grass,Poison,60,65,70,85,75,40,1,FALSE\\n45,Vileplume,Grass,Poison,75,80,85,110,90,50,1,FALSE\\n46,Paras,Bug,Grass,35,70,55,45,55,25,1,FALSE\\n47,Parasect,Bug,Grass,60,95,80,60,80,30,1,FALSE\\n48,Venonat,Bug,Poison,60,55,50,40,55,45,1,FALSE\\n49,Venomoth,Bug,Poison,70,65,60,90,75,90,1,FALSE\\n50,Diglett,Ground,,10,55,25,35,45,95,1,FALSE\\n51,Dugtrio,Ground,,35,80,50,50,70,120,1,FALSE\\n52,Meowth,Normal,,40,45,35,40,40,90,1,FALSE\\n53,Persian,Normal,,65,70,60,65,65,115,1,FALSE\\n54,Psyduck,Water,,50,52,48,65,50,55,1,FALSE\\n55,Golduck,Water,,80,82,78,95,80,85,1,FALSE\\n56,Mankey,Fighting,,40,80,35,35,45,70,1,FALSE\\n57,Primeape,Fighting,,65,105,60,60,70,95,1,FALSE\\n58,Growlithe,Fire,,55,70,45,70,50,60,1,FALSE\\n59,Arcanine,Fire,,90,110,80,100,80,95,1,FALSE\\n60,Poliwag,Water,,40,50,40,40,40,90,1,FALSE\\n61,Poliwhirl,Water,,65,65,65,50,50,90,1,FALSE\\n62,Poliwrath,Water,Fighting,90,95,95,70,90,70,1,FALSE\\n63,Abra,Psychic,,25,20,15,105,55,90,1,FALSE\\n64,Kadabra,Psychic,,40,35,30,120,70,105,1,FALSE\\n65,Alakazam,Psychic,,55,50,45,135,95,120,1,FALSE\\n65,AlakazamMega Alakazam,Psychic,,55,50,65,175,95,150,1,FALSE\\n66,Machop,Fighting,,70,80,50,35,35,35,1,FALSE\\n67,Machoke,Fighting,,80,100,70,50,60,45,1,FALSE\\n68,Machamp,Fighting,,90,130,80,65,85,55,1,FALSE\\n69,Bellsprout,Grass,Poison,50,75,35,70,30,40,1,FALSE\\n70,Weepinbell,Grass,Poison,65,90,50,85,45,55,1,FALSE\\n71,Victreebel,Grass,Poison,80,105,65,100,70,70,1,FALSE\\n72,Tentacool,Water,Poison,40,40,35,50,100,70,1,FALSE\\n73,Tentacruel,Water,Poison,80,70,65,80,120,100,1,FALSE\\n74,Geodude,Rock,Ground,40,80,100,30,30,20,1,FALSE\\n75,Graveler,Rock,Ground,55,95,115,45,45,35,1,FALSE\\n76,Golem,Rock,Ground,80,120,130,55,65,45,1,FALSE\\n77,Ponyta,Fire,,50,85,55,65,65,90,1,FALSE\\n78,Rapidash,Fire,,65,100,70,80,80,105,1,FALSE\\n79,Slowpoke,Water,Psychic,90,65,65,40,40,15,1,FALSE\\n80,Slowbro,Water,Psychic,95,75,110,100,80,30,1,FALSE\\n80,SlowbroMega Slowbro,Water,Psychic,95,75,180,130,80,30,1,FALSE\\n81,Magnemite,Electric,Steel,25,35,70,95,55,45,1,FALSE\\n82,Magneton,Electric,Steel,50,60,95,120,70,70,1,FALSE\\n83,Farfetch'd,Normal,Flying,52,65,55,58,62,60,1,FALSE\\n84,Doduo,Normal,Flying,35,85,45,35,35,75,1,FALSE\\n85,Dodrio,Normal,Flying,60,110,70,60,60,100,1,FALSE\\n86,Seel,Water,,65,45,55,45,70,45,1,FALSE\\n87,Dewgong,Water,Ice,90,70,80,70,95,70,1,FALSE\\n88,Grimer,Poison,,80,80,50,40,50,25,1,FALSE\\n89,Muk,Poison,,105,105,75,65,100,50,1,FALSE\\n90,Shellder,Water,,30,65,100,45,25,40,1,FALSE\\n91,Cloyster,Water,Ice,50,95,180,85,45,70,1,FALSE\\n92,Gastly,Ghost,Poison,30,35,30,100,35,80,1,FALSE\\n93,Haunter,Ghost,Poison,45,50,45,115,55,95,1,FALSE\\n94,Gengar,Ghost,Poison,60,65,60,130,75,110,1,FALSE\\n94,GengarMega Gengar,Ghost,Poison,60,65,80,170,95,130,1,FALSE\\n95,Onix,Rock,Ground,35,45,160,30,45,70,1,FALSE\\n96,Drowzee,Psychic,,60,48,45,43,90,42,1,FALSE\\n97,Hypno,Psychic,,85,73,70,73,115,67,1,FALSE\\n98,Krabby,Water,,30,105,90,25,25,50,1,FALSE\\n99,Kingler,Water,,55,130,115,50,50,75,1,FALSE\\n100,Voltorb,Electric,,40,30,50,55,55,100,1,FALSE\\n101,Electrode,Electric,,60,50,70,80,80,140,1,FALSE\\n102,Exeggcute,Grass,Psychic,60,40,80,60,45,40,1,FALSE\\n103,Exeggutor,Grass,Psychic,95,95,85,125,65,55,1,FALSE\\n104,Cubone,Ground,,50,50,95,40,50,35,1,FALSE\\n105,Marowak,Ground,,60,80,110,50,80,45,1,FALSE\\n106,Hitmonlee,Fighting,,50,120,53,35,110,87,1,FALSE\\n107,Hitmonchan,Fighting,,50,105,79,35,110,76,1,FALSE\\n108,Lickitung,Normal,,90,55,75,60,75,30,1,FALSE\\n109,Koffing,Poison,,40,65,95,60,45,35,1,FALSE\\n110,Weezing,Poison,,65,90,120,85,70,60,1,FALSE\\n111,Rhyhorn,Ground,Rock,80,85,95,30,30,25,1,FALSE\\n112,Rhydon,Ground,Rock,105,130,120,45,45,40,1,FALSE\\n113,Chansey,Normal,,250,5,5,35,105,50,1,FALSE\\n114,Tangela,Grass,,65,55,115,100,40,60,1,FALSE\\n115,Kangaskhan,Normal,,105,95,80,40,80,90,1,FALSE\\n115,KangaskhanMega Kangaskhan,Normal,,105,125,100,60,100,100,1,FALSE\\n116,Horsea,Water,,30,40,70,70,25,60,1,FALSE\\n117,Seadra,Water,,55,65,95,95,45,85,1,FALSE\\n118,Goldeen,Water,,45,67,60,35,50,63,1,FALSE\\n119,Seaking,Water,,80,92,65,65,80,68,1,FALSE\\n120,Staryu,Water,,30,45,55,70,55,85,1,FALSE\\n121,Starmie,Water,Psychic,60,75,85,100,85,115,1,FALSE\\n122,Mr. Mime,Psychic,Fairy,40,45,65,100,120,90,1,FALSE\\n123,Scyther,Bug,Flying,70,110,80,55,80,105,1,FALSE\\n124,Jynx,Ice,Psychic,65,50,35,115,95,95,1,FALSE\\n125,Electabuzz,Electric,,65,83,57,95,85,105,1,FALSE\\n126,Magmar,Fire,,65,95,57,100,85,93,1,FALSE\\n127,Pinsir,Bug,,65,125,100,55,70,85,1,FALSE\\n127,PinsirMega Pinsir,Bug,Flying,65,155,120,65,90,105,1,FALSE\\n128,Tauros,Normal,,75,100,95,40,70,110,1,FALSE\\n129,Magikarp,Water,,20,10,55,15,20,80,1,FALSE\\n130,Gyarados,Water,Flying,95,125,79,60,100,81,1,FALSE\\n130,GyaradosMega Gyarados,Water,Dark,95,155,109,70,130,81,1,FALSE\\n131,Lapras,Water,Ice,130,85,80,85,95,60,1,FALSE\\n132,Ditto,Normal,,48,48,48,48,48,48,1,FALSE\\n133,Eevee,Normal,,55,55,50,45,65,55,1,FALSE\\n134,Vaporeon,Water,,130,65,60,110,95,65,1,FALSE\\n135,Jolteon,Electric,,65,65,60,110,95,130,1,FALSE\\n136,Flareon,Fire,,65,130,60,95,110,65,1,FALSE\\n137,Porygon,Normal,,65,60,70,85,75,40,1,FALSE\\n138,Omanyte,Rock,Water,35,40,100,90,55,35,1,FALSE\\n139,Omastar,Rock,Water,70,60,125,115,70,55,1,FALSE\\n140,Kabuto,Rock,Water,30,80,90,55,45,55,1,FALSE\\n141,Kabutops,Rock,Water,60,115,105,65,70,80,1,FALSE\\n142,Aerodactyl,Rock,Flying,80,105,65,60,75,130,1,FALSE\\n142,AerodactylMega Aerodactyl,Rock,Flying,80,135,85,70,95,150,1,FALSE\\n143,Snorlax,Normal,,160,110,65,65,110,30,1,FALSE\\n144,Articuno,Ice,Flying,90,85,100,95,125,85,1,TRUE\\n145,Zapdos,Electric,Flying,90,90,85,125,90,100,1,TRUE\\n146,Moltres,Fire,Flying,90,100,90,125,85,90,1,TRUE\\n147,Dratini,Dragon,,41,64,45,50,50,50,1,FALSE\\n148,Dragonair,Dragon,,61,84,65,70,70,70,1,FALSE\\n149,Dragonite,Dragon,Flying,91,134,95,100,100,80,1,FALSE\\n150,Mewtwo,Psychic,,106,110,90,154,90,130,1,TRUE\\n150,MewtwoMega Mewtwo X,Psychic,Fighting,106,190,100,154,100,130,1,TRUE\\n150,MewtwoMega Mewtwo Y,Psychic,,106,150,70,194,120,140,1,TRUE\\n151,Mew,Psychic,,100,100,100,100,100,100,1,FALSE\\n152,Chikorita,Grass,,45,49,65,49,65,45,2,FALSE\\n153,Bayleef,Grass,,60,62,80,63,80,60,2,FALSE\\n154,Meganium,Grass,,80,82,100,83,100,80,2,FALSE\\n155,Cyndaquil,Fire,,39,52,43,60,50,65,2,FALSE\\n156,Quilava,Fire,,58,64,58,80,65,80,2,FALSE\\n157,Typhlosion,Fire,,78,84,78,109,85,100,2,FALSE\\n158,Totodile,Water,,50,65,64,44,48,43,2,FALSE\\n159,Croconaw,Water,,65,80,80,59,63,58,2,FALSE\\n160,Feraligatr,Water,,85,105,100,79,83,78,2,FALSE\\n161,Sentret,Normal,,35,46,34,35,45,20,2,FALSE\\n162,Furret,Normal,,85,76,64,45,55,90,2,FALSE\\n163,Hoothoot,Normal,Flying,60,30,30,36,56,50,2,FALSE\\n164,Noctowl,Normal,Flying,100,50,50,76,96,70,2,FALSE\\n165,Ledyba,Bug,Flying,40,20,30,40,80,55,2,FALSE\\n166,Ledian,Bug,Flying,55,35,50,55,110,85,2,FALSE\\n167,Spinarak,Bug,Poison,40,60,40,40,40,30,2,FALSE\\n168,Ariados,Bug,Poison,70,90,70,60,60,40,2,FALSE\\n169,Crobat,Poison,Flying,85,90,80,70,80,130,2,FALSE\\n170,Chinchou,Water,Electric,75,38,38,56,56,67,2,FALSE\\n171,Lanturn,Water,Electric,125,58,58,76,76,67,2,FALSE\\n172,Pichu,Electric,,20,40,15,35,35,60,2,FALSE\\n173,Cleffa,Fairy,,50,25,28,45,55,15,2,FALSE\\n174,Igglybuff,Normal,Fairy,90,30,15,40,20,15,2,FALSE\\n175,Togepi,Fairy,,35,20,65,40,65,20,2,FALSE\\n176,Togetic,Fairy,Flying,55,40,85,80,105,40,2,FALSE\\n177,Natu,Psychic,Flying,40,50,45,70,45,70,2,FALSE\\n178,Xatu,Psychic,Flying,65,75,70,95,70,95,2,FALSE\\n179,Mareep,Electric,,55,40,40,65,45,35,2,FALSE\\n180,Flaaffy,Electric,,70,55,55,80,60,45,2,FALSE\\n181,Ampharos,Electric,,90,75,85,115,90,55,2,FALSE\\n181,AmpharosMega Ampharos,Electric,Dragon,90,95,105,165,110,45,2,FALSE\\n182,Bellossom,Grass,,75,80,95,90,100,50,2,FALSE\\n183,Marill,Water,Fairy,70,20,50,20,50,40,2,FALSE\\n184,Azumarill,Water,Fairy,100,50,80,60,80,50,2,FALSE\\n185,Sudowoodo,Rock,,70,100,115,30,65,30,2,FALSE\\n186,Politoed,Water,,90,75,75,90,100,70,2,FALSE\\n187,Hoppip,Grass,Flying,35,35,40,35,55,50,2,FALSE\\n188,Skiploom,Grass,Flying,55,45,50,45,65,80,2,FALSE\\n189,Jumpluff,Grass,Flying,75,55,70,55,95,110,2,FALSE\\n190,Aipom,Normal,,55,70,55,40,55,85,2,FALSE\\n191,Sunkern,Grass,,30,30,30,30,30,30,2,FALSE\\n192,Sunflora,Grass,,75,75,55,105,85,30,2,FALSE\\n193,Yanma,Bug,Flying,65,65,45,75,45,95,2,FALSE\\n194,Wooper,Water,Ground,55,45,45,25,25,15,2,FALSE\\n195,Quagsire,Water,Ground,95,85,85,65,65,35,2,FALSE\\n196,Espeon,Psychic,,65,65,60,130,95,110,2,FALSE\\n197,Umbreon,Dark,,95,65,110,60,130,65,2,FALSE\\n198,Murkrow,Dark,Flying,60,85,42,85,42,91,2,FALSE\\n199,Slowking,Water,Psychic,95,75,80,100,110,30,2,FALSE\\n200,Misdreavus,Ghost,,60,60,60,85,85,85,2,FALSE\\n201,Unown,Psychic,,48,72,48,72,48,48,2,FALSE\\n202,Wobbuffet,Psychic,,190,33,58,33,58,33,2,FALSE\\n203,Girafarig,Normal,Psychic,70,80,65,90,65,85,2,FALSE\\n204,Pineco,Bug,,50,65,90,35,35,15,2,FALSE\\n205,Forretress,Bug,Steel,75,90,140,60,60,40,2,FALSE\\n206,Dunsparce,Normal,,100,70,70,65,65,45,2,FALSE\\n207,Gligar,Ground,Flying,65,75,105,35,65,85,2,FALSE\\n208,Steelix,Steel,Ground,75,85,200,55,65,30,2,FALSE\\n208,SteelixMega Steelix,Steel,Ground,75,125,230,55,95,30,2,FALSE\\n209,Snubbull,Fairy,,60,80,50,40,40,30,2,FALSE\\n210,Granbull,Fairy,,90,120,75,60,60,45,2,FALSE\\n211,Qwilfish,Water,Poison,65,95,75,55,55,85,2,FALSE\\n212,Scizor,Bug,Steel,70,130,100,55,80,65,2,FALSE\\n212,ScizorMega Scizor,Bug,Steel,70,150,140,65,100,75,2,FALSE\\n213,Shuckle,Bug,Rock,20,10,230,10,230,5,2,FALSE\\n214,Heracross,Bug,Fighting,80,125,75,40,95,85,2,FALSE\\n214,HeracrossMega Heracross,Bug,Fighting,80,185,115,40,105,75,2,FALSE\\n215,Sneasel,Dark,Ice,55,95,55,35,75,115,2,FALSE\\n216,Teddiursa,Normal,,60,80,50,50,50,40,2,FALSE\\n217,Ursaring,Normal,,90,130,75,75,75,55,2,FALSE\\n218,Slugma,Fire,,40,40,40,70,40,20,2,FALSE\\n219,Magcargo,Fire,Rock,50,50,120,80,80,30,2,FALSE\\n220,Swinub,Ice,Ground,50,50,40,30,30,50,2,FALSE\\n221,Piloswine,Ice,Ground,100,100,80,60,60,50,2,FALSE\\n222,Corsola,Water,Rock,55,55,85,65,85,35,2,FALSE\\n223,Remoraid,Water,,35,65,35,65,35,65,2,FALSE\\n224,Octillery,Water,,75,105,75,105,75,45,2,FALSE\\n225,Delibird,Ice,Flying,45,55,45,65,45,75,2,FALSE\\n226,Mantine,Water,Flying,65,40,70,80,140,70,2,FALSE\\n227,Skarmory,Steel,Flying,65,80,140,40,70,70,2,FALSE\\n228,Houndour,Dark,Fire,45,60,30,80,50,65,2,FALSE\\n229,Houndoom,Dark,Fire,75,90,50,110,80,95,2,FALSE\\n229,HoundoomMega Houndoom,Dark,Fire,75,90,90,140,90,115,2,FALSE\\n230,Kingdra,Water,Dragon,75,95,95,95,95,85,2,FALSE\\n231,Phanpy,Ground,,90,60,60,40,40,40,2,FALSE\\n232,Donphan,Ground,,90,120,120,60,60,50,2,FALSE\\n233,Porygon2,Normal,,85,80,90,105,95,60,2,FALSE\\n234,Stantler,Normal,,73,95,62,85,65,85,2,FALSE\\n235,Smeargle,Normal,,55,20,35,20,45,75,2,FALSE\\n236,Tyrogue,Fighting,,35,35,35,35,35,35,2,FALSE\\n237,Hitmontop,Fighting,,50,95,95,35,110,70,2,FALSE\\n238,Smoochum,Ice,Psychic,45,30,15,85,65,65,2,FALSE\\n239,Elekid,Electric,,45,63,37,65,55,95,2,FALSE\\n240,Magby,Fire,,45,75,37,70,55,83,2,FALSE\\n241,Miltank,Normal,,95,80,105,40,70,100,2,FALSE\\n242,Blissey,Normal,,255,10,10,75,135,55,2,FALSE\\n243,Raikou,Electric,,90,85,75,115,100,115,2,TRUE\\n244,Entei,Fire,,115,115,85,90,75,100,2,TRUE\\n245,Suicune,Water,,100,75,115,90,115,85,2,TRUE\\n246,Larvitar,Rock,Ground,50,64,50,45,50,41,2,FALSE\\n247,Pupitar,Rock,Ground,70,84,70,65,70,51,2,FALSE\\n248,Tyranitar,Rock,Dark,100,134,110,95,100,61,2,FALSE\\n248,TyranitarMega Tyranitar,Rock,Dark,100,164,150,95,120,71,2,FALSE\\n249,Lugia,Psychic,Flying,106,90,130,90,154,110,2,TRUE\\n250,Ho-oh,Fire,Flying,106,130,90,110,154,90,2,TRUE\\n251,Celebi,Psychic,Grass,100,100,100,100,100,100,2,FALSE\\n252,Treecko,Grass,,40,45,35,65,55,70,3,FALSE\\n253,Grovyle,Grass,,50,65,45,85,65,95,3,FALSE\\n254,Sceptile,Grass,,70,85,65,105,85,120,3,FALSE\\n254,SceptileMega Sceptile,Grass,Dragon,70,110,75,145,85,145,3,FALSE\\n255,Torchic,Fire,,45,60,40,70,50,45,3,FALSE\\n256,Combusken,Fire,Fighting,60,85,60,85,60,55,3,FALSE\\n257,Blaziken,Fire,Fighting,80,120,70,110,70,80,3,FALSE\\n257,BlazikenMega Blaziken,Fire,Fighting,80,160,80,130,80,100,3,FALSE\\n258,Mudkip,Water,,50,70,50,50,50,40,3,FALSE\\n259,Marshtomp,Water,Ground,70,85,70,60,70,50,3,FALSE\\n260,Swampert,Water,Ground,100,110,90,85,90,60,3,FALSE\\n260,SwampertMega Swampert,Water,Ground,100,150,110,95,110,70,3,FALSE\\n261,Poochyena,Dark,,35,55,35,30,30,35,3,FALSE\\n262,Mightyena,Dark,,70,90,70,60,60,70,3,FALSE\\n263,Zigzagoon,Normal,,38,30,41,30,41,60,3,FALSE\\n264,Linoone,Normal,,78,70,61,50,61,100,3,FALSE\\n265,Wurmple,Bug,,45,45,35,20,30,20,3,FALSE\\n266,Silcoon,Bug,,50,35,55,25,25,15,3,FALSE\\n267,Beautifly,Bug,Flying,60,70,50,100,50,65,3,FALSE\\n268,Cascoon,Bug,,50,35,55,25,25,15,3,FALSE\\n269,Dustox,Bug,Poison,60,50,70,50,90,65,3,FALSE\\n270,Lotad,Water,Grass,40,30,30,40,50,30,3,FALSE\\n271,Lombre,Water,Grass,60,50,50,60,70,50,3,FALSE\\n272,Ludicolo,Water,Grass,80,70,70,90,100,70,3,FALSE\\n273,Seedot,Grass,,40,40,50,30,30,30,3,FALSE\\n274,Nuzleaf,Grass,Dark,70,70,40,60,40,60,3,FALSE\\n275,Shiftry,Grass,Dark,90,100,60,90,60,80,3,FALSE\\n276,Taillow,Normal,Flying,40,55,30,30,30,85,3,FALSE\\n277,Swellow,Normal,Flying,60,85,60,50,50,125,3,FALSE\\n278,Wingull,Water,Flying,40,30,30,55,30,85,3,FALSE\\n279,Pelipper,Water,Flying,60,50,100,85,70,65,3,FALSE\\n280,Ralts,Psychic,Fairy,28,25,25,45,35,40,3,FALSE\\n281,Kirlia,Psychic,Fairy,38,35,35,65,55,50,3,FALSE\\n282,Gardevoir,Psychic,Fairy,68,65,65,125,115,80,3,FALSE\\n282,GardevoirMega Gardevoir,Psychic,Fairy,68,85,65,165,135,100,3,FALSE\\n283,Surskit,Bug,Water,40,30,32,50,52,65,3,FALSE\\n284,Masquerain,Bug,Flying,70,60,62,80,82,60,3,FALSE\\n285,Shroomish,Grass,,60,40,60,40,60,35,3,FALSE\\n286,Breloom,Grass,Fighting,60,130,80,60,60,70,3,FALSE\\n287,Slakoth,Normal,,60,60,60,35,35,30,3,FALSE\\n288,Vigoroth,Normal,,80,80,80,55,55,90,3,FALSE\\n289,Slaking,Normal,,150,160,100,95,65,100,3,FALSE\\n290,Nincada,Bug,Ground,31,45,90,30,30,40,3,FALSE\\n291,Ninjask,Bug,Flying,61,90,45,50,50,160,3,FALSE\\n292,Shedinja,Bug,Ghost,1,90,45,30,30,40,3,FALSE\\n293,Whismur,Normal,,64,51,23,51,23,28,3,FALSE\\n294,Loudred,Normal,,84,71,43,71,43,48,3,FALSE\\n295,Exploud,Normal,,104,91,63,91,73,68,3,FALSE\\n296,Makuhita,Fighting,,72,60,30,20,30,25,3,FALSE\\n297,Hariyama,Fighting,,144,120,60,40,60,50,3,FALSE\\n298,Azurill,Normal,Fairy,50,20,40,20,40,20,3,FALSE\\n299,Nosepass,Rock,,30,45,135,45,90,30,3,FALSE\\n300,Skitty,Normal,,50,45,45,35,35,50,3,FALSE\\n301,Delcatty,Normal,,70,65,65,55,55,70,3,FALSE\\n302,Sableye,Dark,Ghost,50,75,75,65,65,50,3,FALSE\\n302,SableyeMega Sableye,Dark,Ghost,50,85,125,85,115,20,3,FALSE\\n303,Mawile,Steel,Fairy,50,85,85,55,55,50,3,FALSE\\n303,MawileMega Mawile,Steel,Fairy,50,105,125,55,95,50,3,FALSE\\n304,Aron,Steel,Rock,50,70,100,40,40,30,3,FALSE\\n305,Lairon,Steel,Rock,60,90,140,50,50,40,3,FALSE\\n306,Aggron,Steel,Rock,70,110,180,60,60,50,3,FALSE\\n306,AggronMega Aggron,Steel,,70,140,230,60,80,50,3,FALSE\\n307,Meditite,Fighting,Psychic,30,40,55,40,55,60,3,FALSE\\n308,Medicham,Fighting,Psychic,60,60,75,60,75,80,3,FALSE\\n308,MedichamMega Medicham,Fighting,Psychic,60,100,85,80,85,100,3,FALSE\\n309,Electrike,Electric,,40,45,40,65,40,65,3,FALSE\\n310,Manectric,Electric,,70,75,60,105,60,105,3,FALSE\\n310,ManectricMega Manectric,Electric,,70,75,80,135,80,135,3,FALSE\\n311,Plusle,Electric,,60,50,40,85,75,95,3,FALSE\\n312,Minun,Electric,,60,40,50,75,85,95,3,FALSE\\n313,Volbeat,Bug,,65,73,55,47,75,85,3,FALSE\\n314,Illumise,Bug,,65,47,55,73,75,85,3,FALSE\\n315,Roselia,Grass,Poison,50,60,45,100,80,65,3,FALSE\\n316,Gulpin,Poison,,70,43,53,43,53,40,3,FALSE\\n317,Swalot,Poison,,100,73,83,73,83,55,3,FALSE\\n318,Carvanha,Water,Dark,45,90,20,65,20,65,3,FALSE\\n319,Sharpedo,Water,Dark,70,120,40,95,40,95,3,FALSE\\n319,SharpedoMega Sharpedo,Water,Dark,70,140,70,110,65,105,3,FALSE\\n320,Wailmer,Water,,130,70,35,70,35,60,3,FALSE\\n321,Wailord,Water,,170,90,45,90,45,60,3,FALSE\\n322,Numel,Fire,Ground,60,60,40,65,45,35,3,FALSE\\n323,Camerupt,Fire,Ground,70,100,70,105,75,40,3,FALSE\\n323,CameruptMega Camerupt,Fire,Ground,70,120,100,145,105,20,3,FALSE\\n324,Torkoal,Fire,,70,85,140,85,70,20,3,FALSE\\n325,Spoink,Psychic,,60,25,35,70,80,60,3,FALSE\\n326,Grumpig,Psychic,,80,45,65,90,110,80,3,FALSE\\n327,Spinda,Normal,,60,60,60,60,60,60,3,FALSE\\n328,Trapinch,Ground,,45,100,45,45,45,10,3,FALSE\\n329,Vibrava,Ground,Dragon,50,70,50,50,50,70,3,FALSE\\n330,Flygon,Ground,Dragon,80,100,80,80,80,100,3,FALSE\\n331,Cacnea,Grass,,50,85,40,85,40,35,3,FALSE\\n332,Cacturne,Grass,Dark,70,115,60,115,60,55,3,FALSE\\n333,Swablu,Normal,Flying,45,40,60,40,75,50,3,FALSE\\n334,Altaria,Dragon,Flying,75,70,90,70,105,80,3,FALSE\\n334,AltariaMega Altaria,Dragon,Fairy,75,110,110,110,105,80,3,FALSE\\n335,Zangoose,Normal,,73,115,60,60,60,90,3,FALSE\\n336,Seviper,Poison,,73,100,60,100,60,65,3,FALSE\\n337,Lunatone,Rock,Psychic,70,55,65,95,85,70,3,FALSE\\n338,Solrock,Rock,Psychic,70,95,85,55,65,70,3,FALSE\\n339,Barboach,Water,Ground,50,48,43,46,41,60,3,FALSE\\n340,Whiscash,Water,Ground,110,78,73,76,71,60,3,FALSE\\n341,Corphish,Water,,43,80,65,50,35,35,3,FALSE\\n342,Crawdaunt,Water,Dark,63,120,85,90,55,55,3,FALSE\\n343,Baltoy,Ground,Psychic,40,40,55,40,70,55,3,FALSE\\n344,Claydol,Ground,Psychic,60,70,105,70,120,75,3,FALSE\\n345,Lileep,Rock,Grass,66,41,77,61,87,23,3,FALSE\\n346,Cradily,Rock,Grass,86,81,97,81,107,43,3,FALSE\\n347,Anorith,Rock,Bug,45,95,50,40,50,75,3,FALSE\\n348,Armaldo,Rock,Bug,75,125,100,70,80,45,3,FALSE\\n349,Feebas,Water,,20,15,20,10,55,80,3,FALSE\\n350,Milotic,Water,,95,60,79,100,125,81,3,FALSE\\n351,Castform,Normal,,70,70,70,70,70,70,3,FALSE\\n352,Kecleon,Normal,,60,90,70,60,120,40,3,FALSE\\n353,Shuppet,Ghost,,44,75,35,63,33,45,3,FALSE\\n354,Banette,Ghost,,64,115,65,83,63,65,3,FALSE\\n354,BanetteMega Banette,Ghost,,64,165,75,93,83,75,3,FALSE\\n355,Duskull,Ghost,,20,40,90,30,90,25,3,FALSE\\n356,Dusclops,Ghost,,40,70,130,60,130,25,3,FALSE\\n357,Tropius,Grass,Flying,99,68,83,72,87,51,3,FALSE\\n358,Chimecho,Psychic,,65,50,70,95,80,65,3,FALSE\\n359,Absol,Dark,,65,130,60,75,60,75,3,FALSE\\n359,AbsolMega Absol,Dark,,65,150,60,115,60,115,3,FALSE\\n360,Wynaut,Psychic,,95,23,48,23,48,23,3,FALSE\\n361,Snorunt,Ice,,50,50,50,50,50,50,3,FALSE\\n362,Glalie,Ice,,80,80,80,80,80,80,3,FALSE\\n362,GlalieMega Glalie,Ice,,80,120,80,120,80,100,3,FALSE\\n363,Spheal,Ice,Water,70,40,50,55,50,25,3,FALSE\\n364,Sealeo,Ice,Water,90,60,70,75,70,45,3,FALSE\\n365,Walrein,Ice,Water,110,80,90,95,90,65,3,FALSE\\n366,Clamperl,Water,,35,64,85,74,55,32,3,FALSE\\n367,Huntail,Water,,55,104,105,94,75,52,3,FALSE\\n368,Gorebyss,Water,,55,84,105,114,75,52,3,FALSE\\n369,Relicanth,Water,Rock,100,90,130,45,65,55,3,FALSE\\n370,Luvdisc,Water,,43,30,55,40,65,97,3,FALSE\\n371,Bagon,Dragon,,45,75,60,40,30,50,3,FALSE\\n372,Shelgon,Dragon,,65,95,100,60,50,50,3,FALSE\\n373,Salamence,Dragon,Flying,95,135,80,110,80,100,3,FALSE\\n373,SalamenceMega Salamence,Dragon,Flying,95,145,130,120,90,120,3,FALSE\\n374,Beldum,Steel,Psychic,40,55,80,35,60,30,3,FALSE\\n375,Metang,Steel,Psychic,60,75,100,55,80,50,3,FALSE\\n376,Metagross,Steel,Psychic,80,135,130,95,90,70,3,FALSE\\n376,MetagrossMega Metagross,Steel,Psychic,80,145,150,105,110,110,3,FALSE\\n377,Regirock,Rock,,80,100,200,50,100,50,3,TRUE\\n378,Regice,Ice,,80,50,100,100,200,50,3,TRUE\\n379,Registeel,Steel,,80,75,150,75,150,50,3,TRUE\\n380,Latias,Dragon,Psychic,80,80,90,110,130,110,3,TRUE\\n380,LatiasMega Latias,Dragon,Psychic,80,100,120,140,150,110,3,TRUE\\n381,Latios,Dragon,Psychic,80,90,80,130,110,110,3,TRUE\\n381,LatiosMega Latios,Dragon,Psychic,80,130,100,160,120,110,3,TRUE\\n382,Kyogre,Water,,100,100,90,150,140,90,3,TRUE\\n382,KyogrePrimal Kyogre,Water,,100,150,90,180,160,90,3,TRUE\\n383,Groudon,Ground,,100,150,140,100,90,90,3,TRUE\\n383,GroudonPrimal Groudon,Ground,Fire,100,180,160,150,90,90,3,TRUE\\n384,Rayquaza,Dragon,Flying,105,150,90,150,90,95,3,TRUE\\n384,RayquazaMega Rayquaza,Dragon,Flying,105,180,100,180,100,115,3,TRUE\\n385,Jirachi,Steel,Psychic,100,100,100,100,100,100,3,TRUE\\n386,DeoxysNormal Forme,Psychic,,50,150,50,150,50,150,3,TRUE\\n386,DeoxysAttack Forme,Psychic,,50,180,20,180,20,150,3,TRUE\\n386,DeoxysDefense Forme,Psychic,,50,70,160,70,160,90,3,TRUE\\n386,DeoxysSpeed Forme,Psychic,,50,95,90,95,90,180,3,TRUE\\n387,Turtwig,Grass,,55,68,64,45,55,31,4,FALSE\\n388,Grotle,Grass,,75,89,85,55,65,36,4,FALSE\\n389,Torterra,Grass,Ground,95,109,105,75,85,56,4,FALSE\\n390,Chimchar,Fire,,44,58,44,58,44,61,4,FALSE\\n391,Monferno,Fire,Fighting,64,78,52,78,52,81,4,FALSE\\n392,Infernape,Fire,Fighting,76,104,71,104,71,108,4,FALSE\\n393,Piplup,Water,,53,51,53,61,56,40,4,FALSE\\n394,Prinplup,Water,,64,66,68,81,76,50,4,FALSE\\n395,Empoleon,Water,Steel,84,86,88,111,101,60,4,FALSE\\n396,Starly,Normal,Flying,40,55,30,30,30,60,4,FALSE\\n397,Staravia,Normal,Flying,55,75,50,40,40,80,4,FALSE\\n398,Staraptor,Normal,Flying,85,120,70,50,60,100,4,FALSE\\n399,Bidoof,Normal,,59,45,40,35,40,31,4,FALSE\\n400,Bibarel,Normal,Water,79,85,60,55,60,71,4,FALSE\\n401,Kricketot,Bug,,37,25,41,25,41,25,4,FALSE\\n402,Kricketune,Bug,,77,85,51,55,51,65,4,FALSE\\n403,Shinx,Electric,,45,65,34,40,34,45,4,FALSE\\n404,Luxio,Electric,,60,85,49,60,49,60,4,FALSE\\n405,Luxray,Electric,,80,120,79,95,79,70,4,FALSE\\n406,Budew,Grass,Poison,40,30,35,50,70,55,4,FALSE\\n407,Roserade,Grass,Poison,60,70,65,125,105,90,4,FALSE\\n408,Cranidos,Rock,,67,125,40,30,30,58,4,FALSE\\n409,Rampardos,Rock,,97,165,60,65,50,58,4,FALSE\\n410,Shieldon,Rock,Steel,30,42,118,42,88,30,4,FALSE\\n411,Bastiodon,Rock,Steel,60,52,168,47,138,30,4,FALSE\\n412,Burmy,Bug,,40,29,45,29,45,36,4,FALSE\\n413,WormadamPlant Cloak,Bug,Grass,60,59,85,79,105,36,4,FALSE\\n413,WormadamSandy Cloak,Bug,Ground,60,79,105,59,85,36,4,FALSE\\n413,WormadamTrash Cloak,Bug,Steel,60,69,95,69,95,36,4,FALSE\\n414,Mothim,Bug,Flying,70,94,50,94,50,66,4,FALSE\\n415,Combee,Bug,Flying,30,30,42,30,42,70,4,FALSE\\n416,Vespiquen,Bug,Flying,70,80,102,80,102,40,4,FALSE\\n417,Pachirisu,Electric,,60,45,70,45,90,95,4,FALSE\\n418,Buizel,Water,,55,65,35,60,30,85,4,FALSE\\n419,Floatzel,Water,,85,105,55,85,50,115,4,FALSE\\n420,Cherubi,Grass,,45,35,45,62,53,35,4,FALSE\\n421,Cherrim,Grass,,70,60,70,87,78,85,4,FALSE\\n422,Shellos,Water,,76,48,48,57,62,34,4,FALSE\\n423,Gastrodon,Water,Ground,111,83,68,92,82,39,4,FALSE\\n424,Ambipom,Normal,,75,100,66,60,66,115,4,FALSE\\n425,Drifloon,Ghost,Flying,90,50,34,60,44,70,4,FALSE\\n426,Drifblim,Ghost,Flying,150,80,44,90,54,80,4,FALSE\\n427,Buneary,Normal,,55,66,44,44,56,85,4,FALSE\\n428,Lopunny,Normal,,65,76,84,54,96,105,4,FALSE\\n428,LopunnyMega Lopunny,Normal,Fighting,65,136,94,54,96,135,4,FALSE\\n429,Mismagius,Ghost,,60,60,60,105,105,105,4,FALSE\\n430,Honchkrow,Dark,Flying,100,125,52,105,52,71,4,FALSE\\n431,Glameow,Normal,,49,55,42,42,37,85,4,FALSE\\n432,Purugly,Normal,,71,82,64,64,59,112,4,FALSE\\n433,Chingling,Psychic,,45,30,50,65,50,45,4,FALSE\\n434,Stunky,Poison,Dark,63,63,47,41,41,74,4,FALSE\\n435,Skuntank,Poison,Dark,103,93,67,71,61,84,4,FALSE\\n436,Bronzor,Steel,Psychic,57,24,86,24,86,23,4,FALSE\\n437,Bronzong,Steel,Psychic,67,89,116,79,116,33,4,FALSE\\n438,Bonsly,Rock,,50,80,95,10,45,10,4,FALSE\\n439,Mime Jr.,Psychic,Fairy,20,25,45,70,90,60,4,FALSE\\n440,Happiny,Normal,,100,5,5,15,65,30,4,FALSE\\n441,Chatot,Normal,Flying,76,65,45,92,42,91,4,FALSE\\n442,Spiritomb,Ghost,Dark,50,92,108,92,108,35,4,FALSE\\n443,Gible,Dragon,Ground,58,70,45,40,45,42,4,FALSE\\n444,Gabite,Dragon,Ground,68,90,65,50,55,82,4,FALSE\\n445,Garchomp,Dragon,Ground,108,130,95,80,85,102,4,FALSE\\n445,GarchompMega Garchomp,Dragon,Ground,108,170,115,120,95,92,4,FALSE\\n446,Munchlax,Normal,,135,85,40,40,85,5,4,FALSE\\n447,Riolu,Fighting,,40,70,40,35,40,60,4,FALSE\\n448,Lucario,Fighting,Steel,70,110,70,115,70,90,4,FALSE\\n448,LucarioMega Lucario,Fighting,Steel,70,145,88,140,70,112,4,FALSE\\n449,Hippopotas,Ground,,68,72,78,38,42,32,4,FALSE\\n450,Hippowdon,Ground,,108,112,118,68,72,47,4,FALSE\\n451,Skorupi,Poison,Bug,40,50,90,30,55,65,4,FALSE\\n452,Drapion,Poison,Dark,70,90,110,60,75,95,4,FALSE\\n453,Croagunk,Poison,Fighting,48,61,40,61,40,50,4,FALSE\\n454,Toxicroak,Poison,Fighting,83,106,65,86,65,85,4,FALSE\\n455,Carnivine,Grass,,74,100,72,90,72,46,4,FALSE\\n456,Finneon,Water,,49,49,56,49,61,66,4,FALSE\\n457,Lumineon,Water,,69,69,76,69,86,91,4,FALSE\\n458,Mantyke,Water,Flying,45,20,50,60,120,50,4,FALSE\\n459,Snover,Grass,Ice,60,62,50,62,60,40,4,FALSE\\n460,Abomasnow,Grass,Ice,90,92,75,92,85,60,4,FALSE\\n460,AbomasnowMega Abomasnow,Grass,Ice,90,132,105,132,105,30,4,FALSE\\n461,Weavile,Dark,Ice,70,120,65,45,85,125,4,FALSE\\n462,Magnezone,Electric,Steel,70,70,115,130,90,60,4,FALSE\\n463,Lickilicky,Normal,,110,85,95,80,95,50,4,FALSE\\n464,Rhyperior,Ground,Rock,115,140,130,55,55,40,4,FALSE\\n465,Tangrowth,Grass,,100,100,125,110,50,50,4,FALSE\\n466,Electivire,Electric,,75,123,67,95,85,95,4,FALSE\\n467,Magmortar,Fire,,75,95,67,125,95,83,4,FALSE\\n468,Togekiss,Fairy,Flying,85,50,95,120,115,80,4,FALSE\\n469,Yanmega,Bug,Flying,86,76,86,116,56,95,4,FALSE\\n470,Leafeon,Grass,,65,110,130,60,65,95,4,FALSE\\n471,Glaceon,Ice,,65,60,110,130,95,65,4,FALSE\\n472,Gliscor,Ground,Flying,75,95,125,45,75,95,4,FALSE\\n473,Mamoswine,Ice,Ground,110,130,80,70,60,80,4,FALSE\\n474,Porygon-Z,Normal,,85,80,70,135,75,90,4,FALSE\\n475,Gallade,Psychic,Fighting,68,125,65,65,115,80,4,FALSE\\n475,GalladeMega Gallade,Psychic,Fighting,68,165,95,65,115,110,4,FALSE\\n476,Probopass,Rock,Steel,60,55,145,75,150,40,4,FALSE\\n477,Dusknoir,Ghost,,45,100,135,65,135,45,4,FALSE\\n478,Froslass,Ice,Ghost,70,80,70,80,70,110,4,FALSE\\n479,Rotom,Electric,Ghost,50,50,77,95,77,91,4,FALSE\\n479,RotomHeat Rotom,Electric,Fire,50,65,107,105,107,86,4,FALSE\\n479,RotomWash Rotom,Electric,Water,50,65,107,105,107,86,4,FALSE\\n479,RotomFrost Rotom,Electric,Ice,50,65,107,105,107,86,4,FALSE\\n479,RotomFan Rotom,Electric,Flying,50,65,107,105,107,86,4,FALSE\\n479,RotomMow Rotom,Electric,Grass,50,65,107,105,107,86,4,FALSE\\n480,Uxie,Psychic,,75,75,130,75,130,95,4,TRUE\\n481,Mesprit,Psychic,,80,105,105,105,105,80,4,TRUE\\n482,Azelf,Psychic,,75,125,70,125,70,115,4,TRUE\\n483,Dialga,Steel,Dragon,100,120,120,150,100,90,4,TRUE\\n484,Palkia,Water,Dragon,90,120,100,150,120,100,4,TRUE\\n485,Heatran,Fire,Steel,91,90,106,130,106,77,4,TRUE\\n486,Regigigas,Normal,,110,160,110,80,110,100,4,TRUE\\n487,GiratinaAltered Forme,Ghost,Dragon,150,100,120,100,120,90,4,TRUE\\n487,GiratinaOrigin Forme,Ghost,Dragon,150,120,100,120,100,90,4,TRUE\\n488,Cresselia,Psychic,,120,70,120,75,130,85,4,FALSE\\n489,Phione,Water,,80,80,80,80,80,80,4,FALSE\\n490,Manaphy,Water,,100,100,100,100,100,100,4,FALSE\\n491,Darkrai,Dark,,70,90,90,135,90,125,4,TRUE\\n492,ShayminLand Forme,Grass,,100,100,100,100,100,100,4,TRUE\\n492,ShayminSky Forme,Grass,Flying,100,103,75,120,75,127,4,TRUE\\n493,Arceus,Normal,,120,120,120,120,120,120,4,TRUE\\n494,Victini,Psychic,Fire,100,100,100,100,100,100,5,TRUE\\n495,Snivy,Grass,,45,45,55,45,55,63,5,FALSE\\n496,Servine,Grass,,60,60,75,60,75,83,5,FALSE\\n497,Serperior,Grass,,75,75,95,75,95,113,5,FALSE\\n498,Tepig,Fire,,65,63,45,45,45,45,5,FALSE\\n499,Pignite,Fire,Fighting,90,93,55,70,55,55,5,FALSE\\n500,Emboar,Fire,Fighting,110,123,65,100,65,65,5,FALSE\\n501,Oshawott,Water,,55,55,45,63,45,45,5,FALSE\\n502,Dewott,Water,,75,75,60,83,60,60,5,FALSE\\n503,Samurott,Water,,95,100,85,108,70,70,5,FALSE\\n504,Patrat,Normal,,45,55,39,35,39,42,5,FALSE\\n505,Watchog,Normal,,60,85,69,60,69,77,5,FALSE\\n506,Lillipup,Normal,,45,60,45,25,45,55,5,FALSE\\n507,Herdier,Normal,,65,80,65,35,65,60,5,FALSE\\n508,Stoutland,Normal,,85,110,90,45,90,80,5,FALSE\\n509,Purrloin,Dark,,41,50,37,50,37,66,5,FALSE\\n510,Liepard,Dark,,64,88,50,88,50,106,5,FALSE\\n511,Pansage,Grass,,50,53,48,53,48,64,5,FALSE\\n512,Simisage,Grass,,75,98,63,98,63,101,5,FALSE\\n513,Pansear,Fire,,50,53,48,53,48,64,5,FALSE\\n514,Simisear,Fire,,75,98,63,98,63,101,5,FALSE\\n515,Panpour,Water,,50,53,48,53,48,64,5,FALSE\\n516,Simipour,Water,,75,98,63,98,63,101,5,FALSE\\n517,Munna,Psychic,,76,25,45,67,55,24,5,FALSE\\n518,Musharna,Psychic,,116,55,85,107,95,29,5,FALSE\\n519,Pidove,Normal,Flying,50,55,50,36,30,43,5,FALSE\\n520,Tranquill,Normal,Flying,62,77,62,50,42,65,5,FALSE\\n521,Unfezant,Normal,Flying,80,115,80,65,55,93,5,FALSE\\n522,Blitzle,Electric,,45,60,32,50,32,76,5,FALSE\\n523,Zebstrika,Electric,,75,100,63,80,63,116,5,FALSE\\n524,Roggenrola,Rock,,55,75,85,25,25,15,5,FALSE\\n525,Boldore,Rock,,70,105,105,50,40,20,5,FALSE\\n526,Gigalith,Rock,,85,135,130,60,80,25,5,FALSE\\n527,Woobat,Psychic,Flying,55,45,43,55,43,72,5,FALSE\\n528,Swoobat,Psychic,Flying,67,57,55,77,55,114,5,FALSE\\n529,Drilbur,Ground,,60,85,40,30,45,68,5,FALSE\\n530,Excadrill,Ground,Steel,110,135,60,50,65,88,5,FALSE\\n531,Audino,Normal,,103,60,86,60,86,50,5,FALSE\\n531,AudinoMega Audino,Normal,Fairy,103,60,126,80,126,50,5,FALSE\\n532,Timburr,Fighting,,75,80,55,25,35,35,5,FALSE\\n533,Gurdurr,Fighting,,85,105,85,40,50,40,5,FALSE\\n534,Conkeldurr,Fighting,,105,140,95,55,65,45,5,FALSE\\n535,Tympole,Water,,50,50,40,50,40,64,5,FALSE\\n536,Palpitoad,Water,Ground,75,65,55,65,55,69,5,FALSE\\n537,Seismitoad,Water,Ground,105,95,75,85,75,74,5,FALSE\\n538,Throh,Fighting,,120,100,85,30,85,45,5,FALSE\\n539,Sawk,Fighting,,75,125,75,30,75,85,5,FALSE\\n540,Sewaddle,Bug,Grass,45,53,70,40,60,42,5,FALSE\\n541,Swadloon,Bug,Grass,55,63,90,50,80,42,5,FALSE\\n542,Leavanny,Bug,Grass,75,103,80,70,80,92,5,FALSE\\n543,Venipede,Bug,Poison,30,45,59,30,39,57,5,FALSE\\n544,Whirlipede,Bug,Poison,40,55,99,40,79,47,5,FALSE\\n545,Scolipede,Bug,Poison,60,100,89,55,69,112,5,FALSE\\n546,Cottonee,Grass,Fairy,40,27,60,37,50,66,5,FALSE\\n547,Whimsicott,Grass,Fairy,60,67,85,77,75,116,5,FALSE\\n548,Petilil,Grass,,45,35,50,70,50,30,5,FALSE\\n549,Lilligant,Grass,,70,60,75,110,75,90,5,FALSE\\n550,Basculin,Water,,70,92,65,80,55,98,5,FALSE\\n551,Sandile,Ground,Dark,50,72,35,35,35,65,5,FALSE\\n552,Krokorok,Ground,Dark,60,82,45,45,45,74,5,FALSE\\n553,Krookodile,Ground,Dark,95,117,80,65,70,92,5,FALSE\\n554,Darumaka,Fire,,70,90,45,15,45,50,5,FALSE\\n555,DarmanitanStandard Mode,Fire,,105,140,55,30,55,95,5,FALSE\\n555,DarmanitanZen Mode,Fire,Psychic,105,30,105,140,105,55,5,FALSE\\n556,Maractus,Grass,,75,86,67,106,67,60,5,FALSE\\n557,Dwebble,Bug,Rock,50,65,85,35,35,55,5,FALSE\\n558,Crustle,Bug,Rock,70,95,125,65,75,45,5,FALSE\\n559,Scraggy,Dark,Fighting,50,75,70,35,70,48,5,FALSE\\n560,Scrafty,Dark,Fighting,65,90,115,45,115,58,5,FALSE\\n561,Sigilyph,Psychic,Flying,72,58,80,103,80,97,5,FALSE\\n562,Yamask,Ghost,,38,30,85,55,65,30,5,FALSE\\n563,Cofagrigus,Ghost,,58,50,145,95,105,30,5,FALSE\\n564,Tirtouga,Water,Rock,54,78,103,53,45,22,5,FALSE\\n565,Carracosta,Water,Rock,74,108,133,83,65,32,5,FALSE\\n566,Archen,Rock,Flying,55,112,45,74,45,70,5,FALSE\\n567,Archeops,Rock,Flying,75,140,65,112,65,110,5,FALSE\\n568,Trubbish,Poison,,50,50,62,40,62,65,5,FALSE\\n569,Garbodor,Poison,,80,95,82,60,82,75,5,FALSE\\n570,Zorua,Dark,,40,65,40,80,40,65,5,FALSE\\n571,Zoroark,Dark,,60,105,60,120,60,105,5,FALSE\\n572,Minccino,Normal,,55,50,40,40,40,75,5,FALSE\\n573,Cinccino,Normal,,75,95,60,65,60,115,5,FALSE\\n574,Gothita,Psychic,,45,30,50,55,65,45,5,FALSE\\n575,Gothorita,Psychic,,60,45,70,75,85,55,5,FALSE\\n576,Gothitelle,Psychic,,70,55,95,95,110,65,5,FALSE\\n577,Solosis,Psychic,,45,30,40,105,50,20,5,FALSE\\n578,Duosion,Psychic,,65,40,50,125,60,30,5,FALSE\\n579,Reuniclus,Psychic,,110,65,75,125,85,30,5,FALSE\\n580,Ducklett,Water,Flying,62,44,50,44,50,55,5,FALSE\\n581,Swanna,Water,Flying,75,87,63,87,63,98,5,FALSE\\n582,Vanillite,Ice,,36,50,50,65,60,44,5,FALSE\\n583,Vanillish,Ice,,51,65,65,80,75,59,5,FALSE\\n584,Vanilluxe,Ice,,71,95,85,110,95,79,5,FALSE\\n585,Deerling,Normal,Grass,60,60,50,40,50,75,5,FALSE\\n586,Sawsbuck,Normal,Grass,80,100,70,60,70,95,5,FALSE\\n587,Emolga,Electric,Flying,55,75,60,75,60,103,5,FALSE\\n588,Karrablast,Bug,,50,75,45,40,45,60,5,FALSE\\n589,Escavalier,Bug,Steel,70,135,105,60,105,20,5,FALSE\\n590,Foongus,Grass,Poison,69,55,45,55,55,15,5,FALSE\\n591,Amoonguss,Grass,Poison,114,85,70,85,80,30,5,FALSE\\n592,Frillish,Water,Ghost,55,40,50,65,85,40,5,FALSE\\n593,Jellicent,Water,Ghost,100,60,70,85,105,60,5,FALSE\\n594,Alomomola,Water,,165,75,80,40,45,65,5,FALSE\\n595,Joltik,Bug,Electric,50,47,50,57,50,65,5,FALSE\\n596,Galvantula,Bug,Electric,70,77,60,97,60,108,5,FALSE\\n597,Ferroseed,Grass,Steel,44,50,91,24,86,10,5,FALSE\\n598,Ferrothorn,Grass,Steel,74,94,131,54,116,20,5,FALSE\\n599,Klink,Steel,,40,55,70,45,60,30,5,FALSE\\n600,Klang,Steel,,60,80,95,70,85,50,5,FALSE\\n601,Klinklang,Steel,,60,100,115,70,85,90,5,FALSE\\n602,Tynamo,Electric,,35,55,40,45,40,60,5,FALSE\\n603,Eelektrik,Electric,,65,85,70,75,70,40,5,FALSE\\n604,Eelektross,Electric,,85,115,80,105,80,50,5,FALSE\\n605,Elgyem,Psychic,,55,55,55,85,55,30,5,FALSE\\n606,Beheeyem,Psychic,,75,75,75,125,95,40,5,FALSE\\n607,Litwick,Ghost,Fire,50,30,55,65,55,20,5,FALSE\\n608,Lampent,Ghost,Fire,60,40,60,95,60,55,5,FALSE\\n609,Chandelure,Ghost,Fire,60,55,90,145,90,80,5,FALSE\\n610,Axew,Dragon,,46,87,60,30,40,57,5,FALSE\\n611,Fraxure,Dragon,,66,117,70,40,50,67,5,FALSE\\n612,Haxorus,Dragon,,76,147,90,60,70,97,5,FALSE\\n613,Cubchoo,Ice,,55,70,40,60,40,40,5,FALSE\\n614,Beartic,Ice,,95,110,80,70,80,50,5,FALSE\\n615,Cryogonal,Ice,,70,50,30,95,135,105,5,FALSE\\n616,Shelmet,Bug,,50,40,85,40,65,25,5,FALSE\\n617,Accelgor,Bug,,80,70,40,100,60,145,5,FALSE\\n618,Stunfisk,Ground,Electric,109,66,84,81,99,32,5,FALSE\\n619,Mienfoo,Fighting,,45,85,50,55,50,65,5,FALSE\\n620,Mienshao,Fighting,,65,125,60,95,60,105,5,FALSE\\n621,Druddigon,Dragon,,77,120,90,60,90,48,5,FALSE\\n622,Golett,Ground,Ghost,59,74,50,35,50,35,5,FALSE\\n623,Golurk,Ground,Ghost,89,124,80,55,80,55,5,FALSE\\n624,Pawniard,Dark,Steel,45,85,70,40,40,60,5,FALSE\\n625,Bisharp,Dark,Steel,65,125,100,60,70,70,5,FALSE\\n626,Bouffalant,Normal,,95,110,95,40,95,55,5,FALSE\\n627,Rufflet,Normal,Flying,70,83,50,37,50,60,5,FALSE\\n628,Braviary,Normal,Flying,100,123,75,57,75,80,5,FALSE\\n629,Vullaby,Dark,Flying,70,55,75,45,65,60,5,FALSE\\n630,Mandibuzz,Dark,Flying,110,65,105,55,95,80,5,FALSE\\n631,Heatmor,Fire,,85,97,66,105,66,65,5,FALSE\\n632,Durant,Bug,Steel,58,109,112,48,48,109,5,FALSE\\n633,Deino,Dark,Dragon,52,65,50,45,50,38,5,FALSE\\n634,Zweilous,Dark,Dragon,72,85,70,65,70,58,5,FALSE\\n635,Hydreigon,Dark,Dragon,92,105,90,125,90,98,5,FALSE\\n636,Larvesta,Bug,Fire,55,85,55,50,55,60,5,FALSE\\n637,Volcarona,Bug,Fire,85,60,65,135,105,100,5,FALSE\\n638,Cobalion,Steel,Fighting,91,90,129,90,72,108,5,TRUE\\n639,Terrakion,Rock,Fighting,91,129,90,72,90,108,5,TRUE\\n640,Virizion,Grass,Fighting,91,90,72,90,129,108,5,TRUE\\n641,TornadusIncarnate Forme,Flying,,79,115,70,125,80,111,5,TRUE\\n641,TornadusTherian Forme,Flying,,79,100,80,110,90,121,5,TRUE\\n642,ThundurusIncarnate Forme,Electric,Flying,79,115,70,125,80,111,5,TRUE\\n642,ThundurusTherian Forme,Electric,Flying,79,105,70,145,80,101,5,TRUE\\n643,Reshiram,Dragon,Fire,100,120,100,150,120,90,5,TRUE\\n644,Zekrom,Dragon,Electric,100,150,120,120,100,90,5,TRUE\\n645,LandorusIncarnate Forme,Ground,Flying,89,125,90,115,80,101,5,TRUE\\n645,LandorusTherian Forme,Ground,Flying,89,145,90,105,80,91,5,TRUE\\n646,Kyurem,Dragon,Ice,125,130,90,130,90,95,5,TRUE\\n646,KyuremBlack Kyurem,Dragon,Ice,125,170,100,120,90,95,5,TRUE\\n646,KyuremWhite Kyurem,Dragon,Ice,125,120,90,170,100,95,5,TRUE\\n647,KeldeoOrdinary Forme,Water,Fighting,91,72,90,129,90,108,5,FALSE\\n647,KeldeoResolute Forme,Water,Fighting,91,72,90,129,90,108,5,FALSE\\n648,MeloettaAria Forme,Normal,Psychic,100,77,77,128,128,90,5,FALSE\\n648,MeloettaPirouette Forme,Normal,Fighting,100,128,90,77,77,128,5,FALSE\\n649,Genesect,Bug,Steel,71,120,95,120,95,99,5,FALSE\\n650,Chespin,Grass,,56,61,65,48,45,38,6,FALSE\\n651,Quilladin,Grass,,61,78,95,56,58,57,6,FALSE\\n652,Chesnaught,Grass,Fighting,88,107,122,74,75,64,6,FALSE\\n653,Fennekin,Fire,,40,45,40,62,60,60,6,FALSE\\n654,Braixen,Fire,,59,59,58,90,70,73,6,FALSE\\n655,Delphox,Fire,Psychic,75,69,72,114,100,104,6,FALSE\\n656,Froakie,Water,,41,56,40,62,44,71,6,FALSE\\n657,Frogadier,Water,,54,63,52,83,56,97,6,FALSE\\n658,Greninja,Water,Dark,72,95,67,103,71,122,6,FALSE\\n659,Bunnelby,Normal,,38,36,38,32,36,57,6,FALSE\\n660,Diggersby,Normal,Ground,85,56,77,50,77,78,6,FALSE\\n661,Fletchling,Normal,Flying,45,50,43,40,38,62,6,FALSE\\n662,Fletchinder,Fire,Flying,62,73,55,56,52,84,6,FALSE\\n663,Talonflame,Fire,Flying,78,81,71,74,69,126,6,FALSE\\n664,Scatterbug,Bug,,38,35,40,27,25,35,6,FALSE\\n665,Spewpa,Bug,,45,22,60,27,30,29,6,FALSE\\n666,Vivillon,Bug,Flying,80,52,50,90,50,89,6,FALSE\\n667,Litleo,Fire,Normal,62,50,58,73,54,72,6,FALSE\\n668,Pyroar,Fire,Normal,86,68,72,109,66,106,6,FALSE\\n669,Flab\\xc3\\xa9b\\xc3\\xa9,Fairy,,44,38,39,61,79,42,6,FALSE\\n670,Floette,Fairy,,54,45,47,75,98,52,6,FALSE\\n671,Florges,Fairy,,78,65,68,112,154,75,6,FALSE\\n672,Skiddo,Grass,,66,65,48,62,57,52,6,FALSE\\n673,Gogoat,Grass,,123,100,62,97,81,68,6,FALSE\\n674,Pancham,Fighting,,67,82,62,46,48,43,6,FALSE\\n675,Pangoro,Fighting,Dark,95,124,78,69,71,58,6,FALSE\\n676,Furfrou,Normal,,75,80,60,65,90,102,6,FALSE\\n677,Espurr,Psychic,,62,48,54,63,60,68,6,FALSE\\n678,MeowsticMale,Psychic,,74,48,76,83,81,104,6,FALSE\\n678,MeowsticFemale,Psychic,,74,48,76,83,81,104,6,FALSE\\n679,Honedge,Steel,Ghost,45,80,100,35,37,28,6,FALSE\\n680,Doublade,Steel,Ghost,59,110,150,45,49,35,6,FALSE\\n681,AegislashBlade Forme,Steel,Ghost,60,150,50,150,50,60,6,FALSE\\n681,AegislashShield Forme,Steel,Ghost,60,50,150,50,150,60,6,FALSE\\n682,Spritzee,Fairy,,78,52,60,63,65,23,6,FALSE\\n683,Aromatisse,Fairy,,101,72,72,99,89,29,6,FALSE\\n684,Swirlix,Fairy,,62,48,66,59,57,49,6,FALSE\\n685,Slurpuff,Fairy,,82,80,86,85,75,72,6,FALSE\\n686,Inkay,Dark,Psychic,53,54,53,37,46,45,6,FALSE\\n687,Malamar,Dark,Psychic,86,92,88,68,75,73,6,FALSE\\n688,Binacle,Rock,Water,42,52,67,39,56,50,6,FALSE\\n689,Barbaracle,Rock,Water,72,105,115,54,86,68,6,FALSE\\n690,Skrelp,Poison,Water,50,60,60,60,60,30,6,FALSE\\n691,Dragalge,Poison,Dragon,65,75,90,97,123,44,6,FALSE\\n692,Clauncher,Water,,50,53,62,58,63,44,6,FALSE\\n693,Clawitzer,Water,,71,73,88,120,89,59,6,FALSE\\n694,Helioptile,Electric,Normal,44,38,33,61,43,70,6,FALSE\\n695,Heliolisk,Electric,Normal,62,55,52,109,94,109,6,FALSE\\n696,Tyrunt,Rock,Dragon,58,89,77,45,45,48,6,FALSE\\n697,Tyrantrum,Rock,Dragon,82,121,119,69,59,71,6,FALSE\\n698,Amaura,Rock,Ice,77,59,50,67,63,46,6,FALSE\\n699,Aurorus,Rock,Ice,123,77,72,99,92,58,6,FALSE\\n700,Sylveon,Fairy,,95,65,65,110,130,60,6,FALSE\\n701,Hawlucha,Fighting,Flying,78,92,75,74,63,118,6,FALSE\\n702,Dedenne,Electric,Fairy,67,58,57,81,67,101,6,FALSE\\n703,Carbink,Rock,Fairy,50,50,150,50,150,50,6,FALSE\\n704,Goomy,Dragon,,45,50,35,55,75,40,6,FALSE\\n705,Sliggoo,Dragon,,68,75,53,83,113,60,6,FALSE\\n706,Goodra,Dragon,,90,100,70,110,150,80,6,FALSE\\n707,Klefki,Steel,Fairy,57,80,91,80,87,75,6,FALSE\\n708,Phantump,Ghost,Grass,43,70,48,50,60,38,6,FALSE\\n709,Trevenant,Ghost,Grass,85,110,76,65,82,56,6,FALSE\\n710,PumpkabooAverage Size,Ghost,Grass,49,66,70,44,55,51,6,FALSE\\n710,PumpkabooSmall Size,Ghost,Grass,44,66,70,44,55,56,6,FALSE\\n710,PumpkabooLarge Size,Ghost,Grass,54,66,70,44,55,46,6,FALSE\\n710,PumpkabooSuper Size,Ghost,Grass,59,66,70,44,55,41,6,FALSE\\n711,GourgeistAverage Size,Ghost,Grass,65,90,122,58,75,84,6,FALSE\\n711,GourgeistSmall Size,Ghost,Grass,55,85,122,58,75,99,6,FALSE\\n711,GourgeistLarge Size,Ghost,Grass,75,95,122,58,75,69,6,FALSE\\n711,GourgeistSuper Size,Ghost,Grass,85,100,122,58,75,54,6,FALSE\\n712,Bergmite,Ice,,55,69,85,32,35,28,6,FALSE\\n713,Avalugg,Ice,,95,117,184,44,46,28,6,FALSE\\n714,Noibat,Flying,Dragon,40,30,35,45,40,55,6,FALSE\\n715,Noivern,Flying,Dragon,85,70,80,97,80,123,6,FALSE\\n716,Xerneas,Fairy,,126,131,95,131,98,99,6,TRUE\\n717,Yveltal,Dark,Flying,126,131,95,131,98,99,6,TRUE\\n718,Zygarde50% Forme,Dragon,Ground,108,100,121,81,95,95,6,TRUE\\n719,Diancie,Rock,Fairy,50,100,150,100,150,50,6,TRUE\\n719,DiancieMega Diancie,Rock,Fairy,50,160,110,160,110,110,6,TRUE\\n720,HoopaHoopa Confined,Psychic,Ghost,80,110,60,150,130,70,6,TRUE\\n720,HoopaHoopa Unbound,Psychic,Dark,80,160,60,170,130,80,6,TRUE\\n721,Volcanion,Fire,Water,80,110,120,130,90,70,6,TRUE\\n\"}"
            ]
          },
          "metadata": {},
          "execution_count": 109
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IulUcsJynmcB",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "outputId": "3250d332-5991-41b6-aba5-51502568274a"
      },
      "source": [
        "# Read and display the file\n",
        "\n",
        "pokemon_data = pd.read_csv('pokemon_data.csv', index_col = 0)\n",
        "pokemon_data.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Name</th>\n",
              "      <th>Type 1</th>\n",
              "      <th>Type 2</th>\n",
              "      <th>HP</th>\n",
              "      <th>Attack</th>\n",
              "      <th>Defense</th>\n",
              "      <th>Sp. Atk</th>\n",
              "      <th>Sp. Def</th>\n",
              "      <th>Speed</th>\n",
              "      <th>Generation</th>\n",
              "      <th>Legendary</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>#</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Bulbasaur</td>\n",
              "      <td>Grass</td>\n",
              "      <td>Poison</td>\n",
              "      <td>45</td>\n",
              "      <td>49</td>\n",
              "      <td>49</td>\n",
              "      <td>65</td>\n",
              "      <td>65</td>\n",
              "      <td>45</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Ivysaur</td>\n",
              "      <td>Grass</td>\n",
              "      <td>Poison</td>\n",
              "      <td>60</td>\n",
              "      <td>62</td>\n",
              "      <td>63</td>\n",
              "      <td>80</td>\n",
              "      <td>80</td>\n",
              "      <td>60</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Venusaur</td>\n",
              "      <td>Grass</td>\n",
              "      <td>Poison</td>\n",
              "      <td>80</td>\n",
              "      <td>82</td>\n",
              "      <td>83</td>\n",
              "      <td>100</td>\n",
              "      <td>100</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>VenusaurMega Venusaur</td>\n",
              "      <td>Grass</td>\n",
              "      <td>Poison</td>\n",
              "      <td>80</td>\n",
              "      <td>100</td>\n",
              "      <td>123</td>\n",
              "      <td>122</td>\n",
              "      <td>120</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Charmander</td>\n",
              "      <td>Fire</td>\n",
              "      <td>NaN</td>\n",
              "      <td>39</td>\n",
              "      <td>52</td>\n",
              "      <td>43</td>\n",
              "      <td>60</td>\n",
              "      <td>50</td>\n",
              "      <td>65</td>\n",
              "      <td>1</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                    Name Type 1  Type 2  ...  Speed  Generation  Legendary\n",
              "#                                        ...                              \n",
              "1              Bulbasaur  Grass  Poison  ...     45           1      False\n",
              "2                Ivysaur  Grass  Poison  ...     60           1      False\n",
              "3               Venusaur  Grass  Poison  ...     80           1      False\n",
              "3  VenusaurMega Venusaur  Grass  Poison  ...     80           1      False\n",
              "4             Charmander   Fire     NaN  ...     65           1      False\n",
              "\n",
              "[5 rows x 11 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 110
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jDzbsa0qnAd_"
      },
      "source": [
        "### Seaborn's plotting functions"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QBen5lF4nSQJ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 386
        },
        "outputId": "53cbb349-8104-42da-b933-0b6cf0710072"
      },
      "source": [
        "# Recommended way\n",
        "\n",
        "sns.lmplot(x = 'Attack', y = 'Defense', data=pokemon_data)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7f4d567b0e90>"
            ]
          },
          "metadata": {},
          "execution_count": 111
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "L8Pe6GEslu5X",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 386
        },
        "outputId": "47ea7e7c-1fa4-4e3e-855d-ee705f1eafc2"
      },
      "source": [
        "# Scatterplot arguments\n",
        "\n",
        "sns.lmplot(x = 'Attack', y = 'Defense', data=pokemon_data, fit_reg=False, hue='Generation')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7f4d56771710>"
            ]
          },
          "metadata": {},
          "execution_count": 112
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 423.75x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IE2sElhqnDPZ"
      },
      "source": [
        "### Customizing with Matplotlib\n",
        "\n",
        "Matplotlib comes in handy when it comes to setting your axes limits. In order to do that -\n",
        "\n",
        "1. Invoke your seaborn plotting function as normal\n",
        "2. Invoke Matplotlib's customization functions. In this case, we will use its `ylim()` and `xlim()` functions"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g145w20UKWj3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 390
        },
        "outputId": "c46f76f1-7bd4-42d0-a203-73dd89c2f1ab"
      },
      "source": [
        "# Plot using Seaborn\n",
        "\n",
        "sns.lmplot(x = 'Attack', y = 'Defense', data=pokemon_data, fit_reg=False, hue='Generation')\n",
        "\n",
        "plt.xlim(50, 100)\n",
        "plt.ylim(50, 100)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(50.0, 100.0)"
            ]
          },
          "metadata": {},
          "execution_count": 113
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 423.75x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zKJ40RO4p2nC"
      },
      "source": [
        "### Role of Pandas"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RBZmYXldp1i7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "outputId": "d2a2fbe3-86a2-4cb9-ce86-c4faedd69be2"
      },
      "source": [
        "# boxplot\n",
        "\n",
        "sns.boxplot(data=pokemon_data)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f4d4d640090>"
            ]
          },
          "metadata": {},
          "execution_count": 114
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "izlEq9zcp1zy",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "outputId": "f8d88bba-d971-498e-feeb-01a85c1224bd"
      },
      "source": [
        "# We can remove generation and Legendary as they are not combat stats\n",
        "\n",
        "# Pre-format dataframe\n",
        "stats_pokemon = pokemon_data.drop(['Generation', 'Legendary'], axis=1)\n",
        "\n",
        "# New boxplot\n",
        "sns.boxplot(data=stats_pokemon)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f4d4da45650>"
            ]
          },
          "metadata": {},
          "execution_count": 115
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "974ieZ3tqpYF"
      },
      "source": [
        "### Histogram"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2Hyv8WIjqrqi",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 351
        },
        "outputId": "9c210a32-1f9e-4619-b78c-b2892e7c51c7"
      },
      "source": [
        "# Distribution plot for Attack of the Pokemon(s)\n",
        "\n",
        "sns.distplot(pokemon_data.Attack, kde=False)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "  warnings.warn(msg, FutureWarning)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f4d4d708850>"
            ]
          },
          "metadata": {},
          "execution_count": 120
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WMkyxkVyDRk_"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}