EX_14/ex_14_pandas_operations.ipynb

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        "outputId": "e132b76e-9d50-469c-bd69-03807d7a1263"
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      "source": [
        "print(\"Hello Pandas operations!\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Hello Pandas operations!\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TrY6Bh4kX8_-"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p4E1OshdYPrq",
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        "outputId": "0f15e5e3-1c3a-4d2c-caed-5956983b4d54"
      },
      "source": [
        "df = pd.DataFrame({'col1':[1,2,3,4], \n",
        "              'col2':[444,555,666,444],\n",
        "              'col3':['abc','def','ghi','xyz']})\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",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
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              "        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>col1</th>\n",
              "      <th>col2</th>\n",
              "      <th>col3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>444</td>\n",
              "      <td>abc</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>555</td>\n",
              "      <td>def</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>666</td>\n",
              "      <td>ghi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>444</td>\n",
              "      <td>xyz</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   col1  col2 col3\n",
              "0     1   444  abc\n",
              "1     2   555  def\n",
              "2     3   666  ghi\n",
              "3     4   444  xyz"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
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    {
      "cell_type": "code",
      "metadata": {
        "id": "J3OHgj0EYvsJ"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "42oyhtGDa25n"
      },
      "source": [
        "# Operations in a DataFrame"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qgeb4IwLZbpw"
      },
      "source": [
        "## Finding Unique Values"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pIMEo1coZgcW",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "a003744e-e336-4b77-8efc-a5b97ee6b85b"
      },
      "source": [
        "df['col2'].unique()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([444, 555, 666])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
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          "base_uri": "https://localhost:8080/",
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        "outputId": "86e81a4b-af42-46af-f40d-8f5406d70190"
      },
      "source": [
        "len(df['col2'].unique())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "3"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QhKr6VpDZ8Jd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "54c8baa6-1abc-47df-9704-092c01b42af1"
      },
      "source": [
        "df['col2'].nunique()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "3"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qh-2JG49amuC"
      },
      "source": [
        "## Counting Values"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qRVTZLqtaCX3",
        "colab": {
          "base_uri": "https://localhost:8080/",
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        "outputId": "4dccdefb-a645-421c-82d4-f0ceda2e884f"
      },
      "source": [
        "df['col2'].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "444    2\n",
              "555    1\n",
              "666    1\n",
              "Name: col2, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NfbzAYFWaQlq"
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      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "w1yEBNJAbIkD"
      },
      "source": [
        "## Conditional Selections"
      ]
    },
    {
      "cell_type": "code",
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        "id": "RYndsvZyared",
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          "base_uri": "https://localhost:8080/",
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        "outputId": "020a4a4a-38b3-4338-ae3c-ad0e88491430"
      },
      "source": [
        "df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "    }\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>col1</th>\n",
              "      <th>col2</th>\n",
              "      <th>col3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>444</td>\n",
              "      <td>abc</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>555</td>\n",
              "      <td>def</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>666</td>\n",
              "      <td>ghi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>444</td>\n",
              "      <td>xyz</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
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            "text/plain": [
              "   col1  col2 col3\n",
              "0     1   444  abc\n",
              "1     2   555  def\n",
              "2     3   666  ghi\n",
              "3     4   444  xyz"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PKQJal7JbSoM",
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          "base_uri": "https://localhost:8080/",
          "height": 111
        },
        "outputId": "abefacbd-9146-4387-d51a-a4382f7477c5"
      },
      "source": [
        "# Returnning a DataFrame where 'col1' happen to be greater than two\n",
        "df[df['col1']>2]"
      ],
      "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",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\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>col1</th>\n",
              "      <th>col2</th>\n",
              "      <th>col3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>666</td>\n",
              "      <td>ghi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>444</td>\n",
              "      <td>xyz</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   col1  col2 col3\n",
              "2     3   666  ghi\n",
              "3     4   444  xyz"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "h5GZDTM6beRt",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 80
        },
        "outputId": "2cd8faf0-ccbf-4193-e112-910ee3dd90a4"
      },
      "source": [
        "# Combining Conditional Selection\n",
        "df[(df['col1']>2) & (df['col2']==444)]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>col1</th>\n",
              "      <th>col2</th>\n",
              "      <th>col3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>444</td>\n",
              "      <td>xyz</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   col1  col2 col3\n",
              "3     4   444  xyz"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
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    {
      "cell_type": "code",
      "metadata": {
        "id": "AbsFX9qwcF3c"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "e3frr4TIc373"
      },
      "source": [
        "## Apply Method\n",
        "One of the powerful method in our tool belt When using Pandas"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "K_2-nlfmdaPy",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "bb9b1444-ae94-4b1f-a801-c51184af905d"
      },
      "source": [
        "# We can grab a column and call a built-in function of it\n",
        "df['col2'].sum()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2109"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-Mm3NUCidn0m"
      },
      "source": [
        "# But we can apply our custom function:\n",
        "def times2(x):\n",
        "  return x*2"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_Qx8H15Yd3sK",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 102
        },
        "outputId": "21949778-e15a-44c7-8040-bdb058ade971"
      },
      "source": [
        "# We can broadcast our function for each element in that column:\n",
        "df['col2'].apply(times2)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0     888\n",
              "1    1110\n",
              "2    1332\n",
              "3     888\n",
              "Name: col2, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0wGyvzwcd-Qr",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 102
        },
        "outputId": "16bcacbc-9619-484b-d5d6-c93fd469a963"
      },
      "source": [
        "# Let's go ahead and apply it with lambda expression:\n",
        "# This is probably the most powerful feature in Pandas: The ability to apply our custom lambda expression!\n",
        "df['col2'].apply(lambda x:x*2)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0     888\n",
              "1    1110\n",
              "2    1332\n",
              "3     888\n",
              "Name: col2, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UfpyLRxce4iM"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YkLDp61wflVF"
      },
      "source": [
        "## Removing Columns"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GQOAcKRqfn4j",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        },
        "outputId": "03d50279-e587-4697-f8d1-ad22542c1b81"
      },
      "source": [
        "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",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>col1</th>\n",
              "      <th>col2</th>\n",
              "      <th>col3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>444</td>\n",
              "      <td>abc</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>555</td>\n",
              "      <td>def</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>666</td>\n",
              "      <td>ghi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>444</td>\n",
              "      <td>xyz</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   col1  col2 col3\n",
              "0     1   444  abc\n",
              "1     2   555  def\n",
              "2     3   666  ghi\n",
              "3     4   444  xyz"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
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    {
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        "outputId": "0939b432-fe54-4d07-9b80-1bb5dbc6290a"
      },
      "source": [
        "# If you want that to occurs in place, we going to have to specify 'implace=True'\n",
        "df.drop('col1', axis=1)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>col2</th>\n",
              "      <th>col3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>444</td>\n",
              "      <td>abc</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>555</td>\n",
              "      <td>def</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>666</td>\n",
              "      <td>ghi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>444</td>\n",
              "      <td>xyz</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   col2 col3\n",
              "0   444  abc\n",
              "1   555  def\n",
              "2   666  ghi\n",
              "3   444  xyz"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0nBPP4Cwf2b8"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0z85c8RXgRjx"
      },
      "source": [
        "## Returning The Columns Name & Index Attributes"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YhkcoZFMgU9A",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "f1fc1b88-7743-486a-aa75-87a3497bf10a"
      },
      "source": [
        "df.columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['col1', 'col2', 'col3'], dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "c5nTovZ7gckK",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "8cf66d40-767e-457f-db5d-dc153a47105f"
      },
      "source": [
        "df.index"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "RangeIndex(start=0, stop=4, step=1)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_G-5lJKrgpdg"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "v0F1FyHlgvx3"
      },
      "source": [
        "## Sorting & Ordering a DataFrame"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "87FONpHgg5qF",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        },
        "outputId": "89c49214-51a0-4102-b1d7-2896c451bf48"
      },
      "source": [
        "# Just pass in the column we want to sort by:\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>col1</th>\n",
              "      <th>col2</th>\n",
              "      <th>col3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>444</td>\n",
              "      <td>abc</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>555</td>\n",
              "      <td>def</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>666</td>\n",
              "      <td>ghi</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>444</td>\n",
              "      <td>xyz</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   col1  col2 col3\n",
              "0     1   444  abc\n",
              "1     2   555  def\n",
              "2     3   666  ghi\n",
              "3     4   444  xyz"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ctqlwfEthNNg",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        },
        "outputId": "3ee7e7de-a89a-4227-fbed-d6a8eed75c72"
      },
      "source": [
        "df.sort_values('col2')"
      ],
      "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>col1</th>\n",
              "      <th>col2</th>\n",
              "      <th>col3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>444</td>\n",
              "      <td>abc</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>444</td>\n",
              "      <td>xyz</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>555</td>\n",
              "      <td>def</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>666</td>\n",
              "      <td>ghi</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   col1  col2 col3\n",
              "0     1   444  abc\n",
              "3     4   444  xyz\n",
              "1     2   555  def\n",
              "2     3   666  ghi"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fpcUe-UwhTVH",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        },
        "outputId": "289db584-83e2-4eb9-8aff-ab18e2f9d28a"
      },
      "source": [
        "df.sort_values(by='col2')"
      ],
      "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>col1</th>\n",
              "      <th>col2</th>\n",
              "      <th>col3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>444</td>\n",
              "      <td>abc</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>444</td>\n",
              "      <td>xyz</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>555</td>\n",
              "      <td>def</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>666</td>\n",
              "      <td>ghi</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   col1  col2 col3\n",
              "0     1   444  abc\n",
              "3     4   444  xyz\n",
              "1     2   555  def\n",
              "2     3   666  ghi"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3-TtnZzChiCE"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "X2YAUzeLhz_n"
      },
      "source": [
        "## Booleans"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CETEUHV5h1wi",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        },
        "outputId": "64808b12-1390-4048-c933-a24a6195b4ac"
      },
      "source": [
        "df.isnull()"
      ],
      "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>col1</th>\n",
              "      <th>col2</th>\n",
              "      <th>col3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    col1   col2   col3\n",
              "0  False  False  False\n",
              "1  False  False  False\n",
              "2  False  False  False\n",
              "3  False  False  False"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qGVXWkukh34c"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jTx2MkFLh5DJ"
      },
      "source": [
        "# Pivot Tables\n",
        "The pivot table takes simple column-wise data as input and groups the entries into a two-dimensional table that provides a **multidimensional summarization of the data**\n",
        "\n",
        "As we build up the pivot table, I think it’s easiest to take it one step at a time. Add items and check each step to verify you are getting the results you expect. Don’t be afraid to play with the order and the variables to see what presentation makes the most sense for your needs."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uwn0p4gJidUe"
      },
      "source": [
        "data=pd.DataFrame({'A':['foo','foo','foo','bar','bar','bar'],\n",
        "              'B':['one','one','two','two','one', 'one'],\n",
        "              'C':['x','y','x','y','x','y'],\n",
        "              'D':[1,3,2,5,4,1]})\n",
        "\n",
        "#data\n",
        "df=pd.DataFrame(data)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uefvZvqxjjKE",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "2eafb896-0a32-490f-bb77-121f4e73dbc9"
      },
      "source": [
        "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>A</th>\n",
              "      <th>B</th>\n",
              "      <th>C</th>\n",
              "      <th>D</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>foo</td>\n",
              "      <td>one</td>\n",
              "      <td>x</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>foo</td>\n",
              "      <td>one</td>\n",
              "      <td>y</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>foo</td>\n",
              "      <td>two</td>\n",
              "      <td>x</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>bar</td>\n",
              "      <td>two</td>\n",
              "      <td>y</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>bar</td>\n",
              "      <td>one</td>\n",
              "      <td>x</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>bar</td>\n",
              "      <td>one</td>\n",
              "      <td>y</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     A    B  C  D\n",
              "0  foo  one  x  1\n",
              "1  foo  one  y  3\n",
              "2  foo  two  x  2\n",
              "3  bar  two  y  5\n",
              "4  bar  one  x  4\n",
              "5  bar  one  y  1"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8z7bZayBj0Ds",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "04f715d2-126f-4996-e9ca-be802ba971b3"
      },
      "source": [
        "# Pivot method takes 3 values: values, index, and columns\n",
        "df.pivot_table(values='D', index=['A','B'], columns='C')"
      ],
      "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>C</th>\n",
              "      <th>x</th>\n",
              "      <th>y</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>A</th>\n",
              "      <th>B</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">bar</th>\n",
              "      <th>one</th>\n",
              "      <td>4.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>two</th>\n",
              "      <td>NaN</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">foo</th>\n",
              "      <th>one</th>\n",
              "      <td>1.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>two</th>\n",
              "      <td>2.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "C          x    y\n",
              "A   B            \n",
              "bar one  4.0  1.0\n",
              "    two  NaN  5.0\n",
              "foo one  1.0  3.0\n",
              "    two  2.0  NaN"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4QsEC9O4k7VA",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "faebb270-19b9-4f63-d253-457e0d788bd8"
      },
      "source": [
        "# https://medium.com/jungletronics/pandas-operations-4b8f7a4b4139\n",
        "print(\"Thanks everyone! See you in the Next Pandas Lecture o/\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Thanks everyone! See you in the Next Pandas Lecture o/\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}