report.ipynb

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      "name": "report.ipynb",
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    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "nMxtd2OuFt-p"
      },
      "outputs": [],
      "source": [
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "column_names = [\"Runtime min\", \"Runtime avg\", \"Runtime max\",\n",
        "                \"Read min\", \"Read avg\", \"Read max\",\n",
        "                \"Write min\", \"Write avg\", \"Write max\",\n",
        "                \"Tx per block min\", \"Tx per block avg\", \"Tx per block max\"]\n",
        "df = pd.DataFrame(columns=column_names)"
      ],
      "metadata": {
        "id": "L9qtiB3iF3Xk"
      },
      "execution_count": 2,
      "outputs": []
    },
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      "cell_type": "code",
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        "df.loc[10] = [13450000, 57027250, 72936000, 13427, 23032, 26389, 0, 4499, 6205, 371, 144, 68]\n",
        "df.loc[20] = [13490000, 101302250, 131956000, 13467, 32755, 39339, 0, 9127, 12375, 370, 120, 37]\n",
        "df.loc[30] = [13530000, 145577250, 190976000, 13507, 42477, 52289, 0, 13754, 18545, 369, 111, 26]\n",
        "df.loc[40] = [13570000, 189852250, 249996000, 13547, 52200, 65239, 0, 18382, 24715, 368, 107, 20]\n",
        "df.loc[50] = [13610000, 234127250, 304867000, 13587, 61922, 77726, 0, 23009, 30268, 367, 103, 16]\n",
        "df.loc[60] = [13650000, 278402250, 368036000, 13627, 71645, 91139, 0, 27637, 37055, 366, 101, 13]\n",
        "df.loc[70] = [13690000, 322677250, 427056000, 13667, 81367, 104089, 0, 32264, 43225, 365, 99, 11]\n",
        "df.loc[80] = [13730000, 366952250, 481927000, 13707, 91090, 116576, 0, 36892, 48778, 364, 98, 10]\n",
        "df.loc[90] = [13770000, 411227250, 545096000, 13747, 100812, 129989, 0, 41519, 55565, 363, 97, 9]\n",
        "\n",
        "df.loc[100] = [13812000, 455504250, 599969000, 13789, 110537, 142478, 0, 46147, 61118, 362, 96, 8]\n",
        "df.loc[200] = [14312000, 898354250, 1190269000, 14289, 207862, 272078, 0, 92422, 122818, 349, 90, 4]\n",
        "df.loc[300] = [14812000, 1341204250, 1784718000, 14789, 305187, 402141, 0, 138697, 185135, 337, 85, 2]\n",
        "df.loc[400] = [15312000, 1784054250, 2370869000, 15289, 402512, 531278, 0, 184972, 246218, 326, 83, 2]\n",
        "df.loc[500] = [15812000, 2226904250, 2961169000, 15789, 499837, 660878, 0, 231247, 307918, 316, 79, 1]\n",
        "df.loc[600] = [16312000, 2669754250, 3555618000, 16289, 597162, 790941, 0, 277522, 370235, 306, 77, 1]\n",
        "df.loc[700] = [16812000, 3112604250, 4141769000, 16789, 694487, 920078, 0, 323797, 431318, 297, 75, 1]\n",
        "df.loc[800] = [17312000, 3555454250, 4732069000, 17289, 791812, 1049678, 0, 370072, 493018, 288, 72, 1]"
      ],
      "metadata": {
        "id": "deCbiwmWF-On"
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      "outputs": []
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    {
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      "source": [
        "df"
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        "outputId": "9f5b26fe-1a00-4eb4-8427-d6ee33a2d008"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    Runtime min Runtime avg Runtime max Read min Read avg Read max Write min  \\\n",
              "10     13450000    57027250    72936000    13427    23032    26389         0   \n",
              "20     13490000   101302250   131956000    13467    32755    39339         0   \n",
              "30     13530000   145577250   190976000    13507    42477    52289         0   \n",
              "40     13570000   189852250   249996000    13547    52200    65239         0   \n",
              "50     13610000   234127250   304867000    13587    61922    77726         0   \n",
              "60     13650000   278402250   368036000    13627    71645    91139         0   \n",
              "70     13690000   322677250   427056000    13667    81367   104089         0   \n",
              "80     13730000   366952250   481927000    13707    91090   116576         0   \n",
              "90     13770000   411227250   545096000    13747   100812   129989         0   \n",
              "100    13812000   455504250   599969000    13789   110537   142478         0   \n",
              "200    14312000   898354250  1190269000    14289   207862   272078         0   \n",
              "300    14812000  1341204250  1784718000    14789   305187   402141         0   \n",
              "400    15312000  1784054250  2370869000    15289   402512   531278         0   \n",
              "500    15812000  2226904250  2961169000    15789   499837   660878         0   \n",
              "600    16312000  2669754250  3555618000    16289   597162   790941         0   \n",
              "700    16812000  3112604250  4141769000    16789   694487   920078         0   \n",
              "800    17312000  3555454250  4732069000    17289   791812  1049678         0   \n",
              "\n",
              "    Write avg Write max Tx per block min Tx per block avg Tx per block max  \n",
              "10       4499      6205              371              144               68  \n",
              "20       9127     12375              370              120               37  \n",
              "30      13754     18545              369              111               26  \n",
              "40      18382     24715              368              107               20  \n",
              "50      23009     30268              367              103               16  \n",
              "60      27637     37055              366              101               13  \n",
              "70      32264     43225              365               99               11  \n",
              "80      36892     48778              364               98               10  \n",
              "90      41519     55565              363               97                9  \n",
              "100     46147     61118              362               96                8  \n",
              "200     92422    122818              349               90                4  \n",
              "300    138697    185135              337               85                2  \n",
              "400    184972    246218              326               83                2  \n",
              "500    231247    307918              316               79                1  \n",
              "600    277522    370235              306               77                1  \n",
              "700    323797    431318              297               75                1  \n",
              "800    370072    493018              288               72                1  "
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Runtime min</th>\n",
              "      <th>Runtime avg</th>\n",
              "      <th>Runtime max</th>\n",
              "      <th>Read min</th>\n",
              "      <th>Read avg</th>\n",
              "      <th>Read max</th>\n",
              "      <th>Write min</th>\n",
              "      <th>Write avg</th>\n",
              "      <th>Write max</th>\n",
              "      <th>Tx per block min</th>\n",
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              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>13450000</td>\n",
              "      <td>57027250</td>\n",
              "      <td>72936000</td>\n",
              "      <td>13427</td>\n",
              "      <td>23032</td>\n",
              "      <td>26389</td>\n",
              "      <td>0</td>\n",
              "      <td>4499</td>\n",
              "      <td>6205</td>\n",
              "      <td>371</td>\n",
              "      <td>144</td>\n",
              "      <td>68</td>\n",
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              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>13490000</td>\n",
              "      <td>101302250</td>\n",
              "      <td>131956000</td>\n",
              "      <td>13467</td>\n",
              "      <td>32755</td>\n",
              "      <td>39339</td>\n",
              "      <td>0</td>\n",
              "      <td>9127</td>\n",
              "      <td>12375</td>\n",
              "      <td>370</td>\n",
              "      <td>120</td>\n",
              "      <td>37</td>\n",
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              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>13530000</td>\n",
              "      <td>145577250</td>\n",
              "      <td>190976000</td>\n",
              "      <td>13507</td>\n",
              "      <td>42477</td>\n",
              "      <td>52289</td>\n",
              "      <td>0</td>\n",
              "      <td>13754</td>\n",
              "      <td>18545</td>\n",
              "      <td>369</td>\n",
              "      <td>111</td>\n",
              "      <td>26</td>\n",
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              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>13570000</td>\n",
              "      <td>189852250</td>\n",
              "      <td>249996000</td>\n",
              "      <td>13547</td>\n",
              "      <td>52200</td>\n",
              "      <td>65239</td>\n",
              "      <td>0</td>\n",
              "      <td>18382</td>\n",
              "      <td>24715</td>\n",
              "      <td>368</td>\n",
              "      <td>107</td>\n",
              "      <td>20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>13610000</td>\n",
              "      <td>234127250</td>\n",
              "      <td>304867000</td>\n",
              "      <td>13587</td>\n",
              "      <td>61922</td>\n",
              "      <td>77726</td>\n",
              "      <td>0</td>\n",
              "      <td>23009</td>\n",
              "      <td>30268</td>\n",
              "      <td>367</td>\n",
              "      <td>103</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>60</th>\n",
              "      <td>13650000</td>\n",
              "      <td>278402250</td>\n",
              "      <td>368036000</td>\n",
              "      <td>13627</td>\n",
              "      <td>71645</td>\n",
              "      <td>91139</td>\n",
              "      <td>0</td>\n",
              "      <td>27637</td>\n",
              "      <td>37055</td>\n",
              "      <td>366</td>\n",
              "      <td>101</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>70</th>\n",
              "      <td>13690000</td>\n",
              "      <td>322677250</td>\n",
              "      <td>427056000</td>\n",
              "      <td>13667</td>\n",
              "      <td>81367</td>\n",
              "      <td>104089</td>\n",
              "      <td>0</td>\n",
              "      <td>32264</td>\n",
              "      <td>43225</td>\n",
              "      <td>365</td>\n",
              "      <td>99</td>\n",
              "      <td>11</td>\n",
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              "    <tr>\n",
              "      <th>80</th>\n",
              "      <td>13730000</td>\n",
              "      <td>366952250</td>\n",
              "      <td>481927000</td>\n",
              "      <td>13707</td>\n",
              "      <td>91090</td>\n",
              "      <td>116576</td>\n",
              "      <td>0</td>\n",
              "      <td>36892</td>\n",
              "      <td>48778</td>\n",
              "      <td>364</td>\n",
              "      <td>98</td>\n",
              "      <td>10</td>\n",
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              "    <tr>\n",
              "      <th>90</th>\n",
              "      <td>13770000</td>\n",
              "      <td>411227250</td>\n",
              "      <td>545096000</td>\n",
              "      <td>13747</td>\n",
              "      <td>100812</td>\n",
              "      <td>129989</td>\n",
              "      <td>0</td>\n",
              "      <td>41519</td>\n",
              "      <td>55565</td>\n",
              "      <td>363</td>\n",
              "      <td>97</td>\n",
              "      <td>9</td>\n",
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              "      <th>100</th>\n",
              "      <td>13812000</td>\n",
              "      <td>455504250</td>\n",
              "      <td>599969000</td>\n",
              "      <td>13789</td>\n",
              "      <td>110537</td>\n",
              "      <td>142478</td>\n",
              "      <td>0</td>\n",
              "      <td>46147</td>\n",
              "      <td>61118</td>\n",
              "      <td>362</td>\n",
              "      <td>96</td>\n",
              "      <td>8</td>\n",
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              "      <th>200</th>\n",
              "      <td>14312000</td>\n",
              "      <td>898354250</td>\n",
              "      <td>1190269000</td>\n",
              "      <td>14289</td>\n",
              "      <td>207862</td>\n",
              "      <td>272078</td>\n",
              "      <td>0</td>\n",
              "      <td>92422</td>\n",
              "      <td>122818</td>\n",
              "      <td>349</td>\n",
              "      <td>90</td>\n",
              "      <td>4</td>\n",
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              "      <th>300</th>\n",
              "      <td>14812000</td>\n",
              "      <td>1341204250</td>\n",
              "      <td>1784718000</td>\n",
              "      <td>14789</td>\n",
              "      <td>305187</td>\n",
              "      <td>402141</td>\n",
              "      <td>0</td>\n",
              "      <td>138697</td>\n",
              "      <td>185135</td>\n",
              "      <td>337</td>\n",
              "      <td>85</td>\n",
              "      <td>2</td>\n",
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              "      <th>400</th>\n",
              "      <td>15312000</td>\n",
              "      <td>1784054250</td>\n",
              "      <td>2370869000</td>\n",
              "      <td>15289</td>\n",
              "      <td>402512</td>\n",
              "      <td>531278</td>\n",
              "      <td>0</td>\n",
              "      <td>184972</td>\n",
              "      <td>246218</td>\n",
              "      <td>326</td>\n",
              "      <td>83</td>\n",
              "      <td>2</td>\n",
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              "      <th>500</th>\n",
              "      <td>15812000</td>\n",
              "      <td>2226904250</td>\n",
              "      <td>2961169000</td>\n",
              "      <td>15789</td>\n",
              "      <td>499837</td>\n",
              "      <td>660878</td>\n",
              "      <td>0</td>\n",
              "      <td>231247</td>\n",
              "      <td>307918</td>\n",
              "      <td>316</td>\n",
              "      <td>79</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>600</th>\n",
              "      <td>16312000</td>\n",
              "      <td>2669754250</td>\n",
              "      <td>3555618000</td>\n",
              "      <td>16289</td>\n",
              "      <td>597162</td>\n",
              "      <td>790941</td>\n",
              "      <td>0</td>\n",
              "      <td>277522</td>\n",
              "      <td>370235</td>\n",
              "      <td>306</td>\n",
              "      <td>77</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>700</th>\n",
              "      <td>16812000</td>\n",
              "      <td>3112604250</td>\n",
              "      <td>4141769000</td>\n",
              "      <td>16789</td>\n",
              "      <td>694487</td>\n",
              "      <td>920078</td>\n",
              "      <td>0</td>\n",
              "      <td>323797</td>\n",
              "      <td>431318</td>\n",
              "      <td>297</td>\n",
              "      <td>75</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>800</th>\n",
              "      <td>17312000</td>\n",
              "      <td>3555454250</td>\n",
              "      <td>4732069000</td>\n",
              "      <td>17289</td>\n",
              "      <td>791812</td>\n",
              "      <td>1049678</td>\n",
              "      <td>0</td>\n",
              "      <td>370072</td>\n",
              "      <td>493018</td>\n",
              "      <td>288</td>\n",
              "      <td>72</td>\n",
              "      <td>1</td>\n",
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              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[['Runtime min', 'Runtime avg', 'Runtime max']].iloc[0:9].plot()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 293
        },
        "id": "bjXtGZ3ZGF5u",
        "outputId": "a410922a-781f-44ee-8d4f-c15c5eecf615"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7ff84c40e610>"
            ]
          },
          "metadata": {},
          "execution_count": 14
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[['Runtime min', 'Runtime avg', 'Runtime max']].iloc[9:].plot()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 293
        },
        "id": "NFyzw7QmGOgZ",
        "outputId": "d3bf58c8-d580-41a8-d2b6-c898c7dcd816"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7ff84c41e4d0>"
            ]
          },
          "metadata": {},
          "execution_count": 17
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[['Read min', 'Read avg', 'Read max']].iloc[0:9].plot()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "byXvKMFeHh8n",
        "outputId": "5d2de1f2-5217-4db9-9cf9-9054a384144c"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7ff84c2d7810>"
            ]
          },
          "metadata": {},
          "execution_count": 19
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[['Read min', 'Read avg', 'Read max']].iloc[9:].plot()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 293
        },
        "id": "w9GyiAuUHzja",
        "outputId": "c1d091ae-0f98-461e-d287-1e33ac39e8da"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7ff84c247b90>"
            ]
          },
          "metadata": {},
          "execution_count": 20
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[['Write min', 'Write avg', 'Write max']].iloc[0:9].plot()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "utafCuUxIBeX",
        "outputId": "bd90ca8d-7261-4626-ce92-acf3bf82f0ee"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7ff84c172310>"
            ]
          },
          "metadata": {},
          "execution_count": 21
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[['Write min', 'Write avg', 'Write max']].iloc[9:].plot()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "828r0kfKILxS",
        "outputId": "3d163e1b-4e61-47d2-f5b7-00439179f735"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7ff84c104c10>"
            ]
          },
          "metadata": {},
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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wUqoNMALwBxoAPyqlWpjnmgv0A+KBcKVUmNb6wA3quGU3+sZflqyYKhzAxcXokHNwcLiyXfA8NzeXY8eOMW3aNMLDw6lRowajR48mMzMTMJZaPXjwIO7u7iQnJ+Pr63uzv7YQ5SIvP4+wI2F8tPsjzmWco3/j/kzqNAmfaj5Wh2b3SjS6SSnlC9wHLDGfK6APsM7cZQXwgLk9xHyO+frd5v5DgDVa6yyt9TEgFuhiPmK11kfNq4Q1wJBi6rA7VkwVXhKpqalUrVoVLy8vzp49y+bNm6+8NnPmTFq3bs2qVasYM2YMOTk5t1SHEGVp5+mdjPh2BP/Y+g/qV63PJwM+IfQvoZIgSklJryRmAa8CHubzmsBFrXWu+TweKPgX8QFOAmitc5VSKeb+PsD2QucsfMzJP5UHF1OH3SmYKvyRRx65qqyg47k4BVOFF3Rcr1u3jhdeeIGUlBRyc3OZNGkS/v7+Nx1X+/bt6dChA61atcLPz+9K01dMTAxLlixh586deHh40LNnT9577z3efvvtm65DiLIQlxLHjMgZ/Ofkf6hftT4hPUPo37i/3AxXyoqdKlwpdT8wUGv9rFKqF/AyMBrYrrVuZu7jB2zWWrdVSu0H+mut483XjmB86L9lHvOpWb4UKPja2l9rPc4sf/xP+19Tx3VinABMAGjYsGGn48ePX/W6TGddduRvK8pbSlYKC/YuYM2hNbg4uTAuYByPtX4MVydXq0Oza7czVXh3YLBSaiDgitEnMRuorpRyMr/p+wIJ5v4JgB8Qr5RyArwwOrALygsUPuZ65Uk3qOMqWutFwCIw1pMowe8khLAzOXk5fB7zOfP3zictJ40Hmz/Ic4HPUcut+CtxceuK7ZPQWv9Na+2rtW6M0fG8RWv9KPAfYJi52yigYHWaMPM55utbtHG5EgaMUEq5mKOWmgM7gXCguVKqiVKqillHmHlMUXUIISoJrTVbTmxhaNhQpoZPxb+mP18M+oI3u74pCaIc3M6g4deANUqp94DdwFKzfCnwiVIqFriA8aGP1jpaKbUWOADkAs9prfMAlFITge8whsAu01pHF1PHTdNaS1tlKatoqxoK23Mw6SChEaGEnwmniVcT5t49l7t87pL/y+WoUixfeuzYMTw8PKhZs6a8uUqJ1pqkpCQuXbpEkyZNrA5HVDCJ6Yl8uOtDwo6E4eXixXOBz/HXFn/F2cHZ6tAqrEq9fKmvry/x8fGcO3fO6lAqFFdXV7l3QpSq9Jx0VhxYwcf7PyY3P5fR/qMZ124cnlU8iz9YlIlKkSScnZ3l264QNixf57Px6EZm75pNYnoi/Rr1Y3LHyfh5+hV/sChTlSJJCCFsV8SZCEIjQjmQdAD/mv6E9gylY92OVoclTJIkhBCWOJF6gpmRM/nxxI/Uda/LP3v8k/ua3oeDkmVubIkkCSFEuUrJSmFR1CJWHVqFs4MzEwMn8oT/E7g5uVkdmrgOSRJCiHKRk5/DFzFfMH/vfFKyUhjafCgTAydS27221aHZv7xciPsf3NG71E8tSUIIUeZ+TfiV0PBQjqYcJbheMC93fplW3q2sDsv+XU6CXSsgfCmkxsOEn6FBh1KtQpKEEKLMHEs5xrSIafwS/wt+Hn7M7j2b3n695X6l23U6CnYuhH3rIDcTmvSEAVOhXrtSr0qShBCi1KVmp7Jg7wJWH1yNq5MrL3V6iUdaP0IVxypWh2a/8nLg0EbYsRBObANnd2g/ErpMgLptyqxaSRJCiFKTl5/H+sPrmbN7DhezLvJg8weZ2GGizLF0Oy6fh8iPIXwZXDoFNRrDPe9Dh0fBrUaZVy9JQghRKnac3sHU8KkcTj5Mp7qdeK3za7SuKdPI37JTu2HHIti/DvKyoWlvuH8GNL8HHBzLLQxJEkKI23Iy9STTIqax5eQWfKr5MP0v0+nXqJ/0O9yK3Gw4GGY0KcXvBOeq0HGU0aRUu0Xxx5cBSRJCiFuSlp3G4n2L+eTAJzg5OPFChxd4wv8JXBxdij9YXO3SWYhcDhHLIO0MeDeF/h9A4CPg6mVpaJIkhBA3JV/nsyF2A7N3zSYpM4nBdwzmxY4vUse9jtWh2Z/4COOqIforyM+BZn0heA7ccTc42Mad55IkhBAlFnk2kqk7p3LwwkHa127PR30+IqB2gNVh2ZfcLIj+2hjCmhAJVTyg81joPB5qNbM6umtIkhBCFOtU2ilmRM7gu7jvqOtelw/u+oCBTQZKv8PNSD1tNCdFfgyXz0HN5jBwGrQfAS4eVkdXJEkSQogipeeks2z/MpZHL0eheKb9M4z2H427s7vVodkHreHkTuOq4cAGyM+DFvcaHdFNe9tMk9KNSJIQQlwjX+fz7dFvmbVrFonpiQxoMoApnaZQr2o9q0OzDzmZsH+9kRxO7wUXL+jyFHQZZ3RK2xFJEkKIq0Sdi2LqzqlEnY/Cv6Y/0/8yncA6gVaHZR9SEiBiqTFSKT0JareC+2ZAu4fBpZrV0d0SSRJCCADOXj7LrF2z2Hh0I7XdavNe9/cYdMcgWd+hOFob02TsWAgHvwE0tBgAwU8ZcyrZeb+NJAkhKrnM3EyWRy9n2f5l5OXnMT5gPOMCxkm/Q3FyMmDfF8Zd0Wf3gWt16PocdB4HNRpZHV2pkSQhRCWltea7498xM2Impy6fol+jfkzpNAVfD1+rQ7NtF09C+BJjiu6MZKjjD4NmQ8BwqFLxEqskCSEqoQNJB5i6cyq7EnfRskZLlvVYRud6na0Oy3ZpDXG/wo4FELPJKGt1v9Gk1Ki73Tcp3YgkCSEqkfMZ5/lw14d8Hfs1NVxr8GbXNxnabCiO5ThhnF3JvgxRa2HnIkg8AG7e0P1FCBoL1f2sjq5cSJIQohLIzsvmkwOfsHjfYrLyshjlP4oJ7SbgUcV2b+KyVHKc2aS0EjJTjMV8hsyFtn8F58q1FrckCSEqMK01W05sYVrENOLT4unl14uXg16mkWfF6VgtNVrD0Z+Nq4aYzaAcoM1g4/6GhndW6CalG5EkIUQFFXMhhpDwEHae2Umz6s1Y2G8h3Rp0szos25OVBlFrjFFK52PAvRb0fBmCngTPBlZHZzlJEkJUMBcyLzB391zWHV6HRxUP/i/4/3ioxUM4Och/96skHTGalHZ/Blkp0KADPLAA/IeCs6vV0dkMedcIUUHk5OWw+tBqFuxdQHpuOiNbjeSZ9s/g5WLtegQ2JT8fjm4xbnw7/IOxwlubByD4afANqrRNSjciSUKICuCX+F8IDQ8lLjWO7j7deTXoVZpWt685gspUZirsXW30NyTFQtU68JfXIGgMeMh8VDciSUIIO3b04lFCIkL4LeE3Gns2Zu7dc+np29PqsGzH+VgjMexZBdmXwCcIHlxsXD04VbE6OrtQbJJQSrkCvwAu5v7rtNZvKqWaAGuAmkAk8LjWOlsp5QKsBDoBScDDWus481x/A8YCecALWuvvzPL+wGzAEViitf7ALL9uHaX0uwthty5mXmTe3nmsjVmLu5M7r3Z+lREtR+Ds6Gx1aNbLz4fYH40ZWGN/BAdnY+hq8ATw6WR1dHanJFcSWUAfrXWaUsoZ+FUptRmYAszUWq9RSi3A+PCfb/5M1lo3U0qNAKYCDyul2gAjAH+gAfCjUqpgZe+5QD8gHghXSoVprQ+Yx16vDiEqpZy8HNbErGH+3vlczrnMQy0e4tnAZ/F29bY6NOtlphid0OGL4cJRqFYPev8dOo2GarK06q0qNklorTWQZj51Nh8a6AM8YpavAN7C+AAfYm4DrAPmKGP5qiHAGq11FnBMKRULdDH3i9VaHwVQSq0BhiilDt6gDiEqFa01v8T/wrSIacSlxtGtQTdeDnqZ5jWaWx2a9c7FmE1KqyHnMvgFQ583oPVgkCur21aiPgmllCNGc08zjG/9R4CLWutcc5d4wMfc9gFOAmitc5VSKRjNRT7A9kKnLXzMyT+VB5vHFFWHEJXG78m/ExoeyvbT26/0O9zlc1flXjo0Pw9+/85oUjr6Mzi6QMAwY8W3BrL2RWkqUZLQWucBgUqp6sBXQKsyjeomKaUmABMAGjZsaHE0QpSOwvc7VHOuxutdXmd4y+E4O1Tib8cZybD7U9i5GC4eB08fuPsf0HEUVK1ldXQV0k2NbtJaX1RK/QfoClRXSjmZ3/R9gQRztwTAD4hXSjkBXhgd2AXlBQofc73ypBvU8ee4FgGLAIKCgvTN/E5C2JrsvGxWHVzFwqiFZOZmyv0OAGcPGFcNUWshJ92YebXfO8ZMrI4ySLMslWR0U20gx0wQbhgdzFOB/wDDMEYfjQI2mIeEmc+3ma9v0VprpVQYsEopNQOj47o5sBNQQHNzJFMCRuf2I+YxRdUhRIWjtWbLyS1Mj5jOyUsn6enbk5eCXqKpVyW93yEvF37fbNz4Fvc/cHKFgIeM6bnrBVgdXaVRkhRcH1hh9ks4AGu11huVUgeANUqp94DdwFJz/6XAJ2bH9AWMD3201tFKqbXAASAXeM5sxkIpNRH4DmMI7DKtdbR5rteKqEOICuXQhUOEhIcQfibcmGep70K6+VTSeZbSLxgL+oQvhZST4OUHfd+Gjk+Au4ziKm/KGLxUcQQFBemIiAirwxCiRM5nnGfO7jl8efhLvFy8mBg4kb+2+GvlnGfpzD7jqmHfF5CbCY3vMq4aWgyQJqVyoJSK1FoH/blc/vJCWCArL8tY3yFqMdn52TzR5gkmtJ+AZxVPq0MrX3m5cGijkRxObAUnN2g/whilVNff6ugEkiSEKFdaa74//j0zI2eSkJZAH78+TAmaUvnWd7h8HiKXQ8QySE2A6o3gnvegw2PgVsPq6EQhkiSEKCfRSdGE7AxhV+IuWtRowZJ7lhBcP9jqsMrXqT3GjW/71kFeFjTtBQOnQYt7jRlZhc2RJCFEGUtMT2T2rtmEHQnD29Wbt7q+xQPNHqg860rn5cDBMKNJ6eQOcK4KHR83mpRqt7Q6OlEMSRJClJGM3AxWRK9g2f5l5Obn8mTbJxkfMJ5qVapZHVr5SEv8o0np0mmo0QTu/Rd0eBRcK/E9H3ZGkoQQpUxrzeZjm5m5ayZnLp+hX6N+TO40GT8Pv+IPrggSIo2rhuivIC8bmvWFQR8aPx0crI5O3CRJEkKUor3n9hISHkLUuShae7fmXz3+RVC9a0YVVjy52XDgayM5JERAFQ/oNAa6jIdaMgmhPZMkIUQpOHP5DDMjZ7Lp2CZqudXi3e7vMviOwTioCv7N+dIZiPjYaFK6nAg1m8OAUGMYq2slG85bQUmSEOI2pOek83H0xyzfvxyNZnzAeMYFjMPd2d3q0MqO1hAfblw1HPjamJG1+T3Goj5N+0iTUgUjSUKIW5Cv89l4dCOzI2eTmJHIgMYDmNRpEg2qNbA6tLKTmwX7v4QdC+D0HnDxNEYodR4HNe+wOjpRRiRJCHGTdifuZurOqUQnRRNQK4DpvaYTWKcCr2GQkmA0J0Uuh/TzUKsl3Dcd2o0Al0oyUqsSkyQhRAklpCUwM3Im38V9Rx33Ovyzxz+5r+l9FbPfQWs4sc1oUjr4Deh8aDnAuHJo2gsq84JHlYwkCSGKcTnnMkv2LWFl9EoclAPPtn+WUf6jKma/Q06GcTf0zoXGhHuuXtD1WaNJqUZjq6MTFpAkIUQR8vLz2HBkAx/u+pCkzCQGNR3ECx1foF7VelaHVvounoTwJbBrJWRcgDpt4P5Z0G44VKlqdXTCQpIkhLiO8DPhhISHcOjCIdrXbs9HfT4ioHYFW+hGa4j71bhqOPStUdZyIAQ/DY17SJOSACRJCHGVE6knmBE5g59O/ET9qvUJ7RnKvY3vRVWkD8zsdIj63FgnOjHamHW12wvQeSxUlzXixdUkSQgBpGSlsChqEasOrcLZwZnnOzzPE22ewNXJ1erQSk9ynNmk9AlkXoS6ATB4DgQMA2c3q6MTNkqShKjUcvJz+CLmC+bvnU9KVgpDmw9lYuBEarvXtjq00qE1HPuvMUopZjMoB2g9yFjxrWFXaVISxZIkISolrTW/xP/CtIhpxKXGEVwvmFc6v0JL7woydXVWGkStMZqUzh0C95pw1xQIGgtePlZHJ+yIJAlR6cRciCE0IpQdp3fQ2LMxc/rMoadvz4rR7y6SbwEAABofSURBVJB0xGhS2v0ZZKVA/fbwwHzwfxCcK1DTmSg3kiREpXE+4zxzds/hy8Nf4uniyetdXmd4y+E4OzhbHdrtyc+Ho1tgxyI4/L2xwlubIdDlKfDrIk1K4rZIkhAVXmZuJisPrGTJviXk5OfweJvHmdBuAl4udr7wTdYl2LPaWA406TBUrQ09X4GgJ8GzvtXRiQpCkoSosPJ1PpuObWL2rtmcuXyGvg37MrnTZBp62vkwz/OxRmLYswqyL0GDjjB0Efg/AE4uVkcnKhhJEqJC2p24m9DwUPad30dr79b8s8c/6Vyvs9Vh3br8fIj90bjxLfZHcHAG/6HGKCXfSrCokbCMJAlRoZy8dJJZkbP4/vj31HGrw/s93uf+pvfb7yR8mSnGFcPORXDhKFSrB73+DzqNBo+6VkcnKgFJEqJCuJR9icVRi/n04Kc4OTjZ/yR852LMJqXVkHMZfLtA779D68HgVMXq6EQlIklC2LXc/FzW/76euXvmcjHrIoPvGMzzHZ6nblU7/Jadn2eMTtqxEI7+BxyrQNthxopvDTpYHZ2opCRJCLv1v/j/MS1iGkdTjhJUN4hXOr9Cm5ptrA7r5mUkw+5PjRvfLh4HjwbQ5w3oOBqqVZA7v4XdkiQh7M7h5MNMj5jOb6d+o6FHQ2b1nkUfvz72dzPc2QNGk1LU55CTDg27Qb+3odX94Gjn926ICkOShLAb5zPOM2/PPNYfXk9V56q82vlVRrQcgbM9faDm50HMJqNJKe5/4ORqTLDX5Smo387q6IS4hiQJYfOy8rL45MAnLNm3hKzcLEa2GsnT7Z6mumt1q0MrufQLxoI+4Ush5QR4+kLft6DjKHD3tjo6IYokSULYLK01/477N7MiZ3Hq8il6+fViSqcpNPFqYnVoJXdmn3HVsO8LyM2ExnfBve8bi/s4yn8/YfuKfZcqpfyAlUBdQAOLtNazlVLewOdAYyAOGK61TlZGw/BsYCCQDozWWu8yzzUKeMM89Xta6xVmeSdgOeAGbAJe1Frrouq47d9a2Ly95/YSEh5C1LkoWtZoyZLuSwiuH2x1WCWTlwuHNhr9Dcd/Ayc3aD8CukyAuv5WRyfETSnJV5lc4CWt9S6llAcQqZT6ARgN/KS1/kAp9TrwOvAaMABobj6CgflAsPmB/yYQhJFsIpVSYeaH/nxgPLADI0n0Bzab57xeHaKCOpV2ilmRs9gct5labrV4p9s7DL5jMI4OjlaHVrzL5yFyOUQsg9QEY5W3fu9Ch8ekSUnYrWKThNb6NHDa3L6klDoI+ABDgF7mbiuAnzE+wIcAK7XWGtiulKqulKpv7vuD1voCgJlo+iulfgY8tdbbzfKVwAMYSaKoOkQFk5adxtL9S1kZvRIH5cBT7Z7iybZP2sfNcKf2GFcN+9ZBXhY0+QsMnAYt7jVmZBXCjt1Uo6hSqjHQAeMbf10zgQCcwWiOAiOBnCx0WLxZdqPy+OuUc4M6/hzXBGACQMOGdj55WyWTm5/LV7FfMWf3HC5kXmBQ00G80PEF6lWtZ3VoN5aXAwfDjOm5T24H56rGFUOXCVCnldXRCVFqSpwklFLVgPXAJK11auEx6Wb/gS6D+EpUh9Z6EbAIICgoqEzjEKVna8JWQiNCib0YS8c6HZl39zz8a9l4m31a4h9NSpdOQ40mcO+/IPARcLOj0VZClFCJkoRSyhkjQXymtf7SLD6rlKqvtT5tNiclmuUJgF+hw33NsgT+aDoqKP/ZLPe9zv43qkPYsSMXjzAtYhq/JvyKbzVfZvSaQd+GfW37ZriESOOqIfpLyMuGO+6GQbOhWT9wsNPJA4UogZKMblLAUuCg1npGoZfCgFHAB+bPDYXKJyql1mB0XKeYH/LfAf9UStUw97sH+JvW+oJSKlUpdSdGM9YTwEfF1CHs0IXMC8zbM491v6/D3cmdl4NeZmSrkVRxtNEJ63Kz4cAG2LEAEiKgigd0GgNdxkOt5lZHJ0S5KMmVRHfgcWCfUmqPWfZ/GB/ca5VSY4HjwHDztU0Yw19jMYbAjgEwk8G7QLi53zsFndjAs/wxBHaz+eAGdQg7kp2XzWcHP2NR1CIycjMY3nI4z7R/hhquNYo/2AqXzkDExxD5MaSdhZrNYEAItB8Jrp5WRydEuVLGIKSKIygoSEdERFgdhsC4GW7LiS1Mi5hGfFo8PX178lKnl2havanVoV1La4iPMBb1if4a8nOh+T3GDKxN+0iTkqjwlFKRWutrVrCSWz5FmYi5EENIeAg7z+ykWfVmLOy3kG4Nulkd1rVys2D/l0ZyOLUbXDyN5qTO46DmHVZHJ4TlJEmIUnUh8wJzds9h/eH1eFTx4O/Bf2dYi2E4OdjYWy31lDFCKeJjSD8PtVrCfdOh3QhwqWZ1dELYDBv7nyvsVU5eDqsOrWLh3oWk56YzstVInmn/DF4uXlaH9get4cR246rh4DfGjKwtBxj3NjTtBbY8ukoIi0iSELdFa80v8b8wLWIacalxdPfpzqtBr9pWv0NOBuxfb4xSOrMPXL0g+GmjScnbjiYLFMICkiTELTty8Qgh4SFsPbWVxp6NmXv3XHr69rQ6rD+kxEP4EohcARkXoHZruH8WtBsOVapaHZ0QdkGShLhpKVkpzNszj89jPsfdyd1Y/KfVCJwdbGDxH62NmVd3LIRD3wLamJY7+Cljmm5pUhLipkiSECWWm5/L2pi1zNs7j0vZl3ioxUM8F/icbdzvkJ1urNmwcxGc3Q9uNaDb89B5rDEbqxDilkiSECWyNWErIeEhHEk5QnC9YF7t8iotarSwOixIPm40Ke1aCZkXoW4ADP4IAh4CZzeroxPC7kmSEDcUlxLHtIhp/Df+v/h5+DGr9yz6+PWxdp4lreHYL8ZVQ8wmQEHr+43O6IZdpUlJiFIkSUJcV2p2Kov2LuKzQ5/h4ujC5E6Teaz1Y9bOs5R9GfaugZ2L4dxBcK8JPSZD0JPg5Vv88UKImyZJQlwlLz+PL2O/ZM7uOSRnJjO0+VCe7/A8tdxqWRfUhWNGk9LuTyAzBeq3hwfmg/+D4OxqXVxCVAKSJMQV4WfCmbpzKjHJMXSs05H5fefTpmYba4LRGo5sMZqUfv/OWOGtzRDo8hT4dZEmJSHKiSQJwclLJ5kRMYMfT/xIg6oNmPaXadzT6B5r+h2yLplNSovg/O9QtTb0fMVoUvKsX/7xCFHJSZKoxC7nXGZx1GJWHliJk4MTEwMnMsp/FK5OFjThJB0xEsOeVZCVCg06wtBF4P8AOLmUfzxCCECSRKWUr/MJOxLG7F2zOZ9xnkFNB/FixxepW/W6S4iXYSD5cOQn48a32B/AwRn8hxo3vvleM2OxEMICkiQqmd2Ju5m6cyrRSdG0q92O2b1n0652u/INIjPVuGLYuQguHIFqdaHX34xV3zzKOVEJIW5IkkQlcTrtNDMjZ7I5bjN13Ovwr7v+xcAmA3FQ5biYzrnfjcSwdzVkp4FvF+j9f9B6MDjZ6BKmQlRykiQquPScdD6O/pjl+5ej0Tzd/mnG+I/B3dm9fALIz4fD3xvTcx/ZAo5VoO1fjem5fTqWTwxCiFsmSaKC0lrz7bFvmRU5i7PpZ+nfuD+TO02mQbUG5RNAxkXY/SmEL4bkOPCoD33egI6joVrt8olBCHHbJElUQPvP7+eDnR+w99xe2tRsQ0jPEDrWLadv7YmHjKuGvWsgJ92YJuPuN6H1IHC0gVlihRA3RZJEBZKYnsjsXbMJOxJGLbdavNPtHYY0G1L2/Q75efD7v41FfY79Ao4u0O4ho0mpfvuyrVsIUaYkSVQAmbmZrDywkiX7lpCbn8vYtmMZ3248VZ3LeGGd9AvGVBnhS+DiCfD0Na4aOo6CqjXLtm4hRLmQJGHHtNZ8f/x7ZkTM4NTlU/Rt2JcpQVPw8/Ar24rPRhv3NkSthdwMaNQD7nnfWNzHUd5SQlQk8j/aTh1MOsjU8KlEno2kRY0WLO2+lC71u5RdhXm5EPMt7FgEx38FJzdjGdAuE6Be27KrVwhhKUkSduZ8xnk+2v0RXx3+iuou1flH13/wYLMHcXRwLJsKLyfBrhUQvhRS48GrIfR7Bzo8Du7eZVOnEMJmSJKwE1l5WXxy4BMWRy0mOz+bJ9o8wYT2E/Cs4lk2FZ6OMkYp7VsHuZnQ5C8wMARa9DdmZBVCVAqSJGxcQb/DzMiZJKQl0MevDy8FvURDzzJYtzkvBw5+Y9wVfWIbOLtD4CNGk1Kd1qVfnxDC5kmSsGHR56MJCQ9hV+IuWtZoydJ7yqjfIe0c7FoO4cvg0imo0Rju/ScEPgpu1Uu/PiGE3ZAkYYPOXj7Lh7s/JOxIGN6u3rzV9S0eaPZA6fc7JOwyrhr2r4e8bLijD9w/E5r3kyYlIQQgScKmZORmsCJ6Bcv2LyM3P5cn2z7J+IDxVKtSrfQqyc2Gg2HGENb4nVClmnFfQ5cJULtF6dUjhKgQJEnYAK01m45tYmbkTM6mn6Vfo35M7jS5dO93uHQWIj+GiGWQdha874D+U40+B9cy6vwWQti9YpOEUmoZcD+QqLVua5Z5A58DjYE4YLjWOlkZ613OBgYC6cBorfUu85hRwBvmad/TWq8wyzsBywE3YBPwotZaF1XHbf/GNmbvub2EhIcQdS6K1t6t+eCuDwiqV4oL7sRHGFcN0V9Bfg406wfBTxtNSw7lOE24EMIuleRKYjkwB1hZqOx14Cet9QdKqdfN568BA4Dm5iMYmA8Emx/4bwJBgAYilVJh5of+fGA8sAMjSfQHNt+gjgrhzOUzzIycyaZjm6jtVpt3u7/L4DsGl848S7lZRlLYsRBO7YIqHtB5HHQZDzXvuP3zCyEqjWKThNb6F6VU4z8VDwF6mdsrgJ8xPsCHACu11hrYrpSqrpSqb+77g9b6AoBS6gegv1LqZ8BTa73dLF8JPICRJIqqw66l56SzbP8yVkSvQKOZ0G4CY9uOLZ31HVJPG81JkR/D5XNQqwUMnAbtR4CLx+2fXwhR6dxqn0RdrfVpc/sMULDmpA9wstB+8WbZjcrjr1N+ozquoZSaAEwAaNiwDO4fKAX5Op9vjnzDh7s+JDEjkQFNBjC542TqV6t/eyfWGk7uNG58O7DBmJG1xb3GOtFNe4NSpfMLCCEqpdvuuDb7D3RpBHOrdWitFwGLAIKCgso0llux6+wuQsJDiE6KJqBWANN7TSewTuDtnTQn0xi6unMhnN4LLl5GX0PnseDdtHQCF0JUereaJM4qpeprrU+bzUmJZnkCUHhIjq9ZlsAfTUcF5T+b5b7X2f9GddiN+EvxzIycyffHvy+9daVTEiBiKUQuh/QkqN0K7psB7R4Gl1IcKiuEENx6kggDRgEfmD83FCqfqJRag9FxnWJ+yH8H/FMpVcPc7x7gb1rrC0qpVKXUnRgd108AHxVTh827nHOZJfuWsDJ6JY4Ojjzb/llG+Y+69X4HrY1pMnYsgIMbAQ0tBhhNSk16SpOSEKLMlGQI7GqMq4BaSql4jFFKHwBrlVJjgePAcHP3TRjDX2MxhsCOATCTwbtAuLnfOwWd2MCz/DEEdrP54AZ12Ky8/Dw2HNnAh7s+JCkziUFNB/FCxxeoV7XerZ0wJwP2fWFMz312H7hWh67PGSOVajQq3eCFEOI6lDEQqeIICgrSERER5V5v+JlwQsJDOHThEIG1A3m186sE1A64tZNdPGGs9rZrJWQkQ922xh3RAQ9BlVIYBSWEEH+ilIrUWl9zk5bccX2bTqaeZHrkdH468RMNqjYgtGco9za+F3WzTUBaQ9z/jHsbYjYBClrdZzQpNeouTUpCCEtIkrhFl7IvsShqEZ8e/BRnB2de6PACj7d5HFcn15s7UfZlYxnQnYsg8QC4eUP3ScYoJS/f4o8XQogyJEniJuXm5/Ll4S+Zu2cuyZnJPNDsAZ7v8Dy13Wvf3ImS42DnYtj9CWSmQL12MGQutP0rOLuVSexCCHGzJEnchK2nthIaHkrsxVg61e3E/L7zaVOzTclPoDUc/dloUvr936AcoM1g4/4Gv2BpUhJC2BxJEiVwLOUY0yOm89/4/+JTzYeZvWZyd8O7S97vkJUGe1cbVw7nY8C9FvR8GYKeBM8GZRu8EELcBkkSN5CSlcKCvQtYc2gNLk4uTOk0hUdbP0oVxyolO0HSEWOU0u5PISsVGnSABxaA/1Bwvsm+CyGEsIAkievIyc/hi5gvmLd3HpeyL/Fg8wd5LvA5arnVKv7g/Hw4ssWYLuPwD8YKb/5DoctT4BskTUpCCLsiSeJP/hf/P0IjQjmWcozg+sG8EvQKLb1bFn9gZqrZpLQIkmKhah34y2sQNAY8bvFmOiGEsJgkCdORi0cIjQjlt4TfaOjRkA97f0gvv17F9zucP2wkhj2rIDsNfILgwSXQZgg4lbBZSgghbJQkCdO729/l9wu/80rQK4xsNRJnR+eid87Ph9gfjFFKR34Cxyrg/yAETwCfTuUXtBBClDFJEqa3u72NZxVParjWKHqnjIuw5zNjlFLyMfCoD73fgE6joFqd8gtWCCHKiSQJUyPPG0yYl3jIaFLauwZyLoPfnXD3/4PWg+FGVxxCCGHnJEkUJT/PuOFtx0I49l9wdIGAYcZEew1uc8EgIYSwE5Ik/iwjGXZ9AuGLjdlYPX3g7n9Ax1FQtQRDYIUQogKRJFHgbLRx1RC1FnIzjJlX+70Lre4HR/kzCSEqJ/n0K/Dv1+HkTmg33GhSqneLa0EIIUQFIkmiwH0zwd3beAghhAAkSfyhVjOrIxBCCJvjYHUAQgghbJckCSGEEEWSJCGEEKJIkiSEEEIUSZKEEEKIIkmSEEIIUSRJEkIIIYokSUIIIUSRJEkIIYQokiQJIYQQRZIkIYQQokiSJIQQQhRJkoQQQogi2XySUEr1V0rFKKVilVKvWx2PEEJUJjadJJRSjsBcYADQBhiplGpjbVRCCFF52Pp6El2AWK31UQCl1BpgCHCgtCt6+5toDpxKLe3TCiFEuWjTwJM3B/mX+nlt+koC8AFOFnoeb5ZdRSk1QSkVoZSKOHfuXLkFJ4QQFZ2tX0mUiNZ6EbAIICgoSN/KOcoiAwshhL2z9SuJBMCv0HNfs0wIIUQ5sPUkEQ40V0o1UUpVAUYAYRbHJIQQlYZNNzdprXOVUhOB7wBHYJnWOtrisIQQotKw6SQBoLXeBGyyOg4hhKiMbL25SQghhIUkSQghhCiSJAkhhBBFkiQhhBCiSErrW7r3zGYppc4Bx2/x8FrA+VIMp6zZU7wSa9mxp3jtKVawr3hvN9ZGWuvafy6scEnidiilIrTWQVbHUVL2FK/EWnbsKV57ihXsK96yilWam4QQQhRJkoQQQogiSZK42iKrA7hJ9hSvxFp27Clee4oV7CveMolV+iSEEEIUSa4khBBCFEmShBBCiCJVqiShlFqmlEpUSu0vVOatlPpBKXXY/FnDLFdKqQ+VUrFKqSilVMdyjtVPKfUfpdQBpVS0UupFW41XKeWqlNqplNprxvq2Wd5EKbXDjOlzc7p3lFIu5vNY8/XG5RXrn+J2VErtVkpttOV4lVJxSql9Sqk9SqkIs8zm3geF4q2ulFqnlDqklDqolOpqi/EqpVqaf9OCR6pSapItxloo5snm/7H9SqnV5v+9sn3faq0rzQPoCXQE9hcqCwFeN7dfB6aa2wOBzYAC7gR2lHOs9YGO5rYH8DvQxhbjNeusZm47AzvMGNYCI8zyBcAz5vazwAJzewTwuUXvhynAKmCj+dwm4wXigFp/KrO590Gh2FYA48ztKkB1W47XjMMROAM0stVYMZZuPga4FXq/ji7r9225/2NY/QAac3WSiAHqm9v1gRhzeyEw8nr7WRT3BqCfrccLuAO7gGCMuz+dzPKuwHfm9ndAV3PbydxPlXOcvsBPQB9go/kf3ybj5fpJwibfB4CX+UGm/lRuk/EWqvce4DdbjhUjSZwEvM334Ubg3rJ+31aq5qYi1NVanza3zwB1ze2Cf5AC8WZZuTMvEztgfEO3yXjNpps9QCLwA3AEuKi1zr1OPFdiNV9PAWqWV6ymWcCrQL75vCa2G68GvldKRSqlJphlNvk+AJoA54CPzaa8JUqpqthuvAVGAKvNbZuMVWudAEwDTgCnMd6HkZTx+1aSRCHaSLk2NSZYKVUNWA9M0lqnFn7NluLVWudprQMxvqF3AVpZHFKRlFL3A4la60irYymhHlrrjsAA4DmlVM/CL9rS+wDjG2tHYL7WugNwGaPJ5gobixezDX8w8MWfX7OlWM2+kSEYibgBUBXoX9b1SpKAs0qp+gDmz0SzPAHwK7Sfr1lWbpRSzhgJ4jOt9Zdmsc3GC6C1vgj8B+Oyt7pSqmD1w8LxXInVfN0LSCrHMLsDg5VSccAajCan2bYar/kNEq11IvAVRhK21fdBPBCvtd5hPl+HkTRsNV4wku8urfVZ87mtxtoXOKa1Pqe1zgG+xHgvl+n7VpIEhAGjzO1RGG3/BeVPmCMa7gRSCl2CljmllAKWAge11jNsOV6lVG2lVHVz2w2j7+QgRrIYVkSsBb/DMGCL+Y2tXGit/6a19tVaN8ZoZtiitX7UFuNVSlVVSnkUbGO0ne/HBt8HAFrrM8BJpVRLs+hu4ICtxmsayR9NTQUx2WKsJ4A7lVLu5udDwd+2bN+35d1BZOUD441wGsjB+MYzFqON7ifgMPAj4G3uq4C5GG3r+4Cgco61B8ZlbhSwx3wMtMV4gXbAbjPW/cA/zPKmwE4gFuNS3sUsdzWfx5qvN7XwPdGLP0Y32Vy8Zkx7zUc08Hez3ObeB4ViDgQizPfD10ANW40Xo8kmCfAqVGaTsZoxvA0cMv+ffQK4lPX7VqblEEIIUSRpbhJCCFEkSRJCCCGKJElCCCFEkSRJCCGEKJIkCSGEEEWSJCGEEKJIkiSEEEIU6f8D1OtTpvS+19YAAAAASUVORK5CYII=\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[['Tx per block min', 'Tx per block avg', 'Tx per block max']].iloc[0:9].plot()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "-9KOvTzGIRG3",
        "outputId": "9e7a43ae-ef1a-4b43-b9d7-bb6246d44b89"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7ff84c10bf10>"
            ]
          },
          "metadata": {},
          "execution_count": 23
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[['Tx per block min', 'Tx per block avg', 'Tx per block max']].iloc[9:].plot()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "kqG4ernbIfUA",
        "outputId": "eabb0b74-66ce-4c55-f9ea-ab0d30e0b229"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7ff84c08bf50>"
            ]
          },
          "metadata": {},
          "execution_count": 24
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "beGra8KeInV-"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}