SeoulBike.ipynb

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      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/jamal221/Machine_Learning_Project/blob/main/SeoulBike.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
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    {
      "cell_type": "markdown",
      "source": [
        "# Seoul Bike Demand (45 points total)\n",
        "\n",
        "We read the data from `SeoulBikeData.csv` into a pandas DataFrame and check a few sample rows."
      ],
      "metadata": {
        "id": "DuQrsqz16OZu"
      }
    },
    {
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      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
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      },
      "execution_count": 1,
      "outputs": [
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          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
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      "source": [
        "import os\n",
        "os.chdir(\"/content/drive/My Drive/Colab Notebooks/CSV_Files/\")"
      ],
      "metadata": {
        "id": "atBEsUeKMtBb"
      },
      "execution_count": 2,
      "outputs": []
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              "         Date  Rented Bike Count  Hour  Temperature(C)  Humidity(%)  \\\n",
              "0  01/12/2017                254     0            -5.2           37   \n",
              "1  01/12/2017                204     1            -5.5           38   \n",
              "2  01/12/2017                173     2            -6.0           39   \n",
              "3  01/12/2017                107     3            -6.2           40   \n",
              "4  01/12/2017                 78     4            -6.0           36   \n",
              "\n",
              "   Wind speed (m/s)  Visibility (10m)  Dew point temperature(C)  \\\n",
              "0               2.2              2000                     -17.6   \n",
              "1               0.8              2000                     -17.6   \n",
              "2               1.0              2000                     -17.7   \n",
              "3               0.9              2000                     -17.6   \n",
              "4               2.3              2000                     -18.6   \n",
              "\n",
              "   Solar Radiation (MJ/m2)  Rainfall(mm)  Snowfall (cm) Seasons     Holiday  \\\n",
              "0                      0.0           0.0            0.0  Winter  No Holiday   \n",
              "1                      0.0           0.0            0.0  Winter  No Holiday   \n",
              "2                      0.0           0.0            0.0  Winter  No Holiday   \n",
              "3                      0.0           0.0            0.0  Winter  No Holiday   \n",
              "4                      0.0           0.0            0.0  Winter  No Holiday   \n",
              "\n",
              "  Functioning Day  \n",
              "0             Yes  \n",
              "1             Yes  \n",
              "2             Yes  \n",
              "3             Yes  \n",
              "4             Yes  "
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              "      <td>78</td>\n",
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              "      <td>36</td>\n",
              "      <td>2.3</td>\n",
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          },
          "metadata": {},
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      ],
      "source": [
        "import pandas as pd\n",
        "df = pd.read_csv('SeoulBikeData.csv')\n",
        "df.head()"
      ]
    },
    {
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      "outputs": [
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 8760 entries, 0 to 8759\n",
            "Data columns (total 14 columns):\n",
            " #   Column                    Non-Null Count  Dtype  \n",
            "---  ------                    --------------  -----  \n",
            " 0   Date                      8760 non-null   object \n",
            " 1   Rented Bike Count         8760 non-null   int64  \n",
            " 2   Hour                      8760 non-null   int64  \n",
            " 3   Temperature(C)            8760 non-null   float64\n",
            " 4   Humidity(%)               8760 non-null   int64  \n",
            " 5   Wind speed (m/s)          8760 non-null   float64\n",
            " 6   Visibility (10m)          8760 non-null   int64  \n",
            " 7   Dew point temperature(C)  8760 non-null   float64\n",
            " 8   Solar Radiation (MJ/m2)   8760 non-null   float64\n",
            " 9   Rainfall(mm)              8760 non-null   float64\n",
            " 10  Snowfall (cm)             8760 non-null   float64\n",
            " 11  Seasons                   8760 non-null   object \n",
            " 12  Holiday                   8760 non-null   object \n",
            " 13  Functioning Day           8760 non-null   object \n",
            "dtypes: float64(6), int64(4), object(4)\n",
            "memory usage: 958.2+ KB\n"
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        "df.isnull().sum()"
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            "text/plain": [
              "Date                        0\n",
              "Rented Bike Count           0\n",
              "Hour                        0\n",
              "Temperature(C)              0\n",
              "Humidity(%)                 0\n",
              "Wind speed (m/s)            0\n",
              "Visibility (10m)            0\n",
              "Dew point temperature(C)    0\n",
              "Solar Radiation (MJ/m2)     0\n",
              "Rainfall(mm)                0\n",
              "Snowfall (cm)               0\n",
              "Seasons                     0\n",
              "Holiday                     0\n",
              "Functioning Day             0\n",
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              "       Rented Bike Count         Hour  Temperature(C)  Humidity(%)  \\\n",
              "count        8760.000000  8760.000000     8760.000000  8760.000000   \n",
              "mean          704.602055    11.500000       12.882922    58.226256   \n",
              "std           644.997468     6.922582       11.944825    20.362413   \n",
              "min             0.000000     0.000000      -17.800000     0.000000   \n",
              "25%           191.000000     5.750000        3.500000    42.000000   \n",
              "50%           504.500000    11.500000       13.700000    57.000000   \n",
              "75%          1065.250000    17.250000       22.500000    74.000000   \n",
              "max          3556.000000    23.000000       39.400000    98.000000   \n",
              "\n",
              "       Wind speed (m/s)  Visibility (10m)  Dew point temperature(C)  \\\n",
              "count       8760.000000       8760.000000               8760.000000   \n",
              "mean           1.724909       1436.825799                  4.073813   \n",
              "std            1.036300        608.298712                 13.060369   \n",
              "min            0.000000         27.000000                -30.600000   \n",
              "25%            0.900000        940.000000                 -4.700000   \n",
              "50%            1.500000       1698.000000                  5.100000   \n",
              "75%            2.300000       2000.000000                 14.800000   \n",
              "max            7.400000       2000.000000                 27.200000   \n",
              "\n",
              "       Solar Radiation (MJ/m2)  Rainfall(mm)  Snowfall (cm)  \n",
              "count              8760.000000   8760.000000    8760.000000  \n",
              "mean                  0.569111      0.148687       0.075068  \n",
              "std                   0.868746      1.128193       0.436746  \n",
              "min                   0.000000      0.000000       0.000000  \n",
              "25%                   0.000000      0.000000       0.000000  \n",
              "50%                   0.010000      0.000000       0.000000  \n",
              "75%                   0.930000      0.000000       0.000000  \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>Rented Bike Count</th>\n",
              "      <th>Hour</th>\n",
              "      <th>Temperature(C)</th>\n",
              "      <th>Humidity(%)</th>\n",
              "      <th>Wind speed (m/s)</th>\n",
              "      <th>Visibility (10m)</th>\n",
              "      <th>Dew point temperature(C)</th>\n",
              "      <th>Solar Radiation (MJ/m2)</th>\n",
              "      <th>Rainfall(mm)</th>\n",
              "      <th>Snowfall (cm)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>8760.000000</td>\n",
              "      <td>8760.000000</td>\n",
              "      <td>8760.000000</td>\n",
              "      <td>8760.000000</td>\n",
              "      <td>8760.000000</td>\n",
              "      <td>8760.000000</td>\n",
              "      <td>8760.000000</td>\n",
              "      <td>8760.000000</td>\n",
              "      <td>8760.000000</td>\n",
              "      <td>8760.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>704.602055</td>\n",
              "      <td>11.500000</td>\n",
              "      <td>12.882922</td>\n",
              "      <td>58.226256</td>\n",
              "      <td>1.724909</td>\n",
              "      <td>1436.825799</td>\n",
              "      <td>4.073813</td>\n",
              "      <td>0.569111</td>\n",
              "      <td>0.148687</td>\n",
              "      <td>0.075068</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>644.997468</td>\n",
              "      <td>6.922582</td>\n",
              "      <td>11.944825</td>\n",
              "      <td>20.362413</td>\n",
              "      <td>1.036300</td>\n",
              "      <td>608.298712</td>\n",
              "      <td>13.060369</td>\n",
              "      <td>0.868746</td>\n",
              "      <td>1.128193</td>\n",
              "      <td>0.436746</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-17.800000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>27.000000</td>\n",
              "      <td>-30.600000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>191.000000</td>\n",
              "      <td>5.750000</td>\n",
              "      <td>3.500000</td>\n",
              "      <td>42.000000</td>\n",
              "      <td>0.900000</td>\n",
              "      <td>940.000000</td>\n",
              "      <td>-4.700000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>504.500000</td>\n",
              "      <td>11.500000</td>\n",
              "      <td>13.700000</td>\n",
              "      <td>57.000000</td>\n",
              "      <td>1.500000</td>\n",
              "      <td>1698.000000</td>\n",
              "      <td>5.100000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>1065.250000</td>\n",
              "      <td>17.250000</td>\n",
              "      <td>22.500000</td>\n",
              "      <td>74.000000</td>\n",
              "      <td>2.300000</td>\n",
              "      <td>2000.000000</td>\n",
              "      <td>14.800000</td>\n",
              "      <td>0.930000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>3556.000000</td>\n",
              "      <td>23.000000</td>\n",
              "      <td>39.400000</td>\n",
              "      <td>98.000000</td>\n",
              "      <td>7.400000</td>\n",
              "      <td>2000.000000</td>\n",
              "      <td>27.200000</td>\n",
              "      <td>3.520000</td>\n",
              "      <td>35.000000</td>\n",
              "      <td>8.800000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-06bdc6a1-597e-484f-a9c0-7eff4cdc9275')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "\n",
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              "      </button>\n",
              "\n",
              "\n",
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              "              title=\"Suggest charts.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
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              "      </button>\n",
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              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
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              "    width: 32px;\n",
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              "  .colab-df-quickchart:hover {\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
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              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
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              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-956daeb2-34b3-4702-902b-7bfb70acedfd button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
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              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "      width: 32px;\n",
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              "\n",
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              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-06bdc6a1-597e-484f-a9c0-7eff4cdc9275 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-06bdc6a1-597e-484f-a9c0-7eff4cdc9275');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' 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": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "The raw data are hourly bike demand with weather information and categories of days. We will aggregate the data into daily by taking the following steps.\n",
        "\n",
        "Step 1: We extract a summary of select weather variables."
      ],
      "metadata": {
        "id": "qsmGMkQ_GAHR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_daily = df.rename(columns={'Date':'DateStr'}).groupby('DateStr')\\\n",
        ".agg({'Rented Bike Count': 'sum', 'Temperature(C)': 'mean', 'Wind speed (m/s)': 'mean', 'Dew point temperature(C)': 'mean'})\n",
        "df_daily.head()"
      ],
      "metadata": {
        "id": "-7LHS4LDBAUL",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "outputId": "7cfbb073-412d-44e8-e8f5-ba1fc3014f4b"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            Rented Bike Count  Temperature(C)  Wind speed (m/s)  \\\n",
              "DateStr                                                           \n",
              "01/01/2018               4290       -1.283333          1.454167   \n",
              "01/02/2018               5377       -3.866667          1.608333   \n",
              "01/03/2018               5132        0.450000          3.554167   \n",
              "01/04/2018              17388       15.183333          1.570833   \n",
              "01/05/2018              26820       20.341667          1.437500   \n",
              "\n",
              "            Dew point temperature(C)  \n",
              "DateStr                               \n",
              "01/01/2018                -13.866667  \n",
              "01/02/2018                -15.012500  \n",
              "01/03/2018                 -6.387500  \n",
              "01/04/2018                  9.370833  \n",
              "01/05/2018                 15.120833  "
            ],
            "text/html": [
              "\n",
              "\n",
              "  <div id=\"df-7ebc64ac-610c-4fa0-9bdb-2a51597ec435\">\n",
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              "      <th>Rented Bike Count</th>\n",
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              "      <th>Dew point temperature(C)</th>\n",
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              "      <th>01/01/2018</th>\n",
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              "      <td>-13.866667</td>\n",
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              "      <th>01/02/2018</th>\n",
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              "      <td>-6.387500</td>\n",
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              "    <tr>\n",
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          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_daily.index.is_unique"
      ],
      "metadata": {
        "id": "E9WqBbifHZ8r",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1a26910a-c51f-47e8-f412-b643a5bbe756"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Step 2: We extract unique dates, the season they belong to, whether each day is a holiday, and the day of the week."
      ],
      "metadata": {
        "id": "3wKCcFIBGYT4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import calendar\n",
        "df_daytype = df[['Date','Seasons','Holiday']].drop_duplicates().rename(columns={'Date':'DateStr'})\n",
        "df_daytype.set_index('DateStr', inplace=True)\n",
        "df_daytype['Date'] = pd.to_datetime(df_daytype.index, format='%d/%m/%Y')\n",
        "df_daytype['DayOfWeek'] = [calendar.day_name[x.weekday()] for x in df_daytype['Date'].to_list()]\n",
        "df_daytype.head()"
      ],
      "metadata": {
        "id": "s4gegVCWBeGh",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "outputId": "a70d2556-47b9-4b75-9cd3-396decd81d76"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           Seasons     Holiday       Date DayOfWeek\n",
              "DateStr                                            \n",
              "01/12/2017  Winter  No Holiday 2017-12-01    Friday\n",
              "02/12/2017  Winter  No Holiday 2017-12-02  Saturday\n",
              "03/12/2017  Winter  No Holiday 2017-12-03    Sunday\n",
              "04/12/2017  Winter  No Holiday 2017-12-04    Monday\n",
              "05/12/2017  Winter  No Holiday 2017-12-05   Tuesday"
            ],
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              "\n",
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "            + ' to learn more about interactive tables.';\n",
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            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Now, your job is to answer the following questions.\n",
        "\n"
      ],
      "metadata": {
        "id": "gWWbizpgGktW"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Problem 1: Data Verification (5 points total)\n",
        "\n",
        "a) How many records are there in `df_daily`? (1 point)\n",
        "\n",
        "b) How many records are there in `df_daytype`?  (1 point)\n",
        "\n",
        "c) Do `df_daily` and `df_daytype` share the same set of indices? (3 points)\n",
        "\n",
        "*Your answer:*"
      ],
      "metadata": {
        "id": "VTew_dLzGsX9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"How many records are there in df_daily?\", \" Answer: \", len(df_daily))\n",
        "print(\"How many records are there in df_daytype?\", \" Answer: \", len(df_daytype))\n",
        "print(\"df_daily.info() is \")\n",
        "df_daily.info()\n",
        "print(\"df_daytype.info() is \")\n",
        "df_daytype.info()\n"
      ],
      "metadata": {
        "id": "UsdHIRDvHfTA",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1675305e-1b22-40d8-fa22-59e151e66cc1"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "How many records are there in df_daily?  Answer:  365\n",
            "How many records are there in df_daytype?  Answer:  365\n",
            "df_daily.info() is \n",
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Index: 365 entries, 01/01/2018 to 31/12/2017\n",
            "Data columns (total 4 columns):\n",
            " #   Column                    Non-Null Count  Dtype  \n",
            "---  ------                    --------------  -----  \n",
            " 0   Rented Bike Count         365 non-null    int64  \n",
            " 1   Temperature(C)            365 non-null    float64\n",
            " 2   Wind speed (m/s)          365 non-null    float64\n",
            " 3   Dew point temperature(C)  365 non-null    float64\n",
            "dtypes: float64(3), int64(1)\n",
            "memory usage: 22.4+ KB\n",
            "df_daytype.info() is \n",
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Index: 365 entries, 01/12/2017 to 30/11/2018\n",
            "Data columns (total 4 columns):\n",
            " #   Column     Non-Null Count  Dtype         \n",
            "---  ------     --------------  -----         \n",
            " 0   Seasons    365 non-null    object        \n",
            " 1   Holiday    365 non-null    object        \n",
            " 2   Date       365 non-null    datetime64[ns]\n",
            " 3   DayOfWeek  365 non-null    object        \n",
            "dtypes: datetime64[ns](1), object(3)\n",
            "memory usage: 14.3+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_daytype_index=list(df_daytype.index)\n",
        "len(df_daytype_index)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wPX6sCmF4K3K",
        "outputId": "715f0b40-2cca-42a5-9f29-5023f6e44cd3"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "365"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# df_daytype_index.append(\"01/01/2023\")"
      ],
      "metadata": {
        "id": "VatlWz5s6qNJ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# df_daytype_index.pop()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "PApN9FsC7IgG",
        "outputId": "ea7142eb-61cd-4edc-8007-571fe63aa32f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'31/12/2017'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_daily_index=list(df_daily.index)\n",
        "len(df_daily_index)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "It66KSel5QZc",
        "outputId": "7a716505-6930-4a2f-9ce6-79f64aec3b2d"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "365"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Please, check if these two list are same or not. surly to solve this question we have to design a function which comapre all of the data one by one."
      ],
      "metadata": {
        "id": "rizExori5c9f"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_daytype_index.sort()\n",
        "df_daily_index.sort()"
      ],
      "metadata": {
        "id": "5qOER7ld5b4D"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "if df_daytype_index==df_daily_index :\n",
        "  print(\"the two lists are same\")\n",
        "else:\n",
        "  print(\"The two lists are not same\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9hbkq1H16WxL",
        "outputId": "eee0a8c6-2b16-4205-e68a-50e707d89c95"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "the two lists are same\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Problem 2: Merge Tables (5 points total)\n",
        "\n",
        "Join the two tables ensuring that data from the same date shall align.\n",
        "\n",
        "*Your answer:*"
      ],
      "metadata": {
        "id": "tA2REmlTHf2P"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# print(df_daily.columns)\n",
        "# print(df_daytype.columns)\n",
        "df_daily_dtype=pd.concat([df_daily,df_daytype], axis=1, join=\"inner\")\n",
        "df_daily_dtype.head(10)\n"
      ],
      "metadata": {
        "id": "9FK88fWrCQ1t",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "outputId": "bf82f6bb-3802-4c45-9d63-80b70b206de4"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            Rented Bike Count  Temperature(C)  Wind speed (m/s)  \\\n",
              "DateStr                                                           \n",
              "01/01/2018               4290       -1.283333          1.454167   \n",
              "01/02/2018               5377       -3.866667          1.608333   \n",
              "01/03/2018               5132        0.450000          3.554167   \n",
              "01/04/2018              17388       15.183333          1.570833   \n",
              "01/05/2018              26820       20.341667          1.437500   \n",
              "01/06/2018              31928       23.708333          1.954167   \n",
              "01/07/2018               3231       22.025000          0.783333   \n",
              "01/08/2018              20712       33.429167          1.683333   \n",
              "01/09/2018              26010       25.454167          1.208333   \n",
              "01/10/2018              27909       15.437500          2.825000   \n",
              "\n",
              "            Dew point temperature(C) Seasons     Holiday       Date  DayOfWeek  \n",
              "DateStr                                                                         \n",
              "01/01/2018                -13.866667  Winter     Holiday 2018-01-01     Monday  \n",
              "01/02/2018                -15.012500  Winter  No Holiday 2018-02-01   Thursday  \n",
              "01/03/2018                 -6.387500  Spring     Holiday 2018-03-01   Thursday  \n",
              "01/04/2018                  9.370833  Spring  No Holiday 2018-04-01     Sunday  \n",
              "01/05/2018                 15.120833  Spring     Holiday 2018-05-01    Tuesday  \n",
              "01/06/2018                 11.862500  Summer  No Holiday 2018-06-01     Friday  \n",
              "01/07/2018                 20.833333  Summer  No Holiday 2018-07-01     Sunday  \n",
              "01/08/2018                 22.829167  Summer  No Holiday 2018-08-01  Wednesday  \n",
              "01/09/2018                 16.725000  Autumn  No Holiday 2018-09-01   Saturday  \n",
              "01/10/2018                  5.983333  Autumn  No Holiday 2018-10-01     Monday  "
            ],
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              "      <th>Rented Bike Count</th>\n",
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              "      <th>01/07/2018</th>\n",
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              "      <td>22.025000</td>\n",
              "      <td>0.783333</td>\n",
              "      <td>20.833333</td>\n",
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              "      <td>2018-07-01</td>\n",
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              "      <td>1.683333</td>\n",
              "      <td>22.829167</td>\n",
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              "      <td>Saturday</td>\n",
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          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_daily_dtype.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2ItJgw-XAcxG",
        "outputId": "b85898f0-02a1-4257-8399-991e6e684b6f"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Index: 365 entries, 01/01/2018 to 31/12/2017\n",
            "Data columns (total 8 columns):\n",
            " #   Column                    Non-Null Count  Dtype         \n",
            "---  ------                    --------------  -----         \n",
            " 0   Rented Bike Count         365 non-null    int64         \n",
            " 1   Temperature(C)            365 non-null    float64       \n",
            " 2   Wind speed (m/s)          365 non-null    float64       \n",
            " 3   Dew point temperature(C)  365 non-null    float64       \n",
            " 4   Seasons                   365 non-null    object        \n",
            " 5   Holiday                   365 non-null    object        \n",
            " 6   Date                      365 non-null    datetime64[ns]\n",
            " 7   DayOfWeek                 365 non-null    object        \n",
            "dtypes: datetime64[ns](1), float64(3), int64(1), object(3)\n",
            "memory usage: 25.7+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_daily_dtype.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rzwuatmDAhZV",
        "outputId": "6d17bc91-65fb-43fe-e9e1-ad0c5d4197c4"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Rented Bike Count           0\n",
              "Temperature(C)              0\n",
              "Wind speed (m/s)            0\n",
              "Dew point temperature(C)    0\n",
              "Seasons                     0\n",
              "Holiday                     0\n",
              "Date                        0\n",
              "DayOfWeek                   0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Problem 3: Visualization (35 points total)\n",
        "\n",
        "a) Plot the daily demand of rented bikes (`Rented Bike Count`) over time. (10 points)\n",
        "\n",
        "*Your answer:*"
      ],
      "metadata": {
        "id": "yawoxtB98et1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "plt.figure(figsize=(12, 8))\n",
        "# plt.plot(df_daily[:10]['Rented Bike Count'])\n",
        "plt.plot(df_daily_dtype[0:10]['Rented Bike Count'])\n",
        "plt.grid()\n"
      ],
      "metadata": {
        "id": "MdMzz1nW8pPn",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 676
        },
        "outputId": "e566c269-9cd1-4e5b-f9b2-f3508012f8c5"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x800 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "b) Show overlaying histograms of `Wind speed (m/s)` by `Seasons`. (10 points)\n",
        "\n",
        "*Your answer:*"
      ],
      "metadata": {
        "id": "fqR76Q229EPv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_daily_dtype.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DUeorKLeszin",
        "outputId": "470a2b19-369f-42ae-d268-20ef1c0a0993"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Index: 365 entries, 01/01/2018 to 31/12/2017\n",
            "Data columns (total 8 columns):\n",
            " #   Column                    Non-Null Count  Dtype         \n",
            "---  ------                    --------------  -----         \n",
            " 0   Rented Bike Count         365 non-null    int64         \n",
            " 1   Temperature(C)            365 non-null    float64       \n",
            " 2   Wind speed (m/s)          365 non-null    float64       \n",
            " 3   Dew point temperature(C)  365 non-null    float64       \n",
            " 4   Seasons                   365 non-null    object        \n",
            " 5   Holiday                   365 non-null    object        \n",
            " 6   Date                      365 non-null    datetime64[ns]\n",
            " 7   DayOfWeek                 365 non-null    object        \n",
            "dtypes: datetime64[ns](1), float64(3), int64(1), object(3)\n",
            "memory usage: 25.7+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12, 8))\n",
        "plt.bar(df_daily_dtype['Seasons'], df_daily_dtype['Wind speed (m/s)'])\n",
        "\n"
      ],
      "metadata": {
        "id": "ccXIlwol9O4a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 694
        },
        "outputId": "8522345e-c4bb-4440-971f-0ec5f92006bb"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<BarContainer object of 365 artists>"
            ]
          },
          "metadata": {},
          "execution_count": 20
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x800 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "c) Is there a relationship between `Temperature(C)` and `Dew point temperature(C)`? Use a proper visual tool to show it. (5 points)\n",
        "\n",
        "*Your answer:*"
      ],
      "metadata": {
        "id": "GYyWTfZp-eFD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_daily_dtype_corr=df_daily_dtype.corr()\n",
        "df_daily_dtype_corr"
      ],
      "metadata": {
        "id": "MJ3BlBBp-rOb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 231
        },
        "outputId": "49468a67-3f6f-4c71-e316-48f09e602fb4"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-21-0bdde49393b6>:1: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
            "  df_daily_dtype_corr=df_daily_dtype.corr()\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                          Rented Bike Count  Temperature(C)  Wind speed (m/s)  \\\n",
              "Rented Bike Count                  1.000000        0.699824         -0.174859   \n",
              "Temperature(C)                     0.699824        1.000000         -0.258956   \n",
              "Wind speed (m/s)                  -0.174859       -0.258956          1.000000   \n",
              "Dew point temperature(C)           0.602648        0.962614         -0.284104   \n",
              "\n",
              "                          Dew point temperature(C)  \n",
              "Rented Bike Count                         0.602648  \n",
              "Temperature(C)                            0.962614  \n",
              "Wind speed (m/s)                         -0.284104  \n",
              "Dew point temperature(C)                  1.000000  "
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    {
      "cell_type": "code",
      "source": [
        "df_daily_dtype_corr['Temperature(C)']['Dew point temperature(C)']"
      ],
      "metadata": {
        "colab": {
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            "text/plain": [
              "0.9626136983022565"
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          "metadata": {},
          "execution_count": 103
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    {
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      ],
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              "<Figure size 432x288 with 2 Axes>"
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            "image/png": 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nXLyU4MxVZjYaGF2g7O6E5wbcEj5KhCde55xz8eJTRjrnnHOpE/cpIz3xOueci5eYDwv2xOuccy5evMUbL5LqAGPDxfoEo9SWh8vtzWxzJIEVQtJJwGYz+7QEt9kA+JeZnRUutwceATKADcAXwF+B3xEcj7uL2lYUOrVpwF2XH0V6mnh93Pc8M2rODuv/cdmRdGiZAUCVfdKps19ljvjj8ChCTbnBD19D185HsHxFDu1O+XvU4ZQ6M+P+/s+RmTmNKpUrcf8DN9DysGY71Nm48RduvukRFi3MIi09jZNPbsctt16Wv/799yfy5KA3kODQQ5rw8ICbU/02SkTnTofx0F1/ID09jRde/y8Dn/lgh/WNDqjNkw9dQZ3a1Vm1ej29bv03S7KC+R8aNqjNPx+4nAMb1MLMuOjqf7JwcbEG7Za+CvFu8pa7xBsOA28LIKkvsM7MHokqHkkVzGxrEatPAtYBSSfe3WwPgpF5/wrrZgDDgIvNbFJYdiFQHXgPuE/Sg2a2Idn9l6Y0ib5XtuOK+z8ma8VGRvQ/jbFf/MS8xTn5dfq/OC3/+eWntaBlk1pRhBqJF4eNZ/DzY3h24F+iDiUlMjOnsWDBUj4YM4iZM76jX78hvP7GgzvVu/LKczimQys2b97CVVf2IzNzGp06Hcn8+Uv415ARvPxKf2rUqMaKFWsieBfFl5YmBvTtwblXDGRx1irGjbiT0WNn8M28pfl1/ueOi3h1xGe8+tYkOnU8hHt6n881vZ8DYPAjVzLgqdGMmziXqvvuQ26uRfVWkhfvBm/ce8pLhqSjJI2X9IWkMWGrEEmfSBoYzvE5V9LRkt6S9J2k/wnrNJH0taSXwzrDJe2bxHYfkzQVuFHS2ZI+l/SlpI8kZUhqAvwZuFnSdEknSBoaJsa8uNeFf0+SNEHSKGCOpHRJD0uaImmmpGsS3u4FQN7P4euA5/OSLoCZDTez7HAI/SfAWaVwyPdKm+Z1WJC1jkXL1rNlWy7vTlpAl3YNi6x/9rGNeefTBSmMMFoTJ3/NytXrog4jZT4eO4Vu3U5EEm3atmBtznqWL1u1Q50qVfbhmA6tAKhUqSItWzYlOytozQ0f9hE9epxOjRrVAKhTp0Zq30AJOapNU35YsIz5i35my5ZtvPXuFM7s0maHOoc0b0DmpK8ByJz0DWeE6w9p3oAKFdIZN3EuAOs3/MLGTWWm069IlqakHmWVJ97gt9M/gQvN7CjgOaB/wvrNZtYOGAyMJEhWhwM9w25rgEOAp8zst0AO8BdJFXez3Upm1s7MBgD/BTqY2RHAa8DfzWx+uM+BZtbWzCbs5n0cCdxoZi2Aq4E1ZnY0cDTwp3BmlqbAKjP7JXzN4QRdy0WZCpywm/2mTEatKixdsT5/OWvFBjJq7Vto3QPq7kvDetWY9FV2qsJzKbYseyX1G9TNX86oX4fs7KK7SHNy1vPJuKl06Bgk4vnzlzB//hIu6X4nF//hdiZM+LLUYy4NB2TUZPHSlfnLi7NW0yBjx56er75exNmnHQHA2acewX7Vq1CrZlWaN81gTc4GXnrqz0wY1Yf7br+AtDKcsPKV3MxVkSh3Xc2F2IcgAf1HwT9UOrA0YX3e9GGzgNlmthRA0g8Ec3yuBhaZ2cSw3ksE50g/2M12X0943hB4PWwRVwJ+3Iv3MTmcRxTgVKB1Quu4BsHcouvYfj47GcuAAwpbEd7loxdA3XZXs1/z3+1FyKXnrI6N+WDyQnItBt1mrtRt3bqN3rcO5NLLzqRRo/oAbNuay4IFSxn6wr1kZ6/g8kvv4u1RA9lvv6oRR1vy+jwwnEf6dueS849l4pTvWLx0FbnbcqmQnkbHow+m09n3sWjJSoY+0YtLLjiWF4dN3P1GoxSHHwe74Ik3aPHONrOORazPax3mJjzPW847fgW/3S2J7a5PeP5P4FEzGxUOqOpbxGu2EvZSSEojSNKFbU/ADWY2JvHFko4AKicUzQaOImjJF6YysLGwFYl3/fhN91dSkt2yV22kQZ3tX4r16+xL9qrCTz+fdWxj+j43NRVhuRR65eX3GTbsIwBatWpO1tKf89dlZ60gI6NOoa+75+7BNG7cgMuv2H7mJKN+HVq3PpiKFSvQsGEGjZscwIIFS2nVqnnpvokStiR7NQc2qJ2/fGD9mizN3rHLPWvZGi79y2AAqu67D+ecdiRr1m5kcdYqZs1ZxPxFwXF89z/TObpt0zKfeNPSo46geLyrOUim9SR1BJBUUdJhe7iNg/JeD/Qg6Dr+Zg+2W4Ptd8S4IqF8LcFApzzzCRIlwDlAxSK2Nwa4NuzuRlILSVUJ7qrRJKHeIOAKScfkFUg6Pxx0BcFk4F8VsY+Um/n9CprUr07DelWpmJ7GWR0bM/aLgjcSgWYH7EeNqpWY9t3PhWzFxVmPS7oy4u0BjHh7AJ07t2fkyPGYGTOmf0v16vtSb/+dB9M9/tgrrFu7njvuvHKH8s5d2jNl8mwAVq3KYcH8JTRqmLHT68u6aTPn85sm+9O4YR0qVkzn/LOOZvTYGTvUqV2rGmHPG7dc25WXhk/Mf22N/apQp3ZwnrtTx0P4et5SyrqY9zR7i5eg5Xoh8ISkGgTH5DGC1mCyvgGuk/QcMAd42sw2h129yWy3LzBM0irgY6BpWP4OMFxSN+AGgtHIIyXNIOjKXl/ItgCeJUiw0xT837YcONfM1kj6XlJzM5tnZtmSLgYekbR/eCwy2T746mTgjj04DqVqW67Rb+hUht5xMmlpYvgnP/DdT2u46cJWzPpxZX4SPqtjY94tR4Oq8jz/zxs4oeNvqVurOvM+H8R9jw7n+dc/iTqsUtPpxCPJzJzG6adeR+XK+9D//uvy15137q2MeHsAWVkreGbwmzRrdiAXnP83AC65pCsXXtSF449vy6f/nc5ZZ95Ieloavf92OTVrVS9qd2XWtm259O73Km8NvYn0tDReGj6Rr79byp03ncOXsxbw/tgZnHBMC+7523mYwaeTv+XWvq8CkJtr3PXAcEa9eAuSmP7VAp5/fXfDSaJXlpNqMmR+DqxYwtHH75rZ4RGHkhRJ5wFHmVmf3dTLAF4xs86722aquprLuiUT34k6hDJj3YJ/RB1CmVG7+RNRh1CmrPl+SLHT5m+ezkzqO+f7azuVyRTtLd5yxsxGJIzG3pWDgFtLOx7nnNtTcW/xeuItpvCyn1i0dvOY2bNJ1JmSilicc25PeeJ1zjnnUijuo5o98TrnnIuVmF/G64nXOedcvHhXs3POOZdCnnidc865FFLMM68nXuecc7GimM+56InXOedcrKR54nXOOedSJ+Y9zZ54nXPOxYtfTuScc86lUNxbvDHvKXfOOVfelORtASWdLukbSfMk3b6LehdIMkntihu/t3idc87FSlp6yTR5JaUDTwKnAD8BUySNMrM5BepVB24EPi+J/XqL1znnXKyUYIu3PTDPzH4ws83Aa0C3QurdBzwEbCqJ+D3xOueci5VkE6+kXpKmJjx6FdjUgcCihOWfwrKEfelIoJGZvVdS8XtXs3POuVhJdlSzmQ0BhuztfiSlAY8CPfd2G4XxxOuccy5WSnBU82KgUcJyw7AsT3WC+61/Ek5TWR8YJekcM5u6tzv1xOuccy5WSnDKyCnAwZKaEiTci4EeeSvNbA1QN3+/0idA7+IkXfDE65xzLmbSSmgGDTPbKul6YAyQDjxnZrMl3QtMNbNRJbKjAjzxOueci5WSnEDDzEYDowuU3V1E3ZNKYp+eeJ1zzsVK3Geu8sTrim3GCwdEHUKZUKXCP6IOocyo1rh/1CGUGRsX9os6hF8dT7zOOedcCvlNEpxzzrkU8sTrnHPOpVCFNIs6hGLxxOuccy5W4j7XsSde55xzsZImb/E655xzKePneJ1zzrkU8q5m55xzLoXSfXCVc845lzre1eycc86lkHc1O+eccynko5qdc865FPKuZueccy6FvKvZOeecSyGfMtI555xLIe9qds4551LIu5qdc865FPJRzc4551wKeVezc845l0KeeJ1zzrkUquBdzc4551zqeIvXOeecSyEf1VxGSBoILDCzx8LlMcAiM/tjuDwAWAzMA1qa2YN7sO2hwLtmNrzEA08+hp5AOzO7vpB15wKtzezePdzm7QTH6OVC1rUCbjWznnsXcckxMx5+4HUmTviKypUr0bd/T37b8qCd6j35+Nu8N+ozcnI28N8pT+SXD3joDaZO/gaATZs2s3LlWsZPeixl8ZckM+P+/s+RmTmNKpUrcf8DN9DysGY71Nm48RduvukRFi3MIi09jZNPbsctt16Wv/799yfy5KA3kODQQ5rw8ICbU/02St3gh6+ha+cjWL4ih3an/D3qcEqdmdG//xDGj/+CypX34cEHb+Sww5rvUGfjxk3ceONDLFy4lPT0NE4+uT29e/cEYMmSZdx222OsXbuebdty6d37Ck48sV0E7yQ53uItOyYCvwcek5QG1AX2S1h/LHCzmX0GjIogvtL0d+CcvXjdaQTHbCdmNktSQ0kHmdnCYkVXTBMnfMWihct4e/R9fDXzRx6472VeePWOnep1Oqk1v+9xMuedcdcO5bfetv0tvvbyx3wzd1Gpx1xaMjOnsWDBUj4YM4iZM76jX78hvP7Gzr8hr7zyHI7p0IrNm7dw1ZX9yMycRqdORzJ//hL+NWQEL7/Snxo1qrFixZoI3kXpe3HYeAY/P4ZnB/4l6lBSIjPzC+bPX8KHHz7DjBnf0Lfv0wwbNmCneldddR4dOrRm8+Yt9OzZh/Hjp3Liie14+uk36Nr1eHr0OIN58xbSq1c/Pv743xG8k+SoBM/xSjodeBxIB54t2CiTdAvwR2ArsBy4yswWFGefcW+xJ/oU6Bg+Pwz4ClgrqZakfYDfAtMk9ZQ0CIKWrKQnJH0q6QdJF4blkjRI0jeSPgL2L2yHkv4qaY6kmZJeC8v6SnpR0iRJ30n6U0L9v0maEtbvl1B+qaTJkqZLekZSelh+paRvJU0GjisihhbAL2b2c8J7elrSZ+F7OknSc5Lmhi33vNftB1Qys+WSLpL0laQZkjITNv8OcHHS/wKlZPy4GZx5Tgck0apNM9at3cjy5TsnjFZtmlGvXo1dbmvM6CmcdsbRpRVqqft47BS6dTsRSbRp24K1OetZvmzVDnWqVNmHYzq0AqBSpYq0bNmU7KwVAAwf9hE9epxOjRrVAKhTZ9fHK64mTv6alavXRR1Gyowd+xnnnvs7JNG27aHk5Kxn2bKVO9SpUqUyHTq0BvI+F78hOzv4XEiwbt0GANau3cD++9dO7RvYQxWU3GN3wu/aJ4GuQEugu6SWBap9SdDb2BoYDvxvceP/1SReM1sCbJV0EEHrdhLwOUEybgfMMrPNhby0AXA8cBaQ90vnPOAQgn+Iy8PtFeZ24IjwH+TPCeWtgd+F+75b0gGSTgUOBtoDbYGjJHWS9FvgD8BxZtYW2AZcIqkB0I8g4R4fxlKY44BpBcpqhfu+maB1P5Dgx0grSW3DOl2AseHzu4HTzKwNO7acpwInFLHflFmWvZqM+tu/CPbPqMny7FW7eEXhli5ZweLFP3P0MYeWZHgptSx7JfUb1M1fzqhfJ//LszA5Oev5ZNxUOnQMEvH8+UuYP38Jl3S/k4v/cDsTJnxZ6jG70pedvYL69bd/Lurv9nOxjnHjJtOxYxsArr++B++88wmdOvWkV6++9OlzTanHXBxpsqQeSWgPzDOzH8L88BrQLbGCmY0zsw3h4mdAw2LHX9wNlDGfEiTJvMQ7KWF5YhGvedvMcs1sDpARlnUCXjWzbWFC/7iI184EXpZ0KUE3RJ6RZrYxbIWOI/jHPTV8fEmQKA8lSMSdgaOAKZKmh8vNgGOAT8xsefiBeL2IGBoQdH8kesfMDJgFZJvZLDPLBWYDTcI6pwPvh88nAkPD1nl6wnaWAQcUsd/YGfP+FLqceiTp6b+2j33htm7dRu9bB3LpZWfSqFF9ALZtzWXBgqUMfeFeHhlwM/fc9TQ5OesjjtSl0tat27jlloe57LKz8z8X772XyXnndSYzcyhDhvTl739/lNzc3IgjLVqakntI6iVpasKjV4FNHQgknnv6KSwrytVs/97ca7+mc7wQJJBjgVYEXUD9bNkAACAASURBVM2LgFuBHOD/injNLwnP9/SU/ZkESfps4B/hgCSAgj+1LNz2A2b2TOIKSTcAz5vZHQXKz00yho1Awf7CvPeUy47vL5ft/+btgWsBzOzPko4J388Xko4ysxVA5XD7Owk/wL0AHn/qFq7649lJhpucN14dx4jh/wWg5eFNyM7a3m22LHs19TJq7fE2P3x/Krf9o3uJxZgqr7z8PsOGfQRAq1bNyVr6c/667KwVZGTUKfR199w9mMaNG3D5FWfll2XUr0Pr1gdTsWIFGjbMoHGTA1iwYCmtWjUvdBuu7Hr55fd4440xALRqdTBZWds/F1m7+FzcddcgmjQ5gJ49tzfshg//kGefDc5+HXHEofzyy2ZWrcqhTp2apfgO9l6yg6vMbAgwpCT2GTaw2gEnFndbv7af/p8SdBmvDFurK4GaBN2un+7BdjKBP0hKD7t8Ty5YIRzA1cjMxgG3ESS/auHqbpIqS6oDnARMAcYAV0mqFr7+QEn7E3T3Xhg+R1JtSY0JuslPlFRHUkXgoiJinQvs0bempMOAr81sW7j8GzP73MzuJmg9NwqrtiD4AbMTMxtiZu3MrF1JJ12A33c/mVffvItX37yLk37XlvdGfYaZMWvGD1SrVmW353IL+vGHLHJyNtC6bbPdVy5jelzSlRFvD2DE2wPo3Lk9I0eOx8yYMf1bqlffl3r77/wj5PHHXmHd2vXcceeVO5R37tKeKZNnA7BqVQ4L5i+hUcOMnV7vyr5LLjmTkSOfYOTIJ+jSpQNvv/0xZsb06V9Tvfq+hZ6nHTjwRdatW8+dd/5ph/IGDeoxadIMAL7/fhG//LKF2rXL7vn/9CQfSVjM9u87CLqRFxesJKkL8A/gHDP7peD6PfVra/HOIhjN/EqBsmp5g4+SNILgHO0cYCFBl3VB6cBLkmoQtGafMLPVkiDogh4XxnJf2F29JDyfOymssw641MzmSOoDfBgm8y3AdWb2maS+4b5XA9OLiDUTGCBJYfdyMroCHyQsPyzp4PB9jAVmhOUnA+8luc1Sc3ynw5k4YRbduvahcpVK9L3vivx13S+4j1ffDEYxPz7gTT4YPZlNmzbTtfNtnHv+8VxzXfCj4MP3p3Bq13aExz62Op14JJmZ0zj91OuoXHkf+t9/Xf668869lRFvDyArawXPDH6TZs0O5ILz/wbAJZd05cKLunD88W359L/TOevMG0lPS6P33y6nZq3qUb2dUvP8P2/ghI6/pW6t6sz7fBD3PTqc51//JOqwSs2JJ7Zj/PipnHJKL6pU2Yf7778xf123bn9l5MgnyMr6mcGD36BZs4acd95NAFx66ZlcdNFp3H771fTpM4ihQ0ciiQcfvLFM/79SgjdJmAIcLKkpQcK9GOiRWEHSEcAzwOlmtqwkdqrkv6tdMsJkuc7MHknhPh8nOK/7UZL1/wNcbmZLd1FnH2A8cLyZbS2qHsC6LZ/4hwioUqHu7iuVE9Ua9486hDJj48J+u69UrrQodkb/35n/Seo75++tT9ntviSdATxG0Jh6zsz6S7oXmGpmo8IrW1oBed+XC81sby7fzPdra/GWV/cTDMZKipmdkkS1g4Dbd5d0nXMu1dJLsDFuZqOB0QXK7k543qXk9hbwxFvCzKxvBPvMpoQnBTGz74DvSnKbzjlXEnzmKueccy6FSvAcbyQ88TrnnIsVb/E655xzKZTkpUJllide55xzsVIhzbuanXPOuZQpyVHNUfDE65xzLlb8HK9zzjmXQp54nXPOuRTyxOucc86lUEW/jtc555xLHW/xOueccynkidc555xLoXTvanbOOedSx1u8zjnnXAp54nXOOedSqGJa1BEUjyde55xzseK3BXTOOedSKOYNXk+8zjnn4sXP8TrnnHMp5Hcncs4551LI78fryr1WfdZFHUKZsHL4K1GHUGZsXNgv6hDKjCoH3RN1CGXKxoWvFnsb3tXsnHPOpZAPrnLOOedSSN7idc4551In5nk39i1255xz5YyU3CO5bel0Sd9Imifp9kLW7yPp9XD955KaFDd+T7zOOediJV2W1GN3JKUDTwJdgZZAd0ktC1S7GlhlZs2BgcBDxY3fE69zzrlYUZKPJLQH5pnZD2a2GXgN6FagTjfg+fD5cKCzVLyzzJ54nXPOxUqyXc2SekmamvDoVWBTBwKLEpZ/CssKrWNmW4E1QJ3ixO+Dq5xzzsVKss1NMxsCDCnNWPaGt3idc87FSpqSeyRhMdAoYblhWFZoHUkVgBrAimLFX5wXO+ecc6lWgud4pwAHS2oqqRJwMTCqQJ1RwBXh8wuBj82sWHNWelezc865WCmpKSPNbKuk64ExQDrwnJnNlnQvMNXMRgH/Bl6UNA9YSZCci8UTr3POuVgpyQk0zGw0MLpA2d0JzzcBF5XgLj3xOuecixe/SYJzzjmXQjHPu554nXPOxYuSmJWqLPPE65xzLla8q9k555xLobhfB+uJ1znnXKz4/Xidc865FIp53vXE65xzLl68xeucc86lUMzzride55xz8ZIe88y728QraRswC6gIbAVeAAaaWW4px7armO4FMs3so13UOQnYbGaf7sm6skRSE+BYM3ulBLcpYCxwrpnlSKoPPAYcDawGsoGbgFXAi2Z2ekntuyR0alGPe845jDSJ16csZPAn3+9U58zWDbixSwsMmLskh5te+zL1gZaSzp0O46G7/kB6ehovvP5fBj7zwQ7rGx1QmycfuoI6tauzavV6et36b5ZkrQagYYPa/POByzmwQS3MjIuu/icLFxfrJiuRMjP69x/C+PFfULnyPjz44I0cdljzHeps3LiJG298iIULl5KensbJJ7end++eACxZsozbbnuMtWvXs21bLr17X8GJJ7aL4J2UrsEPX0PXzkewfEUO7U75e9ThlIjycB3vRjNrCyBpf+AVYD/gntIMbFcS59HchZOAdUBhyXVX61JKUoXw5sqFaQL0IDjme7LNdDPbVsTqM4AZYdIVMAJ43swuDl/bBsgws28lLZV0nJlN3JP9l5Y0wb3nHs5lz35O1pqNjLz+BD6ak828Zevy6zSpU5VrT2rOhU9/Ss7GLdSpWinCiEtWWpoY0LcH514xkMVZqxg34k5Gj53BN/OW5tf5nzsu4tURn/HqW5Po1PEQ7ul9Ptf0fg6AwY9cyYCnRjNu4lyq7rsPubnx/vLKzPyC+fOX8OGHzzBjxjf07fs0w4YN2KneVVedR4cOrdm8eQs9e/Zh/PipnHhiO55++g26dj2eHj3OYN68hfTq1Y+PP/53BO+kdL04bDyDnx/DswP/EnUoJSbmDd49uxzKzJYBvYDrFUiX9LCkKZJmSroGQNKTks4Jn4+Q9Fz4/CpJ/QtuV9I6SQMlzZY0VlK9sLytpM/CbY+QVCssHyrpwvD5fEn9JE2TNEvSoWFL8c/AzZKmSzohYV87rZNUT9Kb4fuYIum4sG5fSc9LmiBpgaTzJf1vuJ8PJFVMiCGvfLKk5mH5rrb7oqSJBHe9aBLuY1r4ODYM90HghDDOmyX1lDQo4b28G7be847hAEkzgI6SLg1jmS7pGUnp4csuAUaGz08GtpjZ4IR/4xlmNiFcfDusXya0aVSTBSvWs2jlBrZsM96ZsZhTWmbsUOfi9gfx4qT55GzcAsCK9ZsjiLR0HNWmKT8sWMb8RT+zZcs23np3Cmd2abNDnUOaNyBz0tcAZE76hjPC9Yc0b0CFCumMmzgXgPUbfmHjpngfm7FjP+Pcc3+HJNq2PZScnPUsW7ZyhzpVqlSmQ4fWAFSqVJGWLX9DdnbQypdg3boNAKxdu4H996+d2jeQIhMnf83K1et2XzFGpOQeZdUeX4dsZj8Q3D5pf+BqYI2ZHU3QVfknSU2BCUBesjsQaBk+PwHILGSzVQluwXQYMJ7trekXgNvMrDVBd3dRreyfzexI4Gmgt5nNBwYTdIm3TUgkFLHu8XD5aOAC4NmEbf8G+B1wDvASMM7MWgEbgTMT6q0JywcRdN2ym+22BLqYWXdgGXBK+B7+ADwR1rkdmBDGObCI956nKvC5mbUhuEnzH4Djwt6KbWxPoMcBX4TPD094XpipbP93jFz9GlVYunpT/nLWmk3Ur1FlhzpN61Wlad1qDLv2WN667jg6taiX6jBLzQEZNVm8dHtiWZy1mgYZtXao89XXizj7tCMAOPvUI9ivehVq1axK86YZrMnZwEtP/ZkJo/pw3+0XkBbz6X+ys1dQv37d/OX69evkJ9XC5OSsY9y4yXTsGPwYuf76Hrzzzid06tSTXr360qfPNaUesysZJXg/3kgUdwKQU4HLJU0HPgfqAAcTJl5JLYE5QLakBkBHCu/ezQVeD5+/BBwvqQZQ08zGh+XPA52KiOOt8O8XBN2ze6oLMCh8H6OA/SRVC9e9b2ZbCBJ/OpB3Um1WgX29mvC3YxLbHWVmG8PnFYF/SZoFDGP7D5U9sQ14M3zeGTgKmBLuuzPQLFxX28zWJrnNZcABexFLZNLTRJO6Ven+zCT++so0HrigNdUrl58xhH0eGM7x7VswYVQfjjumBYuXriJ3Wy4V0tPoePTB9HlgOCeddz9NGtXjkguO3f0GfyW2bt3GLbc8zGWXnU2jRvUBeO+9TM47rzOZmUMZMqQvf//7o+TmRjZ0xe2BtCQfZdUefyNJakbwJb+M4EfFDWY2ppB6NYHTCVq4tYHfA+uS/NLf05NPv4R/t7F3I7XTgA7hfRfzBadAg22bWa6kLWaWF1tugX1ZIc93td31CUU3EwxqahO+Zof6Cbay4+epcsLzTQnndUVw3vaOwrYhKS0cHDcbuLCIfeVtf2NhKyT1IjjtQJ1Tr6N629Ifg5W1ZiMNam5/y/VrVCZrzcYCdTYxfdEqtuYaP63ayI8/r6dp3arM/GlNqcdX2pZkr+bABtu7Qw+sX5Ol2at2qJO1bA2X/iU4c1B1330457QjWbN2I4uzVjFrziLmL/oZgHf/M52j2zblxWFl4vR90l5++T3eeCP4umnV6mCysn7OX5eVtYKMjDqFvu6uuwbRpMkB9OzZLb9s+PAPefbZfgAcccSh/PLLZlatyqFOnZql+A5cSVBZ7kdOwh79KAjPvQ4GBoUJaAxwbcK5zhaSqobVPyMYHZtJ0ALuHf4tKo68BNAD+K+ZrQFWJZyfvYygGzpZa4HqSa77ELghb0FS2z3YT54/JPydtIfbrQEsDZPhZQQt68LinA+0lZQmqRHQvojtjQUuDAfDIam2pMbhum/Y3vr9GNgnTKJ5MbZOOOYtgK8K24GZDTGzdmbWLhVJF2DmT2toUqcqDWtVoWK6OLvNgXw0N3uHOh/OzqJDs+DLt9a+FWlatyoLV25ISXylbdrM+fymyf40bliHihXTOf+soxk9dsYOdWrXqpb/pXTLtV15afjE/NfW2K8KdWoHHS6dOh7C1wmDsuLikkvOZOTIJxg58gm6dOnA229/jJkxffrXVK++b6HnaQcOfJF169Zz551/2qG8QYN6TJoUHL/vv1/EL79soXbtGil5H654lOR/ZVUyrcMqYXdl3uVELwKPhuueJehunabg//blwLnhugnAqWY2T9ICglZvUYl3PdBeUh+ClnReErsCGCxpX+AH4Mo9eG/vAMMldSNolU8oah3wV+BJSTMJjkkmwQCsPVErfP0vQPewLNntPgW8Kelygq7svNbwTGBbOGBqKMG54x8Juu/nAtMKC8TM5oTH8kNJacAW4DpgAfAewajueWZmks4DHpN0G0FLez7BDyYIBl+9t4fHodRsyzXuGTmbF64+hrQ0MWzKIr7LXsfNp7Rg1k9r+GhuNpnfLueEFvX48JYT2ZZrPDB6Lqs3bIk69BKxbVsuvfu9yltDbyI9LY2Xhk/k6++WcudN5/DlrAW8P3YGJxzTgnv+dh5m8Onkb7m1b3AGJDfXuOuB4Yx68RYkMf2rBTz/elH/O8bDiSe2Y/z4qZxySi+qVNmH+++/MX9dt25/ZeTIJ8jK+pnBg9+gWbOGnHde8LG+9NIzueii07j99qvp02cQQ4eORBIPPnhj7FtShXn+nzdwQsffUrdWdeZ9Poj7Hh3O869/EnVYxRJ8rcWXtvecRhiEtM7Mqu2+ZtkkaT7Qzsx+3l3dqIXn2l8ws1OSqJsJdDOzVbuq1/S2d6P/EJUBK4ePijqEMmPN972jDqHMqHJQZFdelkkbF75a7F83qze/n9R3Ts1KXcvkL6l4/2xwe8zMlhIM5NpvV/XC0wqP7i7pOudcqpWHruZSF+fWLoCZNYk6hj1hZm8kUWc5wXW8zjlXpmyfliCeykTidc4555JXdluzyfDE65xzLlbKcjdyMjzxOueci5W4J14fXOWccy5mUjN3VTgHwn8kfRf+rVVInbaSJim418BMSX8obFsFo3fOOediQ1JSjxJwOzDWzA4mmJjo9kLqbAAuD+81cDrBvAi7nP7ME69zzrlYEWlJPUpAN4L7BBD+PbdgBTP71sy+C58vIZgEapd3Z/FzvM4552ImZW3GjHDuA4AsIGNXlSW1ByoB3++qnide55xzsZLs4KrEm7mEhpjZkAJ1PgLqF/LyfyQuhFPsFjljVjgr4IvAFeG8+0XyxOuccy5Wkj1/GybZIbup02UX+8mW1MDMloaJdVkR9fYjmNf+H2b22e7i8nO8zjnnYqaw294X9ii2UQQ36yH8O3KnSKRKwAiCOfCHJ7NRT7zOOediJYWDqx4ETpH0HdAlXEZSO0nPhnV+D3QCekqaHj52eWtZ72p2zjkXK6m6LaCZrQA6F1I+Ffhj+Pwl4KU92a4nXuecczET75mrPPE655yLlRLqRo6MJ17nnHMx4y1e55xzLmXifpMET7zOOediRUqPOoRi8cTrnHMuVrzF65xzzqWUJ17nnHMuZUroln+R8cTrnHMuZuJ9OZHMirzZgnOxIalXwbuOlFd+LLbzY7GdH4uyI94/G5zbrtfuq5Qbfiy282OxnR+LMsITr3POOZdCnnidc865FPLE634t/NzVdn4stvNjsZ0fizLCB1c555xzKeQtXueccy6FPPE655xzKeSJ18WSpH2SKXPOubLGZ65ycTUJODKJsl81SZWBs4ATgAOAjcBXwHtmNjvK2FJNUkPgYgo5FsD7ZpYbYXgpJakjcCnBsWjAjsfiJTNbE2F45Z4PrnKxIqk+cCDwEtCD7bOl7wcMNrNDo4ot1ST1A84GxgFfAMuAykAL4OTw+a1mNjOyIFNE0v8RfC7eBaay87E4CrjdzDIjCzJFJL0PLAFGUvixOBt41MxGRRZkOeeJ18WKpCuAnkA7gi+VPGuBoWb2VhRxRUHSmWb23i7W7w8cZGZTi6rzayHpcDP7ahfrKxEci3kpDCsSkuqa2c/FreNKjydeF0uSLjCzN6OOI0phN3N1M1teoLwesNbMNkUTWdkgqRbQqDy0+BNJag5kmNnEAuXHAVlm9n00kbk8PrjKxdW7knpIulPS3XmPqINKsScIzuEVdDwwMMWxlAmSPpG0n6TawDTgX5LK27F4DMgppDwnXOci5onXxdVIoBuwFVif8ChPjiqsa93MRgCdIoinLKhhZjnA+cALZnYM0DnimFItw8xmFSwMy5qkPhxXkI9qdnHV0MxOjzqIiO27i3Xl9Ud1BUkNgN8D/4g6mIjU3MW6KimLwhWpvP7P6eLvU0mtog4iYssktS9YKOloYHkh9cuDe4ExwDwzmyKpGfBdxDGl2lRJfypYKOmPBKPfXcR8cJWLJUlzgObAj8AvBJcVmZm1jjSwFAqT7hvAULZ/obYDLgcuNrPPIwot5SR1Bz40sxVRxxI1SRnACGAzO34uKgHnmVlWVLG5gCdeF0uSGhdWbmYLUh1LlMJLhq4DDg+LZgODzGxZdFGlnqTbgNOAisBY4H1gspXjLzhJJ5PwuTCzj6OMx23nidfFkqSDCis3s4WpjsWVHZKqA12A04H2wFzgA2CMmWVHGVuqSKpmZuuKW8eVHk+8LpYkzQKMoIu5MtAU+MbMDos0sBSS9A7BPVY/MLMtBdY1I5hoZL6ZPRdBeGWCpJZAV+BUMzst6nhSQdJYYDrByP8vzGx9WN6MYOaq3wP/MrPh0UVZvnnidb8Kko4E/mJmf4w6llQJp8+8BbgAWEkwoKoywSUj3xN0OY+MLMCISGpNcAzyr9ooTzOaAUg6A7gEOA6oDWwBviGYq/nffp43Wp543a+GpFlmVi5HOktqwvbJ8L81sw2RBhQRSc8BrQnOdefdFMHM7KroonJuR34dr4slSbckLKYR3JVoSUThlAUGVDWzSZKqSKpuZmujDioCHcysZdRBlAWSRNDqbWpm94XjIuqb2eSIQyv3/DpeF1fVEx77EHShdYs0ooiE12wOB54JixoCb0cXUaQmhed1HTwFdCS4ixcENxJ5MrpwXB5v8bpYMrN+EIzODJfL8wjN6whG8H4OYGbfhZcZlUcvECTfLMrp9d0JjjGzIyV9CWBmq8K7NLmIeeJ1sSTpcOBFgoEjSPoZuGJXt4b7FfvFzDYHPYsgqQJB13N59G/gMmAW28/xlldbJKUTfhbCu1aV92NSJnjidXE1BLjFzMYBSDopLDs2yqAiMl7SnUAVSacAfwHeiTimqCz3G7zne4JgBqv9JfUHLgT6RBuSAx/V7GJK0gwza7O7svIgHETzR+BUgq7VMcCz5XHWJklPEdwk4B2CrmagXF5OlAZ0ILjMrDPB52Ksmc2NNDAHeOJ1MSVpBMH9Vl8Miy4luE3eedFFlXphV+JsMzs06ljKAkn/V0hxubycSNKXZnZE1HG4nXnidbEkqRbQj+Cm7wZMAPqZ2apIA4uApJHADT5dpksk6RFgEvBWeez9KMs88bpYkVQZqG5mywuU7w/kmNmmaCKLjqRM4AhgMrA+r9zMzoksqBST1Ad4ysxWFrH+d8C+ZvZuaiOLjqS1QFVgK7CJ7SO894s0MOeDq1zsPEEw6X3Bc3bHEZzjvDblEUXvrqgDKANmAe9I2kRwCiJv+syDgbbAR8D90YWXemZWPeoYXOG8xetiRdIXZnZUEetml6ebJLidSTqY4EdY3vSZc4FMM9sYaWARkNSpsHIzy0x1LG5H3uJ1cbPvLtaVy5nYwi7FvF/QlQjuSbu+PHYpmtl3wHdRx1FG/C3heWWCSVa+AH4XTTgujydeFzfLJLUvON+spKMJuhfLncQuxfDSom4El5K4cszMzk5cltQIeCyicFwC72p2sSKpPfAGMJTg1ztAO+By4GIz+zyi0MoUv5TEFRT+KJvtN5GInrd4XayY2eQw+V5HcKN3CG4Bd4yZLYsssAhJOj9hMY3gh0i5G93tdiTpn2w/BZFGMMhsWnQRuTze4nUu5gpMGrEVmA/8qzz9ECmQZHZiZn9NYThlgqQrEha3AvPNbGJU8bjtvMXrXPw9W/ALVdJxQLlJvMDU8O9xQEvg9XD5ImBOJBFFr6aZPZ5YIOnGgmUu9bzF61zMSZpmZkfurqw8kPQZcLyZbQ2XKwITzKzcDTYr4nPh5/7LAG/xuliTtK+ZbYg6jihI6khwN6Z6km5JWLUfkB5NVJGrRfD+82awqhaWlRuSugM9gKaSEu/UVJ3tx8VFyBOviyVJxwLPEnyxHiSpDXCNmf0l2shSqhLB+69A8KWaJ4fgFnDl0YPAl5LGEUyR2AnoG2lEqfcpsBSoCwxIKF8LzIwkIrcD72p2sSTpc4LkMiqv60zSV2Z2eLSRpZ6kxma2IOo4ygpJ9YFjwsXPzSwrynicK6hczvTjfh3MbFGBom2RBBK9DZIeljRa0sd5j6iDikJ4rWoXoI2ZjQQqhZeflTuSOkiaImmdpM2StknKiTou54nXxdeisLvZJFWU1JtgXt7y6GXga6Apwa0S5wNTogwoQk8BHYHu4fJa4MnowonUIILj8B1QBfgj5fdYlCmeeF1c/ZlgEo0DgcUEkwOUp/O7ieqY2b+BLWY2Przpe3mdj/cYM7uOcAKR8P7MlaINKTpmNg9IN7NtZvZ/wOlRx+R8cJWLr6PN7JLEAkl/BgZHFE+UtoR/l0o6E1gC1I4wnihtkZROOJmGpHpAbrQhRWaDpErAdEn/SzDgyhtbZYD/I7i4uiu8uTkAkv5GcHOA8uh/JNUAbgV6E4z2vjnakCLzBDACyJDUH/gv5ew+vAkuI/iOvx5YDzQCLog0Igf4qGYXU5LqAu8S3PrsdOBQoLuZbY40sBQLW3d/NbOBUcdSVkg6FOhMcDnRWDMrd+f+w8/FCwV7hVzZ4C1eF0tm9jNwDsFgkQOAC8tb0gUws21sH0jkAnWBDWY2CPhZUtOoA0q18HPROOxqdmWMt3hdrCTc9F3h30oEE8AbYOXx5u+SBgIVCeYnXp9Xbmb/3979x+pZ1nccf3/6g0mRtlKLzFV+ZqAVLLgfUOo0uJS5DEQZMtQ/dDLMMoYMZIbook5NzEhGQMwCVIeazW2wDMFE0g6Z0CE/ws+2QxsmDGEQBiK0oUJr/eyP63roOadHapblue77uT+v5Mk59/20yScnT8+313Vf1/ca3Ek0kj5FOZ3pCNuHS3otcI3tVY2jjZ2krwFvAK5n+ufi4mahAsjiquiZqYe+x0uOrl8/M+WeGebK5ncDx1CPv7P9uKShfmZ+UF9zmN7ZLBpL4Y1ekfR629+XNOsBAEMc5dk+oXWGDtlu25JGq5r3aR2oFdt/CcPuZ95VKbzRN+cDH2Z6D9qRQY7yJL2GsnL3tbZ/V9JyYGXd2zs0V0u6Algs6SzgQ8CaxpmaqIdofJlh9zPvpDzjjeg5STcAVwGfsL1C0jzgXttHNY7WhKTVwIn1cp3tf22Zp5X0M++urGqO3pF0UN1ONOpHe4Gkd7XO1dCrbV9NbRRRz6Idat9qgI3AeuCW+v1gpZ95N6XwRq9I+iRwE3C7pM8Bl1C2j5wr6ZKm4dp5XtISdnVrOg54XKJhUgAACrtJREFUrm2kNiT9EXAncCpltHe7pA+1TdVM+pl3VKaao1ckPUBZxbsA+CFwgO1tdXr1viFOo9WFZpcBRwKbgKWUfc2DO3tV0mbgeNs/qtdLgO/aPqJtsvGrs0KXUk5rmgOsBc4d/WyinSyuir55oTbK2C7pB6PVmrZ/KmlwDTSgrOSW9DbgCMr+5s22d+zhr02qH1FOJBrZWu8NTm0yk85VHZTCG32zWNKplAKzsH5PvV7ULlY7kl5BOZnpLZTp5vWSLrf9QttkTfwncIek6yg/i1OADZLOh2E1j5B0KGXEexzlZ3EbcJ7th5oGi0w1R79Iuurl3rf9h+PK0hWSrqaM7P6u3nofsNj2e9qlaqN2rvq5Rntbh0DS7ZSWqv9Qb50BnGP72HapAlJ4I3pP0gO2l+/p3tBImgO80vaW1llakLTB9ptm3Lvf9opWmaLIquaI/runrmQGQNKxwF0N8zQj6euSFtaOVZuAB+qRkUN0g6QLJR1ct+B9DPiWpP0kDfW85k7IiDei5yR9j7Kw6of11oHAZurhETNHPZNM0n22j5b0fuDNwIXA3UP6GYxIevhl3rbtQ8cWJqbJ4qqI/ntH6wAdMl/SfOBdwBdt7xj1bR4a24M7DrEvUnijV6asYp6V7X8ZV5ausP2IpFcBr2PKv+khHhgBXAH8F3A/cIukg4ChPuOdC/wecDDTPxeDWdndVZlqjl6Zsqp5f+B4ShcrgBMojRJOahKsIUmfBT5IOQJu9A/atgd3YMRMkgTMrW00B0XSt4AXKG0zfza6P6SV3V2VEW/0ymi7kKR1wHLbT9TrXwa+0jBaS6cDh9XGIjGFy8hicEW3WjbEZ9t9kFXN0VevGxXd6knKoqIh2gQsbh0iOucGSSfu+Y/FuGXEG331bUlr2dUc4A+AGxvmaenzwL2SNgEvjm7afme7SNEBtwPX1v3MOyjd3Wx7YdtYkWe80VuS3g28tV7eYvvalnlakfQflEVFM5/l3dws1Jhl0d3u6naiU4CNzi/6TsmIN/rsHmCr7RslLZC0r+2te/xbk2eb7S+0DtHYyfXrrIvugMEVXuBRYFOKbvek8EYvSToL+DCwH3AY8CvA5cBvt8zVyHpJnweuZ/pU82C2E2XR3aweAr4j6Qamfy6ynaixFN7oq7OB3wTuALD9oKT920Zq5pj69bgp9wwMcTtRFt3t8nB97VVf0REpvNFXL9reXrZpgqR57NrDOii2T2idoUOy6K4a7deVtGB0bnV0Q7YTRV/dLOnjwN6SVgPXAN9snKkJSa+R9OU6pYik5ZLObJ2rBdt/SllotqK+rrR9TttUbUhaKekB4Pv1eoWkv2kcK8iq5uipukXiTOBEyjaJtbbXtE3VRi24VwGfsL2ijv7vtX1U42jRkKQ7gNOA620fU+9tsn1k22SREW/01Tm219h+j+3TbK+RdG7rUONUCyzAq21fTd1KVNsj7mwWrCFJp0p6UNJzkrZI2ippkL2aAWw/OuPWID8XXZPCG331gVnufXDcIRq7s359XtIS6jPuejbvc81StXUR8E7bi2wvtL3vgBtGPCrpeMCS5ku6APhe61CRxVXRM5LeC7wPOETS9VPe2hd4pk2qZlS/nk/ZSnSYpFuBpZQpxiF60naKS/HHwKWUrXb/DawD/qRpogDyjDd6ph7zdgilTeKFU97aCmwY0ik0kh4DRnsy5wC/RCnGLwI7h7hfU9KlwAHAN5i+d3VwDTQkrbJ9657uxfhlxBu9YvsR4BFgZessHTAXeCW7Rr4jCxpk6YqFwDbKorsRM8zOVZcBb/4F7sWYpfBGL9XevH9FaREohtkA/gnbn2kdoktGHayGTNJKStvMpZLOn/LWQsp/1qKxFN7oq4uAkwf+PG/mSHewJH3M9kWSLmOWRiq2P9IgVit7UWZC5lHWPoxsYbjP/jslhTf6KotohtmX+ucZfRbuapqiA+qpVDdL+kp9NBMdk8VV0UtZRBNTSfozyilE9wxpgV30U0a80VdZRBNTLQMuAV4vaSNwK6UQf9f20LaZRcdlxBsRE0PSXsCvUxYXrayvZ20vbxqsgWwn6q50ropeknS4pG9L2lSv3yTpL1rniub2psyGLKqvx6lHRw7QZb/gvRizTDVHX60B/pxyEg22N0j6OvC5pqmiCUlXAm+kNFK5gzLNfLHtHzcN1kC2E3VfCm/01QLbd47O462yqGa4DqR07nqQ0h7xMeDZponayXaijkvhjb56WtJh7DoY4DTgibaRohXb71D5X9gbKaO9jwJHSnoGuM32p5oGHKNsJ+q+LK6KXpJ0KHAl5Zfsj4GHgffnF01IWgasonw2TgKW2F7cNtX4STocuAA4mCmDLNtvb5UpihTe6DVJ+1AWCW4DzrD9940jRQOSPkIptMcDO6hbiepro+2fNYzXhKT7gcuBu5lyDq/tu5uFCiCFN3pG0kLgbMpRZ9cBN9brj1JOJzqlYbxoRNLF1L27tvPIAZB0t+1fa50jdpfCG70i6TrK1PJtlJaJo0MSzrV9X8tsEV0i6dPA/wDXMr27WxqKNJbCG70iaaPto+r3cykLqg60/ULbZBHdIunhWW7b9qFjDxPTZFVz9M2O0Te2d0p6LEU3Yne2D2mdIWaXEW/0iqSdwPOjS0qnom0M8zzeiN1Iervtm+qZ1bvJQSLtZcQbvWI7nXciXt7bgJuAk2d5LweJdEBGvBEREWOUQxIiIiaQpEWSLpZ0V339taRFrXNFCm9ExKT6W8qhEafX1xbgqqaJAshUc0TERJJ0n+2j93Qvxi8j3oiIyfQTSW8ZXUhaBfykYZ6oMuKNiJhAko4Gvgosomy3ewb4gO0NTYNFCm9ExCSr/c2xvaV1ligy1RwRMYEkLZH0BeA7wL9JulTSksaxghTeiIhJ9Y/AU8DvA6fV7/+paaIAMtUcETGRJG2yfeSMey8dMhLtZMQbETGZ1kk6Q9Kc+jodWNs6VGTEGxExkSRtBfYBdtZbc9l1wEgOFGkohTciImKMMtUcERExRim8ERERY5TCGxERMUYpvBERE0jSZyWtlrRP6ywxXQpvRMRkegh4L3CXpDvrebyntA4VWdUcETHRJB1AOY/3AuBVtvdtHGnwUngjIiaQpC8By4EngfXAvwP32P5p02CRqeaIiAm1hNI041nKkYBPp+h2Q0a8ERETTNIbgN8BzgPm2l7WONLgzWsdICIi/v9JOgn4LeCtwGLgJsqUczSWEW9ExASS9EVKoV1v+/HWeWKXFN6IiAkl6SDgV23fKGlvYJ7tra1zDV0WV0VETCBJZwH/DFxRby0DvtEuUYyk8EZETKazgVXAFgDbDwL7N00UQApvRMSketH29tGFpHlAni12QApvRMRkulnSx4G9Ja0GrgG+2ThTkMVVERETSdIc4EzgREDAWuBLzi/95lJ4IyImlKSlALafap0ldslUc0TEBFHxaUlPA5uBzZKekvTJ1tmiSOGNiJgs51FWM/+G7f1s7wccC6ySdF7baAGZao6ImCiS7gVW2356xv2lwDrbx7RJFiMZ8UZETJb5M4suvPScd36DPDFDCm9ExGTZ/n98L8YkU80RERNE0k7g+dneAl5hO6PexlJ4IyIixihTzREREWOUwhsRETFGKbwRERFjlMIbERExRim8ERERY5TCGxERMUb/C2HovPMCQiOiAAAAAElFTkSuQmCC\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(df_daily_dtype['Temperature(C)'], df_daily_dtype['Wind speed (m/s)'])\n",
        "# prove corelation of data"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 448
        },
        "id": "WWPPkq8k-7Kh",
        "outputId": "ea9d7396-7787-4592-c12d-2634f5a35e4d"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7f0508ccde10>]"
            ]
          },
          "metadata": {},
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "d) Does the demand depend on `Temperature(C)` and `Holiday`? Use proper visualization to demonstrate your point. (10 points)\n",
        "\n",
        "*Your answer:*"
      ],
      "metadata": {
        "id": "Hhr21P1r_X5Y"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(10, 8))\n",
        "plt.bar(df_daily_dtype['Holiday'], df_daily_dtype['Rented Bike Count'])"
      ],
      "metadata": {
        "id": "mERIcXr6_pkM",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 694
        },
        "outputId": "6960322e-9152-4c03-fa5c-97e4a995897d"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<BarContainer object of 365 artists>"
            ]
          },
          "metadata": {},
          "execution_count": 24
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x800 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}