romania-weather-eda.ipynb

{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.13","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":3373208,"sourceType":"datasetVersion","datasetId":2030471}],"dockerImageVersionId":30698,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"import numpy as np \nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nimport warnings\nwarnings.filterwarnings('ignore', category=FutureWarning)","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2024-05-02T07:30:56.037764Z","iopub.execute_input":"2024-05-02T07:30:56.038977Z","iopub.status.idle":"2024-05-02T07:30:58.930261Z","shell.execute_reply.started":"2024-05-02T07:30:56.038926Z","shell.execute_reply":"2024-05-02T07:30:58.929122Z"},"trusted":true},"execution_count":1,"outputs":[]},{"cell_type":"code","source":"df = pd.read_csv(\"/kaggle/input/romania-weather-visual-crossing-weather/weather_2011-2021_Romania.csv\" , encoding='latin-1')\ndf.head()","metadata":{"execution":{"iopub.status.busy":"2024-05-02T07:30:58.932252Z","iopub.execute_input":"2024-05-02T07:30:58.932688Z","iopub.status.idle":"2024-05-02T07:31:00.269902Z","shell.execute_reply.started":"2024-05-02T07:30:58.932661Z","shell.execute_reply":"2024-05-02T07:31:00.268254Z"},"trusted":true},"execution_count":2,"outputs":[{"execution_count":2,"output_type":"execute_result","data":{"text/plain":"               Address   Date time  Minimum Temperature  Maximum Temperature  \\\n0  Alba Iulia, Romania  01/01/2011                -10.1                 -3.6   \n1  Alba Iulia, Romania  01/02/2011                 -9.0                 -1.7   \n2  Alba Iulia, Romania  01/03/2011                 -7.2                 -1.8   \n3  Alba Iulia, Romania  01/04/2011                 -6.7                 -4.5   \n4  Alba Iulia, Romania  01/05/2011                -11.5                 -5.0   \n\n   Temperature  Dew Point  Relative Humidity  Heat Index  Wind Speed  \\\n0         -6.9       -8.2              90.62         NaN         8.9   \n1         -4.6       -6.0              89.80         NaN         8.8   \n2         -4.0       -5.0              93.01         NaN         8.7   \n3         -5.7       -7.4              87.73         NaN         7.0   \n4         -7.9      -10.2              83.54         NaN         8.0   \n\n   Wind Gust  ...  Visibility  Cloud Cover  Sea Level Pressure  \\\n0       21.6  ...         4.8         71.6              1022.3   \n1       14.4  ...         6.5         74.1              1017.9   \n2        7.2  ...         4.3         94.5              1021.1   \n3       14.4  ...         7.4         96.6              1026.5   \n4       15.1  ...         8.1         61.1              1027.9   \n\n                                      Weather Type  Latitude  Longitude  \\\n0                                             Mist   46.0709    23.5805   \n1                            Mist, Light Snow, Fog   46.0709    23.5805   \n2                      Mist, Light Snow, Fog, Snow   46.0709    23.5805   \n3  Mist, Light Snow, Sky Coverage Increasing, Snow   46.0709    23.5805   \n4                                             Mist   46.0709    23.5805   \n\n      Resolved Address                 Name Info        Conditions  \n0  Alba Iulia, România  Alba Iulia, România  NaN  Partially cloudy  \n1  Alba Iulia, România  Alba Iulia, România  NaN  Partially cloudy  \n2  Alba Iulia, România  Alba Iulia, România  NaN          Overcast  \n3  Alba Iulia, România  Alba Iulia, România  NaN          Overcast  \n4  Alba Iulia, România  Alba Iulia, România  NaN  Partially cloudy  \n\n[5 rows x 25 columns]","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Address</th>\n      <th>Date time</th>\n      <th>Minimum Temperature</th>\n      <th>Maximum Temperature</th>\n      <th>Temperature</th>\n      <th>Dew Point</th>\n      <th>Relative Humidity</th>\n      <th>Heat Index</th>\n      <th>Wind Speed</th>\n      <th>Wind Gust</th>\n      <th>...</th>\n      <th>Visibility</th>\n      <th>Cloud Cover</th>\n      <th>Sea Level Pressure</th>\n      <th>Weather Type</th>\n      <th>Latitude</th>\n      <th>Longitude</th>\n      <th>Resolved Address</th>\n      <th>Name</th>\n      <th>Info</th>\n      <th>Conditions</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Alba Iulia, Romania</td>\n      <td>01/01/2011</td>\n      <td>-10.1</td>\n      <td>-3.6</td>\n      <td>-6.9</td>\n      <td>-8.2</td>\n      <td>90.62</td>\n      <td>NaN</td>\n      <td>8.9</td>\n      <td>21.6</td>\n      <td>...</td>\n      <td>4.8</td>\n      <td>71.6</td>\n      <td>1022.3</td>\n      <td>Mist</td>\n      <td>46.0709</td>\n      <td>23.5805</td>\n      <td>Alba Iulia, România</td>\n      <td>Alba Iulia, România</td>\n      <td>NaN</td>\n      <td>Partially cloudy</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Alba Iulia, Romania</td>\n      <td>01/02/2011</td>\n      <td>-9.0</td>\n      <td>-1.7</td>\n      <td>-4.6</td>\n      <td>-6.0</td>\n      <td>89.80</td>\n      <td>NaN</td>\n      <td>8.8</td>\n      <td>14.4</td>\n      <td>...</td>\n      <td>6.5</td>\n      <td>74.1</td>\n      <td>1017.9</td>\n      <td>Mist, Light Snow, Fog</td>\n      <td>46.0709</td>\n      <td>23.5805</td>\n      <td>Alba Iulia, România</td>\n      <td>Alba Iulia, România</td>\n      <td>NaN</td>\n      <td>Partially cloudy</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Alba Iulia, Romania</td>\n      <td>01/03/2011</td>\n      <td>-7.2</td>\n      <td>-1.8</td>\n      <td>-4.0</td>\n      <td>-5.0</td>\n      <td>93.01</td>\n      <td>NaN</td>\n      <td>8.7</td>\n      <td>7.2</td>\n      <td>...</td>\n      <td>4.3</td>\n      <td>94.5</td>\n      <td>1021.1</td>\n      <td>Mist, Light Snow, Fog, Snow</td>\n      <td>46.0709</td>\n      <td>23.5805</td>\n      <td>Alba Iulia, România</td>\n      <td>Alba Iulia, România</td>\n      <td>NaN</td>\n      <td>Overcast</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Alba Iulia, Romania</td>\n      <td>01/04/2011</td>\n      <td>-6.7</td>\n      <td>-4.5</td>\n      <td>-5.7</td>\n      <td>-7.4</td>\n      <td>87.73</td>\n      <td>NaN</td>\n      <td>7.0</td>\n      <td>14.4</td>\n      <td>...</td>\n      <td>7.4</td>\n      <td>96.6</td>\n      <td>1026.5</td>\n      <td>Mist, Light Snow, Sky Coverage Increasing, Snow</td>\n      <td>46.0709</td>\n      <td>23.5805</td>\n      <td>Alba Iulia, România</td>\n      <td>Alba Iulia, România</td>\n      <td>NaN</td>\n      <td>Overcast</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Alba Iulia, Romania</td>\n      <td>01/05/2011</td>\n      <td>-11.5</td>\n      <td>-5.0</td>\n      <td>-7.9</td>\n      <td>-10.2</td>\n      <td>83.54</td>\n      <td>NaN</td>\n      <td>8.0</td>\n      <td>15.1</td>\n      <td>...</td>\n      <td>8.1</td>\n      <td>61.1</td>\n      <td>1027.9</td>\n      <td>Mist</td>\n      <td>46.0709</td>\n      <td>23.5805</td>\n      <td>Alba Iulia, România</td>\n      <td>Alba Iulia, România</td>\n      <td>NaN</td>\n      <td>Partially cloudy</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 25 columns</p>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"df.isna().sum()","metadata":{"execution":{"iopub.status.busy":"2024-05-02T07:31:00.271582Z","iopub.execute_input":"2024-05-02T07:31:00.275884Z","iopub.status.idle":"2024-05-02T07:31:00.439498Z","shell.execute_reply.started":"2024-05-02T07:31:00.275838Z","shell.execute_reply":"2024-05-02T07:31:00.438116Z"},"trusted":true},"execution_count":3,"outputs":[{"execution_count":3,"output_type":"execute_result","data":{"text/plain":"Address                     0\nDate time                   0\nMinimum Temperature         6\nMaximum Temperature         6\nTemperature                 6\nDew Point                   7\nRelative Humidity           7\nHeat Index             130704\nWind Speed                 11\nWind Gust               27661\nWind Direction              9\nWind Chill              67887\nPrecipitation               0\nPrecipitation Cover         6\nSnow Depth              61534\nVisibility                  7\nCloud Cover                 6\nSea Level Pressure      14369\nWeather Type            30976\nLatitude                    0\nLongitude                   0\nResolved Address            0\nName                        0\nInfo                   164738\nConditions                  6\ndtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"df.drop(['Heat Index', 'Info', 'Wind Chill'], axis=1, inplace=True)","metadata":{"execution":{"iopub.status.busy":"2024-05-02T07:31:00.442969Z","iopub.execute_input":"2024-05-02T07:31:00.444388Z","iopub.status.idle":"2024-05-02T07:31:00.466363Z","shell.execute_reply.started":"2024-05-02T07:31:00.444351Z","shell.execute_reply":"2024-05-02T07:31:00.465263Z"},"trusted":true},"execution_count":4,"outputs":[]},{"cell_type":"code","source":"df.dropna(inplace=True)","metadata":{"execution":{"iopub.status.busy":"2024-05-02T07:31:00.468172Z","iopub.execute_input":"2024-05-02T07:31:00.468842Z","iopub.status.idle":"2024-05-02T07:31:00.598997Z","shell.execute_reply.started":"2024-05-02T07:31:00.468799Z","shell.execute_reply":"2024-05-02T07:31:00.597558Z"},"trusted":true},"execution_count":5,"outputs":[]},{"cell_type":"code","source":"df.shape","metadata":{"execution":{"iopub.status.busy":"2024-05-02T07:31:00.600422Z","iopub.execute_input":"2024-05-02T07:31:00.600781Z","iopub.status.idle":"2024-05-02T07:31:00.607758Z","shell.execute_reply.started":"2024-05-02T07:31:00.600751Z","shell.execute_reply":"2024-05-02T07:31:00.606857Z"},"trusted":true},"execution_count":6,"outputs":[{"execution_count":6,"output_type":"execute_result","data":{"text/plain":"(63227, 22)"},"metadata":{}}]},{"cell_type":"code","source":"df.isna().sum()","metadata":{"execution":{"iopub.status.busy":"2024-05-02T07:31:00.609276Z","iopub.execute_input":"2024-05-02T07:31:00.609769Z","iopub.status.idle":"2024-05-02T07:31:00.666425Z","shell.execute_reply.started":"2024-05-02T07:31:00.609741Z","shell.execute_reply":"2024-05-02T07:31:00.665135Z"},"trusted":true},"execution_count":7,"outputs":[{"execution_count":7,"output_type":"execute_result","data":{"text/plain":"Address                0\nDate time              0\nMinimum Temperature    0\nMaximum Temperature    0\nTemperature            0\nDew Point              0\nRelative Humidity      0\nWind Speed             0\nWind Gust              0\nWind Direction         0\nPrecipitation          0\nPrecipitation Cover    0\nSnow Depth             0\nVisibility             0\nCloud Cover            0\nSea Level Pressure     0\nWeather Type           0\nLatitude               0\nLongitude              0\nResolved Address       0\nName                   0\nConditions             0\ndtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"df.duplicated().sum()","metadata":{"execution":{"iopub.status.busy":"2024-05-02T07:31:00.667825Z","iopub.execute_input":"2024-05-02T07:31:00.668195Z","iopub.status.idle":"2024-05-02T07:31:00.754669Z","shell.execute_reply.started":"2024-05-02T07:31:00.668165Z","shell.execute_reply":"2024-05-02T07:31:00.753364Z"},"trusted":true},"execution_count":8,"outputs":[{"execution_count":8,"output_type":"execute_result","data":{"text/plain":"0"},"metadata":{}}]},{"cell_type":"code","source":"df['Date time'] = pd.to_datetime(df['Date time'], format='%m/%d/%Y')","metadata":{"execution":{"iopub.status.busy":"2024-05-02T07:31:00.756210Z","iopub.execute_input":"2024-05-02T07:31:00.756584Z","iopub.status.idle":"2024-05-02T07:31:00.796361Z","shell.execute_reply.started":"2024-05-02T07:31:00.756552Z","shell.execute_reply":"2024-05-02T07:31:00.794969Z"},"trusted":true},"execution_count":9,"outputs":[]},{"cell_type":"code","source":"df['Temperature Range'] = df['Maximum Temperature'] - df['Minimum Temperature']\ndf['Day of Week'] = df['Date time'].dt.day_name()\ndf['Month'] = df['Date time'].dt.month\ndf['Year'] = df['Date time'].dt.year\ndf['Season'] = df['Date time'].dt.month%12 // 3 + 1\ndf['Season'] = df['Season'].map({1: 'Winter', 2: 'Spring', 3: 'Summer', 4: 'Fall'})","metadata":{"execution":{"iopub.status.busy":"2024-05-02T07:31:00.802169Z","iopub.execute_input":"2024-05-02T07:31:00.802771Z","iopub.status.idle":"2024-05-02T07:31:00.852060Z","shell.execute_reply.started":"2024-05-02T07:31:00.802738Z","shell.execute_reply":"2024-05-02T07:31:00.851050Z"},"trusted":true},"execution_count":10,"outputs":[]},{"cell_type":"code","source":"df['Normalized Wind Speed'] = (df['Wind Speed'] - df['Wind Speed'].mean()) / df['Wind Speed'].std()\ndf['Wind Direction Category'] = pd.cut(df['Wind Direction'], bins=[0, 90, 180, 270, 360], \n                                       labels=['North', 'East', 'South', 'West'], right=False)\n","metadata":{"execution":{"iopub.status.busy":"2024-05-02T07:31:00.853809Z","iopub.execute_input":"2024-05-02T07:31:00.854222Z","iopub.status.idle":"2024-05-02T07:31:00.873344Z","shell.execute_reply.started":"2024-05-02T07:31:00.854189Z","shell.execute_reply":"2024-05-02T07:31:00.872163Z"},"trusted":true},"execution_count":11,"outputs":[]},{"cell_type":"code","source":"common_suffix = ', România'\ndf['Resolved Address'] = df['Resolved Address'].str.replace(common_suffix, '', regex=False)\ndf['Name'] = df['Name'].str.replace(common_suffix, '', regex=False)","metadata":{"execution":{"iopub.status.busy":"2024-05-02T07:31:00.874719Z","iopub.execute_input":"2024-05-02T07:31:00.875647Z","iopub.status.idle":"2024-05-02T07:31:01.004824Z","shell.execute_reply.started":"2024-05-02T07:31:00.875614Z","shell.execute_reply":"2024-05-02T07:31:01.003558Z"},"trusted":true},"execution_count":12,"outputs":[]},{"cell_type":"code","source":"df.head()","metadata":{"execution":{"iopub.status.busy":"2024-05-02T07:31:01.006619Z","iopub.execute_input":"2024-05-02T07:31:01.007534Z","iopub.status.idle":"2024-05-02T07:31:01.044795Z","shell.execute_reply.started":"2024-05-02T07:31:01.007478Z","shell.execute_reply":"2024-05-02T07:31:01.043414Z"},"trusted":true},"execution_count":13,"outputs":[{"execution_count":13,"output_type":"execute_result","data":{"text/plain":"               Address  Date time  Minimum Temperature  Maximum Temperature  \\\n0  Alba Iulia, Romania 2011-01-01                -10.1                 -3.6   \n1  Alba Iulia, Romania 2011-01-02                 -9.0                 -1.7   \n2  Alba Iulia, Romania 2011-01-03                 -7.2                 -1.8   \n3  Alba Iulia, Romania 2011-01-04                 -6.7                 -4.5   \n4  Alba Iulia, Romania 2011-01-05                -11.5                 -5.0   \n\n   Temperature  Dew Point  Relative Humidity  Wind Speed  Wind Gust  \\\n0         -6.9       -8.2              90.62         8.9       21.6   \n1         -4.6       -6.0              89.80         8.8       14.4   \n2         -4.0       -5.0              93.01         8.7        7.2   \n3         -5.7       -7.4              87.73         7.0       14.4   \n4         -7.9      -10.2              83.54         8.0       15.1   \n\n   Wind Direction  ...  Resolved Address        Name        Conditions  \\\n0          247.43  ...        Alba Iulia  Alba Iulia  Partially cloudy   \n1          229.96  ...        Alba Iulia  Alba Iulia  Partially cloudy   \n2          241.96  ...        Alba Iulia  Alba Iulia          Overcast   \n3          221.46  ...        Alba Iulia  Alba Iulia          Overcast   \n4          116.25  ...        Alba Iulia  Alba Iulia  Partially cloudy   \n\n   Temperature Range  Day of Week  Month  Year  Season  Normalized Wind Speed  \\\n0                6.5     Saturday      1  2011  Winter              -0.879537   \n1                7.3       Sunday      1  2011  Winter              -0.891007   \n2                5.4       Monday      1  2011  Winter              -0.902477   \n3                2.2      Tuesday      1  2011  Winter              -1.097464   \n4                6.5    Wednesday      1  2011  Winter              -0.982765   \n\n  Wind Direction Category  \n0                   South  \n1                   South  \n2                   South  \n3                   South  \n4                    East  \n\n[5 rows x 29 columns]","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Address</th>\n      <th>Date time</th>\n      <th>Minimum Temperature</th>\n      <th>Maximum Temperature</th>\n      <th>Temperature</th>\n      <th>Dew Point</th>\n      <th>Relative Humidity</th>\n      <th>Wind Speed</th>\n      <th>Wind Gust</th>\n      <th>Wind Direction</th>\n      <th>...</th>\n      <th>Resolved Address</th>\n      <th>Name</th>\n      <th>Conditions</th>\n      <th>Temperature Range</th>\n      <th>Day of Week</th>\n      <th>Month</th>\n      <th>Year</th>\n      <th>Season</th>\n      <th>Normalized Wind Speed</th>\n      <th>Wind Direction Category</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Alba Iulia, Romania</td>\n      <td>2011-01-01</td>\n      <td>-10.1</td>\n      <td>-3.6</td>\n      <td>-6.9</td>\n      <td>-8.2</td>\n      <td>90.62</td>\n      <td>8.9</td>\n      <td>21.6</td>\n      <td>247.43</td>\n      <td>...</td>\n      <td>Alba Iulia</td>\n      <td>Alba Iulia</td>\n      <td>Partially cloudy</td>\n      <td>6.5</td>\n      <td>Saturday</td>\n      <td>1</td>\n      <td>2011</td>\n      <td>Winter</td>\n      <td>-0.879537</td>\n      <td>South</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Alba Iulia, Romania</td>\n      <td>2011-01-02</td>\n      <td>-9.0</td>\n      <td>-1.7</td>\n      <td>-4.6</td>\n      <td>-6.0</td>\n      <td>89.80</td>\n      <td>8.8</td>\n      <td>14.4</td>\n      <td>229.96</td>\n      <td>...</td>\n      <td>Alba Iulia</td>\n      <td>Alba Iulia</td>\n      <td>Partially cloudy</td>\n      <td>7.3</td>\n      <td>Sunday</td>\n      <td>1</td>\n      <td>2011</td>\n      <td>Winter</td>\n      <td>-0.891007</td>\n      <td>South</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Alba Iulia, Romania</td>\n      <td>2011-01-03</td>\n      <td>-7.2</td>\n      <td>-1.8</td>\n      <td>-4.0</td>\n      <td>-5.0</td>\n      <td>93.01</td>\n      <td>8.7</td>\n      <td>7.2</td>\n      <td>241.96</td>\n      <td>...</td>\n      <td>Alba Iulia</td>\n      <td>Alba Iulia</td>\n      <td>Overcast</td>\n      <td>5.4</td>\n      <td>Monday</td>\n      <td>1</td>\n      <td>2011</td>\n      <td>Winter</td>\n      <td>-0.902477</td>\n      <td>South</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Alba Iulia, Romania</td>\n      <td>2011-01-04</td>\n      <td>-6.7</td>\n      <td>-4.5</td>\n      <td>-5.7</td>\n      <td>-7.4</td>\n      <td>87.73</td>\n      <td>7.0</td>\n      <td>14.4</td>\n      <td>221.46</td>\n      <td>...</td>\n      <td>Alba Iulia</td>\n      <td>Alba Iulia</td>\n      <td>Overcast</td>\n      <td>2.2</td>\n      <td>Tuesday</td>\n      <td>1</td>\n      <td>2011</td>\n      <td>Winter</td>\n      <td>-1.097464</td>\n      <td>South</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Alba Iulia, Romania</td>\n      <td>2011-01-05</td>\n      <td>-11.5</td>\n      <td>-5.0</td>\n      <td>-7.9</td>\n      <td>-10.2</td>\n      <td>83.54</td>\n      <td>8.0</td>\n      <td>15.1</td>\n      <td>116.25</td>\n      <td>...</td>\n      <td>Alba Iulia</td>\n      <td>Alba Iulia</td>\n      <td>Partially cloudy</td>\n      <td>6.5</td>\n      <td>Wednesday</td>\n      <td>1</td>\n      <td>2011</td>\n      <td>Winter</td>\n      <td>-0.982765</td>\n      <td>East</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 29 columns</p>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"df.to_csv('cleaned_romania_weather_dataset.csv', index=False)","metadata":{"execution":{"iopub.status.busy":"2024-05-02T07:31:01.046749Z","iopub.execute_input":"2024-05-02T07:31:01.047251Z","iopub.status.idle":"2024-05-02T07:31:03.367359Z","shell.execute_reply.started":"2024-05-02T07:31:01.047211Z","shell.execute_reply":"2024-05-02T07:31:03.366208Z"},"trusted":true},"execution_count":14,"outputs":[]},{"cell_type":"code","source":"monthly_temps = df.groupby('Month')['Temperature'].mean()\n\n# Lineplot for the averae monthly temperature\nplt.figure(figsize=(10, 5))\nsns.lineplot(data=monthly_temps)\nplt.title('Average Monthly Temperature')\nplt.xlabel('Month')\nplt.ylabel('Average Temperature (°C)')\nplt.xticks(range(1, 13), ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'])\nplt.grid(True)\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-05-02T07:31:03.368880Z","iopub.execute_input":"2024-05-02T07:31:03.369235Z","iopub.status.idle":"2024-05-02T07:31:03.828827Z","shell.execute_reply.started":"2024-05-02T07:31:03.369205Z","shell.execute_reply":"2024-05-02T07:31:03.827636Z"},"trusted":true},"execution_count":15,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1000x500 with 1 Axes>","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"weather_counts = df['Weather Type'].value_counts()\n\n# Barplot for top 10 most frequent weather conditions\nplt.figure(figsize=(12, 8))\nbarplot =  sns.barplot(x=weather_counts.head(10).values, y=weather_counts.head(10).index)\nplt.title('Top 10 Weather Condition Combinations')\nplt.xlabel('Frequency')\nplt.ylabel('Weather Condition Combinations')\n\nfor p in barplot.patches:\n    width = p.get_width()    \n    plt.text(width + 3,      \n             p.get_y() + p.get_height() / 2,  \n             '{:1.0f}'.format(width),         \n             ha = 'left',   \n             va = 'center') \n\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-05-02T07:31:03.830272Z","iopub.execute_input":"2024-05-02T07:31:03.830595Z","iopub.status.idle":"2024-05-02T07:31:04.324121Z","shell.execute_reply.started":"2024-05-02T07:31:03.830568Z","shell.execute_reply":"2024-05-02T07:31:04.323141Z"},"trusted":true},"execution_count":16,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1200x800 with 1 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Densityplot of Temperature vs Relative Humidity\nplt.figure(figsize=(10, 6))\nsns.kdeplot(x=df['Temperature'], y=df['Relative Humidity'], cmap='Blues', fill=True)\nplt.title('2D Density Plot of Temperature vs. Relative Humidity')\nplt.xlabel('Temperature (°C)')\nplt.ylabel('Relative Humidity (%)')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-05-02T07:31:04.325449Z","iopub.execute_input":"2024-05-02T07:31:04.326474Z","iopub.status.idle":"2024-05-02T07:31:51.892627Z","shell.execute_reply.started":"2024-05-02T07:31:04.326441Z","shell.execute_reply":"2024-05-02T07:31:51.891580Z"},"trusted":true},"execution_count":17,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1000x600 with 1 Axes>","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"yearly_visibility = df.groupby('Year')['Visibility'].mean().reset_index()\n# Barplot for the average yearly visibility\nplt.figure(figsize=(10, 5))\nsns.barplot(x='Year', y='Visibility', data=yearly_visibility)\nplt.title('Average Yearly Visibility')\nplt.xlabel('Year')\nplt.ylabel('Average Visibility (km)')\nplt.xticks(rotation=45) \nplt.grid(True)\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-05-02T07:31:51.894010Z","iopub.execute_input":"2024-05-02T07:31:51.894376Z","iopub.status.idle":"2024-05-02T07:31:52.248252Z","shell.execute_reply.started":"2024-05-02T07:31:51.894348Z","shell.execute_reply":"2024-05-02T07:31:52.247101Z"},"trusted":true},"execution_count":18,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1000x500 with 1 Axes>","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}