aluguel_bike_final_v2.ipynb

{"cells":[{"metadata":{"trusted":true},"cell_type":"code","source":"import numpy as np\nimport pandas as pd","execution_count":2,"outputs":[]},{"metadata":{"trusted":true,"scrolled":true},"cell_type":"code","source":"data = pd.read_csv('bikes.csv')\ndata.head()","execution_count":12,"outputs":[{"output_type":"execute_result","execution_count":12,"data":{"text/plain":"     city      dteday  season  yr  mkt  mnth  holiday  weekday  workingday  \\\n0  city_0  2011-01-01       1   0    0     1        0        6           0   \n1  city_0  2011-01-02       1   0    0     1        0        0           0   \n2  city_0  2011-01-03       1   0    0     1        0        1           1   \n3  city_0  2011-01-04       1   0    0     1        0        2           1   \n4  city_0  2011-01-05       1   0    0     1        0        3           1   \n\n   weathersit      temp     atemp       hum  windspeed  stock   cnt  target  \n0           2  0.344167  0.363625  0.805833   0.160446    997   929  1257.0  \n1           2  0.363478  0.353739  0.696087   0.248539   1231   765  1096.0  \n2           1  0.196364  0.189405  0.437273   0.248309   1395  1395  1430.0  \n3           1  0.200000  0.212122  0.590435   0.160296   1651  1641   885.0  \n4           1  0.226957  0.229270  0.436957   0.186900   2334  1671  1210.0  ","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>city</th>\n      <th>dteday</th>\n      <th>season</th>\n      <th>yr</th>\n      <th>mkt</th>\n      <th>mnth</th>\n      <th>holiday</th>\n      <th>weekday</th>\n      <th>workingday</th>\n      <th>weathersit</th>\n      <th>temp</th>\n      <th>atemp</th>\n      <th>hum</th>\n      <th>windspeed</th>\n      <th>stock</th>\n      <th>cnt</th>\n      <th>target</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>city_0</td>\n      <td>2011-01-01</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>6</td>\n      <td>0</td>\n      <td>2</td>\n      <td>0.344167</td>\n      <td>0.363625</td>\n      <td>0.805833</td>\n      <td>0.160446</td>\n      <td>997</td>\n      <td>929</td>\n      <td>1257.0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>city_0</td>\n      <td>2011-01-02</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>2</td>\n      <td>0.363478</td>\n      <td>0.353739</td>\n      <td>0.696087</td>\n      <td>0.248539</td>\n      <td>1231</td>\n      <td>765</td>\n      <td>1096.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>city_0</td>\n      <td>2011-01-03</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>0.196364</td>\n      <td>0.189405</td>\n      <td>0.437273</td>\n      <td>0.248309</td>\n      <td>1395</td>\n      <td>1395</td>\n      <td>1430.0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>city_0</td>\n      <td>2011-01-04</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n      <td>0.200000</td>\n      <td>0.212122</td>\n      <td>0.590435</td>\n      <td>0.160296</td>\n      <td>1651</td>\n      <td>1641</td>\n      <td>885.0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>city_0</td>\n      <td>2011-01-05</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>3</td>\n      <td>1</td>\n      <td>1</td>\n      <td>0.226957</td>\n      <td>0.229270</td>\n      <td>0.436957</td>\n      <td>0.186900</td>\n      <td>2334</td>\n      <td>1671</td>\n      <td>1210.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"### Colunas existentes no csv:"},{"metadata":{"trusted":true},"cell_type":"code","source":"data.columns","execution_count":4,"outputs":[{"output_type":"execute_result","execution_count":4,"data":{"text/plain":"Index(['city', 'dteday', 'season', 'yr', 'mkt', 'mnth', 'holiday', 'weekday',\n       'workingday', 'weathersit', 'temp', 'atemp', 'hum', 'windspeed',\n       'stock', 'cnt', 'target'],\n      dtype='object')"},"metadata":{}}]},{"metadata":{"trusted":false},"cell_type":"markdown","source":"## Q1: Influência do clima na quantidade de bikes alugadas"},{"metadata":{"trusted":false},"cell_type":"markdown","source":"#### Média da quantidade de bicicletas alugadas quando o clima está ruim\nClima ruim: Pouca neve ou chuva / Tempestades / Nuvens dispersas e pouca chuva"},{"metadata":{"trusted":true},"cell_type":"code","source":"cnt_bad_weather = data[data['weathersit'] == 3][['cnt','dteday']]\ncnt_bad_weather.mean()","execution_count":17,"outputs":[{"output_type":"execute_result","execution_count":17,"data":{"text/plain":"cnt    1973.595\ndtype: float64"},"metadata":{}}]},{"metadata":{"trusted":false},"cell_type":"markdown","source":"#### Média da quantidade de bicicletas alugadas quando o clima está bom\nClima bom: Tempo limpo / Poucas nuvens / Parcialmente nublado"},{"metadata":{"trusted":true},"cell_type":"code","source":"cnt_good_weather = data[data['weathersit'] == 1][['cnt','dteday']]\ncnt_good_weather.mean()","execution_count":18,"outputs":[{"output_type":"execute_result","execution_count":18,"data":{"text/plain":"cnt    5009.506793\ndtype: float64"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"pct = (cnt_good_weather.mean() / cnt_bad_weather.mean()) - 1\npct","execution_count":23,"outputs":[{"output_type":"execute_result","execution_count":23,"data":{"text/plain":"cnt    1.538265\ndtype: float64"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"##### Conclusão Q1: A média de bicicletas alugadas quando o clima está bom é 153% maior do que quando o clima está ruim."},{"metadata":{},"cell_type":"markdown","source":"## Q2: Variação da média de bicicletas alugadas durante a semana"},{"metadata":{"trusted":true},"cell_type":"code","source":"data[data['weekday'] == 0][['weekday','cnt']].mean()","execution_count":38,"outputs":[{"output_type":"execute_result","execution_count":38,"data":{"text/plain":"weekday       0.000000\ncnt        4360.923714\ndtype: float64"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"data[data['weekday'] == 1][['weekday','cnt']].mean()","execution_count":39,"outputs":[{"output_type":"execute_result","execution_count":39,"data":{"text/plain":"weekday       1.000\ncnt        4478.692\ndtype: float64"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"data[data['weekday'] == 2][['weekday','cnt']].mean()","execution_count":40,"outputs":[{"output_type":"execute_result","execution_count":40,"data":{"text/plain":"weekday       2.000000\ncnt        4648.866058\ndtype: float64"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"data[data['weekday'] == 3][['weekday','cnt']].mean()","execution_count":41,"outputs":[{"output_type":"execute_result","execution_count":41,"data":{"text/plain":"weekday       3.000000\ncnt        4687.672163\ndtype: float64"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"data[data['weekday'] == 4][['weekday','cnt']].mean()","execution_count":42,"outputs":[{"output_type":"execute_result","execution_count":42,"data":{"text/plain":"weekday       4.00000\ncnt        4804.06101\ndtype: float64"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"data[data['weekday'] == 5][['weekday','cnt']].mean()","execution_count":43,"outputs":[{"output_type":"execute_result","execution_count":43,"data":{"text/plain":"weekday       5.000000\ncnt        4824.593077\ndtype: float64"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"data[data['weekday'] == 6][['weekday','cnt']].mean()","execution_count":44,"outputs":[{"output_type":"execute_result","execution_count":44,"data":{"text/plain":"weekday       6.000000\ncnt        4686.245048\ndtype: float64"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"valor_min = 4360.923714 \nvalor_max = 4824.593077\nvar_max_semana = valor_max - valor_min\nvar_max_semana","execution_count":46,"outputs":[{"output_type":"execute_result","execution_count":46,"data":{"text/plain":"463.6693630000009"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"##### Conclusão Q2: Há uma variação máxima de aproximadamente 464 bikes na média de bicicletas alugadas durante diferente dias da semana."},{"metadata":{},"cell_type":"markdown","source":"## Q3: Diferença da quantidade de bikes alugadas nos anos de 2011 e 2012"},{"metadata":{"trusted":false},"cell_type":"markdown","source":"#### Quantidade total de bikes alugadas nos anos de 2011 e 2012, respectivamente:"},{"metadata":{"scrolled":true,"trusted":true},"cell_type":"code","source":"total_ano1 = data[data['yr'] == 0]['cnt'].sum()\ntotal_ano1","execution_count":49,"outputs":[{"output_type":"execute_result","execution_count":49,"data":{"text/plain":"262768114"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"total_ano2 = data[data['yr'] == 1]['cnt'].sum()\ntotal_ano2","execution_count":50,"outputs":[{"output_type":"execute_result","execution_count":50,"data":{"text/plain":"415750962"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"diff = total_ano2 - total_ano1\ndiff","execution_count":52,"outputs":[{"output_type":"execute_result","execution_count":52,"data":{"text/plain":"152982848"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"##### Conclusão Q3: Houve um aumento de aproximadamente 153 milhões de bicicletas alugadas em 2012 (comparado ao ano de 2011)"}],"metadata":{"kernelspec":{"name":"python3","display_name":"Python 3","language":"python"},"language_info":{"name":"python","version":"3.6.9","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":4}