导入
导入数据
导入并初步查看地理空间数据。
MoscowMcD.csv 文件
| Store | lat | long |
|---|---|---|
| StoreA | 55.8335718446519 | 37.64083664695893 |
| StoreB | 55.801166340384995 | 37.8118113719255 |
| StoreC | 55.78302291327372 | 37.68066208490295 |
| StoreD | 55.76873384364866 | 37.6854686032755 |
| StoreE | 55.77916151917434 | 37.631910255695615 |
| StoreF | 55.771823816133235 | 37.6016978544967 |
| StoreG | 55.7803199775828 | 37.58590500841545 |
| StoreH | 55.79769272132777 | 37.55500596173475 |
| StoreI | 55.7416861350695 | 37.412183701521705 |
| StoreJ | 55.65655688623046 | 37.59002488130621 |
| StoreK | 55.65616951170943 | 37.74452011470974 |
| StoreL | 55.74477825112604 | 37.62367050991409 |
| StoreM | 55.76255316385133 | 37.63465683762279 |
1import pandas as pd 2df = pd.read_csv('MoscowMcD.csv') 3print(df)
1import pandas as pd 2def create_data_model(): 3 data = {} 4 data = pd.read_csv('MoscowMcD.csv') 5 return data 6print(create_data_model())
1import pandas as pd 2def create_data_model(): 3 data = {} 4 data = pd.read_csv('MoscowMcD.csv') 5 return data 6 7def main(): 8 print(create_data_model()) 9 10if __name__ == '__main__': 11 main()
DataFrame 摘要
| Store | lat | long |
|---|---|---|
| StoreA | 55.8335718446519 | 37.64083664695893 |
| StoreB | 55.801166340384995 | 37.8118113719255 |
| StoreC | 55.78302291327372 | 37.68066208490295 |
1import pandas as pd 2df = pd.read_csv('MoscowMcD.csv', encoding='UTF-8') 3print(df)
1import pandas as pd 2df = pd.read_csv('MoscowMcD.csv') 3print(df.info())
1import pandas as pd 2df = pd.read_csv('MoscowMcD.csv') 3print(len(df.columns))
1import pandas as pd 2df = pd.read_csv('MoscowMcD.csv') 3StoreB = df[df["Store"].isin(["StoreB"])] 4print(StoreB)
1import pandas as pd 2df = pd.read_csv('MoscowMcD.csv') 3StoreBIndex = df.iloc[1] 4print(StoreBIndex)