1.匯入三方庫

1 import numpy as np
2 import pandas as pd
3 df = pd.read_csv('table.csv',index_col='ID') #用來指定表格的索引值
4 ​
5 df.head(2)

2.索引

1）loc：標籤索引；遵循左閉右閉

a）單行索引

1 df.loc[1103]

School          S_1
Class           C_1
Gender            M
Address    street_2
Height          186
Weight           82
Math           87.2
Physics          B+
Name: 1103, dtype: object

b）多行索引

1 df.loc[[1101,1105,1204,1301]]

1 df.loc[1103:1203]

c）單列索引

1 df.loc[:,'Weight'].head(3)

ID
1101    63
1102    73
1103    82
Name: Weight, dtype: int64

d）多列索引

1 df.loc[:,['Address','Height','Math']].head()

d）綜合索引

1 df.loc[1102:2301,['Address','Height','Math']].head()

2）iloc：位置索引；遵循左閉右開

a）單行索引

1 df.head(9)

1 df.iloc[2]

School          S_1
Class           C_1
Gender            M
Address    street_2
Height          186
Weight           82
Math           87.2
Physics          B+
Name: 1103, dtype: object

b）多行索引

1 df.iloc[2:6]

c）單例索引

1 df.iloc[:,4].head(3)

ID
1101    173
1102    192
1103    186
Name: Height, dtype: int64

d）多列索引

1 df.iloc[:,7::-2].head(3)

e）綜合索引

1 df.iloc[2:6,7::-2].head(3)

3.常用索引函式

a）where函式 對條件為False的單元進行填充

1 df.head()

1 df['Gender'].unique()
2 array(['M', 'F'], dtype=object)
3 df.where(df['Gender']=='M').head()

1 aa = df.where(df['Gender']=='M').dropna().head()
2 #意思是：在通過以上的操作，刪除掉單元格中不滿足條件的行，或提取出篩選後的新陣列
3 #mask對條件為True的單元進行填充
4 aa