建立测试数据集:
import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3], 'b': ['a', 'b', 'c'],'c': ["A","B","C"]})
print(df)
a b c
0 1 a A
1 2 b B
2 3 c C
print(df.loc[1,:])
a 2
b b
c B
Name: 1, dtype: object
print(df.loc[1:2,:])#选择1:2行,slice为1
a b c
1 2 b B
2 3 c C
print(df.loc[::-1,:])#选择所有行,slice为-1,所以为倒序
a b c
2 3 c C
1 2 b B
0 1 a A
print(df.loc[0:2:2,:])#选择0至2行,slice为2,等同于print(df.loc[0:2:2,:])因为只有3行
a b c
0 1 a A
2 3 c C
df.loc[3,:]=4
a b c
0 1.0 a A
1 2.0 b B
2 3.0 c C
3 4.0 4 4
df.loc[[1,2],:]=df.loc[[2,1],:].values
a b c
0 1 a A
1 3 c C
2 2 b B
df.drop(0,axis=0,inplace=True)
print(df)
a b c
1 2 b B
2 3 c C
print(df.loc[:,"a"])
0 1
1 2
2 3
Name: a, dtype: int64
print(df.loc[:,"a":"b"])
a b
0 1 a
1 2 b
2 3 c
df.loc[:,"d"]=4
a b c d
0 1 a A 4
1 2 b B 4
2 3 c C 4
df.loc[:,['b', 'a']] = df.loc[:,['a', 'b']].values
print(df)
a b c
0 a 1 A
1 b 2 B
2 c 3 C
1)直接del DF[‘column-name’]
2)采用drop方法,有下面三种等价的表达式:
- DF= DF.drop(‘column_name’, 1);
- DF.drop(‘column_name’,axis=1, inplace=True)
- DF.drop([DF.columns[[0,1,]]], axis=1,inplace=True
Original: https://blog.csdn.net/MaoZhihang/article/details/126739092
Author: 烈日松饼
Title: 【Pandas学习】行列切片、索引、添加、交换和删除操作
原创文章受到原创版权保护。转载请注明出处:https://www.johngo689.com/751833/
转载文章受原作者版权保护。转载请注明原作者出处!