如何在 pandas 中按索引删除行（附示例）

您可以使用以下语法按索引号从 pandas DataFrame 中删除行：

 #drop first row from DataFrame
df = df. drop (index= 0 )

您可以使用以下语法按索引号从 pandas DataFrame 中删除多行：

 #drop first, second, and fourth row from DataFrame
df = df. drop ( index=[0,1,3 ] )

如果您的 DataFrame 将字符串作为索引值，您只需将名称作为字符串传递即可删除：

 df = df. drop (index=[' first ', ' second ', ' third '])

以下示例展示了实际中如何通过索引删除行。

示例1：按索引删除行

以下代码显示如何删除 pandas DataFrame 中的第二行：

 import pandas as pd

#createDataFrame
df = pd. DataFrame ({' team ': ['Mavs', 'Lakers', 'Spurs', 'Cavs'],
                   ' first ': ['Dirk', 'Kobe', 'Tim', 'Lebron'],
                   ' last ': ['Nowitzki', 'Bryant', 'Duncan', 'James'],
                   ' points ': [26, 31, 22, 29]})

#view DataFrame
df

team first last points
0 Mavs Dirk Nowitzki 26
1 Lakers Kobe Bryant 31
2 Spurs Tim Duncan 22
3 Cavs LeBron James 29

#drop second row from DataFrame
df = df. drop (index= 1 ) 

#view resulting dataFrame
df

        team first last points
0 Mavs Dirk Nowitzki 26
2 Spurs Tim Duncan 22
3 Cavs LeBron James 29

示例2：通过索引删除多行

以下代码显示了如何按索引删除 pandas DataFrame 中的多行：

 import pandas as pd

#createDataFrame
df = pd. DataFrame ({' team ': ['Mavs', 'Lakers', 'Spurs', 'Cavs'],
                   ' first ': ['Dirk', 'Kobe', 'Tim', 'Lebron'],
                   ' last ': ['Nowitzki', 'Bryant', 'Duncan', 'James'],
                   ' points ': [26, 31, 22, 29]})

#view DataFrame
df

team first last points
0 Mavs Dirk Nowitzki 26
1 Lakers Kobe Bryant 31
2 Spurs Tim Duncan 22
3 Cavs LeBron James 29

#drop first, second, and fourth row from DataFrame
df = df. drop ( index=[0,1,3 ] ) 

#view resulting dataFrame
df

	team first last points
2 Spurs Tim Duncan 22

示例 3：当索引为字符串时删除行

以下代码显示了当索引是字符串而不是数字时如何通过索引从 pandas DataFrame 中删除行：

 import pandas as pd

#createDataFrame
df = pd. DataFrame ({' team ': ['Mavs', 'Lakers', 'Spurs', 'Cavs'],
                   ' last ': ['Nowitzki', 'Bryant', 'Duncan', 'James'],
                   ' last ': ['Nowitzki', 'Bryant', 'Duncan', 'James'],
                   ' points ': [26, 31, 22, 29]},
                   index=['A', 'B', 'C', 'D'])

#view DataFrame
df
team first last points
A Mavs Dirk Nowitzki 26
B Lakers Kobe Bryant 31
C Spurs Tim Duncan 22
D Cavs Lebron James 29

#remove rows with index values 'A' and 'C'
df = df. drop (index=[' A ',' C '])

#view resulting DataFrame
df

team first last points
B Lakers Kobe Bryant 31
D Cavs Lebron James 29

其他资源

如何在 Pandas 中按索引删除列
Pandas：如何删除包含特定字符串的行
Pandas：如何删除重复行