如何根据多个条件过滤 pandas dataframe

通常，您可能希望根据多个条件过滤 pandas DataFrame。幸运的是，使用布尔运算很容易做到这一点。

本教程提供了几个示例，介绍如何根据多种条件过滤以下 pandas DataFrame：

 import pandas as pd

#createDataFrame
df = pd.DataFrame({'team': ['A', 'A', 'B', 'B', 'C'],
                   'points': [25, 12, 15, 14, 19],
                   'assists': [5, 7, 7, 9, 12],
                   'rebounds': [11, 8, 10, 6, 6]})

#view DataFrame 
df

        team points assists rebounds
0 to 25 5 11
1 to 12 7 8
2 B 15 7 10
3 B 14 9 6
4 C 19 12 6

示例 1：使用“And”过滤多个条件

以下代码演示了如何使用and ( & ) 运算符过滤 DataFrame：

 #return only rows where points is greater than 13 and assists is greater than 7
df[(df. points > 13) & (df. assists > 7)]

        team points assists rebounds
3 B 14 9 6
4 C 19 12 6

#return only rows where team is 'A' and points is greater than or equal to 15
df[(df. team == 'A') & (df. points >= 15)]


        team points assists rebounds
0 to 25 5 11

示例 2：使用“Or”过滤多个条件

以下代码演示了如何使用或( | ) 运算符过滤 DataFrame：

 #return only rows where points is greater than 13 or assists is greater than 7
df[(df. dots > 13) | (df. assists > 7)]


        team points assists rebounds
0 to 25 5 11
2 B 15 7 10
3 B 14 9 6
4 C 19 12 6

#return only rows where team is 'A' or points is greater than or equal to 15
df[( df.team == 'A') | (df. points >= 15)]

        team points assists rebounds
0 to 25 5 11
1 to 12 7 8
2 B 15 7 10
4 C 19 12 6

示例 3：使用列表过滤多个条件

以下代码演示了如何过滤行值位于列表中的 DataFrame。

 #define a list of values
filter_list = [12, 14, 15]

#return only rows where points is in the list of values
df[df. points . isin (filter_list)]

	team points assists rebounds
1 to 12 7 8
2 B 15 7 10
3 B 14 9 6

#define another list of values
filter_list2 = ['A', 'C']

#return only rows where team is in the list of values
df[df. team . isin (filter_list2)]


        team points assists rebounds
0 to 25 5 11
1 to 12 7 8
4 C 19 12 6

您可以在这里找到更多熊猫教程。