在Pandas数据框中的多个条件下删除行 [英] Drop rows on multiple conditions in pandas dataframe

问题描述

我的df有3列

df = pd.DataFrame({"col_1": (0.0, 0.0, 1.0, 1.0, 0.0, 1.0, 1.0), 
                   "col_2": (0.0, 0.24, 1.0, 0.0, 0.22, 3.11, 0.0),
                    "col_3": ("Mon", "Tue", "Thu", "Fri", "Mon", "Tue", "Thu")}) 

我想删除df.col_1为1.0且df.col_2为0.0的行.所以，我会得到:

I want to drop rows where df.col_1 is 1.0 and df.col_2 is 0.0. So, I would get:

df = pd.DataFrame({"col_1": (0.0, 0.0, 1.0, 0.0, 1.0), 
                   "col_2": (0.0, 0.24, 1.0, 0.22, 3.11),
                    "col_3": ("Mon", "Tue", "Thu", "Mon", "Tue")})

我尝试过:

df_new = df.drop[df[(df['col_1'] == 1.0) & (df['col_2'] == 0.0)].index]

它给了我错误:

'method' object is not subscriptable

有什么办法解决上述问题吗?

Any idea how to solve the above problem?

推荐答案

drop is a method, you are calling it using [], that is why it gives you:

'method' object is not subscriptable

更改为()(常规方法调用)，它应该可以工作:

change to () (a normal method call) an it should work:

import pandas as pd

df = pd.DataFrame({"col_1": (0.0, 0.0, 1.0, 1.0, 0.0, 1.0, 1.0),
                   "col_2": (0.0, 0.24, 1.0, 0.0, 0.22, 3.11, 0.0),
                   "col_3": ("Mon", "Tue", "Thu", "Fri", "Mon", "Tue", "Thu")})

df_new = df.drop(df[(df['col_1'] == 1.0) & (df['col_2'] == 0.0)].index)
print(df_new)

输出

   col_1  col_2 col_3
0    0.0   0.00   Mon
1    0.0   0.24   Tue
2    1.0   1.00   Thu
4    0.0   0.22   Mon
5    1.0   3.11   Tue

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