完整警告为：SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy return super().drop(

解决方法

把原来类似这样的代码：

dataframe.drop('删除列', axis=1, inplace=True)

删除inplace=True，同时赋给新的变量，修改后的代码为：

df_new = dataframe.drop('删除列', axis=1)

问题解析

这样的操作时没有问题的：

import pandas as pddf = pd.DataFrame([[1, 2, 3],[2, 3, 4]])
df.drop(1, axis=1, inplace=True)

但是如果是对切片的dataframe做drop()操作同时还指定inplace=True，就会警告：

import pandas as pddf = pd.DataFrame([[1, 2, 3],[2, 3, 4]])
df[:1].drop(1, axis=1, inplace=True)

而查看df变量发现它其实没有变化

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解决Dataframe删除操作时警告：SettingWithCopyWarning:A value is trying to be set on a copy of a slice from a...

解决方法

问题解析

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