删除Pandas数据框中的NaN/NULL列? [英] Remove NaN/NULL columns in a Pandas dataframe?

问题描述

我在熊猫中有一个dataFrame，并且其中几列的值均为空.有内置的功能可以让我删除那些列吗?

I have a dataFrame in pandas and several of the columns have all null values. Is there a built in function which will let me remove those columns?

推荐答案

是的，dropna.参见 http://pandas.pydata.org/pandas-docs/stable/missing_data.html 和DataFrame.dropna文档字符串:

Yes, dropna. See http://pandas.pydata.org/pandas-docs/stable/missing_data.html and the DataFrame.dropna docstring:

Definition: DataFrame.dropna(self, axis=0, how='any', thresh=None, subset=None)
Docstring:
Return object with labels on given axis omitted where alternately any
or all of the data are missing

Parameters
----------
axis : {0, 1}
how : {'any', 'all'}
    any : if any NA values are present, drop that label
    all : if all values are NA, drop that label
thresh : int, default None
    int value : require that many non-NA values
subset : array-like
    Labels along other axis to consider, e.g. if you are dropping rows
    these would be a list of columns to include

Returns
-------
dropped : DataFrame

要运行的特定命令为:

df=df.dropna(axis=1,how='all')

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