在 pandas 中丢弃南行的更好方法 [英] better way to drop nan rows in pandas

问题描述

我自己找到了一种从熊猫数据框中删除nan行的方法.给定具有列x且包含nan值的数据框dat，是否有更优雅的方法来删除x列中具有nan值的dat的每一行?

On my own I found a way to drop nan rows from a pandas dataframe. Given a dataframe dat with column x which contains nan values,is there a more elegant way to do drop each row of dat which has a nan value in the x column?

dat = dat[np.logical_not(np.isnan(dat.x))]
dat = dat.reset_index(drop=True)

推荐答案

使用 dropna :

dat.dropna()

如果所有标签均为nan或任何标签均为nan，则可以传递参数how删除

You can pass param how to drop if all labels are nan or any of the labels are nan

dat.dropna(how='any')    #to drop if any value in the row has a nan
dat.dropna(how='all')    #to drop if all values in the row are nan

希望能回答您的问题！

修改1: 如果您只想删除特定列中包含nan值的行(如J. Doe在下面的答案中所建议的那样)，则可以使用以下内容:

Edit 1: In case you want to drop rows containing nan values only from particular column(s), as suggested by J. Doe in his answer below, you can use the following:

dat.dropna(subset=[col_list])  # col_list is a list of column names to consider for nan values.

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