pandas 菲娜模式 [英] Pandas Fillna Mode

问题描述

我有一个数据集，其中有一个称为本国"的列，其中包含30000条记录.有些缺少以NaN表示的内容，所以我想用mode()值填充它.我写了这样的东西:

I have a data set in which there is a column known as Native Country which contain around 30000 records. Some are missing represented by NaN so I thought to fill it with mode() value. I wrote something like this:

data['Native Country'].fillna(data['Native Country'].mode(), inplace=True)

但是，当我计算缺失值时:

However when I do a count of missing values:

for col_name in data.columns: 
    print ("column:",col_name,".Missing:",sum(data[col_name].isnull()))

对于本国"列，它仍会提供相同数量的NaN值.

It is still coming up with the same number of NaN values for the column Native Country.

推荐答案

只需调用系列的第一个元素:

Just call first element of series:

data['Native Country'].fillna(data['Native Country'].mode()[0], inplace=True)

或者您也可以使用asssgnment做同样的事情:

or you can do the same with assisgnment:

data['Native Country'] = data['Native Country'].fillna(data['Native Country'].mode()[0])

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