源码:
1 def fillna(self, value=None, method=None, axis=None, inplace=False,
2 limit=None, downcast=None, **kwargs):
3 return super(DataFrame,
4 self).fillna(value=value, method=method, axis=axis,
5 inplace=inplace, limit=limit,
6 downcast=downcast, **kwargs)
7
8 @Appender(_shared_docs['shift'] % _shared_doc_kwargs)
method : {‘backfill’, ‘bfill’, ‘pad’, ‘ffill’, None}
method为ffill时,表示dataframe中每一列向下填充,即
1 df = pd.DataFrame( [[np.nan,2,np.nan,0],
2 [3,4,88,1],
3 [np.nan,np.nan,np.nan,5],
4 [np.nan,3,np.nan,4]],
5 columns=list('ABCD'))
6 print(df)
7 print(df.fillna(method='ffill'))
输出:
1 A B C D
2 0 NaN 2.0 NaN 0
3 1 3.0 4.0 88.0 1
4 2 NaN NaN NaN 5
5 3 NaN 3.0 NaN 4
6 A B C D
7 0 NaN 2.0 NaN 0
8 1 3.0 4.0 88.0 1
9 2 3.0 4.0 88.0 5
10 3 3.0 3.0 88.0 4
参考:https://www.cnblogs.com/sunbigdata/p/7895295.html
转载于:https://www.cnblogs.com/xxswkl/p/10831225.html