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
原文：https://www.cnblogs.com/xxswkl/p/10831225.html