DataFrame.fillna(value=None, method=None, axis=0, inplace=False, limit=None, downcast=None)

Fill NA/NaN values using the specified method

Parameters :

method : {‘backfill’, ‘bfill’, ‘pad’, ‘ffill’, None}, default None

Method to use for filling holes in reindexed Series pad / ffill: propagate last valid observation forward to next valid backfill / bfill: use NEXT valid observation to fill gap

value : scalar or dict

Value to use to fill holes (e.g. 0), alternately a dict of values specifying which value to use for each column (columns not in the dict will not be filled). This value cannot be a list.

axis : {0, 1}, default 0

0: fill column-by-column 1: fill row-by-row

inplace : boolean, default False

If True, fill the DataFrame in place. Note: this will modify any other views on this DataFrame, like if you took a no-copy slice of an existing DataFrame, for example a column in a DataFrame. Returns a reference to the filled object, which is self if inplace=True

limit : int, default None

Maximum size gap to forward or backward fill

downcast : dict, default is None, a dict of item->dtype of what to

downcast if possible

Returns :

filled : DataFrame

See also

reindex, asfreq