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, dict, or Series

Value to use to fill holes (e.g. 0), alternately a dict/Series of values specifying which value to use for each index (for a Series) or column (for a DataFrame). (values not in the dict/Series 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 in place. Note: this will modify any other views on this object, (e.g. a no-copy slice for a column in a DataFrame).

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, or the string ‘infer’ which will try to downcast to an appropriate equal type (e.g. float64 to int64 if possible)

Returns :

filled : same type as caller

See also

reindex, asfreq