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# pandas.Series.fillna

`Series.``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`

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