@@ -1830,23 +1830,24 @@ def fillna(self, value=None, method=None, axis=0, inplace=False,
18301830 Method to use for filling holes in reindexed Series
18311831 pad / ffill: propagate last valid observation forward to next valid
18321832 backfill / bfill: use NEXT valid observation to fill gap
1833- value : scalar or dict
1834- Value to use to fill holes (e.g. 0), alternately a dict of values
1835- specifying which value to use for each column (columns not in the
1836- dict will not be filled). This value cannot be a list.
1833+ value : scalar, dict, or Series
1834+ Value to use to fill holes (e.g. 0), alternately a dict/Series of
1835+ values specifying which value to use for each index (for a Series) or
1836+ column (for a DataFrame). (values not in the dict/Series will not be
1837+ filled). This value cannot be a list.
18371838 axis : {0, 1}, default 0
18381839 0: fill column-by-column
18391840 1: fill row-by-row
18401841 inplace : boolean, default False
18411842 If True, fill in place. Note: this will modify any
18421843 other views on this object, (e.g. a no-copy slice for a column in a
1843- DataFrame). Still returns the object.
1844+ DataFrame).
18441845 limit : int, default None
18451846 Maximum size gap to forward or backward fill
1846- downcast : dict, default is None, a dict of item->dtype of what to
1847- downcast if possible, or the string 'infer' which will try to
1848- downcast to an appropriate equal type (e.g. float64 to int64 if
1849- possible)
1847+ downcast : dict, default is None
1848+ a dict of item->dtype of what to downcast if possible,
1849+ or the string 'infer' which will try to downcast to an appropriate
1850+ equal type (e.g. float64 to int64 if possible)
18501851
18511852 See also
18521853 --------
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