bigframes.pandas.Series.fillna

Series.fillna(value=None) → Series

Fill NA (NULL in BigQuery) values using the specified method.

Note that empty strings '', numpy.inf, and numpy.nan are *not* considered NA values. This NA/NULL logic differs from numpy, but it is the same as BigQuery and the pandas.ArrowDtype.

Examples:

>>> s = bpd.Series(
...     pa.array([np.nan, 2, None, -1], type=pa.float64()),
...     dtype=pd.ArrowDtype(pa.float64()),
... )
>>> s
0     NaN
1     2.0
2    <NA>
3    -1.0
dtype: Float64

Replace all NA (NULL) elements with 0s.

>>> s.fillna(0)
0    NaN
1    2.0
2    0.0
3   -1.0
dtype: Float64

You can use fill values from another Series:

>>> s_fill = bpd.Series([11, 22, 33])
>>> s.fillna(s_fill)
0     NaN
1     2.0
2    33.0
3    -1.0
dtype: Float64

Parameters:

value (scalar, dict, Series, or DataFrame, default None) – Value to use to fill holes (e.g. 0).

Returns:

Object with missing values filled or None.

Return type:

bigframes.pandas.Series or None