bigframes.pandas.DataFrame.combine

DataFrame.combine(other: DataFrame, func: Callable[[Series, Series], Series], fill_value=None, overwrite: bool = True, *, how: str = 'outer') → DataFrame

Perform column-wise combine with another DataFrame.

Combines a DataFrame with other DataFrame using func to element-wise combine columns. The row and column indexes of the resulting DataFrame will be the union of the two.

Examples:

>>> df1 = bpd.DataFrame({'A': [0, 0], 'B': [4, 4]})
>>> df2 = bpd.DataFrame({'A': [1, 1], 'B': [3, 3]})
>>> take_smaller = lambda s1, s2: s1 if s1.sum() < s2.sum() else s2
>>> df1.combine(df2, take_smaller)
   A  B
0  0  3
1  0  3

[2 rows x 2 columns]

Parameters:

• other (DataFrame) – The DataFrame to merge column-wise.

• func (function) – Function that takes two series as inputs and return a Series or a scalar. Used to merge the two dataframes column by columns.

• fill_value (scalar value, default None) – The value to fill NaNs with prior to passing any column to the merge func.

• overwrite (bool, default True) – If True, columns in self that do not exist in other will be overwritten with NaNs.

Returns:

Combination of the provided DataFrames.

Return type:

bigframes.pandas.DataFrame

Raises:

ValueError – If func return value is not Series.