pd.DataFrame.where

pandas.DataFrame.where(cond, other=np.nan, inplace=False, axis=1, level=None, errors='raise', try_cast=NoDefault.no_default)

Supported Arguments

• cond: Boolean DataFrame, Boolean Series, Boolean Array
  • If 1-dimensional array or Series is provided, equivalent to Pandas df.where with axis=1.
• other: Scalar, DataFrame, Series, 1 or 2-D Array, None
  • Data types in other must match corresponding entries in DataFrame.
  • None or omitting argument defaults to the respective NA value for each type.

Note

DataFrame can contain categorical data if other is a scalar.

Example Usage

>>> @bodo.jit
... def f(df, cond, other):
...   return df.where(cond, other)
>>> df = pd.DataFrame({"A": [1,2,3], "B": [4.3, 2.4, 1.2]})
>>> cond = df > 2
>>> other = df + 100
>>> f(df, cond, other)
     A      B
0  101    4.3
1  102    2.4
2    3  101.2