pd.DataFrame.apply

pandas.DataFrame.apply(func, axis=0, raw=False, result_type=None, args=(), _bodo_inline=False, \**kwargs)

Supported Arguments

• func: function (e.g. lambda) (axis must = 1), jit function (axis must = 1), String which refers to a supported DataFrame method
  • Must be constant at Compile Time
• axis: Integer (0, 1), String (only if the method takes axis as an argument )
  • Must be constant at Compile Time
• _bodo_inline: boolean
  • Must be constant at Compile Time

Example Usage

>>> @bodo.jit
... def f():
...   df = pd.DataFrame({"A": [1,2,3], "B": [4,5,6], "C": [7,8,9]})
...   return df.apply(lambda x: x["A"] * (x["B"] + x["C"]))
>>> f()
0    11
1    26
2    45
dtype: int64

Note

Supports extra _bodo_inline boolean argument to manually control bodo's inlining behavior. Inlining user-defined functions (UDFs) can potentially improve performance at the expense of extra compilation time. Bodo uses heuristics to make a decision automatically if _bodo_inline is not provided.