pandas.Series.map — pandas 3.0.0.dev0+2177.g8a1d5a06f9 documentation (original) (raw)

Series.map(func=None, na_action=None, engine=None, **kwargs)[source]#

Map values of Series according to an input mapping or function.

Used for substituting each value in a Series with another value, that may be derived from a function, a dict or a Series.

Parameters:

funcfunction, collections.abc.Mapping subclass or Series

Function or mapping correspondence.

na_action{None, ‘ignore’}, default None

If ‘ignore’, propagate NaN values, without passing them to the mapping correspondence.

enginedecorator, optional

Choose the execution engine to use to run the function. Only used for functions. If map is called with a mapping or Series, an exception will be raised. If engine is not provided the function will be executed by the regular Python interpreter.

Options include JIT compilers such as Numba, Bodo or Blosc2, which in some cases can speed up the execution. To use an executor you can provide the decorators numba.jit, numba.njit, bodo.jit or blosc2.jit. You can also provide the decorator with parameters, likenumba.jit(nogit=True).

Not all functions can be executed with all execution engines. In general, JIT compilers will require type stability in the function (no variable should change data type during the execution). And not all pandas and NumPy APIs are supported. Check the engine documentation for limitations.

Added in version 3.0.0.

**kwargs

Additional keyword arguments to pass as keywords arguments toarg.

Added in version 3.0.0.

Returns:

Series

Same index as caller.

Notes

When arg is a dictionary, values in Series that are not in the dictionary (as keys) are converted to NaN. However, if the dictionary is a dict subclass that defines __missing__ (i.e. provides a method for default values), then this default is used rather than NaN.

Examples

s = pd.Series(["cat", "dog", np.nan, "rabbit"]) s 0 cat 1 dog 2 NaN 3 rabbit dtype: object

map accepts a dict or a Series. Values that are not found in the dict are converted to NaN, unless the dict has a default value (e.g. defaultdict):

s.map({"cat": "kitten", "dog": "puppy"}) 0 kitten 1 puppy 2 NaN 3 NaN dtype: object

It also accepts a function:

s.map("I am a {}".format) 0 I am a cat 1 I am a dog 2 I am a nan 3 I am a rabbit dtype: object

To avoid applying the function to missing values (and keep them asNaN) na_action='ignore' can be used:

s.map("I am a {}".format, na_action="ignore") 0 I am a cat 1 I am a dog 2 NaN 3 I am a rabbit dtype: object