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modin.pandas.Series.map

Series.map(arg: Callable | Mapping | Series, na_action: Literal['ignore'] | None = None) → Series[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:

  • arg (function, collections.abc.Mapping subclass or Series) – Mapping correspondence.

  • na_action ({None, 'ignore'}, default None) – If ‘ignore’, propagate NULL values, without passing them to the mapping correspondence. Note that, it will not bypass NaN values in a FLOAT column in Snowflake.

Returns:

Same index as caller.

Return type:

Series

See also

Series.apply : For applying more complex functions on a Series.

DataFrame.apply : Apply a function row-/column-wise.

DataFrame.applymap : Apply a function elementwise on a whole DataFrame.

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      None
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      None
3      None
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 <NA>
3    I am a rabbit
dtype: object

To avoid applying the function to missing values (and keep them as NaN) 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             None
3    I am a rabbit
dtype: object

Note that in the above example, the missing value in Snowflake is NULL, it is mapped to None in a string/object column.