code: def softmax(s: "Series") -> "Series":
      """Take the softmax transform of the series.
  
      The softmax function transforms each element of a collection by
      computing the exponential of each element divided by the sum of the
      exponentials of all the elements.
  
      That is, if x is a one-dimensional numpy array or pandas Series:
  
      ```python
      softmax(x) = exp(x)/sum(exp(x))
      ```
  
      Examples:
          >>> import pandas as pd
          >>> import janitor
          >>> s = pd.Series([0, 1, 3], name="numbers")
          >>> s.softmax()
          0    0.042010
          1    0.114195
          2    0.843795
          Name: numbers, dtype: float64
  
      Args:
          s: Input Series.
  
      Returns:
          Transformed Series.
      """
      import pandas as pd
      import scipy
  
      return pd.Series(
          scipy.special.softmax(s), index=s.index, name=s.name
      )
  
file_path: pyjanitor/janitor/math.py
imports: import warnings
  from typing import TYPE_CHECKING, Tuple
  import pandas_flavor
label_desc: Use image node_id 4 for calling a global function with example usage: softmax(s) and returns: pd