code: def net(f, c="close", o=1):
      r"""Calculate the net change of a given column.
  
      Parameters
      ----------
      f : pandas.DataFrame
          Dataframe containing the column ``c``.
      c : str
          Name of the column in the dataframe ``f``.
      o : int, optional
          Offset value for shifting the series.
  
      Returns
      -------
      new_column : pandas.Series (float)
          The array containing the new feature.
  
      References
      ----------
      *Net change is the difference between the closing price of a security
      on the day's trading and the previous day's closing price. Net change
      can be positive or negative and is quoted in terms of dollars* [IP_NET]_.
  
      .. [IP_NET] http://www.investopedia.com/terms/n/netchange.asp
  
      """
      new_column = f[c] - f[c].shift(o)
      return new_column
  
imports: from alphapy.calendrical import biz_day_month
  from alphapy.calendrical import biz_day_week
  from alphapy.globals import NULLTEXT
  from alphapy.globals import BSEP, PSEP, USEP
  from alphapy.variables import vexec
  import itertools
  import logging
  import math
  import numpy
  import pandas
label_desc: Use image node_id 32 for calling a global function with example usage: net(f, c, o) and returns: new_column