code: def diff(series, k_diff=1, k_seasonal_diff=None, seasonal_periods=1):
      r"""
      Difference a series simply and/or seasonally along the zero-th axis.
  
      Given a series (denoted :math:`y_t`), performs the differencing operation
  
      .. math::
  
          \Delta^d \Delta_s^D y_t
  
      where :math:`d =` `diff`, :math:`s =` `seasonal_periods`,
      :math:`D =` `seasonal\_diff`, and :math:`\Delta` is the difference
      operator.
  
      Parameters
      ----------
      series : array_like
          The series to be differenced.
      k_diff : int, optional
          The number of simple differences to perform. Default is 1.
      k_seasonal_diff : int or None, optional
          The number of seasonal differences to perform. Default is no seasonal
          differencing.
      seasonal_periods : int, optional
          The seasonal lag. Default is 1. Unused if there is no seasonal
          differencing.
  
      Returns
      -------
      differenced : ndarray
          The differenced array.
      """
      pandas = _is_using_pandas(series, None)
      differenced = np.asanyarray(series) if not pandas else series
  
      # Seasonal differencing
      if k_seasonal_diff is not None:
          while k_seasonal_diff > 0:
              if not pandas:
                  differenced = (
                      differenced[seasonal_periods:]
                      - differenced[:-seasonal_periods]
                  )
              else:
                  sdiffed = differenced.diff(seasonal_periods)
                  differenced = sdiffed[seasonal_periods:]
              k_seasonal_diff -= 1
  
      # Simple differencing
      if not pandas:
          differenced = np.diff(differenced, k_diff, axis=0)
      else:
          while k_diff > 0:
              differenced = differenced.diff()[1:]
              k_diff -= 1
      return differenced
  
imports: import numpy
  from scipy.linalg import solve_sylvester
  import pandas
  from statsmodels.compat.pandas import Appender
  from statsmodels.tools.data import _is_using_pandas
  from scipy.linalg.blas import find_best_blas_type
  from .None import _initialization, _representation, _kalman_filter, _kalman_smoother, _simulation_smoother, _cfa_simulation_smoother, _tools
label_desc: Use image node_id 3 for calling a global function with example usage: diff(series, k_diff, k_seasonal_diff, seasonal_periods) and returns: differenced