code: def gskew(x):
      interpolation = "nearest"
      median_mag = np.median(x)
      F_3_value = np.percentile(x, 3, interpolation=interpolation)
      F_97_value = np.percentile(x, 97, interpolation=interpolation)
  
      skew = (
          np.median(x[x <= F_3_value])
          + np.median(x[x >= F_97_value])
          - 2 * median_mag
      )
  
      return skew
  
imports: import pandas
  import numpy
  from statsmodels.tsa.stattools import acf, adfuller, pacf
  import itertools
  from statsmodels.tsa.ar_model import AR
  from scipy.signal import cwt, find_peaks_cwt, ricker, welch
  from scipy.stats import linregress
  import scipy.stats
  from scipy.stats import kurtosis
  from scipy.stats import skew
  import numpy
  from scipy import signal, integrate
  from scipy.interpolate import interp1d
  import math
  from statsmodels.tools.sm_exceptions import MissingDataError
  from numpy.linalg import LinAlgError
label_desc: Use image node_id 13 for calling a global function with example usage: gskew(x) and returns: skew