text: 
  """
  Examples of deriv_data.
  
  One example with GMAG variables, and one example with sinx variable.
  
  """
  import numpy as np
  import pytplot
  import pyspedas
  from pyspedas.analysis.deriv_data import deriv_data
  
  
  def ex_deriv():
      """Find the derivative of a GMAG variable."""
      # Derivative of data
      pytplot.del_data()
  
      # Define a time rage as a list
      trange = ['2007-03-23', '2007-03-23']
  
      # Download gmag files and load data into pytplot variables
      sites = ['ccnv']
      var = 'thg_mag_ccnv'
      pyspedas.themis.gmag(sites=sites, trange=trange, varnames=[var])
      # pytplot.tplot_options('title', 'GMAG data, thg_mag_ccnv 2007-03-23')
      pyspedas.subtract_average(var, median=1)
      var += '-m'
  
      # Five minute average
      deriv_data(var)
      # pytplot.options(var, 'ytitle', var)
      # pytplot.options(var + '-der', 'ytitle', var + '-der')
      pytplot.tplot([var, var + '-der'])
  
      # Return 1 as indication that the example finished without problems.
      return 1
  
  
  def ex_deriv2():
      """Find the derivative of sinx."""
      # Delete any existing pytplot variables
      pytplot.del_data()
  
      # Create a sin wave plot
      a = list(range(0, 101))
      b = [2.0 / 100.0 * np.pi * s for s in a]
      c = pyspedas.time_float('2017-01-01')
      x = list()
      y = list()
      for i in range(len(b)):
          x.append(c + 60.0 / (2 * np.pi) * 60.0 * b[i])
          y.append(1000.0 * np.sin(b[i]))
  
      # Store data
      pytplot.store_data('sinx', data={'x': x, 'y': y})
  
      var = 'sinx'
      deriv_data(var)
      pytplot.tplot([var, var + '-der'])
  
      return 1
  
  
  # Run the example code
  # ex_deriv()
  