code: import pandas as pd
  import matplotlib.pyplot as plt, mpld3
  import numpy as np
  import scipy.signal as sp
  import matplotlib.ticker as plticker
  df=pd.read_csv('numbers2.csv')
  df.columns=['DATE', 'EMPLOYEES']
  df.DATE=pd.to_datetime(df.DATE)
  df.EMPLOYEES=np.log(df.EMPLOYEES)
  trend=sp.savgol_filter(df.EMPLOYEES, 707, 4)
  unsp=df.EMPLOYEES-trend
  unep=abs(unsp)
  unyp=(sp.savgol_filter(unep, 707, 6))
  uns=-(unsp)*(.5/(np.log(2)-np.log(1)))
  une=abs(uns)
  uny=(sp.savgol_filter(une, 707, 6))
  unw=uns+uny-(uns+uny).min()
  fig, ax = plt.subplots()
  plt.plot(df.DATE, unw, color='blue', lw=2)
  start, end = ax.get_xlim()
  plt.xticks(np.arange(start, end, 1825.5))
  plt.xticks(rotation=90)
  axes = plt.gca()
  axes.set_ylim([unw.min(), unw.max()])
  axes.set_xlim([df.DATE.min(), df.DATE.max()])
  plt.savefig('foom.png', bbox_inches='tight')
  
apis: scipy.signal.savgol_filter matplotlib.pyplot.xticks pandas.read_csv matplotlib.pyplot.savefig matplotlib.pyplot.gca matplotlib.pyplot.subplots numpy.arange pandas.to_datetime numpy.log matplotlib.pyplot.plot