# Time series decomposition

import statsmodels.api as sm

import matplotlib.pyplot as plt

from pylab import rcParams

rcParams['figure.figsize'] = 11, 9

decomposition = sm.tsa.seasonal_decompose(df['col'])

fig = decomposition.plot()

plt.show()

print(dir(decomposition)) # See what can be used

decomp_seasonal = decomposition.seasonal # Seasonal component

decomp_trend = decomposition.trend # Trend component

decomp_resid = decomp.resid # Residual component