title: How to calculate frequency (freq) when using seasonal decomposition()
body: <p>I am trying to separate seasonality, trend and residual from timeseries 'XYZ.csv' (sales data collected over 2 years of time). </p>
  
  <p>[XYZ.csv contains 2 columns - date and sales. Date has been set as an index within the code.]</p>
  
  <pre><code>import pandas as pd
  
  import statsmodels.api as sm
  
  df = pd.read_csv('XYZ.csv')
  
  df.date=pd.to_datetime(df.date)
  
  df.set_index('date',inplace=True)
  
  res = sm.tsa.seasonal_decompose
  (df.colA.interpolate(),freq=?, model='additive')
  
  resplot= res.plot()
  
  observed = res.observed
  
  seasonality = res.seasonal
  </code></pre>
  
  <p>This code works fine. The only trouble is to understand how to calculate the frequency for this time series? And if there is any predefined way in which I can do it. 
  Thanks for any help/suggestions in advance! </p>