title: Pandas - Split dataframe into multiple dataframes based on dates?
body: <p>I have a dataframe with multiple columns along with a date column. The date format is 12/31/15 and I have set it as a datetime object.</p>
  
  <p>I set the datetime column as the index and want to perform a regression calculation for each month of the dataframe. </p>
  
  <p>I believe the methodology to do this would be to split the dataframe into multiple dataframes based on month, store into a list of dataframes, then perform regression on each dataframe in the list. </p>
  
  <p>I have used groupby which successfully split the dataframe by month, but am unsure how to correctly convert each group in the groupby object into a dataframe to be able to run my regression function on it.</p>
  
  <p>Does anyone know how to split a dataframe into multiple dataframes based on date, or a better approach to my problem?</p>
  
  <p>Here is my code I've written so far</p>
  
  <pre><code>import pandas as pd
  import numpy as np
  import statsmodels.api as sm
  from patsy import dmatrices
  
  df = pd.read_csv('data.csv')
  df['date'] = pd.to_datetime(df['date'], format='%Y%m%d')
  df = df.set_index('date')
  
  # Group dataframe on index by month and year 
  # Groupby works, but dmatrices does not 
  for df_group in df.groupby(pd.TimeGrouper("M")):
      y,X = dmatrices('value1 ~ value2 + value3', data=df_group,      
      return_type='dataframe')
  </code></pre>