title: grouping and plotting data by time in python
body: <p>I have a csv file and I am trying to plot the average of some values per month. My csv file is structured as shown below, so I believe that I should group my data daily, then monthly in order to calculate the mean value.</p>
  
  <pre><code>timestamp,heure,lat,lon,impact,type
  2007-01-01 00:00:00,13:58:43,33.837,-9.205,10.3,1
  2007-01-02 00:00:00,00:07:28,34.5293,-10.2384,17.7,1
  2007-01-02 00:00:00,23:01:03,35.0617,-1.435,-17.1,2
  2007-01-03 00:00:00,01:14:29,36.5685,0.9043,36.8,1
  2007-01-03 00:00:00,05:03:51,34.1919,-12.5061,-48.9,1
  </code></pre>
  
  <p>I am using this code:</p>
  
  <pre><code>import pandas as pd
  import seaborn as sns
  import numpy as np
  import matplotlib.pyplot as plt
  
  df= pd.read_csv("ave.txt", sep=',', names =["timestamp","heure","lat","lon","impact","type"])
  daily = df.set_index('timestamp').groupby(pd.TimeGrouper(key='timestamp', freq='D', axis=1), axis=1)['impact'].count()
  monthly = daily.groupby(pd.TimeGrouper(freq='M')).mean()
  ax = monthly.plot(kind='bar')
  plt.show()
  </code></pre>
  
  <p>But, I keep getting errors like this: </p>
  
  <blockquote>
    <p>KeyError: 'The grouper name timestamp is not found'</p>
  </blockquote>
  
  <p>any ideas ??</p>