title: Updating part of column in Pandas data frame with a Numpy array
body: <p>I have data in a format close to that of df (shown below). My problem now is that I want to populate the data in <strong>avg_value</strong> with the average value for the past "days_back" days.</p>
  
  <pre><code>import numpy as np
  import pandas as pd
  
  df = pd.DataFrame({ 'DAY': np.append(np.ones(24),
                                   [np.multiply(np.ones(24), 2),
                                    np.multiply(np.ones(24), 3),
                                    np.multiply(np.ones(24), 4)]),
                  'value': np.random.randn(1, 24*4)[0],
                  'avg_value': 0.},
                  index=pd.date_range('20150101', periods=24*4, freq="H"))
  
  print(df.tail())
                       DAY  avg_value     value
  2015-01-04 19:00:00  4.0        0.0  0.685153
  2015-01-04 20:00:00  4.0        0.0  0.670713
  2015-01-04 21:00:00  4.0        0.0 -0.519541
  2015-01-04 22:00:00  4.0        0.0  0.795619
  2015-01-04 23:00:00  4.0        0.0 -0.150966
  </code></pre>
  
  <p>Coming from R, this would be an easy thing to do..
  But when I try to do</p>
  
  <pre><code>df.loc[df["DAY"] == the_day_I_want].avg_value = my_numpy_array
  </code></pre>
  
  <p>I get</p>
  
  <pre><code>A value is trying to be set on a copy of a slice from a DataFrame.
  Try using .loc[row_indexer,col_indexer] = value instead
  </code></pre>
  
  <p>So, as the good boy I am, I proceed with the following</p>
  
  <pre><code>index_row = df.loc[df["DAY"] == the_day_I_want].index
  index_col = df.columns.get_loc("avg_value")
  df.loc[index_row, index_col] = my_numpy_array
  </code></pre>
  
  <p>But I still end up with the same error! I bet there is a real easy solution to this problem but I just can't find it :/ Any help would be much appreciated!</p>