title: Change dataframes in dict
body: <p>Please help me to understand how to change dataframes in dictionary.</p>
  
  <p>Let's consider the simplest case and create two dataframes and construct the dict from them.</p>
  
  <pre><code>dates = pd.date_range('20130101',periods=6)
  df1 =pd.DataFrame(np.random.randn(6,4),index=dates,columns=list('ABCD'))
  df2 =pd.DataFrame(np.random.randn(6,4),index=dates,columns=list('ABCD'))
  DICTOR={}
  DICTOR['d1']=df1
  DICTOR['d2']=df2
  m=DICTOR
  </code></pre>
  
  <p>Now I want to exclude rows from DataFrames inside dict <code>m</code>, for example rows with where values in <code>B</code> columns are zero or negative.</p>
  
  <p>I tried following code:</p>
  
  <pre><code>for name,df in m.items():
       for index, row in df.iterrows():
           if df.at[index,'B']&lt;0:
               df.drop(index,axis=0)
  </code></pre>
  
  <p>or:</p>
  
  <pre><code>for name,df in m.items():
      df=df[df.B&gt;0]
  </code></pre>
  
  <p>but it does not work.</p>
  
  <p>I guess my problem is due to mutable/immutable objects, but i'm not sure.</p>