python - pandas value_counts applied to each column -


I have a dataframe Many of them have no value at the CSV file, or they always have the same, in this way, I have to see value_counts for each column quickly, how can I do this?

For example 

  id, temporary, name 1 34, blank, mark 2 22, blank, mark 3 34, blank, number  
     
  •  ID: & gt; 2, 22 - & gt; 1  
  •  Temporary: Blank - & gt; 3  
  •  Name: Symbol - & gt; 3   
     So I would know that the temp is irrelevant and the name is not interesting (always the same)   
     
     
      df = pd.DataFrame (data = [[34, 'null', 'mark'], [22, 'null', 'mark'], [34, 'blank  / pre> 
     The following code:  
      
      in df.column: print "----% s ---"% c print df [c] .value_counts ()   
     will generate the following results :  
      ---- ID --- 34 2 22 1 dtype: int64 ---- temp --- null 3 dtype: int64 ---- name --- Icon 3 dtype: int64

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