python - pandas value_counts applied to each column

Question

I have a dataframe with numerous columns (≈30) from an external source (csv file) but several of them have no value or always the same. Thus, I would to see quickly the value_counts for each column, how can i do that?

For example

  Id, temp, name
1 34, null, mark
2 22, null, mark
3 34, null, mark

Would return me an object stating that

• Id: 34 -> 2, 22 -> 1
• temp: null -> 3
• name: mark -> 3

So I would know that temp is irrelevant and name is not interesting (always the same)

Answer 1

For the dataframe,

df = pd.DataFrame(data=[[34, 'null', 'mark'], [22, 'null', 'mark'], [34, 'null', 'mark']], columns=['id', 'temp', 'name'], index=[1, 2, 3]) 

the following code

for c in df.columns:
    print "---- %s ---" % c
    print df[c].value_counts()

will produce the following result:

---- id ---
34    2
22    1
dtype: int64
---- temp ---
null    3
dtype: int64
---- name ---
mark    3
dtype: int64