Count frequency of values in pandas DataFrame column

Question

I want to count number of times each values is appearing in dataframe.

Here is my dataframe - df:

    status 1     N 2     N 3     C 4     N 5     S 6     N 7     N 8     S 9     N 10    N 11    N 12    S 13    N 14    C 15    N 16    N 17    N 18    N 19    S 20    N 

I want to dictionary of counts:

ex. counts = {N: 14, C:2, S:4}

I have tried df['status']['N'] but it gives keyError and also df['status'].value_counts but no use.

Answer 1

You can use value_counts and to_dict:

print df['status'].value_counts() N    14 S     4 C     2 Name: status, dtype: int64  counts = df['status'].value_counts().to_dict() print counts {'S': 4, 'C': 2, 'N': 14} 

Answer 2

An alternative one liner using underdog Counter:

In [3]: from collections import Counter  In [4]: dict(Counter(df.status)) Out[4]: {'C': 2, 'N': 14, 'S': 4}