Count the frequency that a value occurs in a dataframe column

If you want to apply to all columns you can use:

df.apply(pd.value_counts)

This will apply a column based aggregation function (in this case value_counts) to each of the columns.

Use value_counts() as @DSM commented.

In [37]:
df = pd.DataFrame({'a':list('abssbab')})
df['a'].value_counts()

Out[37]:

b    3
a    2
s    2
dtype: int64

Also groupby and count. Many ways to skin a cat here.

In [38]:
df.groupby('a').count()

Out[38]:

   a
a   
a  2
b  3
s  2

[3 rows x 1 columns]

See the online docs.

If you wanted to add frequency back to the original dataframe use transform to return an aligned index:

In [41]:
df['freq'] = df.groupby('a')['a'].transform('count')
df

Out[41]:

   a freq
0  a    2
1  b    3
2  s    2
3  s    2
4  b    3
5  a    2
6  b    3

[7 rows x 2 columns]