count the frequency that a value occurs in a dataframe column

Question

I have a dataset

|category|
cat a
cat b
cat a

I\'d like to be able to return something like (showing unique values and frequency)

Answer 1

Use groupby and count:

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

Out[37]:

   a
a   
a  2
b  3
s  2

[3 rows x 1 columns]

See the online docs: https://pandas.pydata.org/pandas-docs/stable/user_guide/groupby.html

Also value_counts() as @DSM has commented, many ways to skin a cat here

In [38]:
df['a'].value_counts()

Out[38]:

b    3
a    2
s    2
dtype: int64

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]