How Can I Count the Frequency of Values in a Pandas DataFrame Column?

Counting Frequency of Values in Dataframe Columns

Given a dataframe with a column containing categorical values, you may encounter the need to count the frequency of occurrence of each unique value.

Consider the following dataframe:

category
cat a
cat b
cat a

To retrieve the distinct values and their corresponding frequencies, follow these steps:

Using value_counts()

As suggested by @DSM, utilize value_counts() to accomplish this task:

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

Output:

b    3
a    2
s    2
dtype: int64

Using groupby() and count()

Alternatively, you can employ groupby() and count():

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

Output:

   a
a   
a  2
b  3
s  2

[3 rows x 1 columns]

Additional Options:

For further insight, refer to the pandas documentation at https://pandas.pydata.org.

Incorporating Frequency Back into the Dataframe

If you wish to add the frequency values back to the original dataframe, you can utilize transform() with count():

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

Output:

   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]

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