count the frequency that a value occurs in a dataframe column
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)
category | freq |
cat a 2
cat b 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: http://pandas.pydata.org/pandas-docs/stable/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]
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