Get count of count of unique values in pandas dataframe

Question

I'm trying to get counts of unique counts of unique values for a column in pandas dataframe.

Sample data bellow:

In [3]: df = pd.DataFrame([[1, 1], [2, 1], [3, 2], [4, 3], [5, 1]], columns=['AppointmentId', 'PatientId'])

In [4]: df
Out[4]:
   AppointmentId  PatientId
0              1          1
1              2          1
2              3          2
3              4          3
4              5          1

Actual dataset has over 50000 unique values of PatientId . I want to visualize appointment count per patient, but simply grouping by PatientId and getting sizes of groups doesn't work well for plotting, because that would be 50000 bars.

For that reason I'm trying to plot how many patients had a specific number of appointments plotted, instead of plotting number of appointments against PatientId .

Based on sample data above I want to get something like this:

   AppointmentCount  PatientCount
0                 1             2
1                 3             3

I approach this by first grouping on PatientId and getting group sizes, drop PatientId , and group sizes, but I can't find a way to extract it after grouping.

In [24]: appointment_counts = df.groupby('PatientId').size()

In [25]: appointment_counts
Out[25]:
PatientId
1    3
2    1
3    1
dtype: int64

In [26]: type(appointment_counts)
Out[26]: pandas.core.series.Series

Answer 1

After your groupby adding value_counts

df.groupby('PatientId').size().value_counts()
Out[877]: 
1    2
3    1
dtype: int64

Then you can add rename

df.groupby('PatientId').size().value_counts().reset_index().rename(columns={'index':'Aid',0:'Pid'})
Out[883]: 
   Aid  Pid
0    1    2
1    3    1