Making operations with Multindex DataFrame

Question

I have a GroupBy Data Frame that is similar to this one:

I want to create a column named PL as the difference between the Position of the same Product of the same Client buyed on the same day with the previous day’s position. Also the first dates should have PL = 0.

The dataframe should look like this

Edit:
the unstacked dataframe looks like this:

Link to original dataframe

Dataframe constructor:

data = {'Client': ['Client 1', 'Client 1', 'Client 2', 'Client 2', 'Client 1', 'Client 1', 'Client 2', 'Client 2'],
        'Position Date': ['2022-01-02', '2022-01-02', '2022-01-02', '2022-01-02', '2022-01-03', '2022-01-03', '2022-01-03', '2022-01-03'],
        'Product': ['Product 1', 'Product 4', 'Product 2', 'Product 3', 'Product 1', 'Product 4', 'Product 2', 'Product 3'],
        'Buy Date': ['2022-05-02', '2022-06-02', '2022-03-12', '2022-01-25', '2022-05-02', '2022-06-02', '2022-03-12', '2022-01-25'],
        'Position': [100, 5000, 120, 50, 150, 7000, 200, 100]}
df = pd.DataFrame(data).set_index(['Position Date', 'Client', 'Product', 'Buy Date'])

Asked By: João Weckerle

||

Source

Answer 1

You can use groupby with level as parameter of your index levels:

df['PL'] = df.groupby(level=['Client', 'Product', 'Buy Date']).diff().fillna(0)
print(df)

# Output
                                             Position      PL
Position Date Client   Product   Buy Date                    
2022-01-02    Client 1 Product 1 2022-05-02       100     0.0
                       Product 4 2022-06-02      5000     0.0
              Client 2 Product 2 2022-03-12       120     0.0
                       Product 3 2022-01-25        50     0.0
2022-01-03    Client 1 Product 1 2022-05-02       150    50.0
                       Product 4 2022-06-02      7000  2000.0
              Client 2 Product 2 2022-03-12       200    80.0
                       Product 3 2022-01-25       100    50.0

Answered By: Corralien

Making operations with Multindex DataFrame

Question:

Answers: