Percent change using Pandera for Pandas DataFrame

Question

I have the following DataFrame. I need to do validation of balance and other numeric measures over date range. I want to check if for any group and date, the balance or other measures have changed by more than 25%. I can filter numerically using pct_change(). Is it possible to do this kind of validation in Pandera over date range?

DataFrame:

         date  id groupId  bal  num_meas1
0  2022-01-01   1      g1   10          1
1  2022-01-01   1      g1   11          1
2  2022-01-01   2      g2   12          2
3  2022-02-01   1      g1   13          3
4  2022-02-01   1      g1   14          3
5  2022-02-01   2      g2   15          4
6  2022-03-01   1      g1   16          5
7  2022-03-01   1      g1   17          5
8  2022-03-01   2      g2   20          6

Current Code:

d = {'date': ['2022-01-01', '2022-01-01', '2022-01-01', '2022-02-01', '2022-02-01', '2022-02-01', '2022-03-01', '2022-03-01', '2022-03-01'], 
     'id': [1, 1, 2, 1, 1, 2, 1, 1, 2], 
     'groupId': ['g1', 'g1', 'g2', 'g1', 'g1', 'g2', 'g1', 'g1', 'g2'], 
     'bal': [10, 11, 12, 13, 14, 15, 16, 17, 20],
     'num_meas1': [1, 1, 2, 3, 3, 4, 5, 5, 6]
    }
df = pd.DataFrame(d)
df = df.groupby(['date', 'groupId']).agg({'bal':[sum]}).reset_index()
df.columns = ['date', 'groupId', 'totalBal']
df.sort_values(['groupId','date'], inplace=True)
df['pct_change'] = df.groupby(['groupId'])['totalBal'].pct_change()
df[df['pct_change'] >= 0.25]

Output:

         date groupId  totalBal  pct_change
2  2022-02-01      g1        27    0.285714
3  2022-02-01      g2        15    0.250000
5  2022-03-01      g2        20    0.333333