AttributeError: 'DataFrameGroupBy' object has no attribute 'parallel_apply'

[beyondguo]

General

• Operating System: ubuntu
• Python version: 3.8
• Pandas version: 2.0.3
• Pandarallel version: 1.6.5

Acknowledgement

• [ *] My issue is NOT present when using pandas without alone (without pandarallel)
• [ *] If I am on Windows, I read the Troubleshooting page
  before writing a new bug report

Bug description

sentiment_df.groupby('scode').parallel_apply(lambda x: x['f'].rolling(window=window_size, min_periods=1).apply(func, raw=True))

Observed behavior

AttributeError: 'DataFrameGroupBy' object has no attribute 'parallel_apply'
Write here the observed behavior

Expected behavior

Write here the expected behavior

Minimal but working code sample to ease bug fix for pandarallel team

[nalepae]

Pandaral·lel is looking for a maintainer!
If you are interested, please open an GitHub issue.

[shermansiu]

I typed up the above code example.

import pandas as pd
import time
from pandarallel import pandarallel
import math
import numpy as np

df_size = int(3e7)
df = pd.DataFrame(dict(a=np.random.randint(1, 1000, df_size),
                       b=np.random.rand(df_size)))

def func(df):
    dum = 0
    for item in df.b:
        dum += math.log10(math.sqrt(math.exp(item**2)))
    return dum / len(df.b)

res_parallel = df.groupby("a").parallel_apply(func)

It works just fine for me.

Python: 3.10.13
Pandarallel: 1.6.5
Pandas: 2.1.0

[rmonstein]

I have the same issue as described above. If I run the example of @shermansiu, I get the error

AttributeError: 'DataFrameGroupBy' object has no attribute 'parallel_apply'

Python: 3.11.7
Pandarallel: 1.6.5
Pandas: 2.2.2

Any idea on how to fix this issue?