[Python] unexpected content after groupby on a dataframe restored from partitioned parquet with filters

import numpy as np
import os
import pandas as pd  # 1.3.4
import pyarrow as pa  # 6.0.1
import random
import shutil
import string
import tempfile

from datetime import datetime, timedelta

if __name__ == '__main__':
    # 1. generate random data frame
    day_count = 5
    data_length = 10

    numpy_random_gen = np.random.default_rng()
    label_choices = [''.join(random.choices(string.ascii_uppercase + string.digits, k=8)) for _ in range(5)]
    partial_dfs = []

    start_date = datetime.today().date() - timedelta(days=day_count)
    for date in (start_date + timedelta(n) for n in range(day_count)):
        date_array = pd.to_datetime(np.full(data_length, date)).date

        label_array = np.full(data_length, [random.choice(label_choices) for _ in range(data_length)])

        value_array = numpy_random_gen.integers(low=1, high=500, size=data_length)

        partial_dfs.append(pd.DataFrame(data={'date': date_array, 'label': label_array, 'value': value_array}))

    df = pd.concat(partial_dfs, ignore_index=True)
    print(f"Unique dates before restore:\n{df.drop_duplicates(subset='date')['date']}")

    # 2. persist data frame partitioned by date
    dataset_dir = tempfile.mkdtemp()

    df.to_parquet(path=dataset_dir, engine='pyarrow', partition_cols=['date', 'label'])

    # 3. restore from parquet partitioned dataset
    restored_df = pd.read_parquet(dataset_dir, engine='pyarrow', filters=[
        ('date', '=', str(start_date))], use_legacy_dataset=False)
    print(f"Unique dates after restore:\n{restored_df.drop_duplicates(subset='date')['date']}")

    group_by_df = restored_df.groupby(by=['date', 'label'])['value'].sum().reset_index(name='val_sum')
    print(group_by_df)

    shutil.rmtree(dataset_dir) 

    group_by_df = restored_df.groupby(by=['date', 'label'])['value'].sum().reset_index(name='val_sum')
    print(group_by_df)