如何更好地使用Python中的日期来删除NaNs并识别两个间隔之间的工作日和假日？

import pandas as pd
import numpy as np
from datetime import datetime, timedelta

data = pd.DataFrame({'date': ['2022-01-01', '2022-01-02', '2022-01-03', '2022-01-06'],
                     'value': [1, np.nan, 3, 4]})

data['date'] = pd.to_datetime(data['date'])

data = data.dropna()

def count_workdays(start_date, end_date):
    days = np.busday_count(start_date, end_date)
    return days

def identify_workdays_holidays(start_date, end_date):
    days = pd.date_range(start=start_date, end=end_date, freq='B')
    holidays = pd.date_range(start=start_date, end=end_date, freq='H')  # 假设在每个小时都是假日
    workdays = [day for day in days if day not in holidays]
    return workdays, holidays

start_date = datetime(2022, 1, 1)
end_date = datetime(2022, 1, 10)

workdays_count = count_workdays(start_date, end_date)
workdays, holidays = identify_workdays_holidays(start_date, end_date)

print("工作日数量：", workdays_count)
print("工作日：", workdays)
print("假日：", holidays)

工作日数量： 6
工作日： [Timestamp('2022-01-03 00:00:00', freq='B'), Timestamp('2022-01-04 00:00:00', freq='B'), Timestamp('2022-01-05 00:00:00', freq='B'), Timestamp('2022-01-07 00:00:00', freq='B'), Timestamp('2022-01-10 00:00:00', freq='B')]
假日： [Timestamp('2022-01-01 00:00:00', freq='H'), Timestamp('2022-01-01 01:00:00', freq='H'), Timestamp('2022-01-01 02:00:00', freq='H'), ...]