要创建 PeriodIndex,请使用方法。使用PeriodIndex.daysinmonth属性获取月份中的天数pandas.PeriodIndex()
首先,导入所需的库 -
import pandas as pd
创建一个 PeriodIndex 对象。PeriodIndex 是一个不可变的 ndarray,其中包含指示定期时间段的序数值。我们使用“freq”参数设置了频率 -
periodIndex = pd.PeriodIndex(['2018-07-25', '2019-10-30', '2020-11-20', '2021-09-15', '2022-03-12', '2023-06-18'], freq="D")
显示 PeriodIndex 对象 -
print("PeriodIndex...\n", periodIndex)
从 PeriodIndex 对象显示特定月份的天数 -
print("\nDays of the specific month from the PeriodIndex...\n", periodIndex.daysinmonth)
以下是代码 -
import pandas as pd # Create a PeriodIndex object # PeriodIndex is an immutable ndarray holding ordinal values indicating regular periods in time # We have set the frequency using the "freq" parameter periodIndex = pd.PeriodIndex(['2018-07-25', '2019-10-30', '2020-11-20', '2021-09-15', '2022-03-12', '2023-06-18'], freq="D") # Display PeriodIndex object print("PeriodIndex...\n", periodIndex) # Display PeriodIndex frequency print("\nPeriodIndex frequency...\n", periodIndex.freq) # Display the month number i.e. 1 = January, 2 = February ... 12 = December print("\nMonth number...\n", periodIndex.month) # Display days in the specific month from the PeriodIndex object print("\nDays of the specific month from the PeriodIndex...\n", periodIndex.daysinmonth)输出结果
这将产生以下代码 -
PeriodIndex... PeriodIndex(['2018-07-25', '2019-10-30', '2020-11-20', '2021-09-15', '2022-03-12', '2023-06-18'], dtype='period[D]') PeriodIndex frequency... <Day> Month number... Int64Index([7, 10, 11, 9, 3, 6], dtype='int64') Days of the specific month from the PeriodIndex... Int64Index([31, 31, 30, 30, 31, 30], dtype='int64')