Python Pandas - 计算在指定频率下转换为 PeriodArray 的索引值和索引之间的差异的 TimedeltaArray

要计算索引值与在指定频率下转换为PeriodArray的索引之间的差异的TimedeltaArray，请使用方法。使用freq参数设置频率。datetimeindex.to_perioddelta()

首先，导入所需的库-

import pandas as pd

创建一个日期时间索引，周期为7，频率为Y，即年份-

datetimeindex = pd.date_range(2021-10-18 07:20:32.261811624, periods=5, freq=2Y)

显示日期时间索引-

print("DateTimeIndex...\n", datetimeindex)

计算索引值与转换为PeriodArray的索引之间的差异的TimedeltaArray。我们已经使用值为“M”的“freq”参数设置了周期频率-

print("\nConvert DateTimeIndex to PeriodDelta...\n", datetimeindex.to_perioddelta(freq=M))

示例

以下是代码-

import pandas as pd #DatetimeIndexwithperiod7andfrequencyasYi.e.year #timezoneisAustralia/Adelaide datetimeindex = pd.date_range(2021-10-18 07:20:32.261811624, periods=5, freq=2Y) #displayDateTimeIndex print("DateTimeIndex...\n", datetimeindex) #displayDateTimeIndex frequency print("DateTimeIndex frequency...\n", datetimeindex.freq) #ConvertDateTimeIndextoPeriod # We have set the frequency as Month using the "freq" parameter with value M print("\nConvert DateTimeIndex to Period...\n", datetimeindex.to_period(freq=M)) #CalculateTimedeltaArrayofdifferencebetweenindexvaluesandindexconvertedtoPeriodArray # We have set the Period frequency using the "freq" parameter with value M print("\nConvert DateTimeIndex to PeriodDelta...\n", datetimeindex.to_perioddelta(freq=M))输出结果

这将产生以下代码-

DateTimeIndex... DatetimeIndex([2021-12-31 07:20:32.261811624, 2023-12-31 07:20:32.261811624, 2025-12-31 07:20:32.261811624, 2027-12-31 07:20:32.261811624, 2029-12-31 07:20:32.261811624], dtype=datetime64[ns], freq=2A-DEC) DateTimeIndex frequency... <2 * YearEnds: month=12> Convert DateTimeIndex to Period... PeriodIndex([2021-12, 2023-12, 2025-12, 2027-12, 2029-12], dtype=period[M]) Convert DateTimeIndex to PeriodDelta... TimedeltaIndex([30 days 07:20:32.261811624, 30 days 07:20:32.261811624, 30 days 07:20:32.261811624, 30 days 07:20:32.261811624, 30 days 07:20:32.261811624], dtype=timedelta64[ns], freq=None)