Python Pandas - 从 DateTimeIndex 创建一个 DataFrame 但覆盖结果列的名称

要从DateTimeIndex创建DataFrame，请使用.我们已经设置了name参数来覆盖结果列的名称。datetimeindex.to_frame()

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5，频率为S，即秒-

datetimeindex = pd.date_range(2021-10-18 07:20:32.261811624, periods=5, tz=Australia/Adelaide, freq=40S)

显示日期时间索引-

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

未使用False参数在返回的DataFrame中设置原始索引。为了覆盖结果列的名称，我们使用了name参数-

print("\nDateTimeIndex to DataFrame...\n", datetimeindex.to_frame(index=False, name = DateTimeData))

示例

以下是代码-

import pandas as pd #DatetimeIndexwithperiod5andfrequencyasSi.e.seconds #timezoneisAustralia/Adelaide datetimeindex = pd.date_range(2021-10-18 07:20:32.261811624, periods=5, tz=Australia/Adelaide, freq=40S) #displayDateTimeIndex print("DateTimeIndex...\n", datetimeindex) #displayDateTimeIndex frequency print("\nDateTimeIndex frequency...\n", datetimeindex.freq) #CreateaDataFramefromDateTimeIndex # The original index isnt set in the returned DataFrame using the False parameter # To override the name of the resulting column, we have used the name parameter print("\nDateTimeIndex to DataFrame...\n", datetimeindex.to_frame(index=False, name = DateTimeData))输出结果

这将产生以下代码-

DateTimeIndex... DatetimeIndex([2021-10-18 07:20:32.261811624+10:30, 2021-10-18 07:21:12.261811624+10:30, 2021-10-18 07:21:52.261811624+10:30, 2021-10-18 07:22:32.261811624+10:30, 2021-10-18 07:23:12.261811624+10:30], dtype=datetime64[ns, Australia/Adelaide], freq=40S) DateTimeIndex frequency... <40 * Seconds> DateTimeIndex to DataFrame... DateTimeData 0 2021-10-18 07:20:32.261811624+10:30 1 2021-10-18 07:21:12.261811624+10:30 2 2021-10-18 07:21:52.261811624+10:30 3 2021-10-18 07:22:32.261811624+10:30 4 2021-10-18 07:23:12.261811624+10:30