ts6_datetime_format_Timestamp_NaN NaT NA None_tz_localize_convert_Holidays_CustomBusinessHour_offset

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分类专栏： pythonForFinance2 文章标签： python

于 2023-02-20 19:00:49 首次发布

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本章节主要介绍了如何在Python中使用pandas库进行时间序列数据的日期时间处理。内容涵盖使用DateTimeIndex、Unix纪元时间戳、时间差、时区转换、日期偏移量（如节假日、交易日）以及自定义工作日的处理。通过pandas的Timestamp、Timedelta、Period和DateOffset等类，你可以将各种日期时间格式转换为DatetimeIndex，方便进行高效的时间序列操作。此外，还讨论了如何处理节假日，包括使用内置的USFederalHolidayCalendar和创建自定义假日。

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At the core of time-series data is time. Time-series data is a sequence of observations or data points captured in successive order. In the context of a DataFrame, time-series data has an ordered index type DatetimeIndex as you have seen in earlier chapters.

Being familiar with manipulating date and time in time-series data is an essential component of time series analysis and modeling. In this chapter, you will find recipes for common scenarios when working with date and time in time-series data.

Python has several built-in modules for working with