The use of pandas advanced interface DT in Python data analysis library

Series Objects and DataFrame The column data of provides cat、dt、str Three attribute interfaces （accessors）, Corresponding to classification data respectively 、 Date time data and string data , Through these interfaces, specific functions can be realized quickly , It is fast . Read today pandas The official documents summarize the following commonly used api.
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1.dt.date and dt.normalize(), They all return a date Date part , That is, only the date of . But the difference is date Back to Series yes object Type of ,normalize() Back to Series yes datetime64 Type of . Here is a simple creation dataframe.

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2.dt.year、dt.month、dt.day、dt.hour、dt.minute、dt.second、dt.week (dt.weekofyear and dt.week equally ) Return the year of the date respectively 、 month 、 Japan 、 Hours 、 branch 、 Seconds and the week of the year

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3.dt.weekday（dt.dayofweek equally ） Returns the day of the week ,0 On behalf of Monday ,6 For Sunday ,dt.weekday_name Return to the English of the day of the week .

4.dt.dayofyear Return to the day of the year ,dt.quarter Get what quarter each date is .

5.dt.is_month_start and dt.is_month_end Determine whether the date is the first or last day of each month , Can be month Switch to year and quarter Whether the corresponding judgment date is the first or last day of each year or quarter .

6.dt.is_leap_year Determine if it's a leap year

7.dt.month_name() Return the English name of the month .