聊一聊几种日期的转换

numpy.datetime64 转为 pandas的日期格式

bond_dates =
array([‘2012-09-10T00:00:00.000000000‘, ‘2013-01-11T00:00:00.000000000‘,
       ‘2013-02-08T00:00:00.000000000‘, ‘2013-03-18T00:00:00.000000000‘,
       ‘2014-06-01T00:00:00.000000000‘, ‘2014-12-07T00:00:00.000000000‘,
       ‘2015-04-25T00:00:00.000000000‘, ‘2015-12-02T00:00:00.000000000‘,
       ‘2016-02-16T00:00:00.000000000‘, ‘2016-06-08T00:00:00.000000000‘,
       ‘2016-10-19T00:00:00.000000000‘, ‘2017-02-15T00:00:00.000000000‘,
       ‘2017-07-21T00:00:00.000000000‘, ‘2018-01-27T00:00:00.000000000‘,
       ‘2018-07-06T00:00:00.000000000‘, ‘2018-10-12T00:00:00.000000000‘,
       ‘2019-03-07T00:00:00.000000000‘, ‘2020-05-12T00:00:00.000000000‘,
       ‘2020-06-24T00:00:00.000000000‘, ‘2021-01-19T00:00:00.000000000‘,
       ‘2021-03-16T00:00:00.000000000‘, ‘2021-06-16T00:00:00.000000000‘,
       ‘2021-08-18T00:00:00.000000000‘, ‘2021-11-17T00:00:00.000000000‘,
       ‘2022-02-23T00:00:00.000000000‘], dtype=‘datetime64[ns]‘)

这种日期太长， 怎么转短一些？

import pandas as pd
pd_dates = pd.to_datetime(bond_dates)
#得到：
pd_dates
Out[1]: 
DatetimeIndex([‘2012-09-10‘, ‘2013-01-11‘, ‘2013-02-08‘, ‘2013-03-18‘,
               ‘2014-06-01‘, ‘2014-12-07‘, ‘2015-04-25‘, ‘2015-12-02‘,
               ‘2016-02-16‘, ‘2016-06-08‘, ‘2016-10-19‘, ‘2017-02-15‘,
               ‘2017-07-21‘, ‘2018-01-27‘, ‘2018-07-06‘, ‘2018-10-12‘,
               ‘2019-03-07‘, ‘2020-05-12‘, ‘2020-06-24‘, ‘2021-01-19‘,
               ‘2021-03-16‘, ‘2021-06-16‘, ‘2021-08-18‘, ‘2021-11-17‘,
               ‘2022-02-23‘],
              dtype=‘datetime64[ns]‘, freq=None)

pandas读取excel文件时指定列的格式

import pandas as pd
file_name =‘RB30A1.xlsx‘
jsh_list =pd.read_excel(file_name, dtype={‘交易编号‘:str,‘交易日期‘:datetime64},header =2)

聊一聊几种日期的转换

原文：https://www.cnblogs.com/treasury-manager/p/14179972.html