参考https://pypi.org/project/chinesecalendar/#description。 也可以直接请求节假日数据接口"""fromchinese_calendarimportis_holiday year= 2021#得到一年中所有的日期defget_whole_year(year=year): begin= datetime.date(year, 1, 1) now=begin end= datetime.date(year, 12, 31) delta= datetime.timedelta(...
在datetime中新建时间对象可以直接使用datetime(y, m,d,tzinfo)输入参数,用datetime.now()获得当前时间,通过datetime.fromtimestamp(ts)可以将时间戳ts转为时间对象,生成的datetime时间对象在获取属性时用到的语句类似dt.year,有year/month/day/hour/second/tzinfo等可以用。tzinfo是时区属性,datetime在时区相关处理时通...
),"八字":"".join([a.year8Char, a.month8Char, a.day8Char, a.twohour8Char]),"今日节气": a.todaySolarTerms,"下一节气": (a.nextSolarTerm, a.nextSolarTermDate, a.nextSolarTermYear),"今年节气表": a.thisYearSolarTermsDic,"季节": a.lunarSeason,"今日时辰": a.twohour8CharList,"时...
df['today']=datetime.date.today() 提取日期实体 ? 代码语言:javascript 代码运行次数:0 运行 AI代码解释 # 提取日期实体 df['day']=df['datetime64'].dt.day #天 df['weekday']=df['datetime64'].dt.weekday #周 df['month']=df['datetime64'].dt.month #月 df['year']=df['datetime64']....
1 import time 2 import datetime 3 4 print(time.asctime()) # 返回时间格式:Sun May 7 21:46:15 2017 5 print(time.time()) # 返回时间戳 ‘1494164954.6677325’ 6 print(time.gmtime()) # 返回本地时间 的struct time对象格式,time.struct_time(tm_year=2017, tm_mon=5, tm_mday=7, tm_hour...
from datetime import date, datetime from calendar import Calendar as Cal START_YEAR = 1901 def is_leap_year(tm): y = tm.year return (not (y % 4)) and (y % 100) or (not (y % 400)) def show_month(tm): (ly, lm, ld) = get_ludar_date(tm) ...
在datetime中新建时间对象可以直接使用datetime(y, m,d,tzinfo)输入参数,用datetime.now()获得当前时间,通过datetime.fromtimestamp(ts)可以将时间戳ts转为时间对象,生成的datetime时间对象在获取属性时用到的语句类似dt.year,有year/month/day/hour/second/tzinfo等可以用。tzinfo是时区属性,datetime在时区相关处理时通...
Date Output When we execute the code from the example above the result will be: 2025-05-22 06:16:36.464291 The date contains year, month, day, hour, minute, second, and microsecond. Thedatetimemodule has many methods to return information about the date object. ...
apply(lambda x: get_recent_month(x, 6)) fundamentals['trade_date'] = fundamentals['trade_date'].apply(lambda x: (x.year * 100 + x.month) * 100 + x.day) monthly_data = pd.merge(old_data, fundamentals, on=['trade_date', 'cusip'], how='outer') monthly_data.sort_values(by=...
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