sangreal-calendar
由于开源数据不稳定，现改为需要自行注入
安装
pip install sangreal-calendar
交易日处理函数
from sangreal_calenadr import *
# 获取历史交易日
tmp_series = get_xxx() -> pd.Series
CALENDAR.inject(tmp_series)
# 获取交易日列表
get_trade_dts(begin_dt='20180101', end_dt='20180201')
['20180102', '20180103', ..., '20180201']
# 获取交易日DataFrame
get_trade_dts(begin_dt='20180101', end_dt='20180201', astype='pd')
trade_dt
6613 20180102
6614 20180103
6615 20180104
6616 20180105
6617 20180108
# 调整非交易日至之前的最近一个交易日
adjust_trade_dt('20180101')
'20171229'
# 调整非交易日至之前的最后一个交易日
adjust_trade_dt('20180101', 'next')
'20180102'
# 往后step 1个交易日
# 注意，对于非交易日的输入，会自动将其adjust至之后的最近一个交易日
# 本质上是 step_trade_dt('20180102', 1)
step_trade_dt('20180101', 1)
'20180103'
# 往后step 1个交易日
step_trade_dt('20180101', -1)
'20171229'
# 计算两个日期间的交易日长度
delta_trade_dt('20180101', '20180305')
40
时间频率处理函数
支持weekly biweekly monthly quarterly reportly halfyearly yearly
以weekly为例
# 返回每周的第一个交易日
# 格式为Series 及 datetime
Weekly(1).get('20180101', '20190101')
6613 20180102
6617 20180108
6622 20180115
6627 20180122
6632 20180129
6637 20180205
# 返回每周的最后一个交易日
Weekly(-1).get('20180101', '20190101')
6621 20180112
6626 20180119
6631 20180126
6636 20180202
6641 20180209
6644 20180214
# 返回每周的第一个及最后一个交易日
Weekly(1, -1).get('20180101', '20190101')
6613 20180102
6617 20180108
6621 20180112
6622 20180115
6626 20180119
6627 20180122
Monthly() BiWeekly() Quarterly() ....
1 maintainer
Metadata
1 maintainer
Release files for sangreal-calendar 0.1.5
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Total release size: 51.3 kB
Release files / sangreal_calendar-0.1.5.tar.gz
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