Python3如何将日期转换为第一个时期为9月的每月时期

问题描述

与一个从9月开始的会计年度的小组一起工作.我有一个带有一堆日期的数据框，我想计算一个9月= 1的月度周期.

Working with a group that has a Fiscal Year that starts in September. I have a dataframe with a bunch of dates that I want to calculate a monthly period that = 1 in September.

有效方法:

# Convert date column to datetime format
df['Hours_Date'] = pd.to_datetime(df['Hours_Date'])

# First quarter starts in September - Yes!   
df['Quarter'] = pd.PeriodIndex(df['Hours_Date'], freq='Q-Aug').strftime('Q%q')

什么不起作用:

# Gives me monthly periods starting in January.  Don't want.
df['Period'] = pd.PeriodIndex(df['Hours_Date'], freq='M').strftime('%m')

# Gives me an error
df['Period'] = pd.PeriodIndex(df['Hours_Date'], freq='M-Aug').strftime('%m')

有没有一种可以调整每月频率的方法?

Is there a way to adjust the monthly frequency?

推荐答案

我认为它尚未实现，请检查锚定的偏移量.

I think it is not implemented, check anchored offsets.

可能的解决方案是减去或 8移8个月:

Possible solution is subtract or Index.shift 8 for shift by 8 months:

rng = pd.date_range('2017-04-03', periods=10, freq='m')
df = pd.DataFrame({'Hours_Date': rng}) 

df['Period'] = (pd.PeriodIndex(df['Hours_Date'], freq='M') - 8).strftime('%m')

或者:

df['Period'] = pd.PeriodIndex(df['Hours_Date'], freq='M').shift(-8).strftime('%m')

---

print (df)
  Hours_Date Period
0 2017-04-30     08
1 2017-05-31     09
2 2017-06-30     10
3 2017-07-31     11
4 2017-08-31     12
5 2017-09-30     01
6 2017-10-31     02
7 2017-11-30     03
8 2017-12-31     04
9 2018-01-31     05

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