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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.

What works:

# 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')

What doesn't work: 

# 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')

Is there a way to adjust the monthly frequency?

Arthur D. Howland
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2 Answers2

2

I think it is not implemented, check anchored offsets.

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')

Or:

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
jezrael
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1

I think 'M-Aug' is not applicable for month , so you can do little bit adjust by using np.where, Data From Jez

np.where(df['Hours_Date'].dt.month-8<=0,df['Hours_Date'].dt.month+4,df['Hours_Date'].dt.month-8)
Out[271]: array([ 8,  9, 10, 11, 12,  1,  2,  3,  4,  5], dtype=int64)
BENY
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