Sure I could write this myself, but before I go reinventing the wheel is there a function that already does this?
IF you are already using pandas
, it's quite simple.
import datetime as dt
import pandas as pd
quarter = pd.Timestamp(dt.date(2016, 2, 29)).quarter
assert quarter == 1
If you have a date
column in a dataframe, you can easily create a new quarter
column:
df['quarter'] = df['date'].dt.quarter
For those, who are looking for financial year quarter data, using pandas,
import datetime
import pandas as pd
today_date = datetime.date.today()
quarter = pd.PeriodIndex(today_date, freq='Q-MAR').strftime('Q%q')
reference: pandas period index
hmmm so calculations can go wrong, here is a better version (just for the sake of it)
first, second, third, fourth=1,2,3,4# you can make strings if you wish :)
quarterMap = {}
quarterMap.update(dict(zip((1,2,3),(first,)*3)))
quarterMap.update(dict(zip((4,5,6),(second,)*3)))
quarterMap.update(dict(zip((7,8,9),(third,)*3)))
quarterMap.update(dict(zip((10,11,12),(fourth,)*3)))
print quarterMap[6]
This method works for any mapping:
month2quarter = {
1:1,2:1,3:1,
4:2,5:2,6:2,
7:3,8:3,9:3,
10:4,11:4,12:4,
}.get
We have just generated a function int->int
month2quarter(9) # returns 3
This method is also fool-proof
month2quarter(-1) # returns None
month2quarter('July') # returns None
for m in range(1, 13):
print ((m*3)//10)
I would suggest another arguably cleaner solution. If X is a datetime.datetime.now()
instance, then the quarter is:
import math
Q=math.ceil(X.month/3.)
ceil has to be imported from math module as it can't be accessed directly.