CODEWITHSUNDEEP
pythonnumpydatetime
Camilla
Camilla

Reputation: 131

Filling column with dates using numpy

I need to fill an array with dates, starting from period 2021-07-15 for 120 periods with monthly frequency. currently I use code :

dates= []
for i in range (0, len(output)):
   if (i%120 == 0):
      for e in[d.strftime("%Y-%m-%d") for d in pd.date_range(start='2021-7-1', periods=120, 
         freq='MS').shift(14,freq='D')]:
         dates.append(e)

This code works no problem, but I would like to use numpy as it usually faster then pandas or list. Does anybody know how can I replace this code using numpy datetime64?

Upvotes: 0

Views: 135

Answers (1)

hpaulj
hpaulj

Reputation: 231385

arange can work with datetime64 objects:

In [35]: stop=start+np.timedelta64(120)
In [36]: arr=np.arange(start,stop)
In [37]: arr.shape
Out[37]: (120,)
In [38]: arr[:10]
Out[38]: 
array(['2021-07-15', '2021-07-16', '2021-07-17', '2021-07-18',
       '2021-07-19', '2021-07-20', '2021-07-21', '2021-07-22',
       '2021-07-23', '2021-07-24'], dtype='datetime64[D]')
In [39]: arr[::10]
Out[39]: 
array(['2021-07-15', '2021-07-25', '2021-08-04', '2021-08-14',
       '2021-08-24', '2021-09-03', '2021-09-13', '2021-09-23',
       '2021-10-03', '2021-10-13', '2021-10-23', '2021-11-02'],
      dtype='datetime64[D]')

Upvotes: 1

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