prepare the input

In [1]:
start_yyyymmdd = '20201203'
fmt = '%Y%m%d'
from datetime import datetime
start_date = datetime.strptime(start_yyyymmdd, fmt)

In [2]:
print(start_date)
2020-12-03 00:00:00

In [3]:
import pandas as pd
days_original = [158, 928, 882, 341, 596, 878, 526]
offset_years = [round(x/365.0, 9) for x in days_original]
df = pd.DataFrame({'offset_years': offset_years})

In [4]:
print(df)
   offset_years
0      0.432877
1      2.542466
2      2.416438
3      0.934247
4      1.632877
5      2.405479
6      1.441096

Convert the offset to days

In [5]:
import numpy as np
df['offset_days'] = (df['offset_years']*365.0).round().astype(np.int)
df
Out[5]:
   offset_years  offset_days
0      0.432877          158
1      2.542466          928
2      2.416438          882
3      0.934247          341
4      1.632877          596
5      2.405479          878
6      1.441096          526

Apply the offset to get end dates

In [6]:
df['end_yyyymmdd'] = (start_date + pd.to_timedelta(df['offset_days'], 'd')).dt.strftime(fmt)
df
Out[6]:
   offset_years  offset_days end_yyyymmdd
0      0.432877          158     20210510
1      2.542466          928     20230619
2      2.416438          882     20230504
3      0.934247          341     20211109
4      1.632877          596     20220722
5      2.405479          878     20230430
6      1.441096          526     20220513

Used | Python 3.8.5, ipython 7.18.1, pandas 1.1.3, numpy 1.19.2

demonstrates | round float to int

Given

In [1]: 
import pandas as pd
df = pd.DataFrame({'begin': ['20201107', '20201121'], 'offset': [5, -6]})
df
Out[1]: 
      begin  offset
0  20201107       5
1  20201121      -6

In [2]: 
df.dtypes
Out[2]: 
begin     object
offset     int64
dtype: object

we want

      begin  offset       end
0  20201107       5  20201112
1  20201121      -6  20201115

where end date = begin date + offset

Solution:

In [3]: 
fmt='%Y%m%d'
from datetime import datetime
df['end'] = (df['begin'].apply(lambda x: datetime.strptime(x, fmt)) +
             pd.to_timedelta(df['offset'], 'd')).dt.strftime(fmt)
df
Out[3]: 
      begin  offset       end
0  20201107       5  20201112
1  20201121      -6  20201115

Intermediate steps:

In [4]: 
df['begin'].apply(lambda x: datetime.strptime(x, fmt))
Out[4]: 
0   2020-11-07
1   2020-11-21
Name: begin, dtype: datetime64[ns]

In [5]: 
df['begin'].apply(lambda x: datetime.strptime(x, fmt)) + pd.to_timedelta(df['offset'], 'd')
Out[5]: 
0   2020-11-12
1   2020-11-15
dtype: datetime64[ns]

In [6]: 
(df['begin'].apply(lambda x: datetime.strptime(x, fmt)) +
 pd.to_timedelta(df['offset'], 'd')).dt.strftime(fmt)
Out[6]: 
0    20201112
1    20201115
dtype: object

In [1]: 
from datetime import datetime, timedelta
print(datetime.now())
2020-11-21 23:54:10.971599

In [2]: 
print(datetime.now() + timedelta(days=10))
2020-12-01 23:54:32.393776

• https://github.com/KamarajuKusumanchi/market_data_processor/blob/master/add_days.py
• https://pandas.pydata.org/docs/reference/api/pandas.to_timedelta.html

If the offsets are computed from floating point numbers that were originally derived from integers, watch out for round off errors.

For example, let's say:

• There are two applications App1 and App2
• App1 converts the number of days (an integer value) into number of years (a floating point number) and rounds it to 9 digits
• App2 reads that as input

In [1]:
days_original = [158, 928, 882, 341, 596, 878, 526]
years_given = [round(x/365.0, 9) for x in days_original]
print(years_given)
[0.432876712, 2.542465753, 2.416438356, 0.934246575, 1.632876712, 2.405479452, 1.44109589]

Now if App2 tries to compute the offsets by multiplying with 365 and converting that back to integer, it will give wrong results (due to limitations in floating point representation).

In [2]:
wrong_offsets = [int(x*365.0) for x in years_given]
print(wrong_offsets)
[157, 927, 881, 340, 595, 877, 525]

The correct approach is to multiply by 365, apply round() and then convert it back to integer.

In [3]:
correct_offsets = [int(round(x*365.0)) for x in years_given]
print(correct_offsets)
[158, 928, 882, 341, 596, 878, 526]