How to change year value in numpy datetime64?

Question

I have a pandas DataFrame with dtype=numpy.datetime64 In the data I want to change

'2011-11-14T00:00:00.000000000'

to:

'2010-11-14T00:00:00.000000000'

or other year. Timedelta is not known, only year number to assign. this displays year in int

Dates_profit.iloc[50][stock].astype('datetime64[Y]').astype(int)+1970

but can't assign value. Anyone know how to assign year to numpy.datetime64?

Answer 1

Since you're using a DataFrame, consider using pandas.Timestamp.replace:

In [1]: import pandas as pd

In [2]: dates = pd.DatetimeIndex([f'200{i}-0{i+1}-0{i+1}' for i in range(5)])

In [3]: df = pd.DataFrame({'Date': dates})

In [4]: df
Out[4]:
        Date
0 2000-01-01
1 2001-02-02
2 2002-03-03
3 2003-04-04
4 2004-05-05

In [5]: df.loc[:, 'Date'] = df['Date'].apply(lambda x: x.replace(year=1999))

In [6]: df
Out[6]:
        Date
0 1999-01-01
1 1999-02-02
2 1999-03-03
3 1999-04-04
4 1999-05-05

Answer 2

numpy.datetime64 objects are hard to work with. To update a value, it is normally easier to convert the date to a standard Python datetime object, do the change and then convert it back to a numpy.datetime64 value again:

import numpy as np
from datetime import datetime

dt64 = np.datetime64('2011-11-14T00:00:00.000000000')

# convert to timestamp:
ts = (dt64 - np.datetime64('1970-01-01T00:00:00Z')) / np.timedelta64(1, 's')

# standard utctime from timestamp
dt = datetime.utcfromtimestamp(ts)

# get the new updated year
dt = dt.replace(year=2010)

# convert back to numpy.datetime64:
dt64 = np.datetime64(dt)

There might be simpler ways, but this works, at least.