I`m looking to create a new row for a date with the following formatting:
2022-07-20 0:00:00
So basically, today's date and the time as h:mm:ss, all as 0
I'm trying to use pd.to_datetime('today') but the time is my current time and not 0. I also tried to use the same code but with .normalize() and then my time disappears, only the date remains.
Is there a way to do that?
There are a few approaches you could take. I think in most cases it really depends on what you prefer, or what fits your use case best.
from datetime import datetime, date
datetime.now().replace(hour=0, minute=0, second=0, microsecond=0)
datetime.fromordinal(date.today().toordinal())
datetime.combine(date.today(), datetime.time(datetime.min))
>>> datetime.datetime(2022, 7, 20, 0, 0)
>>> datetime.datetime(2022, 7, 20, 0, 0)
>>> datetime.datetime(2022, 7, 20, 0, 0)
If your dataframe is df, try:
from datetime import datetime
df['time'] = datetime.(year= ..., month= ..., day= ...)
Perhaps I misunderstand, but does this do what you want?
import pandas as pd
dtrng = pd.date_range('2022-07-01', periods=31, freq='D')
df = pd.DataFrame({'Date' : dtrng})
df['DateTime'] = df.Date.dt.strftime('%Y-%m-%d %H:%M:%S')
df['DateHMSutc'] = pd.to_datetime(df['Date'], format='%Y-%m-%d %H:%M:%S', utc=True)
df.head()
Date DateTime DateHMSutc
0 2022-07-01 2022-07-01 00:00:00 2022-07-01 00:00:00+00:00
1 2022-07-02 2022-07-02 00:00:00 2022-07-02 00:00:00+00:00
2 2022-07-03 2022-07-03 00:00:00 2022-07-03 00:00:00+00:00
3 2022-07-04 2022-07-04 00:00:00 2022-07-04 00:00:00+00:00
4 2022-07-05 2022-07-05 00:00:00 2022-07-05 00:00:00+00:00
df.dtypes
Date datetime64[ns]
DateTime object
DateHMSutc datetime64[ns, UTC]
dtype: object