Adding date to pd.to_datetime

I’m looking for a way to add custom date to pd.to_datetime. So, for example:

csv_file = str(datetime.now().strftime('%Y-%m-%d')) + '.csv'
csv_file2 = str((datetime.now() + timedelta(days=1)).strftime('%Y-%m-%d')) + '.csv'
data = pd.concat(map(pd.read_csv, [csv_file, csv_file2]))
data['time'] = pd.to_datetime(data['time'], errors='coerce')

Print:

4      2021-08-23 00:00:40
20     2021-08-23 00:02:54
36     2021-08-23 00:05:09
...        

pd.to_datetime keeps adding today’s date which is fine in case of csv_file but csv_file2 need to contain tomorrow’s date.

Here’s sample of csv files:

piece,time
2259,12:03:50
2259,12:07:42
2259,12:34:05
2259,12:45:29

Answer

Idea is create helper column file for distingush if tomorrow and last add 1 day by condition for compare new column:

data = pd.concat(map(pd.read_csv, [csv_file, csv_file2]), keys=('today','tomorrow'))

data = data.reset_index(level=1, drop=True).rename_axis('new').reset_index()

d = pd.to_datetime(data['time'], errors='coerce')
data['time'] = np.where(data['new'].eq('tomorrow'), d + pd.Timedelta(1, 'd'), d)

Or:

files = [csv_file, csv_file2]
names = ('today','tomorrow')
data= pd.concat([pd.read_csv(f).assign(new=name) for f, name in zip(files, names)])
d = pd.to_datetime(data['time'], errors='coerce')
data['time'] = np.where(data['new'].eq('tomorrow'), d + pd.Timedelta(1, 'd'), d)