The information you want is at
pandas.Timestamp — pandas 1.2.4 documentation[
^].
[edit]
This is not perfect, but shows how to get the timedelta value between two items in the table, and remove the offending rows:
from datetime import datetime
from datetime import date
from datetime import time
from datetime import timedelta
data = ('135 2021-10-29 10:16:00 167 167.0 -3.0 15.45 15.45 17.95 17.45\n'
'155 2021-10-29 12:56:00 162 162.0 -15.0 15.35 15.35 17.95 16.00\n'
'243 2021-10-29 20:16:00 133 133.0 0.0 15.25 15.25 19.85 15.75\n'
'245 2021-10-29 20:26:00 134 134.0 0.0 15.50 15.50 15.75 15.60\n'
'113 2021-10-29 09:26:00 130 130.0 1.0 16.75 16.75 0.00 21.70')
rawtable = pd.read_csv(StringIO(data), header=None, delimiter=' ')
table = rawtable.sort_values(2, 0, key=lambda col: col.str.lower(), ignore_index=True)
tmin = timedelta(0, 0, 0, 0, 60)
tprev = datetime.combine(datetime.min, time(0, 0))
for index, row in table.iterrows():
s = row.iloc[1:3]
dt = date.fromisoformat(s[1])
td = time.fromisoformat(s[2])
dttd = datetime.combine(dt, td)
delta = dttd - tprev
if delta < tmin:
table.drop(index, inplace=True)
tprev = dttd
print("\n\n")
print(table)
[/edit]