I have a datetime column where I am trying to add a constant number of seconds to the original time. The end goal is to create a rolling window function with a fixed window based on seconds. The first step is identical to this question.
My question is why is my application of this solution to this question not working? How can I add a constant timedelta to the previous time in order to try and get the r
# ========== create dataset and try add 3 seconds to datetime column=================================================================== #
import pandas as pd
from datetime import timedelta, datetime
timestamp_list = ["2022-02-07 11:38:08.625",
"2022-02-07 11:38:09.676",
"2022-02-07 11:38:10.084",
"2022-02-07 11:38:10.10000",
"2022-02-07 11:38:11.2320"]
value_list = [1.14338,
1.14341,
1.14340,
1.1434334,
1.1534334]
df = pd.DataFrame.from_dict(zip(timestamp_list, value_list))
df.columns = ['timestamp','value']
# make date time object
df.timestamp = [datetime.strptime(time_i, "%Y-%m-%d %H:%M:%S.%f") for time_i in df.timestamp]
# get the time second value of datetime
df["timestamp_to_sec"] = df["timestamp"].dt.strftime("%Y%m%d %H:%M:%S")
# add 3 seconds to the original timestep
temp = df.timestamp_to_sec + timedelta(seconds=3)
#output with error
0 -83211 days +23:06:15.727111680
1 -83211 days +23:06:16.727111680
2 -83211 days +23:06:17.727111680
3 -83211 days +23:06:17.727111680
4 -83211 days +23:06:18.727111680
Name: timestamp_to_sec, dtype: timedelta64[ns]
Use to_datetime for datetimes, then remove microseconds by Series.dt.floor and add 3 seconds:
# make date time object
df.timestamp = pd.to_datetime(df.timestamp)
# get the time second value of datetime
df["timestamp"] = df["timestamp"].dt.floor('s') + pd.Timedelta(seconds=3)
print (df)
timestamp value
0 2022-02-07 11:38:11 1.143380
1 2022-02-07 11:38:12 1.143410
2 2022-02-07 11:38:13 1.143400
3 2022-02-07 11:38:13 1.143433
4 2022-02-07 11:38:14 1.153433