Question :
How to add/subtract time (hours, minutes, etc.) from a Pandas DataFrame.Index whos objects are of type datetime.time?
I’ve got a DataFrame who’s index is just datetime.time and there’s no method in DataFrame.Index and datetime.time to shift the time. datetime.time has replace but that’ll only work on individual items of the Series?
Here’s an example of the index used:
In[526]: dfa.index[:5]
Out[526]: Index([21:12:19, 21:12:20, 21:12:21, 21:12:21, 21:12:22], dtype='object')
In[527]: type(dfa.index[0])
Out[527]: datetime.time
Answer #1:
Liam’s link looks great, but also check out pandas.Timedelta – looks like it plays nicely with NumPy’s and Python’s time deltas.
https://pandas.pydata.org/pandas-docs/stable/timedeltas.html
pd.date_range('2014-01-01', periods=10) + pd.Timedelta(days=1)
Answer #2:
This one worked for me:
>> print(df)
TotalVolume Symbol
2016-04-15 09:00:00 108400 2802.T
2016-04-15 09:05:00 50300 2802.T
>> print(df.set_index(pd.to_datetime(df.index.values) - datetime(2016, 4, 15)))
TotalVolume Symbol
09:00:00 108400 2802.T
09:05:00 50300 2802.T
Answer #3:
The Philippe solution but cleaner:
My subtraction data is: ‘2018-09-22T11:05:00.000Z’
import datetime
import pandas as pd
df_modified = pd.to_datetime(df_reference.index.values) - datetime.datetime(2018, 9, 22, 11, 5, 0)
