Calculating time difference - TypeError: Cannot compare type 'Timestamp' with type 'int'

Question

So, I would like create a new column called df["Diff"] by getting the difference between two datetime columns. My code is, thus:

df["Diff"] = df["Time"] - df_target["Time"]

When I run this code, I get the following error-message:

TypeError: Cannot compare type 'Timestamp' with type 'int'

I have however made sure that both columns are datetime-data type using .dtype.
I have also checked for any integer-values in any of the columns, but cannot find any.

Here is an example of the data for the two columns:

df.Time

Time
2017-09-01 01:31:10.000  2017-09-01 01:31:10

df_target

Time
2017-12-01 22:17:00  2017-12-01 22:17:00

Answer 1

Okay, so I figured out the answer.

Since one of the dataframes had an index based on datetime, while the other had an index on integer, I used reset_index to make both dataframes have an index consisting of integers. This then let me use the above code mentioned.

df["Diff"] = df["Time"] - df_target["Time"]

Thank you for all your help!

Answer 2

Pandas timestamp differences returns a datetime.timedelta object. This can easily be converted into hours by using the as_type method, like so

import pandas
df = pandas.DataFrame(columns=['to','fr','ans'])
df.to = [pandas.Timestamp('2014-01-24 13:03:12.050000'), pandas.Timestamp('2014-01-27 
11:57:18.240000'), pandas.Timestamp('2014-01-23 10:07:47.660000')]
df.fr = [pandas.Timestamp('2014-01-26 23:41:21.870000'), pandas.Timestamp('2014-01-27 
15:38:22.540000'), pandas.Timestamp('2014-01-23 18:50:41.420000')]
(df.fr-df.to).astype('timedelta64[h]')

to yield,

0    58
1     3
2     8
dtype: float64

Answer 3

Convert both columns with dates to pd.to_datetime and then perform the operation.