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I have a dataframe that looks like this:
from to datetime other
-------------------------------------------------
11 1 2016-11-06 22:00:00 -
11 1 2016-11-06 20:00:00 -
11 1 2016-11-06 15:45:00 -
11 12 2016-11-06 15:00:00 -
11 1 2016-11-06 12:00:00 -
11 18 2016-11-05 10:00:00 -
11 12 2016-11-05 10:00:00 -
12 1 2016-10-05 10:00:59 -
12 3 2016-09-06 10:00:34 -
I want to groupby "from" and then "to" columns and then sort the "datetime" in descending order and then finally want to calculate the time difference within these grouped by objects between the current time and the next time. For eg, in this case, I would like to have a dataframe like the following:
from to timediff in minutes others
11 1 120
11 1 255
11 1 225
11 1 0 (preferrably subtract this date from the epoch)
11 12 300
11 12 0
11 18 0
12 1 25
12 3 0
I can't get my head around figuring this out!! Is there a way out for this? Any help will be much much appreciated!! Thank you so much in advance!
282
We create a Panda DataFrame with 3 columns. Then we set the values of the to and fr columns to Pandas timestamps. Next, we subtract the values from df.fr by df.to and convert the type to timedelta64 with astype and assign that to df.
Comparison between pandas timestamp objects is carried out using simple comparison operators: >, <,==,< = , >=. The difference can be calculated using a simple '–' operator. Given time can be converted to pandas timestamp using pandas. Timestamp() method.
When the function receives the date string it will first use the Pandas to_datetime() function to convert it to a Python datetime and it will then use the timedelta() function to subtract the number of days defined in the days variable.
Pandas has a built-in function called to_datetime()that converts date and time in string format to a DateTime object. As you can see, the 'date' column in the DataFrame is currently of a string-type object. Thus, to_datetime() converts the column to a series of the appropriate datetime64 dtype.
df.assign(
timediff=df.sort_values(
'datetime', ascending=False
).groupby(['from', 'to']).datetime.diff(-1).dt.seconds.div(60).fillna(0))
97
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