Assume we have a series that contains time difference values.
na_removed_order_time_diff.head() 0 00:46:33 1 00:12:07 2 00:14:59 3 00:09:43 4 00:12:22 dtype: timedelta64[ns]
Let’s find rows which have time difference more than an hour. According to the pandas documentation, the pandas timedelta is actually using the python’s
datetime module’s timedelta.
For first make a datetime.timedelta object that contains a value of one hour and use this as a comparison against our pandas series to extract the rows that satisfy the condition.
td = datetime.timedelta(hours=1) over_threshold = order_time_diff > td 0 False 1 False 2 False 3 False 4 False dtype: bool
Now we can select the rows with this array of booleans.