Time interval calculation yields wrong results
Question:
I have a dataframe that looks like this:( not putting all the rows since it is alot)
commitDate commits api_spec_id info_version Days-diff
29193 2021-03-10 10:24:56 181 156422 1.225.430 0
29192 2021-03-10 15:14:12 181 156422 1.225.497 0
29191 2021-03-10 18:33:18 181 156422 1.225.541 0
29190 2021-03-11 16:14:49 181 156422 1.225.712 1
29189 2021-03-15 10:31:03 181 156422 1.226.49 5
29188 2021-03-15 17:11:09 181 156422 1.226.157 5
29187 2021-03-16 12:33:34 181 156422 1.226.376 6
29186 2021-03-17 12:54:09 181 156422 1.226.680 7
29185 2021-03-18 15:33:44 181 156422 1.226.959 8
29184 2021-03-22 10:38:21 181 156422 1.227.290 12
29312 2021-12-08 08:15:07 181 156422 1.270.370 273
29311 2021-12-14 15:20:23 181 156422 1.271.471 279
29310 2021-12-15 17:26:35 181 156422 1.271.782 280
29309 2021-12-17 09:01:14 181 156422 1.272.43 282
29308 2021-12-20 17:14:55 181 156422 1.272.573 285
29307 2021-12-23 09:39:24 181 156422 1.273.170 288
I have been calculating the time interval between the last and the first commit date: which is 23 Dec 2021 as last, and March 3 2021 as first. However the days_diff only comes correct when I specify the basedate and not otherwise.
The code on which it works is this:
basedate = pd.Timestamp('2021-03-10')
data4['Days-diff'] = (data4['commitDate'] - basedate).dt.days
I saw this instance of wrong calculation while looking at this subset of my dataframe, and had used this code for age calculation:
g = final_api.groupby('api_spec_id')['commitDate']
final_api['Age-final'] = g.transform('last').sub(g.transform('first'))
and this:
t = pd.to_datetime(final_api['commitDate'])
final_api['Days_difference'] = t.sub(t.groupby(final_api['api_spec_id']).transform('min')).dt.days
The Age should come as 289 days but it is coming as 525 days when I use these code above. For days_difference as well my output comes like this:
commitDate Days-diff Age-final Days_difference
29193 2021-03-10 10:24:56 0 67 days 22:17:54 236
29192 2021-03-10 15:14:12 0 67 days 22:17:54 237
29191 2021-03-10 18:33:18 0 67 days 22:17:54 237
29190 2021-03-11 16:14:49 1 67 days 22:17:54 238
29189 2021-03-15 10:31:03 5 67 days 22:17:54 241
which is wrong since it is supposed to start from 0 for days_difference. I am lost as to where I am going wrong.any help will be appreciated.
Answers:
In the code that you have shown, it seems like you are trying to calculate the number of days between the first and the last commit date for each api_spec_id group.
To do this, you can use the groupby method to group the dataframe by api_spec_id and then use the agg method to calculate the number of days between the first and the last commit date for each group.
Here is an example of how you can do this:
# Group the dataframe by api_spec_id
g = final_api.groupby('api_spec_id')
# Use the agg method to calculate the number of days between the first and last commit date
# for each group.
final_api['Age-final'] = g.commitDate.agg(lambda x: x.max() - x.min())
This code will calculate the number of days between the first and last commit date for each group and store the result in the Age-final column of the final_api dataframe.
To calculate the difference between each commit date and the first commit date for the corresponding api_spec_id group, you can use the transform method in combination with the min function.
Here is an example of how you can do this:
# Get the datetime values of the commitDate column
t = pd.to_datetime(final_api['commitDate'])
# Group the datetime values by api_spec_id and calculate the minimum value for each group
# using the min function
first_commit_date = t.groupby(final_api['api_spec_id']).transform('min')
# Calculate the difference between each commit date and the first commit date for the corresponding
# api_spec_id group using the transform method.
final_api['Days_difference'] = t.sub(first_commit_date).dt.days
This code will calculate the difference between each commit date and the first commit date for the corresponding api_spec_id group and store the result in the Days_difference column of the final_api dataframe.
I have a dataframe that looks like this:( not putting all the rows since it is alot)
commitDate commits api_spec_id info_version Days-diff
29193 2021-03-10 10:24:56 181 156422 1.225.430 0
29192 2021-03-10 15:14:12 181 156422 1.225.497 0
29191 2021-03-10 18:33:18 181 156422 1.225.541 0
29190 2021-03-11 16:14:49 181 156422 1.225.712 1
29189 2021-03-15 10:31:03 181 156422 1.226.49 5
29188 2021-03-15 17:11:09 181 156422 1.226.157 5
29187 2021-03-16 12:33:34 181 156422 1.226.376 6
29186 2021-03-17 12:54:09 181 156422 1.226.680 7
29185 2021-03-18 15:33:44 181 156422 1.226.959 8
29184 2021-03-22 10:38:21 181 156422 1.227.290 12
29312 2021-12-08 08:15:07 181 156422 1.270.370 273
29311 2021-12-14 15:20:23 181 156422 1.271.471 279
29310 2021-12-15 17:26:35 181 156422 1.271.782 280
29309 2021-12-17 09:01:14 181 156422 1.272.43 282
29308 2021-12-20 17:14:55 181 156422 1.272.573 285
29307 2021-12-23 09:39:24 181 156422 1.273.170 288
I have been calculating the time interval between the last and the first commit date: which is 23 Dec 2021 as last, and March 3 2021 as first. However the days_diff only comes correct when I specify the basedate and not otherwise.
The code on which it works is this:
basedate = pd.Timestamp('2021-03-10')
data4['Days-diff'] = (data4['commitDate'] - basedate).dt.days
I saw this instance of wrong calculation while looking at this subset of my dataframe, and had used this code for age calculation:
g = final_api.groupby('api_spec_id')['commitDate']
final_api['Age-final'] = g.transform('last').sub(g.transform('first'))
and this:
t = pd.to_datetime(final_api['commitDate'])
final_api['Days_difference'] = t.sub(t.groupby(final_api['api_spec_id']).transform('min')).dt.days
The Age should come as 289 days but it is coming as 525 days when I use these code above. For days_difference as well my output comes like this:
commitDate Days-diff Age-final Days_difference
29193 2021-03-10 10:24:56 0 67 days 22:17:54 236
29192 2021-03-10 15:14:12 0 67 days 22:17:54 237
29191 2021-03-10 18:33:18 0 67 days 22:17:54 237
29190 2021-03-11 16:14:49 1 67 days 22:17:54 238
29189 2021-03-15 10:31:03 5 67 days 22:17:54 241
which is wrong since it is supposed to start from 0 for days_difference. I am lost as to where I am going wrong.any help will be appreciated.
In the code that you have shown, it seems like you are trying to calculate the number of days between the first and the last commit date for each api_spec_id group.
To do this, you can use the groupby method to group the dataframe by api_spec_id and then use the agg method to calculate the number of days between the first and the last commit date for each group.
Here is an example of how you can do this:
# Group the dataframe by api_spec_id
g = final_api.groupby('api_spec_id')
# Use the agg method to calculate the number of days between the first and last commit date
# for each group.
final_api['Age-final'] = g.commitDate.agg(lambda x: x.max() - x.min())
This code will calculate the number of days between the first and last commit date for each group and store the result in the Age-final column of the final_api dataframe.
To calculate the difference between each commit date and the first commit date for the corresponding api_spec_id group, you can use the transform method in combination with the min function.
Here is an example of how you can do this:
# Get the datetime values of the commitDate column
t = pd.to_datetime(final_api['commitDate'])
# Group the datetime values by api_spec_id and calculate the minimum value for each group
# using the min function
first_commit_date = t.groupby(final_api['api_spec_id']).transform('min')
# Calculate the difference between each commit date and the first commit date for the corresponding
# api_spec_id group using the transform method.
final_api['Days_difference'] = t.sub(first_commit_date).dt.days
This code will calculate the difference between each commit date and the first commit date for the corresponding api_spec_id group and store the result in the Days_difference column of the final_api dataframe.