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Tag: group-by

Creating time delta diff column based on groupby id

I have the following sample df I want to groupby Id, and get the timedelta difference between the timestamps, i manage to get something similar to the wanted series. Through this code. Although, it is taking quite a long time, is there a way to do it more efficiently? Wanted series Answer here is one way about it btw, if

Apply function to each unique value of column seperately

I have a dataframe with more than 500 cities which look like this city value datetime london 23 2022-03-25 17:59:18 dubai 12 2022-03-25 17:59:36 berlin 5 2022-03-25 17:59:42 london 25 2022-03-25 18:01:18 dubai 12 2022-03-25 18:02:18 berlin 5 2022-03-25 18:03:18 I have a function called rolling_mean which creates a new column ‘rolling_mean’ which calculates the last hour rolling average. However

Divide into groups according to the specified attribute

I need to group the data in such a way that if the difference between the adjacent values from column a1 was equal to the same pre-specified value, then they belong to the same group. If the value between two adjacent elements is different, then all subsequent data belong to a different group. For example, I have such a data

How to sum a value based on group?

I am trying to figure out how to sum a value from rank 5 to the LOWEST rank (I.E. 5-1,000) for each geography in my dataframe. However, I am getting the error: ‘DataFrameGroupBy’ object has no attribute ‘iloc’ Am I using iloc incorrectly? Answer IIUC, try:

Can repeating query be saved?

In my Python / Sqlite program, I am running queries like this So the “basic” query is the same, and the rows Sqlite gathers are the same, but because of the different grouping , I have to run the same query multiple times. I wonder if there is a way to achieve the same output more effectively, ie. run the

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