pivot_table | Transform an ActiveRecord-ish data set into pivot table | SQL Database library

I am trying to split the dataset into two groups based on whether the value in the last row of that column is bigger than 0.

To illustrate:

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This allows me to split the 1,000 clients into two groups.

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I have this data

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I have the pandas dataframe which look like this.

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I am trying to pass a criteria to the aggregate function to pandas pivot_table and I am not able to figure out how to pass the criteria to the aggfunc. I have a data table which is converted to pandas df.

The input table data:

col1 col2 col3 col4 col5 col6 col7 1 test1 t1 Dummy1 result1 10 102.2 2 test1 t1 Dummy2 result2 20 101.2 3 test1 t1 Dummy3 result3 30 102.3 4 test1 t1 Dummy4 result4 40 101.4 5 test2 t1 Dummy1 result1 10 100 6 test2 t1 Dummy2 result2 20 103 7 test2 t1 Dummy3 result3 30 104 8 test2 t1 Dummy4 result4 40 105 9 test3 t1 Dummy1 result1 10 102 10 test3 t1 Dummy2 result2 20 87 11 test3 t1 Dummy3 result3 30 107 12 test3 t1 Dummy5 result4 50 110.2 13 test4 t1 Dummy2 result2 20 120 14 test5 t1 Dummy6 result1 100 88 15 test1 t1 Dummy1 result2 10 106.2 16 test1 t1 Dummy1 result6 10 101.1

I want to get the maximum on col7 data, but only when the maximum is greater than 100. If any of the col7 data is greater than the user defined criteria, then all the other columns data needs to be populated irrespective if the data met the criteria or not.

Tried the following:

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I have spent much time on this but I am nowhere closer to a solution.

I have a dataframe which outputs as

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I am converting my data frame to pivot table. Here's my Data frame.

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I have the following df:

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I am carrying out a spatial alignment task where I am exploring the effect of different score/rescore functions on the quality of the alignment (measured by RMSD). I have long form data where I have run all scoring / rescoring combinations for different systems and have repeated 3 times.

Here's some sample test data:

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Difference in differences (DID) is a statistical technique that calculates the effect of a treatment on an outcome by comparing the average change over time in the outcome variable for the treatment group [1]. I have this dataset where after means the months where the treatment was introduced and campaign explains if the treatment was applied, on a set of stores, and I want to observe the effect of the campaign on sales:

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