What is the quickest method to iterate through columns and determine the IQR for each group, followed by calculating the proportionate IQR for every group based on a reference group?

edit

One possible approach is to use the pandas library in Python to group the data by a categorical variable, calculate the IQR for each group using the .quantile() method, and then divide each group's IQR by the IQR of the reference group using broadcasting. Here's an example code snippet:

import pandas as pd # load data as a pandas DataFrame data = pd.read_csv("data.csv") # group data by categorical variable and calculate IQR for each group grouped = data.groupby("category")["value"].quantile(0.75) - data.groupby("category")["value"].quantile(0.25) # calculate proportionate IQR for each group based on reference group ref_group = "A" proportionate = grouped / grouped[ref_group] # print results print("IQR by group:\n", grouped) print("Proportionate IQR by group (relative to group {}):\n".format(ref_group), proportionate) 

In this example, "data.csv" is a file containing the data with columns "category" and "value". The code first groups the data by "category" and calculates the IQR for each group using the .quantile() method. Then, it calculates the proportionate IQR for each group by dividing each group's IQR by the IQR of the reference group specified (in this case, "A"). Finally, it prints the results for both the IQR by group and the proportionate IQR by group relative to the reference group.