I want to compute the rolling Pearson correlation between all pairs of columns in a large Pandas DataFrame. Here’s the current implementation I am using:

I have a table with row elements that have a minimum and a maximum height and width, and I am trying to find a way to calculate the minimum number of sizes that I need to to satisfy all the conditions of being between the min and the max. I tried to use ChatGPT and it offered me a solution using Intervalltree, but it does not seem to work and the documentation on it seems sparse:

I am working on a project where I need to process a large amount of Betfair historical betting data provided in a tar file. This tar file contains multiple bz2 files, each of which includes a single file with a JSON object per line.

I have 2 dataframes of number x and y of same length and an input number a. I would like to find the fastest way to calculate a third list z such as :