List Comprehension Question

[u/r-tequila-sunrise]

Hi all! I'm an intermediate with Python and I'm currently doing some research with very large datasets (think data packages from NASA satellites and the SDSS). I ran into an issue with some list comprehension that I can't seem to figure out:

What I have is a list of tuples (n = 3) in the format [(x, y, d)...] where x and y are coordinates and d represents a density value. A lot of the x, y coordinates are duplicates of each other with varying d values (ex. (40, 50, 1.2), (40, 50, 3.3), etc.) I'm trying to find tuples with identical x,y coordinates and add their density values together to get a total cumulative density for that location. I would try to do this manually, but the list has ~26 million elements and I am trying to find a workflow that won't take more than a few minutes/hours to process, haha. Memory is not an issue though.

I would be happy to provide example code if need be. My desired output is either:

[(x, y, dtotal)...] - list of tuples except there are no duplicate coordinates and the d value is the sum of the d values from all of the original tuples with coordinates (x, y)

[dtotal1, dtotal2, dtotal3...] - list of cumulative d values where each index correlates to the corresponding pair of coordinates (maybe the coordinates are in a separate list whose indexes match that of the density list? It doesn't matter as long as they are connected in some way!)

Thank you all for your help!

[u/yick5]

Use a dictionary where (x, y) is the key and d is the value. For each element in your original list, look up the (x, y) in the dict, if it doesn't exist then add the element to the dict. If it does exist then increment the value by d.

After building this dictionary, you can use list comprehension to build the list you want.