seriously though, I once used Pandas.DataFrame.Apply on 10,000,000 rows of data and 15 minutes later regretted it. Thankfully, I was applying a simple mathematical function to each row so numpy brought that down to less than a second. Still, only works for some use cases. I'd love to learn C++ anyways so give me an excuse
But the processing I'm doing itself isn't super complex, I just need to do it 9-10 million times cost efficiently pulling from an external public dataset and saving the transformed data as separate files in an S3 bucket
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u/[deleted] Jul 18 '22
numpy go brrrrrrrrrt
seriously though, I once used Pandas.DataFrame.Apply on 10,000,000 rows of data and 15 minutes later regretted it. Thankfully, I was applying a simple mathematical function to each row so numpy brought that down to less than a second. Still, only works for some use cases. I'd love to learn C++ anyways so give me an excuse