Can Python Pandas handle 10 million rows?

10 million rows isn’t really a problem for pandas. The library is highly optimized for dealing with large tabular datasets through its DataFrame structure. I’ve used it to handle tables with up to 100 million rows. The constraint is the amount of RAM on your computer. read more

I have recently written a decently complex script with pandas in python to map dozens of files together. This script includes a lot of merges, concats, and filtering. Initially I anticipated that this script would be used for data files that are at max a 2 gigs large, about 2 million rows by 50 - 150 columns. read more

I extracted a .csv file from Google Bigquery of 2 columns and 10 Million rows. I have downloaded the file locally as a .csv with the size of 170Mb, then I uploaded the file to Google Drive, and I want to use pandas.read_csv() function to read it into pandas DataFrame in my Jupyter Notebook. read more