Shittu Olumide recommends a few other packages:
If you’ve worked with data in Python, chances are you’ve used Pandas many times. And for good reason; it’s intuitive, flexible, and great for day-to-day analysis. But as your datasets start to grow, Pandas starts to show its limits. Maybe it’s memory issues, sluggish performance, or the fact that your machine sounds like it’s about to lift off when you try to group by a few million rows.
That’s the point where a lot of data analysts and scientists start asking the same question: what else is out there?
Read on for seven options, including six libraries and one built-in programming technique.