While dealing with pandas DataFrames, sooner or later you’ll face an issue with the default types handling. Surely, that’s quite convenient to just load all the data via the .read_csv method and then implement all the logic required to analyze the dataset without much effort. That unfortunately rarely works that easily. If you use too large data types, like int64 for every single integer, even though the values come from a really narrow range of values, your data frame may grow to a size that won’t fit your memory anymore. …

Kacper Łukawski

Founder & Chairman at AI Embassy. Data Science Consultant. Public speaker. Cracow, Poland.

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