Python Bytes

#325 It's called a merge conflict

Informações:

Sinopsis

Watch on YouTube About the show Sponsored by Microsoft for Startups Founders Hub. Connect with the hosts Michael: @mkennedy@fosstodon.org Brian: @brianokken@fosstodon.org Show: @pythonbytes@fosstodon.org Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesdays at 11am PT. Older video versions available there too. Michael #1: Python Parquet and Arrow: Using PyArrow With Pandas Parquet is an efficient, compressed, column-oriented storage format for arrays and tables of data. Less wrangle-able than Pandas, but way faster and lower memory Questions answered Can we use Pandas DataFrames and Arrow tables together, and if so, how is this done? (It turns out the answer is yes, and it’s quite simple, as we’ll see). In what ways are Arrow tables “better” than Pandas DataFrames? In other words, for which tasks are Arrow tables better suited? Conversely, what tasks are possible or easy in Pandas that are difficult or impossible in Arrow? As an on-disk format, how does Parquet com