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Thank you, your the only person to correctly interpret my comment :)
Really? You've written out all the ratios and thresholds manually. If a user wanted to change the set of thresholds the polars way is far superior. In what way do you consider this better?
Here are a couple reasons: - much faster, multithreaded by default. Read in a big csv with it and see how it feels. - no index/MultiIndex. Pandas special treatment of index always felt like more trouble than it was…
What is it about polars syntax you don't like? The fact that is very verbose? At first I wasn't a fan, but over time I've grown to really like it. That never happened to me with pandas, always felt the syntax was messy
Fair point, but you can do something like `df.select("x", y=pl.col.w/pl.col.z)`
I don't find this convincing at all. The actual interesting attempt at scientific theory of harmony in this could be distilled to a couple of lines, yet the author rambles endlessly in ways that don't add to the piece…
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Thank you, your the only person to correctly interpret my comment :)
Really? You've written out all the ratios and thresholds manually. If a user wanted to change the set of thresholds the polars way is far superior. In what way do you consider this better?
Here are a couple reasons: - much faster, multithreaded by default. Read in a big csv with it and see how it feels. - no index/MultiIndex. Pandas special treatment of index always felt like more trouble than it was…
What is it about polars syntax you don't like? The fact that is very verbose? At first I wasn't a fan, but over time I've grown to really like it. That never happened to me with pandas, always felt the syntax was messy
Fair point, but you can do something like `df.select("x", y=pl.col.w/pl.col.z)`
I don't find this convincing at all. The actual interesting attempt at scientific theory of harmony in this could be distilled to a couple of lines, yet the author rambles endlessly in ways that don't add to the piece…