Sorting and uniqueness in Python

sort by several columns, take the top rows, or drop duplicates.

import polars as pl

frame = pl.DataFrame({
    "lang": ["python", "rust", "python", "sql"],
    "tpm": [104, 98, 91, 79],
})

print(frame.sort(["lang", "tpm"], descending=[False, True]))
print(frame.top_k(2, by="tpm"))
print(frame.unique(subset="lang", keep="first").sort("lang"))
print(frame["lang"].n_unique(), frame.height, frame.width)

How it works

sort takes descending per column.
top_k avoids sorting the whole frame.
unique keeps the first or last row per key.

Keywords and builtins used here

as
print

The run, in numbers

Lines: 11
Characters to type: 332
Tokens: 136
Three-star pace: 105 tpm

At the three-star pace of 105 tokens a minute, this run takes about 78 seconds.

Type this snippet

Step 2 of 3 in Filtering & sorting, step 10 of 32 in Polars.

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