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Polars-readme-2.py(file creato)

@@ -0,0 +1,33 @@
1 + >>> df = pl.scan_csv("docs/assets/data/iris.csv")
2 + >>> ## OPTION 1
3 + >>> # run SQL queries on frame-level
4 + >>> df.sql("""
5 + ... SELECT species,
6 + ... AVG(sepal_length) AS avg_sepal_length
7 + ... FROM self
8 + ... GROUP BY species
9 + ... """).collect()
10 + shape: (3, 2)
11 + ┌────────────┬──────────────────┐
12 + │ species ┆ avg_sepal_length │
13 + │ --- ┆ --- │
14 + │ str ┆ f64 │
15 + ╞════════════╪══════════════════╡
16 + │ Virginica ┆ 6.588 │
17 + │ Versicolor ┆ 5.936 │
18 + │ Setosa ┆ 5.006 │
19 + └────────────┴──────────────────┘
20 + >>> ## OPTION 2
21 + >>> # use pl.sql() to operate on the global context
22 + >>> df2 = pl.LazyFrame({
23 + ... "species": ["Setosa", "Versicolor", "Virginica"],
24 + ... "blooming_season": ["Spring", "Summer", "Fall"]
25 + ...})
26 + >>> pl.sql("""
27 + ... SELECT df.species,
28 + ... AVG(df.sepal_length) AS avg_sepal_length,
29 + ... df2.blooming_season
30 + ... FROM df
31 + ... LEFT JOIN df2 ON df.species = df2.species
32 + ... GROUP BY df.species, df2.blooming_season
33 + ... """).collect()
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