polars Polars
Table of ContentsClose
1. Snippets
1.1. Cardinality
1.1.1. Total for column
for col in df.columns:
print(f"{col}: {df[col].n_unique()}")
1.1.2. Freq/count Group by unique in column
pl.Series(<col_name>, df[<col_name>]).value_counts()
1.1.3. Filter by value in a column
See Implement method for retrieving a single row by predicate · Issue #4675 · pola-rs/polars · GitHub
pl.Series("block_range", poop["block_range"]).value_counts().row(by_predicate=(pl.col("block_range")=="18070000")
1.2. Uniqueness
unique()on a lazy frame works nicely