polars.Series.value_counts#
- Series.value_counts( ) DataFrame [source]#
Count the occurrences of unique values.
- Parameters:
- sort
Sort the output by count in descending order. If set to
False
(default), the order of the output is random.- parallel
Execute the computation in parallel.
Note
This option should likely not be enabled in a group by context, as the computation is already parallelized per group.
- name
Give the resulting count column a specific name; if
normalize
is True defaults to “proportion”, otherwise defaults to “count”.- normalize
If true gives relative frequencies of the unique values
- Returns:
- DataFrame
Mapping of unique values to their count.
Examples
>>> s = pl.Series("color", ["red", "blue", "red", "green", "blue", "blue"]) >>> s.value_counts() shape: (3, 2) ┌───────┬───────┐ │ color ┆ count │ │ --- ┆ --- │ │ str ┆ u32 │ ╞═══════╪═══════╡ │ red ┆ 2 │ │ green ┆ 1 │ │ blue ┆ 3 │ └───────┴───────┘
Sort the output by count and customize the count column name.
>>> s.value_counts(sort=True, name="n") shape: (3, 2) ┌───────┬─────┐ │ color ┆ n │ │ --- ┆ --- │ │ str ┆ u32 │ ╞═══════╪═════╡ │ blue ┆ 3 │ │ red ┆ 2 │ │ green ┆ 1 │ └───────┴─────┘