unique

unique(data, columns=None, group_by=None)

Check if there are no duplicated values in each one of the selected columns.

This is a column oriented check, where each columns are search independently for duplicated values. For a row oriented check see unique_combination_of_columns

Parameters

data: PolarsLazyOrDataFrame: The input DataFrame to check for unique values.
columns: Optional[PolarsColumnType] = None: Columns to consider for uniqueness check. By default, all columns are checked.
group_by: Optional[PolarsOverClauseInput] = None: Use this option to ensure uniqueness with data segmented by group. by default None

Returns

Name	Type	Description
	PolarsLazyOrDataFrame	The original polars DataFrame or LazyFrame when the check passes

Examples

>>> import polars as pl
>>> import pelage as plg
>>> df = pl.DataFrame({"a": [1, 2]})
>>> df.pipe(plg.unique, "a")  # Can also use ["a", ...], pl.col("a)
shape: (2, 1)
┌─────┐
│ a   │
│ --- │
│ i64 │
╞═════╡
│ 1   │
│ 2   │
└─────┘

>>> df = pl.DataFrame({"a": [1, 1, 2]})
>>> df.pipe(plg.unique, "a")
Traceback (most recent call last):
...
pelage.types.PolarsAssertError: Details
shape: (2, 1)
┌─────┐
│ a   │
│ --- │
│ i64 │
╞═════╡
│ 1   │
│ 1   │
└─────┘
Error with the DataFrame passed to the check function:
--> Somes values are duplicated within the specified columns

Below are examples with group_by option:

>>> df = pl.DataFrame(
...     [
...         [1, 1, 1],
...         [1, 1, 2],
...     ],
...     schema=["col1", "col2", "group"],
...     orient="row",
... )
>>> df.pipe(plg.unique, ["col1", "col2"], group_by="group")
shape: (2, 3)
┌──────┬──────┬───────┐
│ col1 ┆ col2 ┆ group │
│ ---  ┆ ---  ┆ ---   │
│ i64  ┆ i64  ┆ i64   │
╞══════╪══════╪═══════╡
│ 1    ┆ 1    ┆ 1     │
│ 1    ┆ 1    ┆ 2     │
└──────┴──────┴───────┘

>>> df = pl.DataFrame(
...     [
...         [1, 1, 1],
...         [1, 1, 1],
...         [1, 1, 2],
...     ],
...     schema=["col1", "col2", "group"],
...     orient="row",
... )
>>> df.pipe(plg.unique, ["col1", "col2"], group_by="group")
Traceback (most recent call last):
...
pelage.types.PolarsAssertError: Details
shape: (2, 3)
┌──────┬──────┬───────┐
│ col1 ┆ col2 ┆ group │
│ ---  ┆ ---  ┆ ---   │
│ i64  ┆ i64  ┆ i64   │
╞══════╪══════╪═══════╡
│ 1    ┆ 1    ┆ 1     │
│ 1    ┆ 1    ┆ 1     │
└──────┴──────┴───────┘
Error with the DataFrame passed to the check function:
--> Somes values are duplicated within the specified columns