polars.DataFrame.describe#

DataFrame.describe( percentiles: Sequence[float] | float | None = (0.25, 0.5, 0.75), *, interpolation: RollingInterpolationMethod = 'nearest', ) → DataFrame[source]#

Summary statistics for a DataFrame.

Parameters:

percentiles: One or more percentiles to include in the summary statistics. All values must be in the range [0, 1].
interpolation{‘nearest’, ‘higher’, ‘lower’, ‘midpoint’, ‘linear’}: Interpolation method used when calculating percentiles.

Warning

We do not guarantee the output of describe to be stable. It will show statistics that we deem informative, and may be updated in the future. Using describe programmatically (versus interactive exploration) is not recommended for this reason.

See also

glimpse

Notes

The median is included by default as the 50% percentile.

Examples

>>> from datetime import date, time
>>> df = pl.DataFrame(
...     {
...         "float": [1.0, 2.8, 3.0],
...         "int": [40, 50, None],
...         "bool": [True, False, True],
...         "str": ["zz", "xx", "yy"],
...         "date": [date(2020, 1, 1), date(2021, 7, 5), date(2022, 12, 31)],
...         "time": [time(10, 20, 30), time(14, 45, 50), time(23, 15, 10)],
...     }
... )

Show default frame statistics:

>>> df.describe()
shape: (9, 7)
┌────────────┬──────────┬──────────┬──────────┬──────┬────────────┬──────────┐
│ statistic  ┆ float    ┆ int      ┆ bool     ┆ str  ┆ date       ┆ time     │
│ ---        ┆ ---      ┆ ---      ┆ ---      ┆ ---  ┆ ---        ┆ ---      │
│ str        ┆ f64      ┆ f64      ┆ f64      ┆ str  ┆ str        ┆ str      │
╞════════════╪══════════╪══════════╪══════════╪══════╪════════════╪══════════╡
│ count      ┆ 3.0      ┆ 2.0      ┆ 3.0      ┆ 3    ┆ 3          ┆ 3        │
│ null_count ┆ 0.0      ┆ 1.0      ┆ 0.0      ┆ 0    ┆ 0          ┆ 0        │
│ mean       ┆ 2.266667 ┆ 45.0     ┆ 0.666667 ┆ null ┆ 2021-07-02 ┆ 16:07:10 │
│ std        ┆ 1.101514 ┆ 7.071068 ┆ null     ┆ null ┆ null       ┆ null     │
│ min        ┆ 1.0      ┆ 40.0     ┆ 0.0      ┆ xx   ┆ 2020-01-01 ┆ 10:20:30 │
│ 25%        ┆ 2.8      ┆ 40.0     ┆ null     ┆ null ┆ 2021-07-05 ┆ 14:45:50 │
│ 50%        ┆ 2.8      ┆ 50.0     ┆ null     ┆ null ┆ 2021-07-05 ┆ 14:45:50 │
│ 75%        ┆ 3.0      ┆ 50.0     ┆ null     ┆ null ┆ 2022-12-31 ┆ 23:15:10 │
│ max        ┆ 3.0      ┆ 50.0     ┆ 1.0      ┆ zz   ┆ 2022-12-31 ┆ 23:15:10 │
└────────────┴──────────┴──────────┴──────────┴──────┴────────────┴──────────┘

Customize which percentiles are displayed, applying linear interpolation:

>>> with pl.Config(tbl_rows=12):
...     df.describe(
...         percentiles=[0.1, 0.3, 0.5, 0.7, 0.9],
...         interpolation="linear",
...     )
shape: (11, 7)
┌────────────┬──────────┬──────────┬──────────┬──────┬────────────┬──────────┐
│ statistic  ┆ float    ┆ int      ┆ bool     ┆ str  ┆ date       ┆ time     │
│ ---        ┆ ---      ┆ ---      ┆ ---      ┆ ---  ┆ ---        ┆ ---      │
│ str        ┆ f64      ┆ f64      ┆ f64      ┆ str  ┆ str        ┆ str      │
╞════════════╪══════════╪══════════╪══════════╪══════╪════════════╪══════════╡
│ count      ┆ 3.0      ┆ 2.0      ┆ 3.0      ┆ 3    ┆ 3          ┆ 3        │
│ null_count ┆ 0.0      ┆ 1.0      ┆ 0.0      ┆ 0    ┆ 0          ┆ 0        │
│ mean       ┆ 2.266667 ┆ 45.0     ┆ 0.666667 ┆ null ┆ 2021-07-02 ┆ 16:07:10 │
│ std        ┆ 1.101514 ┆ 7.071068 ┆ null     ┆ null ┆ null       ┆ null     │
│ min        ┆ 1.0      ┆ 40.0     ┆ 0.0      ┆ xx   ┆ 2020-01-01 ┆ 10:20:30 │
│ 10%        ┆ 1.36     ┆ 41.0     ┆ null     ┆ null ┆ 2020-04-20 ┆ 11:13:34 │
│ 30%        ┆ 2.08     ┆ 43.0     ┆ null     ┆ null ┆ 2020-11-26 ┆ 12:59:42 │
│ 50%        ┆ 2.8      ┆ 45.0     ┆ null     ┆ null ┆ 2021-07-05 ┆ 14:45:50 │
│ 70%        ┆ 2.88     ┆ 47.0     ┆ null     ┆ null ┆ 2022-02-07 ┆ 18:09:34 │
│ 90%        ┆ 2.96     ┆ 49.0     ┆ null     ┆ null ┆ 2022-09-13 ┆ 21:33:18 │
│ max        ┆ 3.0      ┆ 50.0     ┆ 1.0      ┆ zz   ┆ 2022-12-31 ┆ 23:15:10 │
└────────────┴──────────┴──────────┴──────────┴──────┴────────────┴──────────┘