modin.pandas.Series.describe¶

Series.describe(percentiles: ListLike | None = None, include: ListLike | Literal['all'] | None = None, exclude: ListLike | None = None) → Series[source]¶

Generate descriptive statistics.

For non-numeric datasets, computes count (# of non-null items), unique (# of unique items), top (the mode; the element at the lowest position if multiple), and freq (# of times the mode appears).

For numeric datasets, computes count (# of non-null items), mean, std, min, the specified percentiles, and max.

Parameters:

• percentiles (Optional[ListLike], default None) – The percentiles to compute for numeric columns. If unspecified, defaults to [0.25, 0.5, 0.75], which returns the 25th, 50th, and 75th percentiles. All values should fall between 0 and 1. The median (0.5) will always be added to the displayed percentile if not already included; the min and max are always displayed in addition to the percentiles.

• include (Optional[List[str, ExtensionDtype | np.dtype]] | "all", default None) – Ignored for Series.

• exclude (Optional[List[str, ExtensionDtype | np.dtype]], default None) – Ignored for Series.

Returns:

A series containing statistics for the dataset.

Return type:

Series

Examples

Describing numeric data:

>>> pd.Series([1, 2, 3]).describe()  
count    3.0
mean     2.0
std      1.0
min      1.0
25%      1.5
50%      2.0
75%      2.5
max      3.0
dtype: float64

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Describing non-numeric data:

>>> pd.Series(['a', 'b', 'c']).describe()  
count     3
unique    3
top       a
freq      1
dtype: object

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