pandas.Series.describe¶

Generate descriptive statistics that summarize the central tendency, dispersion and shape of a dataset’s distribution, excluding NaN values.

Analyzes both numeric and object series, as well as DataFrame column sets of mixed data types. The output will vary depending on what is provided. Refer to the notes below for more detail.

param percentiles

list-like of numbers, optional: The percentiles to include in the output. All should fall between 0 and 1. The default is [.25, .5, .75], which returns the 25th, 50th, and 75th percentiles.

param include

‘all’, list-like of dtypes or None (default), optional

A white list of data types to include in the result. Ignored for Series. Here are the options:

‘all’ : All columns of the input will be included in the output.
A list-like of dtypesLimits the results to the
provided data types. To limit the result to numeric types submit numpy.number. To limit it instead to object columns submit the numpy.object data type. Strings can also be used in the style of select_dtypes (e.g. df.describe(include=['O'])). To select pandas categorical columns, use 'category'
None (default) : The result will include all numeric columns.

param exclude

list-like of dtypes or None (default), optional,

A black list of data types to omit from the result. Ignored for Series. Here are the options:

A list-like of dtypesExcludes the provided data types
from the result. To exclude numeric types submit numpy.number. To exclude object columns submit the data type numpy.object. Strings can also be used in the style of select_dtypes (e.g. df.describe(include=['O'])). To exclude pandas categorical columns, use 'category'
None (default) : The result will exclude nothing.

return

Series or DataFrame Summary statistics of the Series or Dataframe provided.

Limitations¶

Parameters include and exclude are currently unsupported by Intel Scalable Dataframe Compiler.
For string Series resulting values are returned as strings.

Examples¶

Generate descriptive statistics.¶

import numpy as np
import pandas as pd
from numba import njit


@njit
def series_describe():
    s = pd.Series([5., 0, 3.3, 4.4, 9.2])

    return s.describe()


print(series_describe())

$ python ./series/series_describe.py
count    5.000000
mean     4.380000
std      3.315419
min      0.000000
25%      3.300000
50%      4.400000
75%      5.000000
max      9.200000
dtype: float64

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pandas.Series.describe¶

Limitations¶

Examples¶