DESCRIBE

Overview

The DESCRIBE function computes descriptive statistics of a dataset, including the number of elements, minimum and maximum values, mean, variance, skewness, and kurtosis. It is a wrapper for the scipy.stats.describe function, which provides a convenient summary of the central tendency, dispersion, and shape of a dataset’s distribution. This function is useful for quickly summarizing the main characteristics of a dataset in Excel. For more details, see the scipy.stats.describe documentation .

This function exposes the most commonly used parameters: the data array and an option to specify if the data is already flattened. The axis and nan_policy parameters are not exposed for simplicity. This example function is provided as-is without any representation of accuracy.

Usage

To use the function in Excel:


=DESCRIBE(data, [ddof], [bias])

data (2D list, required): Table of numeric values (float). Must have at least two rows and one column.
ddof (int, optional, default=0): Delta degrees of freedom for variance calculation.
bias (bool, optional, default=False): If True, calculations are corrected for statistical bias.

The function returns a 2D list with a single row containing the following values: [nobs, min, max, mean, variance, skewness, kurtosis], or an error message (list of strings) if the input is invalid.

Examples

Example 1: Basic Statistics

Inputs:

data			ddof	bias
1	2	3	0	FALSE
4	5	6

Excel formula:


=DESCRIBE({1,2,3;4,5,6}, 0, FALSE)

Expected output:

nobs	min	max	mean	variance	skewness	kurtosis
6	1	6	3.5	2.9167	0	-1.2

Example 2: With ddof=1

Inputs:

data			ddof	bias
1	2	3	1	FALSE
4	5	6

Excel formula:


=DESCRIBE({1,2,3;4,5,6}, 1, FALSE)

Expected output:

nobs	min	max	mean	variance	skewness	kurtosis
6	1	6	3.5	3.5	0	-1.2

Example 3: With bias correction

Inputs:

data			ddof	bias
1	2	3	0	TRUE
4	5	6

Excel formula:


=DESCRIBE({1,2,3;4,5,6}, 0, TRUE)

Expected output:

nobs	min	max	mean	variance	skewness	kurtosis
6	1	6	3.5	2.9167	0	-1.2686

Example 4: Different Data

Inputs:

data			ddof	bias
10	20	30	0	FALSE
40	50	60

Excel formula:


=DESCRIBE({10,20,30;40,50,60}, 0, FALSE)

Expected output:

nobs	min	max	mean	variance	skewness	kurtosis
6	10	60	35	291.6667	0	-1.2

This means the function returns a summary row with the main descriptive statistics for the input data.

Python Code


from scipy.stats import describe as scipy_describe
 
def describe(data, ddof=0, bias=False):
    """
    Compute descriptive statistics of a dataset: nobs, min, max, mean, variance, skewness, kurtosis.
 
    Args:
        data: 2D list of numbers (float), at least two rows and one column.
        ddof: Delta degrees of freedom for variance calculation (int, default: 0).
        bias: If True, calculations are corrected for statistical bias (bool, default: False).
 
    Returns:
        2D list with a single row: [nobs, min, max, mean, variance, skewness, kurtosis], or a list of strings if input is invalid.
 
    This example function is provided as-is without any representation of accuracy.
    """
    # Validate data
    if not isinstance(data, list) or len(data) < 2 or not isinstance(data[0], list):
        return [["Invalid input: data must be a 2D list with at least two rows."]]
    try:
        flat = [float(x) for row in data for x in row]
    except Exception:
        return [["Invalid input: data must contain only numbers."]]
    if len(flat) < 2:
        return [["Invalid input: data must contain at least two values."]]
    try:
        res = scipy_describe(flat, ddof=ddof, bias=bias)
    except Exception as e:
        return [[f"scipy.stats.describe error: {e}"]]
    # Prepare output row
    out = [
        int(res.nobs),
        float(res.minmax[0]),
        float(res.minmax[1]),
        float(res.mean),
        float(res.variance),
        float(res.skewness),
        float(res.kurtosis),
    ]
    return [out]

Live Demo

Example Workbook

Link to Workbook