analyze()

Analyze a dataset using the specified method.

Usage

analyze(
    data,
    method="mean",
)

Computes summary statistics on the input data using the chosen aggregation method. The result includes the computed value and metadata about the analysis.

Parameters

data: list

A list of numeric values to analyze.

method: str = "mean"

The aggregation method to use. One of "mean", "median", or "sum". Defaults to "mean".

Returns

dict

A dictionary with keys "value" (the computed result), "method" (the method used), and "count" (number of data points).

Raises

ValueError

If data is empty or method is not recognized.

TypeError

If data contains non-numeric values.

Notes

The mean is computed as the arithmetic mean. For large datasets, consider using chunked processing to avoid memory issues.

The implementation uses a simple single-pass algorithm:

\[ \bar{x} = \frac{1}{n} \sum_{i=1}^{n} x_i \]

Warnings

This function loads all data into memory. For datasets larger than available RAM, use a streaming approach instead.

References

1. Knuth, D. “The Art of Computer Programming”, Vol 2.
2. https://en.wikipedia.org/wiki/Arithmetic_mean

Examples

>>> analyze([1, 2, 3, 4, 5])
{'value': 3.0, 'method': 'mean', 'count': 5}

>>> analyze([10, 20, 30], method="sum")
{'value': 60, 'method': 'sum', 'count': 3}

See Also

• transform(): Transform data before analysis.