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Descriptive statistics on a dataset

Compute standard summary statistics on a dataset in one pass using numpy-ts reduction functions.

Building histograms

Use histogram to bin data into intervals and compute counts. This is the basis for visualizing distributions.

Correlation matrix with corrcoef

Compute the Pearson correlation coefficient matrix to understand relationships between variables.

Monte Carlo simulation

Use random sampling to estimate quantities that are difficult to compute analytically.

Weighted average

Compute a weighted mean when some observations carry more importance than others.

Working with NaN-safe reductions

Real datasets often contain missing values. Use the nan* family of functions to ignore NaN entries.