Quick start

This guide presents the simplest path for using mespy: load a file, run a few basic statistics, create a plot, and, if needed, perform a linear fit.

If you want to study the function code and the mathematical meaning of the results, go directly to the Modules section. Each module collects the conceptual overview and the pages dedicated to individual public functions.

Main modules

io_utils handles CSV loading.
stats_utils collects the statistical functions.
plot_utils contains the visualization tools.
fit_utils contains the linear fit and its result type.

First workflow

from mespy import histogram, load_csv, variance

df = load_csv(
    "data/reference/test_misure.csv",
    rename_columns={"misura_n": "n", "lunghezza_mm": "lunghezza", "sigma_mm": "sigma"},
    required_columns=["n", "lunghezza", "sigma"],
    missing="drop",
)

var_l = variance(df["lunghezza"])
fig, ax = histogram(df["lunghezza"], title=f"Varianza = {var_l:.3f} mm^2")

How to navigate the docs

Start from the module landing page to see its purpose, imports, and internal links.
Then open the function page for its signature, parameters, return value, errors, and examples.
If you want to understand the input checks, consult Internal checks and helpers.

Examples