tspellenckit 0.1.3

Time-series visualisation for multi-machine multi-sensor data

tspellenckit

Python toolkit for time-series visualisation and analysis of multi-machine, multi-sensor fleets.

Built for industrial telemetry data where each machine reports dozens of timestamped metrics, and where you need to quickly compare behaviour across machines, seasons, and sensors.

Features

• Multi-machine visualisation — one subplot per machine, overlaying multiple years on a shared calendar axis
• Column type detection — automatically identifies numeric, categorical and other column types in wide DataFrames
• Adaptive axis scaling — adaptive margins, filtering by date range or year
• More modules coming (anomaly detection, alerting, aggregations...)

Installation

pip install tspellenckit

Quick start

import tspellenckit as tsk

fig = tsk.vis_metric(
    df,
    "PORTEUR_VITESSE_AVANCEMENT",
    years_filter=[2024, 2025],
    period_filter=["06-01", "09-01"]
)
fig.savefig("speed.png", dpi=150)

Expected data format

A pandas DataFrame with a MultiIndex (SerialNumber, time), where each row is a timestamped reading for a given machine.