pylot-plotter 1.0.1

Pylot: A Simple Python Plotter

Pylot: A Simple Python Plotter

Plot CSV data instantly — no notebook, no boilerplate.

Open one or more CSV files, choose your X and Y columns, and plot — in seconds. Mix series across files, style each one independently, compute error metrics, and export publication-ready figures. Runs on Linux, Windows, and macOS.

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Install

pip install pylot-plotter

Then launch from anywhere:

pylot

Linux — the application menu entry is registered automatically on first launch.

Windows — run pylot-register once after installing to add a Start Menu shortcut (it also runs automatically on first launch):

pylot-register

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Quick start

1. File → Open CSV… (or drag-and-drop) — load one or more files.
2. Series tab — each row is an independent series. Pick X and Y columns from any loaded file, choose Line or Scatter, and hit Plot.
3. Appearance / Axes tabs — toggle grid, log scale, limits, fonts, and annotations.
4. Export tab — save as PNG, PDF, or SVG at any DPI.

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Features

Data loading

• Load multiple CSV files at once; auto-detects delimiters (comma, semicolon, tab, …)
• Inline preview table shows up to 1 000 rows per file
• Recent files menu (last 8 files) with one-click re-open
• Duplicate filenames get automatic (2), (3) suffixes so nothing overwrites

Series

• Per-series X / Y pickers — any column from any loaded file; cross-file pairs work as long as lengths match
• Line or Scatter per series, plus a right Y-axis option (Line (R) / Scatter (R))
• Drag rows to change plotting / legend order
• Add all columns — one click to plot every numeric column against the first column
• Duplicate a series (copies style and data selection in one click)
• Show / hide individual series without deleting them
• Color swatch in the table — click directly to change color without opening a dialog

Style (per series)

• Color, line style, line width, opacity
• Marker symbol: Circle, Square, Triangle, Diamond, Plus, Cross, Star, Point, or None
• Marker edge outline on / off
• Scatter point size

Appearance tab

• Grid lines, X / Y log scale, equal aspect ratio
• Custom axes W : H — control the plot box proportions independently of data units
• Reference lines — horizontal or vertical marker lines at any position, each with its own color / style / width / opacity
• Fill bands — shaded axhspan / axvspan regions with custom color and opacity; useful for tolerance bands or highlighted ranges

Axes tab

• Axis labels and title (#none to suppress any of them)
• Manual X / Y limits (blank = auto)
• Tick label size and tick count, controlled per-axis
• Font family picker (all system fonts, live preview in the plot)
• Legend: position, frame, show / hide
• Spine (border) width
• Text annotations — place styled text anywhere using axes coordinates (0 – 1) or data coordinates

Metrics tab (hidden by default)

• RMSD, MAE, MSE computed between any two numeric columns
• Works across files (same-length requirement)
• Add to plot checkbox injects each metric as a text annotation on the figure
• Per-metric annotation settings: position, font size / weight, color, alignment, units, decimal places

Enable the Metrics tab via the ⚙ button on the tab bar.

Export

• PNG, PDF, SVG with automatic extension management
• DPI control (72 – 600) for raster formats
• Transparent background (respected in the exported file)
• All export settings persist between sessions

App

• Publication-style defaults via SciencePlots (science, notebook) — DejaVu Serif, clean spines, no grid
• Undo / Redo (Ctrl+Z / Ctrl+Y) for series, reference lines, fill bands, and annotations — 20-level history
• Tab visibility — show / hide individual tabs via the ⚙ corner button; choice persists across sessions
• Window geometry, splitter position, and export settings all persist between sessions
• Reset view button on the plot toolbar — redraws from current settings, undoing any zoom / pan

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Keyboard shortcuts

Action	Shortcut
Open CSV	Ctrl+O
Undo	Ctrl+Z
Redo	Ctrl+Y
Quit	Ctrl+Q

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Requirements

• Python 3.9+
• PySide6 ≥ 6.5
• pandas ≥ 2.0
• matplotlib ≥ 3.7
• scienceplots ≥ 2.1
• qtawesome ≥ 1.3

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License

MIT