CSV Plotter - Simple Julia Visualization Tool

A simple, cross-platform Julia tool to visualize 2-column CSV data interactively.

Features

• Cross-platform: Works on Linux, Windows, and macOS
• Interactive plots: Supports interactive visualization
• Multiple plot types: Line, scatter, bar, and histogram plots
• Customizable: Set titles, axis labels, and dimensions
• Save capability: Export plots to image files
• Standalone executable: Can be compiled to run without Julia installed

Requirements

• Julia 1.8 or higher
• Required packages: ArgParse, CSV, DataFrames, Plots

Installation

Method 1: Clone and run directly

# Clone the repository
git clone https://github.com/IJ1TI/testDashboard.git
cd testDashboard

# Install dependencies (first time only)
julia --project -e 'using Pkg; Pkg.instantiate()'

# Run the plotter
julia --project csv_plotter.jl sample_data.csv

Method 2: Add as a package (optional)

using Pkg
Pkg.add(url="https://github.com/IJ1TI/testDashboard.git")

Method 3: Standalone Executable (No Julia Required)

Build a standalone executable that includes the Julia runtime:

# Clone the repository
git clone https://github.com/IJ1TI/testDashboard.git
cd testDashboard

# Install PackageCompiler (if not already installed)
julia -e 'using Pkg; Pkg.add("PackageCompiler")'

# Build the standalone executable
julia build_standalone.jl

# Run the executable (no Julia installation needed)
./csv_plotter sample_data.csv --title "My Plot"

Note: The standalone executable will be larger (~50-100MB) as it includes the Julia runtime.

Windows Standalone

:: Build
julia build_standalone.jl

:: Run
csv_plotter.exe data.csv --title "My Plot"

Linux/macOS Standalone

# Make executable
chmod +x csv_plotter

# Run
./csv_plotter data.csv --title "My Plot"

Usage

Basic usage

# Plot a CSV file with default settings
julia --project csv_plotter.jl data.csv

# With custom labels and title
julia --project csv_plotter.jl data.csv --xlabel "Time" --ylabel "Value" --title "My Data"

# As a scatter plot
julia --project csv_plotter.jl data.csv --type scatter

# Save plot to file
julia --project csv_plotter.jl data.csv --save plot.png

# Non-interactive mode
julia --project csv_plotter.jl data.csv --interactive false

Command-line options

Usage: julia csv_plotter.jl [filename.csv] [options]

Options:
    --xlabel XLABEL    Set x-axis label (default: "X")
    --ylabel YLABEL    Set y-axis label (default: "Y")
    --title TITLE      Set plot title (default: "CSV Data Plot")
    --type PLOT_TYPE   Set plot type: line, scatter, bar, histogram (default: line)
    --interactive      Use interactive backend (default: true)
    --save FILENAME    Save plot to file
    --width WIDTH      Plot width in pixels (default: 800)
    --height HEIGHT    Plot height in pixels (default: 600)
    --help             Show help

CSV Format

The CSV file must have exactly 2 columns. The first column is used for x-values, the second for y-values.

Example data.csv:

x,y
1,2
2,4
3,6
4,8
5,10

Backends

The tool automatically selects the best available backend:

1. GR (default): Fast, works well cross-platform
2. Plotly: Web-based interactive plots
3. PyPlot: Matplotlib-based plots

For best interactive experience, install the GR backend:

using Pkg
Pkg.add("GR")

Windows Setup

Option 1: Using Julia from command prompt

1. Install Julia from https://julialang.org/downloads/
2. Add Julia to PATH during installation
3. Open Command Prompt and navigate to the repository
4. Run the plotter as shown above

Option 2: Create a batch file

Create plot.bat:

@echo off
julia --project csv_plotter.jl %1 %2 %3 %4 %5 %6 %7 %8 %9

Then run:

plot.bat data.csv --title "My Plot"

Linux Setup

Install Julia

# Ubuntu/Debian
sudo apt install julia

# Fedora
sudo dnf install julia

# Arch Linux
sudo pacman -S julia

Create a shell script

Create csv-plot:

#!/bin/bash
julia --project "$(dirname "$0")/csv_plotter.jl" "$@"

Make it executable:

chmod +x csv-plot

Then run:

./csv-plot data.csv --title "My Plot"

Example Plots

Line plot (default)

julia --project csv_plotter.jl sample_data.csv --title "Linear Data"

Scatter plot

julia --project csv_plotter.jl sample_data.csv --type scatter --title "Scatter Plot"

Bar chart

julia --project csv_plotter.jl sample_data.csv --type bar --title "Bar Chart"

Histogram

julia --project csv_plotter.jl sample_data.csv --type histogram --ylabel "Frequency"

Building Standalone Executable

To create a standalone executable that runs without Julia installed:

Requirements for Building

• Julia 1.8+ (only needed for building, not for running the final executable)
• PackageCompiler.jl package

Build Steps

1. Install PackageCompiler (if not already installed):

   using Pkg
   Pkg.add("PackageCompiler")

2. Build the executable:

   julia build_standalone.jl

3. Run the executable:

   # Linux/macOS
   ./csv_plotter data.csv --title "My Plot"
   
   # Windows
   csv_plotter.exe data.csv --title "My Plot"

Notes

• The first build may take several minutes
• The executable will be ~50-100MB in size
• The executable includes the Julia runtime and all dependencies
• First run of the executable may take a few seconds to initialize

Troubleshooting

"Package not found" errors

Run:

using Pkg
Pkg.instantiate()

No plot window appears

Try specifying a different backend:

using Plots
plotly()  # or pyplot(), or gr()

CSV reading issues

Ensure your CSV has exactly 2 columns and uses commas as separators.

License

MIT License

Contributing

Feel free to submit issues and pull requests!