Using sviewgui: A PyQt5 GUI Tool for Interactive Matplotlib and Seaborn Plotting with PDF Export

Today we share a PyQt5 GUI tool called sviewgui that allows users to create plots with Python's Matplotlib or Seaborn simply by dragging the mouse, and then export the results as high‑resolution PDFs.

Installation

pip install sviewgui

Basic Usage

The library provides a single method, buildGUI() , to launch the graphical interface.

import sviewgui.sview as sv
sv.buildGUI()

After launching, the interface guides the user through three steps to read a tips.csv file.

Data Import Methods

Method 1: Drag‑and‑drop the CSV file into the GUI.

Method 2: Provide an absolute file path. import sviewgui.sview as sv sv.buildGUI('Desktop/jobs/py/sviewgui/tips.csv') # pass the path to tips.csv

Method 3: Load the data with pandas and pass the DataFrame. import sviewgui.sview as sv import pandas as pd df = pd.read_csv('Desktop/jobs/py/sviewgui/tips.csv') sv.buildGUI(df)

Once the data is loaded, users can drag fields onto the canvas to generate plots. The generated plot can be viewed in the log panel, where the underlying Python code is displayed and can be copied for further refinement.

If the default plot style is unsatisfactory, the code from the log can be edited in a Python environment to improve aesthetics. The tutorial also demonstrates switching to a different Seaborn theme, resulting in a more polished visual appearance.

Key Features

Simple one‑line GUI launch.

Three flexible data‑loading options.

Interactive drag‑and‑drop plotting.

Export to high‑resolution PDF.

Access to generated Python code for further customization.