Getting started

Clusterfun can be installed with pip:

pip install clusterfun

Clusterfun requires Python 3.8 or higher.

Plots accept data in the form of a pandas DataFrame, which will be installed automatically if not already present.

A simple example

import pandas as pd 
import clusterfun as clt

df = pd.read_csv("https://raw.githubusercontent.com/gietema/clusterfun-data/main/wiki-art.csv")
clt.scatter(df, x="x", y="y", media="img_path", color="painter")

As you can see, a clusterfun plot takes as input a pandas dataframe and column names indicating which columns to use for the visualisation. In this way, it is similar to the seaborn or the plotly library. But in clusterfun, you can:

• Click and drag to select data to visualise it in a grid
• Hover over data points to see them on the right side of the page
• Click on data points to view zoomed in versions of the image related to the data point

This makes clusterfun ideal for quickly visualising image data, which can be useful in the context of building datasets, exploring edge cases and debugging model performance.