Engaging plots, made easy.

Easily turn your data into engaging visualizations. Powerful API for coders. Powerful app for everyone.

main.py
notebook.ipynb
main.rs
from plotapi import Chord

Chord(matrix, names).show()

API for coders

Heat Map

Everything you need to create beautiful, engaging, and interactive Heat Map visualizations.


Importing PlotAPI Heat Map

Let’s import HeatMap from the PlotAPI package.

from plotapi import HeatMap

We’ve already activated our license with the license activation instructions.

Data structure

PlotAPI Heat Map expects a matrix (list[list[float]]) as input.

matrix = [
    [0, 5, 6, 4, 7, 4],
    [5, 0, 5, 4, 6, 5],
    [6, 5, 0, 4, 5, 5],
    [4, 4, 4, 0, 5, 5],
    [7, 6, 5, 5, 0, 4],
    [4, 5, 5, 5, 4, 0],
]

Optionally, we can include a list of row_names and col_names (list[str]).

row_names = ["Action", "Adventure", "Comedy", "Drama", "Fantasy", "Thriller"]
col_names = ["Action", "Adventure", "Comedy", "Drama", "Fantasy", "Thriller"]
Action Adventure Comedy Drama Fantasy Thriller
Action 0 5 6 4 7 4
Adventure 5 0 5 4 6 5
Comedy 6 5 0 4 5 5
Drama 4 4 4 0 5 5
Fantasy 7 6 5 5 0 4
Thriller 4 5 5 5 4 0

Default visualization

Creating our first Heat Map Diagram is as easy as calling PlotAPI with our inputs.

Be sure to interact with the visualisation to see what the default settings can do!

With row and column names

HeatMap(matrix, row_names=row_names, col_names=col_names).show()

Without row and column names

If we omit the row_names and col_names, Plotapi will auto-generate the names for us.

HeatMap(matrix).show()
PlotAPI - Heat Map Diagram
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