Connected Scatterplot

A connected scatterplot is a line chart where each data point is shown by a circle or any type of marker. This section explains how to build a connected scatterplot with Python, using both the Matplotlib and the Seaborn libraries.

⏱ Quick start

# libraries
  import matplotlib.pyplot as plt
  import numpy as np
  import pandas as pd

  # data
  df = pd.DataFrame({
      'x_axis': range(1,10),
      'y_axis': np.random.randn(9)*80+range(1,10)

  # plot
  plt.plot('x_axis', 'y_axis', data=df, linestyle='-', marker='o')

⚠️ Two types of connected scatterplot

There are two types of connected scatterplot, and it often creates confusion.

The first is simply a lineplot with dots added on top of it. It takes as input 2 numeric variables only. The second shows the relationship between 2 numeric variables across time. It requires 3 numeric variables as input.

Confusing? Visit data-to-viz to clarify..

Seaborn logoConnected scatterplot with Seaborn

Building a connected scatterplot with Seaborn looks pretty much the same as for a line chart. It is made thanks to the lineplot() function.

Click the following images to get a long form tutorial on how to create a basic connected scatterplot with Seaborn, how to draw multiple groups and how to customize the lines and the markers.

Matplotlib logoConnected scatterplot with Matplotlib

As for scatterplots, Matplotlib will help us build a bubble plot thanks to the the plt.scatter() function. This function provides a s parameter allowing to pass a third variable that will be mapped to the markers size.

Cheatsheet: line customization with Matplotlib and the linestyle parameter.

Cheat sheet: line customization with matplotlib

Cheat sheet: line customization with matplotlib

Matplotlib logoBest python connected scatterplot examples

The web is full of astonishing charts made by awesome bloggers, (often using R). The Python graph gallery tries to display (or translate from R) some of the best creations and explain how their source code works. If you want to display your work here, please drop me a word or even better, submit a Pull Request!


👋 This document is a work by Yan Holtz. You can contribute on github, send me a feedback on twitter or subscribe to the newsletter to know when new examples are published! 🔥