Streamgraph

Streamgraph with `Matplotlib`

Matplotlib can build streamgraphs but there isn't any prebuilt function for it so be ready for quite a lot of code. 🍿

The process starts pretty much like for a stacked area graph. The baseline parameter of the stackplot() function is used to place groups around the X axis. The tricky part is to interpolate points between each value of the X axis to get the smooth visual. This is done thanks to the scipy.interpolate library.

Everything starts with a stacked area chart with a custom baseline

Apply some smoothing to get a stream chart

Some more smoothing control using grids

Customize the color palette

Custom colormap in a streamchart with a line chart

Change order of the lines

Smooth the chart

🔎 `stackplot()` function parameters→ see full doc

→ Description

The stackplot() function from matplotlib creates a stacked area plot. This type of plot is used to show how multiple variables change over time, with each variable stacked on top of the previous ones. It's particularly useful for visualizing the composition of a whole over time.

→ Arguments

Description

The x coordinates of the data points.

Possible values → array-like

Pass a 1D array-like object for the x-axis values. This is typically the time axis.

Code Example

import matplotlib.pyplot as plt
import numpy as np

x = np.arange(10)
y1 = np.random.rand(10)
y2 = np.random.rand(10)

fig, ax = plt.subplots(figsize=(10,10))
ax.stackplot(x, y1, y2)
plt.show()

More about the stackplot() function.

Best python streamchart 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!

A streamchart made with Python, Matplotlib and the scipy.stats package.

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Streamgraph with Matplotlib

🔎 stackplot() function parameters→ see full doc