Saturday 4 May 2024

Streamgraphs using Python

 

Code:

import matplotlib.pyplot as plt

import numpy as np


x = np.linspace(0, 10, 100)

y1 = np.sin(x)

y2 = np.cos(x)


plt.stackplot(x, y1, y2, baseline='wiggle')

plt.title('Streamgraph')

plt.show()

Explanation: 

This code snippet creates a streamgraph using Matplotlib, a popular plotting library in Python. Let's break down the code:

Importing Libraries:

import matplotlib.pyplot as plt
import numpy as np
matplotlib.pyplot as plt: This imports the pyplot module of Matplotlib and assigns it the alias plt, which is a common convention.
numpy as np: This imports the NumPy library and assigns it the alias np. NumPy is commonly used for numerical computing in Python.
Generating Data:

x = np.linspace(0, 10, 100)
y1 = np.sin(x)
y2 = np.cos(x)
np.linspace(0, 10, 100): This creates an array x of 100 evenly spaced numbers between 0 and 10.
np.sin(x): This calculates the sine of each value in x, resulting in an array y1.
np.cos(x): This calculates the cosine of each value in x, resulting in an array y2.
Creating the Streamgraph:

plt.stackplot(x, y1, y2, baseline='wiggle')
plt.stackplot(x, y1, y2, baseline='wiggle'): This function creates a stack plot (streamgraph) with the x-values from x and the y-values from y1 and y2. The baseline='wiggle' argument specifies that the baseline for the stacked areas should be wiggled, which can help to visually separate the layers in the streamgraph.
Setting Title:

plt.title('Streamgraph')
plt.title('Streamgraph'): This sets the title of the plot to "Streamgraph".
Displaying the Plot:

plt.show()
plt.show(): This command displays the plot on the screen. Without this command, the plot would not be shown.
Overall, the code generates a streamgraph showing the variations of sine and cosine functions over the range of 0 to 10. The streamgraph visually represents how these functions change over the given range, with the wiggled baseline helping to distinguish between the layers.

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