Summary - Visualization

In this group you learned scatter, histogram, and line plots.

Summary: visualisation

In this group:

fig, ax = plt.subplots(); drawing on the axis, savefig on the figure.
Scatter: relationship of two variables, classes with c=y; the truth-prediction plot.
Histogram: single-variable distribution, bins, np.histogram.
Line: validation and learning curves.
Box: quartiles, median, outliers.

Give every plot a title and axis names; the reader may not know the context.

Exercise Two-panel figure

Open two axes with plt.subplots(1, 2): draw the histogram of x (bins=5) on the left and the scatter plot of y against x on the right, then save. Then print the correlation of x and y with round(..., 2).

Show example solution

import numpy as np
import matplotlib.pyplot as plt

rng = np.random.default_rng(1)
x = rng.normal(0, 1, 200)
y = 2 * x + rng.normal(0, 1, 200)

fig, (ax1, ax2) = plt.subplots(1, 2)
ax1.hist(x, bins=5)
ax2.scatter(x, y)
fig.savefig("panel.png")
print(round(np.corrcoef(x, y)[0, 1], 2))

Test yourself

Which plot best shows a feature's outliers and the difference between classes at the same time?
- A single line plot
- A pie chart
- A table
- A box plot per class
Show answer

A box plot per class — Side-by-side boxes show medians, spread and outliers together.

Create two axes side by side.

fig, (ax1, ax2) = plt.subplots(1, ____)

Show answer

fig, (ax1, ax2) = plt.subplots(1, 2)

Match the questions with the plots.

Are two variables related?

Scatter
How are the values distributed?

Histogram
How does the score change?

Line
How do the groups differ?

Box

Next lesson: Challenge 1

We Are Enhancing Your Experience

Cookie Preferences

Strictly Necessary Cookies

Analytical Cookies