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📚 Python for Introductory Statistics
Chapters ▾
0. Why Learn Python?1. Introduction to Python2. Python Lists3. Python Syntax4. Python Loops5. Frequency Distributions and Graphs6. Measures of Center and Variation7. Measures of Position8. Discrete Probability Distributions9. Continuous Probability Distributions10. Confidence Intervals11. Hypothesis Testing12. Linear Regression and Correlation13. Analysis of Categorical Data14. Advanced Statistics TopicsAppendix 1: Python Installing StepsAppendix 2: Random Integer GeneratorAppendix 3: Counting, Permutations and CombinationsCode ReferencesResources

5.7 Scatter Plots

Watch demo video

A data set with a pair of quantitative variables can be displayed with a scatter plot.

Example: Age in years and the corresponding height in centimeters is given below. Draw a scatter plot.

age(yrs)Height(cm)
595
6100
7105
8107
9110
10115
  1. Click + Code
  2. Type import matplotlib.pyplot as plt
  3. Type x = [5,6,7,8,9,10]
  4. Type y = [95,100,105,107,110,115]
  5. Type plt.scatter(x,y)
  6. Type plt.suptitle('Scatter Plot Age vs Height')
  7. Type plt.xlabel('Age(yrs)')
  8. Type plt.ylabel('Height(cm)')
  9. Click play button
import matplotlib.pyplot as plt

x = [5,6,7,8,9,10]
y = [95,100,105,107,110,115]

plt.scatter(x,y)

plt.suptitle('Scatter Plot Age vs Height')
plt.xlabel('Age(yrs)')
plt.ylabel('Height(cm)')
Show expected output
Text(0, 0.5, 'Height(cm)')
Scatter plot titled Scatter Plot Age vs Height: six points rising steadily from (5, 95) to (10, 115); axes labeled Age(yrs) and Height(cm).

Adapted from Python for Introductory Statistics, by Simon Aman (Truman College, City Colleges of Chicago), licensed under CC BY 4.0. Changes were made: reformatted as an accessible XYZ web edition with live in-browser code cells. License: CC-BY-4.0.