Error bar plots in Matplotlib - Mini Project: Build & Apply

Error Bar Plots

📖 Scenario: You are a scientist measuring the average heights of plants grown under different light conditions. You want to show the average height and the variability (error) in your measurements using an error bar plot.

🎯 Goal: Create an error bar plot that shows the average plant heights for three light conditions with their measurement errors.

📋 What You'll Learn

Create a dictionary called plant_heights with keys as light conditions and values as average heights

Create a dictionary called height_errors with keys as light conditions and values as error margins

Use matplotlib.pyplot.errorbar to plot the average heights with error bars

Label the x-axis as Light Condition and y-axis as Average Height (cm)

Display the plot with plt.show()

💡 Why This Matters

🌍 Real World

Scientists and engineers often measure data with some uncertainty. Error bar plots help show this uncertainty visually.

💼 Career

Data analysts and scientists use error bar plots to communicate data reliability and variability clearly in reports and presentations.

1

Create the plant heights data

Create a dictionary called plant_heights with these exact entries: 'Low': 15, 'Medium': 22, 'High': 30.

Matplotlib

# Create the plant_heights dictionary with exact values
# Your code here

Need a hint?

Use curly braces {} to create a dictionary with keys and values separated by colons.

2

Create the height errors data

Create a dictionary called height_errors with these exact entries: 'Low': 2, 'Medium': 3, 'High': 4.

Matplotlib

plant_heights = {'Low': 15, 'Medium': 22, 'High': 30}
# Create the height_errors dictionary with exact values
# Your code here

Need a hint?

Similar to Step 1, create a dictionary for the error values.

3

Plot the error bar graph

Import matplotlib.pyplot as plt. Use plt.errorbar with x as the list of light conditions, y as the list of average heights, and yerr as the list of errors from height_errors. Label the x-axis as 'Light Condition' and y-axis as 'Average Height (cm)'.

Matplotlib

plant_heights = {'Low': 15, 'Medium': 22, 'High': 30}
height_errors = {'Low': 2, 'Medium': 3, 'High': 4}
# Import matplotlib.pyplot as plt
# Use plt.errorbar to plot with error bars
# Label the axes
# Your code here

Need a hint?

Use list() to convert dictionary keys and values to lists for plotting.

The fmt='o' draws points, and capsize=5 adds caps to error bars.

4

Display the plot

Use plt.show() to display the error bar plot.

Matplotlib

import matplotlib.pyplot as plt

plant_heights = {'Low': 15, 'Medium': 22, 'High': 30}
height_errors = {'Low': 2, 'Medium': 3, 'High': 4}

x = list(plant_heights.keys())
y = list(plant_heights.values())
yerr = list(height_errors.values())

plt.errorbar(x, y, yerr=yerr, fmt='o', capsize=5)
plt.xlabel('Light Condition')
plt.ylabel('Average Height (cm)')
# Display the plot
# Your code here

Need a hint?

Call plt.show() to open the plot window.