Bar chart color customization in Matplotlib - Mini Project: Build & Apply

Bar chart color customization

📖 Scenario: You work in a small bakery and want to show how many cakes you sold each day last week. You want to make a bar chart to show this clearly to your team.

🎯 Goal: Create a bar chart using matplotlib that shows the number of cakes sold each day. Customize the colors of the bars so that each day has a different color.

📋 What You'll Learn

Create a dictionary called sales with days of the week as keys and number of cakes sold as values.

Create a list called colors with a different color for each day.

Use matplotlib.pyplot.bar() to make a bar chart with the sales data and the colors list.

Display the bar chart with plt.show().

💡 Why This Matters

🌍 Real World

Businesses often use bar charts to show sales or performance data clearly to teams and customers.

💼 Career

Data analysts and scientists use color customization in charts to make reports easier to understand and visually appealing.

1

Create the sales data dictionary

Create a dictionary called sales with these exact entries: 'Monday': 20, 'Tuesday': 35, 'Wednesday': 30, 'Thursday': 25, 'Friday': 40, 'Saturday': 50, 'Sunday': 45.

Matplotlib

# Create the sales dictionary with days and cake counts
# Your code here

Hint

Use curly braces {} to create the dictionary with the exact days and numbers.

2

Create a list of colors for the bars

Create a list called colors with these exact color names in order: 'red', 'orange', 'yellow', 'green', 'blue', 'indigo', 'violet'.

Matplotlib

sales = {'Monday': 20, 'Tuesday': 35, 'Wednesday': 30, 'Thursday': 25, 'Friday': 40, 'Saturday': 50, 'Sunday': 45}
# Create the colors list with the 7 colors
# Your code here

Hint

Make sure the list has exactly these colors in this order.

3

Create the bar chart with colors

Import matplotlib.pyplot as plt. Use plt.bar() with the days from sales.keys(), the cake counts from sales.values(), and the colors list to set the bar colors.

Matplotlib

sales = {'Monday': 20, 'Tuesday': 35, 'Wednesday': 30, 'Thursday': 25, 'Friday': 40, 'Saturday': 50, 'Sunday': 45}
colors = ['red', 'orange', 'yellow', 'green', 'blue', 'indigo', 'violet']
import matplotlib.pyplot as plt
# Create the bar chart with plt.bar() using sales keys, sales values, and colors
# Your code here

Hint

Use plt.bar() with the color parameter set to the colors list.

4

Display the bar chart

Use plt.show() to display the bar chart you created.

Matplotlib

sales = {'Monday': 20, 'Tuesday': 35, 'Wednesday': 30, 'Thursday': 25, 'Friday': 40, 'Saturday': 50, 'Sunday': 45}
colors = ['red', 'orange', 'yellow', 'green', 'blue', 'indigo', 'violet']
import matplotlib.pyplot as plt
plt.bar(sales.keys(), sales.values(), color=colors)
# Show the bar chart
# Your code here

Hint

Call plt.show() to display the chart window.

Practice

1. What does the color parameter do in the plt.bar() function in matplotlib?

easy

A. It changes the color of the bars in the bar chart.

B. It changes the size of the bars.

C. It adds labels to the bars.

D. It changes the style of the axes.

Solution

1. Step 1: Understand the role of plt.bar()

   The plt.bar() function draws bars for a bar chart.

2. Step 2: Identify the color parameter effect

   The color parameter sets the color of the bars, either one color for all or a list for each bar.

3. Final Answer:

   It changes the color of the bars in the bar chart. -> Option A

4. Quick Check:

   color changes bar colors [OK]

Hint: Remember: color = bar colors in plt.bar() [OK]

Common Mistakes:

• Confusing color with size or labels
• Thinking color changes axes or grid
• Using color parameter outside plt.bar()

2. Which of the following is the correct syntax to set all bars to blue in a bar chart using matplotlib?

easy

A. plt.bar(x, height, bar_color='blue')

B. plt.bar(x, height, color='blue')

C. plt.bar(x, height, col='blue')

D. plt.bar(x, height, colors='blue')

Solution

1. Step 1: Recall the correct parameter name

   The parameter to set bar colors is color, not colors, col, or bar_color.

2. Step 2: Check the syntax for setting a single color

   Using color='blue' applies blue color to all bars.

3. Final Answer:

   plt.bar(x, height, color='blue') -> Option B

4. Quick Check:

   Use color parameter exactly [OK]

Hint: Use exact parameter name: color='colorname' [OK]

Common Mistakes:

• Using 'colors' instead of 'color'
• Using 'col' or 'bar_color' which are invalid
• Misspelling 'color' parameter

3. What will be the color of each bar in the following code?

import matplotlib.pyplot as plt
x = [1, 2, 3]
height = [4, 5, 6]
colors = ['red', 'green', 'blue']
plt.bar(x, height, color=colors)
plt.show()

medium

A. Bars will be red, green, and blue respectively.

B. Bars will be blue, green, and red respectively.

C. All bars will be red.

D. The code will cause an error.

Solution

1. Step 1: Understand color list usage in plt.bar()

   When a list of colors is passed to color, each bar gets the corresponding color in order.

2. Step 2: Match colors to bars

   Bars at x=1,2,3 get colors 'red', 'green', 'blue' respectively.

3. Final Answer:

   Bars will be red, green, and blue respectively. -> Option A

4. Quick Check:

   List of colors assigns colors in order [OK]

Hint: List colors in order to color bars individually [OK]

Common Mistakes:

• Assuming all bars get first color only
• Mixing order of colors
• Expecting error from list input

4. Identify the error in this code snippet that tries to color bars individually:

import matplotlib.pyplot as plt
x = [1, 2, 3]
height = [4, 5, 6]
colors = ['red', 'green']
plt.bar(x, height, color=colors)
plt.show()

medium

A. The colors list has fewer colors than bars, causing an error.

B. The colors list should be a tuple, not a list.

C. There is no error; the code runs fine.

D. The color parameter should be named colors.

Solution

1. Step 1: Check length of colors list vs bars

   There are 3 bars but only 2 colors provided.

2. Step 2: Understand matplotlib behavior

   Matplotlib allows a shorter list of colors and cycles through them to color bars.

3. Final Answer:

   There is no error; the code runs fine. -> Option C

4. Quick Check:

   Colors list cycles if shorter than bars [OK]

Hint: Matplotlib cycles colors if list shorter than bars [OK]

Common Mistakes:

• Using fewer colors than bars
• Wrong parameter name 'colors'
• Assuming matplotlib throws error on shorter color list

5. You want to create a bar chart with 5 bars where bars at even positions are blue and odd positions are orange. Which code correctly customizes the bar colors?

hard

A. colors = ['blue', 'orange', 'blue', 'orange', 'blue']
plt.bar(x, height, color=colors)

B. colors = ['blue', 'blue', 'orange', 'orange', 'blue']
plt.bar(x, height, color=colors)

C. colors = ['orange', 'orange', 'blue', 'blue', 'orange']
plt.bar(x, height, color=colors)

D. colors = ['orange', 'blue', 'orange', 'blue', 'orange']
plt.bar(x, height, color=colors)

Solution

1. Step 1: Identify bar positions and colors

   Positions: 1 (odd), 2 (even), 3 (odd), 4 (even), 5 (odd). Odd bars = orange, even bars = blue.

2. Step 2: Map colors to positions in list

   List must be ['orange', 'blue', 'orange', 'blue', 'orange'] to match positions.

3. Final Answer:

   colors = ['orange', 'blue', 'orange', 'blue', 'orange'] plt.bar(x, height, color=colors) -> Option D

4. Quick Check:

   Color list matches odd/even bar positions [OK]

Hint: Assign colors by position index for pattern [OK]

Common Mistakes:

• Swapping colors for odd/even positions
• Using wrong order in colors list
• Not matching list length to bars