Vertical bar chart with plt.bar in Matplotlib - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a vertical bar chart using plt.bar.

Matplotlib

import matplotlib.pyplot as plt

categories = ['A', 'B', 'C']
values = [5, 7, 3]

plt.[1](categories, values)
plt.show()

Drag options to blanks, or click blank then click option'

Ascatter

Bplot

Cbar

Dhist

Attempts:

3 left

💡 Hint

Common Mistakes

Using plt.plot instead of plt.bar

Using plt.scatter which creates scatter plots

Using plt.hist which creates histograms

The plt.bar function creates a vertical bar chart using the categories and their values.

2fill in blank

medium

Complete the code to add labels to the x-axis of the bar chart.

Matplotlib

import matplotlib.pyplot as plt

categories = ['X', 'Y', 'Z']
values = [4, 6, 8]

plt.bar(categories, values)
plt.[1]('Categories')
plt.show()

Drag options to blanks, or click blank then click option'

Atitle

Bylabel

Clegend

Dxlabel

Attempts:

3 left

💡 Hint

Common Mistakes

Using plt.ylabel which labels the y-axis

Using plt.title which sets the chart title

Using plt.legend which adds a legend

The plt.xlabel function sets the label for the x-axis, which in this case are the categories.

3fill in blank

hard

Fix the error in the code to correctly display the bar chart with custom colors.

Matplotlib

import matplotlib.pyplot as plt

categories = ['P', 'Q', 'R']
values = [10, 15, 7]
colors = ['red', 'green', 'blue']

plt.bar(categories, values, [1]=colors)
plt.show()

Drag options to blanks, or click blank then click option'

Acolor

Bcolors

Ccol

Dcolour

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'colors' instead of 'color' parameter

Using British spelling 'colour'

Using 'col' which is not a valid parameter

The correct parameter name to set bar colors in plt.bar is color.

4fill in blank

hard

Fill both blanks to create a bar chart with a title and y-axis label.

Matplotlib

import matplotlib.pyplot as plt

categories = ['Jan', 'Feb', 'Mar']
values = [20, 25, 30]

plt.bar(categories, values)
plt.[1]('Monthly Sales')
plt.[2]('Sales')
plt.show()

Drag options to blanks, or click blank then click option'

Atitle

Bxlabel

Cylabel

Dlegend

Attempts:

3 left

💡 Hint

Common Mistakes

Using xlabel instead of ylabel for y-axis label

Using legend instead of title or ylabel

plt.title adds a title to the chart, and plt.ylabel labels the y-axis.

5fill in blank

hard

Fill all three blanks to create a bar chart with custom colors, x-axis label, and title.

Matplotlib

import matplotlib.pyplot as plt

categories = ['Red', 'Green', 'Blue']
values = [7, 3, 5]
colors = ['#FF0000', '#00FF00', '#0000FF']

plt.bar(categories, values, [1]=colors)
plt.[2]('Colors')
plt.[3]('Color Counts')
plt.show()

Drag options to blanks, or click blank then click option'

Acolor

Bxlabel

Ctitle

Dylabel

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'colors' instead of 'color' parameter

Mixing up xlabel and ylabel

Forgetting to add the title

Use color to set bar colors, xlabel to label the x-axis, and title to add a chart title.

Practice

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

easy

A. It creates a scatter plot with dots.

B. It creates a line chart connecting data points.

C. It creates a pie chart showing proportions.

D. It creates a vertical bar chart using categories and their values.

Solution

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

   The plt.bar() function is designed to draw vertical bars representing data values for different categories.

2. Step 2: Compare with other chart types

   Other functions like plt.plot() create line charts, plt.scatter() creates scatter plots, and plt.pie() creates pie charts, so they are different from plt.bar().

3. Final Answer:

   It creates a vertical bar chart using categories and their values. -> Option D

4. Quick Check:

   plt.bar() = vertical bar chart [OK]

Hint: Remember: bar = vertical bars for categories [OK]

Common Mistakes:

• Confusing bar chart with line or pie charts
• Thinking plt.bar() draws horizontal bars
• Mixing up plt.bar() with scatter plot functions

2. Which of the following is the correct syntax to create a vertical bar chart with categories ['A', 'B', 'C'] and values [5, 7, 3]?

easy

A. plt.bar(['A', 'B', 'C'], [5, 7, 3])

B. plt.bar([5, 7, 3], ['A', 'B', 'C'])

C. plt.bar('A', 5, 'B', 7, 'C', 3)

D. plt.bar([5, 7, 3])

Solution

1. Step 1: Identify correct parameter order for plt.bar()

   The first argument should be the categories (x-axis labels), and the second argument should be the heights (values).

2. Step 2: Check each option

   plt.bar(['A', 'B', 'C'], [5, 7, 3]) uses categories first and values second, which is correct. plt.bar([5, 7, 3], ['A', 'B', 'C']) reverses them, which is wrong. plt.bar('A', 5, 'B', 7, 'C', 3) uses multiple arguments incorrectly. plt.bar([5, 7, 3]) misses categories.

3. Final Answer:

   plt.bar(['A', 'B', 'C'], [5, 7, 3]) -> Option A

4. Quick Check:

   Categories first, values second in plt.bar() [OK]

Hint: Categories go first, values second in plt.bar() [OK]

Common Mistakes:

• Swapping categories and values order
• Passing multiple separate arguments instead of lists
• Omitting categories or values

3. What will be the height of the bar labeled 'B' in this code?

import matplotlib.pyplot as plt
categories = ['A', 'B', 'C']
values = [4, 9, 2]
plt.bar(categories, values)
plt.show()

medium

A. 9

B. Cannot determine

C. 2

D. 4

Solution

1. Step 1: Match categories with values

   The list categories is ['A', 'B', 'C'] and values is [4, 9, 2]. The bar for 'B' corresponds to the second value, 9.

2. Step 2: Confirm bar height for 'B'

   Since 'B' is the second category, its bar height is the second value, which is 9.

3. Final Answer:

   9 -> Option A

4. Quick Check:

   Bar 'B' height = 9 [OK]

Hint: Match category index to value index [OK]

Common Mistakes:

• Mixing up category and value positions
• Assuming bar height is category label
• Ignoring list order

4. Identify the error in this code that tries to plot a vertical bar chart:

import matplotlib.pyplot as plt
categories = ['X', 'Y', 'Z']
values = [3, 6]
plt.bar(categories, values)
plt.show()

medium

A. The categories list has fewer items than values list.

B. plt.bar() requires numeric categories, not strings.

C. The values list has fewer items than categories list.

D. plt.show() is missing.

Solution

1. Step 1: Compare lengths of categories and values

   The categories list has 3 items ['X', 'Y', 'Z'], but values list has only 2 items [3, 6]. This mismatch causes an error.

2. Step 2: Understand plt.bar() requirements

   Each category must have a corresponding value. Since values are fewer, matplotlib will raise a ValueError.

3. Final Answer:

   The values list has fewer items than categories list. -> Option C

4. Quick Check:

   Lengths must match: values shorter than categories [OK]

Hint: Check categories and values list lengths match [OK]

Common Mistakes:

• Ignoring length mismatch between categories and values
• Thinking categories must be numeric
• Forgetting plt.show()

5. You want to create a vertical bar chart showing sales for products ['Pen', 'Notebook', 'Eraser'] with sales [10, 15, 10]. You also want to highlight the product with the highest sales in red and others in blue. Which code correctly achieves this?

hard

A. plt.bar(['Pen', 'Notebook', 'Eraser'], [10, 15, 10], color='red')
plt.show()

B. colors = ['blue', 'red', 'blue']
plt.bar(['Pen', 'Notebook', 'Eraser'], [10, 15, 10], color=colors)
plt.show()

C. colors = ['red', 'blue', 'blue']
plt.bar(['Pen', 'Notebook', 'Eraser'], [10, 15, 10], color=colors)
plt.show()

D. plt.bar(['Pen', 'Notebook', 'Eraser'], [10, 15, 10])
plt.show()

Solution

1. Step 1: Identify highest sales product

   The sales are [10, 15, 10], so 'Notebook' has the highest sales (15).

2. Step 2: Assign colors to highlight highest sales

   We want 'Notebook' bar in red and others in blue. colors = ['blue', 'red', 'blue'] plt.bar(['Pen', 'Notebook', 'Eraser'], [10, 15, 10], color=colors) plt.show() sets colors as ['blue', 'red', 'blue'], matching the order of products.

3. Step 3: Check other options

   plt.bar(['Pen', 'Notebook', 'Eraser'], [10, 15, 10], color='red') plt.show() colors all bars red, not highlighting only highest. colors = ['red', 'blue', 'blue'] plt.bar(['Pen', 'Notebook', 'Eraser'], [10, 15, 10], color=colors) plt.show() colors 'Pen' red incorrectly. plt.bar(['Pen', 'Notebook', 'Eraser'], [10, 15, 10]) plt.show() uses default colors without highlight.

4. Final Answer:

   colors = ['blue', 'red', 'blue'] plt.bar(['Pen', 'Notebook', 'Eraser'], [10, 15, 10], color=colors) plt.show() -> Option B

5. Quick Check:

   Color list matches bars, red on highest sales [OK]

Hint: Use color list matching bars, red for highest [OK]

Common Mistakes:

• Coloring all bars same color
• Assigning wrong color order
• Not using color parameter