Bar charts in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the library needed to create bar charts.

Data Analysis Python

import [1] as plt

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

Aseaborn

Bnumpy

Cpandas

Dmatplotlib.pyplot

Attempts:

3 left

💡 Hint

Common Mistakes

Importing pandas or numpy instead of matplotlib.pyplot.

Using seaborn without importing matplotlib.pyplot.

We use matplotlib.pyplot to create bar charts in Python.

2fill in blank

medium

Complete the code to create a simple bar chart from the data.

Data Analysis Python

plt.bar([1], [5, 7, 3])
plt.show()

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

A["X", "Y", "Z"]

B[1, 2, 3]

C["A", "B", "C"]

D[10, 20, 30]

Attempts:

3 left

💡 Hint

Common Mistakes

Using numbers as x-axis labels without meaning.

Using a list of values that does not match the bar heights.

The x-axis labels should be categorical names like ["A", "B", "C"] to match the bar heights.

3fill in blank

hard

Fix the error in the code to correctly label the bars.

Data Analysis Python

labels = ["Red", "Blue", "Green"]
values = [10, 15, 7]
plt.bar(range(len(values)), values)
plt.xticks([1], labels)
plt.show()

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

Arange(len(values))

Bvalues

Clabels

D[0, 1, 2]

Attempts:

3 left

💡 Hint

Common Mistakes

Passing labels instead of positions to plt.xticks.

Passing values instead of positions to plt.xticks.

The plt.xticks() function needs the positions of the bars, which is range(len(values)).

4fill in blank

hard

Fill both blanks to create a bar chart with custom colors and title.

Data Analysis Python

colors = [[1]]
plt.bar(["A", "B", "C"], [3, 6, 9], color=[2])
plt.title("[3]")
plt.show()

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

A["red", "green", "blue"]

B[3, 6, 9]

C["cyan", "magenta", "yellow"]

DBar Chart

Attempts:

3 left

💡 Hint

Common Mistakes

Using numbers instead of color names for colors.

Not adding a title or using a wrong type for title.

We use a list of color names for the color argument and add a title string.

5fill in blank

hard

Fill all three blanks to create a horizontal bar chart with labels and values.

Data Analysis Python

labels = ["Apple", "Banana", "Cherry"]
values = [10, 5, 8]
plt.barh([1], [2], color="orange")
plt.xlabel("[3]")
plt.show()

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

Alabels

Bvalues

CQuantity

Dcolors

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping labels and values in the barh function.

Not labeling the x-axis properly.

For horizontal bars, labels go on the y-axis and values on the x-axis. The xlabel describes the values.

Practice

1. What does a bar chart mainly help you do with data?

easy

A. See differences between groups using bars

B. Calculate exact averages of numbers

C. Show data as a continuous line

D. Display data in a table format

Solution

1. Step 1: Understand the purpose of bar charts

   Bar charts use bars to visually compare values across categories.

2. Step 2: Compare options to bar chart use

   Only See differences between groups using bars describes using bars to see differences between groups.

3. Final Answer:

   See differences between groups using bars -> Option A

4. Quick Check:

   Bar charts = Visual group comparison [OK]

Hint: Bar charts show group sizes as bars [OK]

Common Mistakes:

• Confusing bar charts with line charts
• Thinking bar charts show exact calculations
• Mixing bar charts with tables

2. Which of these is the correct way to create a vertical bar chart using matplotlib in Python?

easy

A. plt.plot(x, height)

B. plt.barh(x, height)

C. plt.bar(x, height)

D. plt.scatter(x, height)

Solution

1. Step 1: Recall matplotlib bar chart functions

   plt.bar() creates vertical bars; plt.barh() creates horizontal bars.

2. Step 2: Match function to vertical bars

   Only plt.bar(x, height) creates vertical bar charts.

3. Final Answer:

   plt.bar(x, height) -> Option C

4. Quick Check:

   Vertical bars use plt.bar() [OK]

Hint: Use plt.bar() for vertical bars [OK]

Common Mistakes:

• Using plt.barh() for vertical bars
• Confusing plt.plot() with bar charts
• Using plt.scatter() for bar charts

3. What will the following code display?

import matplotlib.pyplot as plt
categories = ['A', 'B', 'C']
values = [5, 3, 7]
plt.bar(categories, values)
plt.show()

medium

A. A vertical bar chart with bars for A=5, B=3, C=7

B. A horizontal bar chart with bars for A=5, B=3, C=7

C. A line chart connecting points A, B, C

D. An error because plt.bar() needs numeric x values

Solution

1. Step 1: Understand plt.bar() with categorical x

   plt.bar() accepts category labels as x and numeric heights as values.

2. Step 2: Analyze the code output

   It creates vertical bars labeled A, B, C with heights 5, 3, 7 respectively.

3. Final Answer:

   A vertical bar chart with bars for A=5, B=3, C=7 -> Option A

4. Quick Check:

   plt.bar(categories, values) = vertical bars [OK]

Hint: plt.bar() accepts category labels for x-axis [OK]

Common Mistakes:

• Thinking plt.bar() only accepts numbers for x
• Confusing vertical and horizontal bars
• Expecting a line chart from plt.bar()

4. The code below is meant to create a horizontal bar chart but it shows a vertical one instead. What is the error?

import matplotlib.pyplot as plt
labels = ['X', 'Y', 'Z']
values = [10, 20, 15]
plt.bar(labels, values)
plt.show()

medium

A. The labels list should be numeric, not strings

B. plt.show() must be called before plt.bar()

C. Values must be strings, not numbers

D. plt.bar() creates vertical bars; use plt.barh() for horizontal bars

Solution

1. Step 1: Identify the function used for bar charts

   plt.bar() creates vertical bars; plt.barh() creates horizontal bars.

2. Step 2: Find why chart is vertical

   Using plt.bar() causes vertical bars, so to get horizontal bars, plt.barh() is needed.

3. Final Answer:

   plt.bar() creates vertical bars; use plt.barh() for horizontal bars -> Option D

4. Quick Check:

   Horizontal bars need plt.barh() [OK]

Hint: Use plt.barh() for horizontal bars [OK]

Common Mistakes:

• Thinking labels must be numbers
• Swapping order of plt.show() and plt.bar()
• Using string values instead of numbers

5. You have sales data for 3 products: {'Product A': 30, 'Product B': 45, 'Product C': 25}. You want to create a bar chart showing these sales with product names on the x-axis and sales on the y-axis. Which code snippet correctly creates this chart with labels and a title?

hard

A. import matplotlib.pyplot as plt
sales = {'Product A': 30, 'Product B': 45, 'Product C': 25}
plt.barh(sales.values(), sales.keys())
plt.xlabel('Products')
plt.ylabel('Sales')
plt.title('Sales by Product')
plt.show()

B. import matplotlib.pyplot as plt
sales = {'Product A': 30, 'Product B': 45, 'Product C': 25}
plt.bar(sales.keys(), sales.values())
plt.xlabel('Products')
plt.ylabel('Sales')
plt.title('Sales by Product')
plt.show()

C. import matplotlib.pyplot as plt
sales = {'Product A': 30, 'Product B': 45, 'Product C': 25}
plt.plot(sales.keys(), sales.values())
plt.xlabel('Products')
plt.ylabel('Sales')
plt.title('Sales by Product')
plt.show()

D. import matplotlib.pyplot as plt
sales = {'Product A': 30, 'Product B': 45, 'Product C': 25}
plt.bar(sales.values(), sales.keys())
plt.xlabel('Products')
plt.ylabel('Sales')
plt.title('Sales by Product')
plt.show()

Solution

1. Step 1: Understand data and desired chart

   We want vertical bars with product names on x-axis and sales on y-axis.

2. Step 2: Check code snippets for correct bar chart

   import matplotlib.pyplot as plt sales = {'Product A': 30, 'Product B': 45, 'Product C': 25} plt.bar(sales.keys(), sales.values()) plt.xlabel('Products') plt.ylabel('Sales') plt.title('Sales by Product') plt.show() uses plt.bar() with keys as x and values as heights, plus labels and title correctly set.

3. Step 3: Identify errors in other options

   import matplotlib.pyplot as plt sales = {'Product A': 30, 'Product B': 45, 'Product C': 25} plt.barh(sales.values(), sales.keys()) plt.xlabel('Products') plt.ylabel('Sales') plt.title('Sales by Product') plt.show() uses plt.barh() but swaps x and y labels incorrectly. import matplotlib.pyplot as plt sales = {'Product A': 30, 'Product B': 45, 'Product C': 25} plt.plot(sales.keys(), sales.values()) plt.xlabel('Products') plt.ylabel('Sales') plt.title('Sales by Product') plt.show() uses plt.plot() which is a line chart. import matplotlib.pyplot as plt sales = {'Product A': 30, 'Product B': 45, 'Product C': 25} plt.bar(sales.values(), sales.keys()) plt.xlabel('Products') plt.ylabel('Sales') plt.title('Sales by Product') plt.show() swaps keys and values in plt.bar(), causing wrong axes.

4. Final Answer:

   Code that correctly creates the labeled vertical bar chart -> Option B

5. Quick Check:

   Keys on x, values on y with plt.bar() [OK]

Hint: Use plt.bar(keys, values) with labels and title [OK]

Common Mistakes:

• Swapping keys and values in plt.bar()
• Using plt.plot() instead of plt.bar()
• Mixing up plt.bar() and plt.barh() axes