Ranking charts in Matplotlib - Mini Project: Build & Apply

Ranking Charts with Matplotlib

📖 Scenario: You work for a small company that wants to see how their products rank in sales compared to each other. They want a simple chart that shows the ranking of each product by sales numbers.

🎯 Goal: You will create a ranking chart using matplotlib to visualize product sales rankings clearly.

📋 What You'll Learn

Create a dictionary with product names and their sales numbers

Create a variable to hold the number of top products to show

Use sorting and slicing to get the top products by sales

Create a horizontal bar chart showing product names and their sales

Display the chart with clear labels and title

💡 Why This Matters

🌍 Real World

Ranking charts help businesses quickly see which products or items perform best, making it easier to focus on popular items.

💼 Career

Data analysts and business intelligence professionals often create ranking charts to present sales or performance data clearly to stakeholders.

1

Create the sales data dictionary

Create a dictionary called product_sales with these exact entries: 'Laptop': 120, 'Smartphone': 300, 'Tablet': 150, 'Headphones': 90, 'Smartwatch': 80.

Matplotlib

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

Hint

Use curly braces {} to create a dictionary with keys as product names and values as sales numbers.

2

Set the number of top products to display

Create a variable called top_n and set it to 3 to show the top 3 products.

Matplotlib

product_sales = {'Laptop': 120, 'Smartphone': 300, 'Tablet': 150, 'Headphones': 90, 'Smartwatch': 80}
# Create the variable top_n and set it to 3
# Your code here

Hint

Just assign the number 3 to the variable top_n.

3

Get the top products by sales

Create a list called top_products that contains the top top_n products sorted by sales in descending order. Use sorted() with product_sales.items() and a lambda function to sort by sales.

Matplotlib

product_sales = {'Laptop': 120, 'Smartphone': 300, 'Tablet': 150, 'Headphones': 90, 'Smartwatch': 80}
top_n = 3
# Create top_products list with top_n products sorted by sales descending
# Your code here

Hint

Use sorted() with key=lambda x: x[1] and reverse=True to sort by sales descending, then slice with [:top_n].

4

Plot the ranking chart and display it

Use matplotlib.pyplot to create a horizontal bar chart of the top products. Extract product names and sales from top_products. Use plt.barh() to plot, set the title to 'Top 3 Product Sales', label the x-axis as 'Sales', and show the plot with plt.show().

Matplotlib

import matplotlib.pyplot as plt

product_names = [item[0] for item in top_products]
sales_values = [item[1] for item in top_products]

# Create a horizontal bar chart with plt.barh()
# Set title to 'Top 3 Product Sales'
# Label x-axis as 'Sales'
# Show the plot
# Your code here

Hint

Remember to reverse the lists to show the highest sales at the top in the horizontal bar chart.

Practice

1. What is the main purpose of a ranking chart in matplotlib?

easy

A. To display items ordered by their values from highest to lowest

B. To show random data points without any order

C. To plot data only on the x-axis without y-axis labels

D. To create 3D surface plots

Solution

1. Step 1: Understand ranking chart purpose

   Ranking charts are designed to show items sorted by their values, usually from highest to lowest.

2. Step 2: Compare options with definition

   Only To display items ordered by their values from highest to lowest correctly describes this purpose, while others describe unrelated chart types or features.

3. Final Answer:

   To display items ordered by their values from highest to lowest -> Option A

4. Quick Check:

   Ranking chart = ordered display [OK]

Hint: Ranking charts always sort data before plotting [OK]

Common Mistakes:

• Thinking ranking charts show unsorted data
• Confusing ranking charts with scatter plots
• Assuming ranking charts are 3D plots

2. Which of the following matplotlib code snippets correctly sorts data for a ranking chart?

easy

A. data_sorted = data.sort_values(ascending=False)

B. data_sorted = data.random_shuffle()

C. data_sorted = data.sort_index()

D. data_sorted = data.dropna()

Solution

1. Step 1: Identify sorting method for ranking

   Ranking charts require sorting values in descending order to rank from highest to lowest.

2. Step 2: Evaluate each option

   data_sorted = data.sort_values(ascending=False) uses sort_values(ascending=False) which sorts data correctly. Others either shuffle, sort by index, or drop missing values, which are unrelated.

3. Final Answer:

   data_sorted = data.sort_values(ascending=False) -> Option A

4. Quick Check:

   Sort values descending = correct sorting [OK]

Hint: Use sort_values(ascending=False) to rank highest first [OK]

Common Mistakes:

• Using sort_index instead of sort_values
• Shuffling data randomly before plotting
• Dropping data instead of sorting

3. What will be the output of this code snippet?

import matplotlib.pyplot as plt
values = [50, 20, 30]
labels = ['A', 'B', 'C']
plt.barh(labels, values)
plt.gca().invert_yaxis()
plt.show()

medium

A. A horizontal bar chart with 'C' at the top and 'A' at the bottom

B. A vertical bar chart with bars labeled A, B, C

C. A horizontal bar chart with 'A' at the top and 'C' at the bottom

D. An error because invert_yaxis() is invalid here

Solution

1. Step 1: Understand horizontal bar chart with invert_yaxis()

   The barh function plots horizontal bars with labels on y-axis. By default, y-axis starts from bottom.

2. Step 2: Effect of invert_yaxis()

   Calling invert_yaxis() flips the y-axis so the first label 'A' appears at the top, making ranking easier to read.

3. Final Answer:

   A horizontal bar chart with 'A' at the top and 'C' at the bottom -> Option C

4. Quick Check:

   invert_yaxis flips labels top-down [OK]

Hint: invert_yaxis() flips bars so top label is first [OK]

Common Mistakes:

• Thinking invert_yaxis() causes error
• Confusing horizontal with vertical bars
• Assuming labels order stays bottom-up

4. Identify the error in this ranking chart code:

import matplotlib.pyplot as plt
values = [10, 40, 30]
labels = ['X', 'Y', 'Z']
plt.barh(labels, values)
plt.show()

medium

A. plt.show() is missing

B. The bars are not sorted, so ranking is incorrect

C. barh() cannot plot horizontal bars

D. The labels list is missing one label

Solution

1. Step 1: Check if data is sorted for ranking

   The values are [10, 40, 30] but not sorted. Ranking charts require sorted data to show correct order.

2. Step 2: Confirm other parts are correct

   Labels match values count, barh is valid, and plt.show() is present. So only sorting is missing.

3. Final Answer:

   The bars are not sorted, so ranking is incorrect -> Option B

4. Quick Check:

   Ranking needs sorted data [OK]

Hint: Always sort values before plotting ranking charts [OK]

Common Mistakes:

• Ignoring sorting before plotting
• Assuming barh() plots vertical bars
• Forgetting plt.show()

5. You have a dictionary of sales data:

sales = {'Store A': 300, 'Store B': 450, 'Store C': 200, 'Store D': 450}

How can you create a ranking chart that correctly shows stores ranked by sales, with ties handled by alphabetical order, using matplotlib?

hard

A. Sort by sales ascending, then plot horizontal bars without inverting y-axis

B. Plot bars directly without sorting, then invert y-axis

C. Sort only by store name ascending, then plot vertical bars

D. Sort by sales descending, then by store name ascending, then plot horizontal bars with inverted y-axis

Solution

1. Step 1: Sort data by sales descending and store name ascending

   To handle ties, first sort by sales descending, then by store name ascending to break ties alphabetically.

2. Step 2: Plot horizontal bars and invert y-axis for ranking

   Plot sorted data with barh and call invert_yaxis() to show highest rank at top.

3. Final Answer:

   Sort by sales descending, then by store name ascending, then plot horizontal bars with inverted y-axis -> Option D

4. Quick Check:

   Sort by value desc + name asc + invert_yaxis = ranking [OK]

Hint: Sort by value desc and name asc, then invert y-axis [OK]

Common Mistakes:

• Not sorting by store name to break ties
• Plotting without sorting
• Using vertical bars without ranking logic