Exercise 5 - Pandas Filtering and Sorting

• 🏆 20 points available
• ✏️ Last updated on 9/13/2022

▶️ First, run the code cell below to import unittest, a module used for 🧭 Check Your Work sections and the autograder.

🎯 Challenge 1: Import Pandas and NumPy¶

👇 Tasks¶

• ✔️ Import the following Python packages.
  1. pandas: Use alias pd.
  2. numpy: Use alias np.

🧭 Check Your Work¶

Run the code cell below to test your solution.

• ✔️ If the code cell runs without errors, you’re good to move on.
• ❌ If the code cell produces an error, review your code and fix any mistakes.

🎯 Challenge 2: Create a Pandas Series¶

👇 Tasks¶

• ✔️ Create a new Pandas Series named sample_series with the following four values: -20, -10, 10, 20

🚀 Hint¶

The code below creates a new Pandas Series with the values 1 and 2.

my_new_series = pd.Series([1, 2])

🧭 Check Your Work¶

Run the code cell below to test your solution.

• ✔️ If the code cell runs without errors, you’re good to move on.
• ❌ If the code cell produces an error, review your code and fix any mistakes.

🎯 Challenge 3: Create a Pandas DataFrame¶

👇 Tasks¶

• ✔️ You are given two lists - brands and rankings that contain the names of make-up products and the number of reviews on Sephora.com.
• ✔️ Using the two lists, create a new Pandas DataFrame named df_brands that has the following two columns:
  1. brand: Names of the brands
  2. ranking: Ranking of the brands
• ✔️ Note that the column names are singular.

🚀 Hint¶

The code below creates a new Pandas DataFrame from two series.

my_new_dataframe = pd.DataFrame({
    "column_one": my_series1,
    "column_two": my_series2
})

🔑 Expected Output¶

🧭 Check Your Work¶

Run the code cell below to test your solution.

• ✔️ If the code cell runs without errors, you’re good to move on.
• ❌ If the code cell produces an error, review your code and fix any mistakes.

Exercises using the Maven Toys Dataset¶

For the remainder of this exercise, you’ll be working with toy products data.

Data Source: Maven Analytics Datasets

📌 Load data¶

▶️ Run the code cell below to create a new DataFrame named df_products.

The table below describes the columns in df_products.

🎯 Challenge 4: Find the number of rows and columns¶

👇 Tasks¶

• ✔️ Store the number of rows in df_products to a new variable named num_rows.
• ✔️ Store the number of columns in df_products to a new variable named num_cols.
• ✔️ Use .shape, not len().

🧭 Check Your Work¶

Run the code cell below to test your solution.

• ✔️ If the code cell runs without errors, you’re good to move on.
• ❌ If the code cell produces an error, review your code and fix any mistakes.

🎯 Challenge 5: Find all games¶

👇 Tasks¶

• ✔️ Using df_products, find all products in the "Games" category (df_products["Product_Category"] == "Games").
• ✔️ Store the result to a new variable named df_games.
• ✔️ df_products should remain unaltered.

🔑 Expected Output of df_games¶

🧭 Check Your Work¶

Run the code cell below to test your solution.

• ✔️ If the code cell runs without errors, you’re good to move on.
• ❌ If the code cell produces an error, review your code and fix any mistakes.

🎯 Challenge 6: Find electronics with a product cost over $10¶

👇 Tasks¶

• ✔️ Using df_products, find all products that matches the following two conditions:
  1. in the "Electronics" category (df_products["Product_Category"] == "Electronics")
  2. and the product cost is over 10 dollars (df_products["Product_Cost"] > 10).
• ✔️ Store the result to a new variable named df_electronics_over_10.
• ✔️ df_products should remain unaltered.

🔑 Expected Output of df_electronics_over_10¶

🧭 Check Your Work¶

Run the code cell below to test your solution.

• ✔️ If the code cell runs without errors, you’re good to move on.
• ❌ If the code cell produces an error, review your code and fix any mistakes.

🎯 Challenge 7: Sort by Price in Descending Order¶

👇 Tasks¶

• ✔️ Sort df_products by price (Product_Price column) in descending order.
• ✔️ Store the sorted result to a new variable named df_sorted_by_price.
• ✔️ df_products should remain unaltered.

🧭 Check Your Work¶

Run the code cell below to test your solution.

• ✔️ If the code cell runs without errors, you’re good to move on.
• ❌ If the code cell produces an error, review your code and fix any mistakes.

🎯 Challenge 8: Sort by Product Category and Product Name¶

👇 Tasks¶

• ✔️ Sort df_products by product category in ascending order and then by product price in descending order for products within each category.
• ✔️ Store the sorted result to a new variable named df_sorted_by_category_price.
• ✔️ If two rows have the same product category and the same price, the order of those two rows doesn’t matter.
• ✔️ df_products should remain unaltered.

🔑 Sample Output of df_sorted_by_category_price¶

🧭 Check Your Work¶

Run the code cell below to test your solution.

• ✔️ If the code cell runs without errors, you’re good to move on.
• ❌ If the code cell produces an error, review your code and fix any mistakes.