Array indexing and slicing in Data Analysis Python - Mini Project: Build & Apply

Array indexing and slicing

📖 Scenario: You work in a small bakery that tracks daily sales of different types of bread. You have a list of daily sales numbers for a week, and you want to analyze specific days or parts of the week.

🎯 Goal: Learn how to use array indexing and slicing to select specific sales data from a list.

📋 What You'll Learn

Create a list with exact daily sales numbers

Create a variable to select a specific day using indexing

Use slicing to select a range of days

Print the selected sales data

💡 Why This Matters

🌍 Real World

Selecting specific days' sales helps businesses analyze performance on particular days or periods.

💼 Career

Data analysts often use indexing and slicing to extract relevant data from larger datasets for reports and insights.

1

Create the daily sales list

Create a list called daily_sales with these exact values: 20, 35, 30, 25, 40, 50, 45 representing sales for each day of the week.

Data Analysis Python

# Create the daily_sales list with the exact values
# Your code here

Hint

Use square brackets [] to create a list and separate numbers with commas.

2

Select sales for Wednesday using indexing

Create a variable called wednesday_sales that gets the sales number for Wednesday from daily_sales using indexing. Remember, the list starts at index 0 for Monday.

Data Analysis Python

daily_sales = [20, 35, 30, 25, 40, 50, 45]
# Select Wednesday sales using indexing
# Your code here

Hint

Wednesday is the third day, so use index 2.

3

Select sales from Tuesday to Thursday using slicing

Create a variable called midweek_sales that slices daily_sales to get sales from Tuesday to Thursday (inclusive). Use slicing with the correct start and end indexes.

Data Analysis Python

daily_sales = [20, 35, 30, 25, 40, 50, 45]
wednesday_sales = daily_sales[2]
# Slice daily_sales from Tuesday to Thursday
# Your code here

Hint

Slicing includes the start index but excludes the end index.

4

Print the selected sales data

Print the variables wednesday_sales and midweek_sales to display the sales for Wednesday and the midweek range.

Data Analysis Python

daily_sales = [20, 35, 30, 25, 40, 50, 45]
wednesday_sales = daily_sales[2]
midweek_sales = daily_sales[1:4]
# Print wednesday_sales and midweek_sales
# Your code here

Hint

Use two print statements, one for each variable.

Practice

1. What does the expression arr[2] do when arr is a Python list?

easy

A. Returns the first two elements of the list

B. Removes the element at index 2 from the list

C. Returns a new list with elements from index 0 to 2

D. Returns the element at index 2 (third element) of the list

Solution

1. Step 1: Understand list indexing

   In Python, list indexing starts at 0, so index 2 means the third element.

2. Step 2: Identify what arr[2] returns

   This expression returns the single element at position 2, not a range or removal.

3. Final Answer:

   Returns the element at index 2 (third element) of the list -> Option D

4. Quick Check:

   Index 2 means third element [OK]

Hint: Indexing gets one element by position [OK]

Common Mistakes:

• Thinking slicing syntax is used for single element
• Confusing index 2 with first two elements
• Assuming it removes an element

2. Which of the following is the correct syntax to get a slice of a list lst from index 1 to 4 (excluding 4)?

easy

A. lst(1:4)

B. lst[1:4]

C. lst[1,4]

D. lst[1-4]

Solution

1. Step 1: Recall Python slice syntax

   Slicing uses square brackets with colon: start:stop, where stop is excluded.

2. Step 2: Check each option

   Only lst[1:4] uses correct slice syntax to get elements at indices 1, 2, 3.

3. Final Answer:

   lst[1:4] -> Option B

4. Quick Check:

   Slice syntax uses colon [OK]

Hint: Use colon inside brackets for slicing [OK]

Common Mistakes:

• Using comma instead of colon
• Using parentheses instead of brackets
• Using dash instead of colon

3. Given arr = [10, 20, 30, 40, 50], what is the output of arr[1:4]?

medium

A. [20, 30, 40]

B. [10, 20, 30, 40]

C. [30, 40, 50]

D. [20, 30, 40, 50]

Solution

1. Step 1: Understand slicing indices

   The slice arr[1:4] includes elements from index 1 up to but not including index 4.

2. Step 2: Extract elements at indices 1, 2, 3

   These are 20 (index 1), 30 (index 2), and 40 (index 3).

3. Final Answer:

   [20, 30, 40] -> Option A

4. Quick Check:

   Slice excludes stop index [OK]

Hint: Slice includes start, excludes stop index [OK]

Common Mistakes:

• Including element at stop index
• Confusing indices with values
• Off-by-one errors in slicing

4. What is wrong with this code snippet?

arr = [1, 2, 3, 4, 5]
print(arr[2:6])

medium

A. It will print elements from index 2 to 6 including index 6

B. It will cause an IndexError because 6 is out of range

C. It will print elements from index 2 to 5 without error

D. It will print only the element at index 6

Solution

1. Step 1: Understand slicing behavior with out-of-range stop

   Python slicing does not raise error if stop index is beyond list length; it stops at the list end.

2. Step 2: Check what arr[2:6] returns

   It returns elements from index 2 to the end (index 4), which are [3, 4, 5].

3. Final Answer:

   It will print elements from index 2 to 5 without error -> Option C

4. Quick Check:

   Slicing stop can exceed length safely [OK]

Hint: Slicing stop index can exceed list length safely [OK]

Common Mistakes:

• Expecting IndexError for slicing beyond length
• Thinking slice includes stop index
• Confusing slicing with indexing

5. You have a list data = [5, 10, 15, 20, 25, 30]. How do you get every second element starting from index 1 up to index 5?

hard

A. data[1:6:2]

B. data[1:5:2]

C. data[1:5]

D. data[::2]

Solution

1. Step 1: Understand slicing with step

   Slicing syntax is start:stop:step. To get every second element, step=2.

2. Step 2: Identify correct start and stop

   Start is 1, stop is 6 to include element at index 5 (stop excluded).

3. Step 3: Verify the slice

   data[1:6:2] returns elements at indices 1, 3, 5 -> [10, 20, 30].

4. Final Answer:

   data[1:6:2] -> Option A

5. Quick Check:

   Use step in slice for skipping elements [OK]

Hint: Use third slice value for step size [OK]

Common Mistakes:

• Using wrong stop index excluding last element
• Omitting step and getting all elements
• Confusing step with start or stop