np.arange() for range arrays in NumPy - Mini Project: Build & Apply

Create and Use Arrays with np.arange()

📖 Scenario: You are working with daily temperatures recorded over a week. You want to create arrays representing days and temperature ranges to analyze the data easily.

🎯 Goal: Build arrays using np.arange() to represent days and temperature ranges, then print the arrays to see the results.

📋 What You'll Learn

Use np.arange() to create arrays

Create arrays with specific start, stop, and step values

Print the arrays to display the data

💡 Why This Matters

🌍 Real World

Scientists and analysts often need to create sequences of numbers to represent time, measurements, or ranges for experiments and data analysis.

💼 Career

Knowing how to create arrays with <code>np.arange()</code> is essential for data scientists and analysts to prepare and manipulate data efficiently.

1

Create an array of days using np.arange()

Import the numpy library as np. Then create an array called days using np.arange() that starts at 1 and ends at 8 (not including 8) to represent days 1 to 7.

NumPy

import numpy as np
# Create the days array using np.arange()
# Your code here

Hint

Use np.arange(start, stop) where stop is one more than the last day you want.

2

Create an array of temperatures from 20 to 30

Create an array called temps using np.arange() that starts at 20, ends at 31 (not including 31), with a step of 1 to represent temperatures from 20 to 30 degrees.

NumPy

import numpy as np
days = np.arange(1, 8)
# Create the temps array using np.arange() with step 1
# Your code here

Hint

Remember to include the step value as the third argument in np.arange().

3

Create an array of temperatures with step 0.5

Create an array called temps_half using np.arange() that starts at 20, ends at 22 (not including 22), with a step of 0.5 to represent temperatures increasing by half degrees.

NumPy

import numpy as np
days = np.arange(1, 8)
temps = np.arange(20, 31, 1)
# Create the temps_half array using np.arange() with step 0.5
# Your code here

Hint

Use a decimal number for the step to get half-degree increments.

4

Print all three arrays

Print the arrays days, temps, and temps_half each on a separate line to see their values.

NumPy

import numpy as np
days = np.arange(1, 8)
temps = np.arange(20, 31, 1)
temps_half = np.arange(20, 22, 0.5)
# Print the days, temps, and temps_half arrays
# Your code here

Hint

Use three separate print() statements, one for each array.

Practice

1. What does np.arange(3) produce?

easy

A. [0, 1, 2]

B. [1, 2, 3]

C. [0, 1, 2, 3]

D. [3]

Solution

1. Step 1: Understand default start value

   If only one number is given, np.arange starts from 0 by default.

2. Step 2: Identify stop value exclusion

   The stop value 3 is excluded, so the array includes 0, 1, 2.

3. Final Answer:

   [0, 1, 2] -> Option A

4. Quick Check:

   Start=0, stop=3 excluded, so [0,1,2] [OK]

Hint: Remember: stop value is NOT included in output [OK]

Common Mistakes:

• Including the stop value in the array
• Starting from 1 instead of 0
• Confusing step with stop

2. Which of these is the correct syntax to create an array from 2 to 6 (excluding 6) with step 1 using np.arange()?

easy

A. np.arange(6, 2, 1)

B. np.arange(2, 6, 0)

C. np.arange(2, 7)

D. np.arange(2, 6, 1)

Solution

1. Step 1: Check start, stop, and step order

   Start should be less than stop for positive step; step cannot be zero.

2. Step 2: Validate each option

   np.arange(2, 6, 1) uses start=2, stop=6, step=1 correctly. np.arange(6, 2, 1) reverses start and stop. np.arange(2, 7) sets stop=7, producing [2 3 4 5 6] which includes 6. np.arange(2, 6, 0) has step=0 which is invalid.

3. Final Answer:

   np.arange(2, 6, 1) -> Option D

4. Quick Check:

   Start=2, stop=6, step=1 is correct syntax [OK]

Hint: Step must not be zero; start < stop for positive step [OK]

Common Mistakes:

• Using zero as step value
• Reversing start and stop values
• Using wrong stop value

3. What is the output of this code?

import numpy as np
arr = np.arange(1, 10, 3)
print(arr)

medium

A. [1 4 7]

B. [1 3 6 9]

C. [1 2 3 4 5 6 7 8 9]

D. [3 6 9]

Solution

1. Step 1: Understand parameters of np.arange

   Start=1, stop=10 (excluded), step=3 means numbers start at 1 and increase by 3 until less than 10.

2. Step 2: Calculate values

   Values are 1, 4 (1+3), 7 (4+3). Next would be 10 which is excluded.

3. Final Answer:

   [1 4 7] -> Option A

4. Quick Check:

   Start=1, step=3, stop=10 excluded gives [1,4,7] [OK]

Hint: Add step repeatedly until reaching stop (excluded) [OK]

Common Mistakes:

• Including stop value 10
• Adding step incorrectly
• Confusing step with stop

4. What is wrong with this code?

import numpy as np
arr = np.arange(5, 2, 1)
print(arr)

medium

A. It raises a ValueError

B. It produces an empty array

C. It produces [5, 4, 3]

D. It produces [2, 3, 4, 5]

Solution

1. Step 1: Analyze start, stop, and step values

   Start=5, stop=2, step=1 means counting up from 5 to less than 2, which is impossible.

2. Step 2: Understand np.arange behavior

   Since step is positive but start > stop, no values satisfy condition, so result is empty array.

3. Final Answer:

   It produces an empty array -> Option B

4. Quick Check:

   Positive step with start > stop gives empty array [OK]

Hint: Positive step needs start < stop to produce values [OK]

Common Mistakes:

• Expecting reversed array without negative step
• Thinking it raises error
• Confusing start and stop order

5. You want to create an array starting at 10, decreasing by 2, stopping before 0. Which np.arange() call is correct?

hard

A. np.arange(0, 10, -2)

B. np.arange(10, 0, 2)

C. np.arange(10, 0, -2)

D. np.arange(0, 10, 2)

Solution

1. Step 1: Identify start, stop, and step for decreasing sequence

   Start=10, stop=0 (excluded), step must be negative to decrease.

2. Step 2: Check each option

   np.arange(10, 0, -2) uses step=-2 correctly. np.arange(10, 0, 2) has positive step, so no values. Options C and D start at 0, which is not desired.

3. Final Answer:

   np.arange(10, 0, -2) -> Option C

4. Quick Check:

   Decreasing sequence needs negative step [OK]

Hint: Use negative step to count down in np.arange [OK]

Common Mistakes:

• Using positive step for decreasing sequence
• Swapping start and stop values
• Starting at stop value instead of start