Course Content

NumPy in a Nutshell

1. Getting Started with NumPy

What is NumPy?Function array()Basic Array Creation Quiz

2. Dimensions in Arrays

1-D Arrays Mathematical Operations with 1-D Arrays 2-D Arrays 3-D Arrays Multidimensional Arrays Quiz

3. Indexing and Slicing

Access Array Elements Match Math Operations Access 2-D and 3-D Arrays Match the Slicing Negative Indexing Match the Indices Get One Dimensional Array Using Slice and Only Positive Indexes Get One Dimensional Array Using Only Negative Indexes

4. Important Functions

Reshaping Flattening Joining Sorting Arrays Copying Arrays

Copying Arrays

It's worth noting that NumPy offers various methods for duplicating arrays. In this section, we'll explore one of these methods, namely: .copy().

Note
The .copy() method creates a new array with the data from the original one.

Using the .copy() method:


              123456789
            
import numpy as np

arr = np.array([7, 43, 56, 123, 10, 3])
x = arr.copy()

arr[0] = 42

print(arr)
print(x)

Task

You have the following array: [12, 56, 78, 65, 1, 5].

You have to obtain the following arrays using the correct method: arr_1 = [11, 56, 78, 0, 1, 5] arr_2 = [12, 56, 78, 65, 1, 5]

Replace element 12 with 11, and element 65 with 0.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 4. Chapter 5

Copying Arrays

It's worth noting that NumPy offers various methods for duplicating arrays. In this section, we'll explore one of these methods, namely: .copy().

Note
The .copy() method creates a new array with the data from the original one.

Using the .copy() method:


              123456789
            
import numpy as np

arr = np.array([7, 43, 56, 123, 10, 3])
x = arr.copy()

arr[0] = 42

print(arr)
print(x)

Task

You have the following array: [12, 56, 78, 65, 1, 5].

You have to obtain the following arrays using the correct method: arr_1 = [11, 56, 78, 0, 1, 5] arr_2 = [12, 56, 78, 65, 1, 5]

Replace element 12 with 11, and element 65 with 0.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 4. Chapter 5

Copying Arrays

It's worth noting that NumPy offers various methods for duplicating arrays. In this section, we'll explore one of these methods, namely: .copy().

Note
The .copy() method creates a new array with the data from the original one.

Using the .copy() method:


              123456789
            
import numpy as np

arr = np.array([7, 43, 56, 123, 10, 3])
x = arr.copy()

arr[0] = 42

print(arr)
print(x)

Task

You have the following array: [12, 56, 78, 65, 1, 5].

You have to obtain the following arrays using the correct method: arr_1 = [11, 56, 78, 0, 1, 5] arr_2 = [12, 56, 78, 65, 1, 5]

Replace element 12 with 11, and element 65 with 0.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

It's worth noting that NumPy offers various methods for duplicating arrays. In this section, we'll explore one of these methods, namely: .copy().

Note
The .copy() method creates a new array with the data from the original one.

Using the .copy() method:


              123456789
            
import numpy as np

arr = np.array([7, 43, 56, 123, 10, 3])
x = arr.copy()

arr[0] = 42

print(arr)
print(x)

Task

You have the following array: [12, 56, 78, 65, 1, 5].

You have to obtain the following arrays using the correct method: arr_1 = [11, 56, 78, 0, 1, 5] arr_2 = [12, 56, 78, 65, 1, 5]

Replace element 12 with 11, and element 65 with 0.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Section 4. Chapter 5

Switch to desktop for real-world practiceContinue from where you are using one of the options below