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Ultimate NumPy
course content

Course Content

Ultimate NumPy

Ultimate NumPy

1. NumPy Basics
Introduction to NumPyBasic Array CreationCreating Higher Dimensional ArraysCreation Functions for 1D ArraysCreation Functions for 2D ArraysGeneral Array Creation FunctionsRandom Arrays
2. Indexing and Slicing
Basic IndexingMultidimensional IndexingSlicingSlicing in 2D ArraysInteger Array IndexingInteger Array Indexing in 2D ArraysBoolean IndexingMore about Comparisons Boolean Indexing in 2D ArraysAssigning Values to Indexed ElementsAssigning Values to Indexed Subarrays
3. Commonly used NumPy Functions
Sorting ArraysSorting 2D ArraysCopying ArraysReshaping ArraysFlattening ArraysArray Concatenation
4. Math with NumPy
BroadcastingBasic Mathematical OperationsStatistical OperationsBasic Linear Algebra with NumPy

bookBasic Indexing

Every NumPy array has elements and their respective indices. Here we will focus on indices in 1D arrays. Let's take a look at the following image:

Here we have an array of five elements: [9, 6, 4, 8, 10]. Every element has a positive and negative index. For example, 9 has 0 as its positive index and -5 as its negative index. As you can see, positive indexing in arrays starts at 0 and goes up to n-1, where n is the length of the array. Negative indexing, on the other hand, starts at -n and goes up to -1.

Accessing Elements by Indices

To access an element by its index, you should specify the index of this element in square brackets, e.g., array[2].

Note

If a specified index is out of bounds, an IndexError is thrown, so be cautious of that.

Let's take a look at an example:


              
1234567891011121314

            
import numpy as np
array = np.array([9, 6, 4, 8, 10])
# Accessing the first element (positive index)
print(f'The first element (positive index): {array[0]}')
# Accessing the first element (negative index)
print(f'The first element (negative index): {array[-5]}')
# Accessing the last element (positive index)
print(f'The last element (positive index): {array[4]}')
# Accessing the last element (negative index)
print(f'The last element (negative index): {array[-1]}')
# Accessing the third element (positive index)
print(f'The third element (positive index): {array[2]}')
# Accessing the third element (negative index)
print(f'The third element (negative index): {array[-3]}')
copy

As you can see, there is nothing complicated here.

Note

It is common practice to access the first element of the array using a positive index (0) and the last element using a negative index (-1).

Since the elements of our array are just numbers, we can perform all kinds of operations on them that we would do with regular numbers:


              
1234

            
import numpy as np
array = np.array([9, 6, 4, 8, 10])
# Finding the average between the first and the last element
print((array[0] + array[-1]) / 2)
copy

Here, we calculated the average of the first and the last elements of our array.

Task
test

Swipe to show code editor

Calculate the average of the first, fourth, and last elements:

  1. Use a positive index to access the first element.
  2. Use a positive index to access the fourth element.
  3. Use a negative index to access the last element.
  4. Calculate the average of these numbers.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 2. Chapter 1
toggle bottom row

bookBasic Indexing

Every NumPy array has elements and their respective indices. Here we will focus on indices in 1D arrays. Let's take a look at the following image:

Here we have an array of five elements: [9, 6, 4, 8, 10]. Every element has a positive and negative index. For example, 9 has 0 as its positive index and -5 as its negative index. As you can see, positive indexing in arrays starts at 0 and goes up to n-1, where n is the length of the array. Negative indexing, on the other hand, starts at -n and goes up to -1.

Accessing Elements by Indices

To access an element by its index, you should specify the index of this element in square brackets, e.g., array[2].

Note

If a specified index is out of bounds, an IndexError is thrown, so be cautious of that.

Let's take a look at an example:


              
1234567891011121314

            
import numpy as np
array = np.array([9, 6, 4, 8, 10])
# Accessing the first element (positive index)
print(f'The first element (positive index): {array[0]}')
# Accessing the first element (negative index)
print(f'The first element (negative index): {array[-5]}')
# Accessing the last element (positive index)
print(f'The last element (positive index): {array[4]}')
# Accessing the last element (negative index)
print(f'The last element (negative index): {array[-1]}')
# Accessing the third element (positive index)
print(f'The third element (positive index): {array[2]}')
# Accessing the third element (negative index)
print(f'The third element (negative index): {array[-3]}')
copy

As you can see, there is nothing complicated here.

Note

It is common practice to access the first element of the array using a positive index (0) and the last element using a negative index (-1).

Since the elements of our array are just numbers, we can perform all kinds of operations on them that we would do with regular numbers:


              
1234

            
import numpy as np
array = np.array([9, 6, 4, 8, 10])
# Finding the average between the first and the last element
print((array[0] + array[-1]) / 2)
copy

Here, we calculated the average of the first and the last elements of our array.

Task
test

Swipe to show code editor

Calculate the average of the first, fourth, and last elements:

  1. Use a positive index to access the first element.
  2. Use a positive index to access the fourth element.
  3. Use a negative index to access the last element.
  4. Calculate the average of these numbers.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 2. Chapter 1
toggle bottom row

bookBasic Indexing

Every NumPy array has elements and their respective indices. Here we will focus on indices in 1D arrays. Let's take a look at the following image:

Here we have an array of five elements: [9, 6, 4, 8, 10]. Every element has a positive and negative index. For example, 9 has 0 as its positive index and -5 as its negative index. As you can see, positive indexing in arrays starts at 0 and goes up to n-1, where n is the length of the array. Negative indexing, on the other hand, starts at -n and goes up to -1.

Accessing Elements by Indices

To access an element by its index, you should specify the index of this element in square brackets, e.g., array[2].

Note

If a specified index is out of bounds, an IndexError is thrown, so be cautious of that.

Let's take a look at an example:


              
1234567891011121314

            
import numpy as np
array = np.array([9, 6, 4, 8, 10])
# Accessing the first element (positive index)
print(f'The first element (positive index): {array[0]}')
# Accessing the first element (negative index)
print(f'The first element (negative index): {array[-5]}')
# Accessing the last element (positive index)
print(f'The last element (positive index): {array[4]}')
# Accessing the last element (negative index)
print(f'The last element (negative index): {array[-1]}')
# Accessing the third element (positive index)
print(f'The third element (positive index): {array[2]}')
# Accessing the third element (negative index)
print(f'The third element (negative index): {array[-3]}')
copy

As you can see, there is nothing complicated here.

Note

It is common practice to access the first element of the array using a positive index (0) and the last element using a negative index (-1).

Since the elements of our array are just numbers, we can perform all kinds of operations on them that we would do with regular numbers:


              
1234

            
import numpy as np
array = np.array([9, 6, 4, 8, 10])
# Finding the average between the first and the last element
print((array[0] + array[-1]) / 2)
copy

Here, we calculated the average of the first and the last elements of our array.

Task
test

Swipe to show code editor

Calculate the average of the first, fourth, and last elements:

  1. Use a positive index to access the first element.
  2. Use a positive index to access the fourth element.
  3. Use a negative index to access the last element.
  4. Calculate the average of these numbers.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Every NumPy array has elements and their respective indices. Here we will focus on indices in 1D arrays. Let's take a look at the following image:

Here we have an array of five elements: [9, 6, 4, 8, 10]. Every element has a positive and negative index. For example, 9 has 0 as its positive index and -5 as its negative index. As you can see, positive indexing in arrays starts at 0 and goes up to n-1, where n is the length of the array. Negative indexing, on the other hand, starts at -n and goes up to -1.

Accessing Elements by Indices

To access an element by its index, you should specify the index of this element in square brackets, e.g., array[2].

Note

If a specified index is out of bounds, an IndexError is thrown, so be cautious of that.

Let's take a look at an example:


              
1234567891011121314

            
import numpy as np
array = np.array([9, 6, 4, 8, 10])
# Accessing the first element (positive index)
print(f'The first element (positive index): {array[0]}')
# Accessing the first element (negative index)
print(f'The first element (negative index): {array[-5]}')
# Accessing the last element (positive index)
print(f'The last element (positive index): {array[4]}')
# Accessing the last element (negative index)
print(f'The last element (negative index): {array[-1]}')
# Accessing the third element (positive index)
print(f'The third element (positive index): {array[2]}')
# Accessing the third element (negative index)
print(f'The third element (negative index): {array[-3]}')
copy

As you can see, there is nothing complicated here.

Note

It is common practice to access the first element of the array using a positive index (0) and the last element using a negative index (-1).

Since the elements of our array are just numbers, we can perform all kinds of operations on them that we would do with regular numbers:


              
1234

            
import numpy as np
array = np.array([9, 6, 4, 8, 10])
# Finding the average between the first and the last element
print((array[0] + array[-1]) / 2)
copy

Here, we calculated the average of the first and the last elements of our array.

Task
test

Swipe to show code editor

Calculate the average of the first, fourth, and last elements:

  1. Use a positive index to access the first element.
  2. Use a positive index to access the fourth element.
  3. Use a negative index to access the last element.
  4. Calculate the average of these numbers.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Section 2. Chapter 1
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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