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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

bookMultidimensional Indexing

Now that you are able to access elements in 1D arrays, it’s time to learn about indexing in higher-dimensional arrays.

2D Arrays Indexing

Let's first take a look at a 2D array example:

This is a 2x3 array, which means it consists of 2 1D arrays along axis 0, and each of these 1D arrays has 3 elements along axis 1.

The images below will clarify positive and negative indexing in 2D arrays:

As you can see, indexing along each of the axes is identical to indexing in 1D arrays.

Accessing Elements in 2D Arrays

In 1D arrays, we accessed elements by specifying the index of the element in square brackets. If we do the same in 2D arrays, we retrieve a 1D array at the specified index, which may be exactly what we need.

However, if we want to retrieve a particular element of an inner 1D array, we should specify the index of the 1D array (along axis 0) and the index of its element (along axis 1), e.g., array[0, 1]. We could also write array[0][1] as we do with Python list, but this is less efficient since it performs the search twice for each index instead of once.

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:


              
12345678910

            
import numpy as np
array_2d = np.array([[1, 2, 3], [4, 5, 6]])
# Accessing the first element (1D array) with positive index
print(array_2d[0])
print('-' * 7)
# Accessing the second element of the first 1D array with positive index
print(array_2d[0, 1])
print('-' * 7)
# Accessing the last element of the last 1D array with negative index
print(array_2d[-1, -1])
copy
Task
test

Swipe to show code editor

stock_prices contains simulated stock prices over five days for five different companies. Each row corresponds to a particular company, and each column corresponds to a particular day. Consequently, each element in the matrix represents the closing price of a certain company's stock on a given day.

Your task is the following:

  1. Retrieve all the stock prices of the first company over five days with a positive index.

  2. Retrieve the stock price of the third company on the second day with positive indices.

  3. Retrieve the stock price of the last company on the last day with negative indices.

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

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Thanks for your feedback!

Section 2. Chapter 2
toggle bottom row

bookMultidimensional Indexing

Now that you are able to access elements in 1D arrays, it’s time to learn about indexing in higher-dimensional arrays.

2D Arrays Indexing

Let's first take a look at a 2D array example:

This is a 2x3 array, which means it consists of 2 1D arrays along axis 0, and each of these 1D arrays has 3 elements along axis 1.

The images below will clarify positive and negative indexing in 2D arrays:

As you can see, indexing along each of the axes is identical to indexing in 1D arrays.

Accessing Elements in 2D Arrays

In 1D arrays, we accessed elements by specifying the index of the element in square brackets. If we do the same in 2D arrays, we retrieve a 1D array at the specified index, which may be exactly what we need.

However, if we want to retrieve a particular element of an inner 1D array, we should specify the index of the 1D array (along axis 0) and the index of its element (along axis 1), e.g., array[0, 1]. We could also write array[0][1] as we do with Python list, but this is less efficient since it performs the search twice for each index instead of once.

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:


              
12345678910

            
import numpy as np
array_2d = np.array([[1, 2, 3], [4, 5, 6]])
# Accessing the first element (1D array) with positive index
print(array_2d[0])
print('-' * 7)
# Accessing the second element of the first 1D array with positive index
print(array_2d[0, 1])
print('-' * 7)
# Accessing the last element of the last 1D array with negative index
print(array_2d[-1, -1])
copy
Task
test

Swipe to show code editor

stock_prices contains simulated stock prices over five days for five different companies. Each row corresponds to a particular company, and each column corresponds to a particular day. Consequently, each element in the matrix represents the closing price of a certain company's stock on a given day.

Your task is the following:

  1. Retrieve all the stock prices of the first company over five days with a positive index.

  2. Retrieve the stock price of the third company on the second day with positive indices.

  3. Retrieve the stock price of the last company on the last day with negative indices.

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 2
toggle bottom row

bookMultidimensional Indexing

Now that you are able to access elements in 1D arrays, it’s time to learn about indexing in higher-dimensional arrays.

2D Arrays Indexing

Let's first take a look at a 2D array example:

This is a 2x3 array, which means it consists of 2 1D arrays along axis 0, and each of these 1D arrays has 3 elements along axis 1.

The images below will clarify positive and negative indexing in 2D arrays:

As you can see, indexing along each of the axes is identical to indexing in 1D arrays.

Accessing Elements in 2D Arrays

In 1D arrays, we accessed elements by specifying the index of the element in square brackets. If we do the same in 2D arrays, we retrieve a 1D array at the specified index, which may be exactly what we need.

However, if we want to retrieve a particular element of an inner 1D array, we should specify the index of the 1D array (along axis 0) and the index of its element (along axis 1), e.g., array[0, 1]. We could also write array[0][1] as we do with Python list, but this is less efficient since it performs the search twice for each index instead of once.

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:


              
12345678910

            
import numpy as np
array_2d = np.array([[1, 2, 3], [4, 5, 6]])
# Accessing the first element (1D array) with positive index
print(array_2d[0])
print('-' * 7)
# Accessing the second element of the first 1D array with positive index
print(array_2d[0, 1])
print('-' * 7)
# Accessing the last element of the last 1D array with negative index
print(array_2d[-1, -1])
copy
Task
test

Swipe to show code editor

stock_prices contains simulated stock prices over five days for five different companies. Each row corresponds to a particular company, and each column corresponds to a particular day. Consequently, each element in the matrix represents the closing price of a certain company's stock on a given day.

Your task is the following:

  1. Retrieve all the stock prices of the first company over five days with a positive index.

  2. Retrieve the stock price of the third company on the second day with positive indices.

  3. Retrieve the stock price of the last company on the last day with negative indices.

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!

Now that you are able to access elements in 1D arrays, it’s time to learn about indexing in higher-dimensional arrays.

2D Arrays Indexing

Let's first take a look at a 2D array example:

This is a 2x3 array, which means it consists of 2 1D arrays along axis 0, and each of these 1D arrays has 3 elements along axis 1.

The images below will clarify positive and negative indexing in 2D arrays:

As you can see, indexing along each of the axes is identical to indexing in 1D arrays.

Accessing Elements in 2D Arrays

In 1D arrays, we accessed elements by specifying the index of the element in square brackets. If we do the same in 2D arrays, we retrieve a 1D array at the specified index, which may be exactly what we need.

However, if we want to retrieve a particular element of an inner 1D array, we should specify the index of the 1D array (along axis 0) and the index of its element (along axis 1), e.g., array[0, 1]. We could also write array[0][1] as we do with Python list, but this is less efficient since it performs the search twice for each index instead of once.

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:


              
12345678910

            
import numpy as np
array_2d = np.array([[1, 2, 3], [4, 5, 6]])
# Accessing the first element (1D array) with positive index
print(array_2d[0])
print('-' * 7)
# Accessing the second element of the first 1D array with positive index
print(array_2d[0, 1])
print('-' * 7)
# Accessing the last element of the last 1D array with negative index
print(array_2d[-1, -1])
copy
Task
test

Swipe to show code editor

stock_prices contains simulated stock prices over five days for five different companies. Each row corresponds to a particular company, and each column corresponds to a particular day. Consequently, each element in the matrix represents the closing price of a certain company's stock on a given day.

Your task is the following:

  1. Retrieve all the stock prices of the first company over five days with a positive index.

  2. Retrieve the stock price of the third company on the second day with positive indices.

  3. Retrieve the stock price of the last company on the last day with negative indices.

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