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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

bookBoolean Indexing in 2D Arrays

Boolean indexing in 2D and higher-dimensional arrays works similarly to 1D arrays. However, the boolean array must have the same number of dimensions as the initial array (e.g., 2D for two-dimensional arrays). The returned array, however, will be 1D.

Here is an example:


              
12345678

            
import numpy as np
array_2d = np.array([
   [1, 2, 3],
   [4, 5, 6],
   [7, 8, 9]
])
# Retrieving elements less than 3 or greater than OR greater than or equal to 8
print(array_2d[(array_2d < 3) | (array_2d >= 8)])
copy

Let’s visualize it:

The boolean array on the right is the resulting boolean array of these two combined conditions. Once again, purple elements match the conditions, and green elements don’t. So when applying array_2d[(array_2d < 3) | (array_2d >= 8)], we get a 1D array of purple elements.

Task

You are analyzing the temperatures recorded in two different cities over four days. The temperatures are stored in the city_temperatures array where each row represents a city and each column represents a day. Your task is to include only the temperatures that are less than or equal to 15 degrees OR greater than 30 degrees Celsius using boolean indexing.

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Section 2. Chapter 9
toggle bottom row

bookBoolean Indexing in 2D Arrays

Boolean indexing in 2D and higher-dimensional arrays works similarly to 1D arrays. However, the boolean array must have the same number of dimensions as the initial array (e.g., 2D for two-dimensional arrays). The returned array, however, will be 1D.

Here is an example:


              
12345678

            
import numpy as np
array_2d = np.array([
   [1, 2, 3],
   [4, 5, 6],
   [7, 8, 9]
])
# Retrieving elements less than 3 or greater than OR greater than or equal to 8
print(array_2d[(array_2d < 3) | (array_2d >= 8)])
copy

Let’s visualize it:

The boolean array on the right is the resulting boolean array of these two combined conditions. Once again, purple elements match the conditions, and green elements don’t. So when applying array_2d[(array_2d < 3) | (array_2d >= 8)], we get a 1D array of purple elements.

Task

You are analyzing the temperatures recorded in two different cities over four days. The temperatures are stored in the city_temperatures array where each row represents a city and each column represents a day. Your task is to include only the temperatures that are less than or equal to 15 degrees OR greater than 30 degrees Celsius using boolean indexing.

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 9
toggle bottom row

bookBoolean Indexing in 2D Arrays

Boolean indexing in 2D and higher-dimensional arrays works similarly to 1D arrays. However, the boolean array must have the same number of dimensions as the initial array (e.g., 2D for two-dimensional arrays). The returned array, however, will be 1D.

Here is an example:


              
12345678

            
import numpy as np
array_2d = np.array([
   [1, 2, 3],
   [4, 5, 6],
   [7, 8, 9]
])
# Retrieving elements less than 3 or greater than OR greater than or equal to 8
print(array_2d[(array_2d < 3) | (array_2d >= 8)])
copy

Let’s visualize it:

The boolean array on the right is the resulting boolean array of these two combined conditions. Once again, purple elements match the conditions, and green elements don’t. So when applying array_2d[(array_2d < 3) | (array_2d >= 8)], we get a 1D array of purple elements.

Task

You are analyzing the temperatures recorded in two different cities over four days. The temperatures are stored in the city_temperatures array where each row represents a city and each column represents a day. Your task is to include only the temperatures that are less than or equal to 15 degrees OR greater than 30 degrees Celsius using boolean indexing.

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!

Boolean indexing in 2D and higher-dimensional arrays works similarly to 1D arrays. However, the boolean array must have the same number of dimensions as the initial array (e.g., 2D for two-dimensional arrays). The returned array, however, will be 1D.

Here is an example:


              
12345678

            
import numpy as np
array_2d = np.array([
   [1, 2, 3],
   [4, 5, 6],
   [7, 8, 9]
])
# Retrieving elements less than 3 or greater than OR greater than or equal to 8
print(array_2d[(array_2d < 3) | (array_2d >= 8)])
copy

Let’s visualize it:

The boolean array on the right is the resulting boolean array of these two combined conditions. Once again, purple elements match the conditions, and green elements don’t. So when applying array_2d[(array_2d < 3) | (array_2d >= 8)], we get a 1D array of purple elements.

Task

You are analyzing the temperatures recorded in two different cities over four days. The temperatures are stored in the city_temperatures array where each row represents a city and each column represents a day. Your task is to include only the temperatures that are less than or equal to 15 degrees OR greater than 30 degrees Celsius using boolean indexing.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Section 2. Chapter 9
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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