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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

bookMore about Comparisons

Most conditions you will use are comparisons, so it's important to discuss them in more detail. Comparisons are based on the following comparison operators:

  • > (greater than);
  • < (less than);
  • >= (greater than or equal to);
  • <= (less than or equal to);
  • == (equal to);
  • != (not equal to).

Moreover, you can combine multiple conditions and comparisons using the following logical operators:

  • & (logical and);
  • | (logical or).

If at least one of the conditions is True, then | returns True; otherwise, it returns False. If at least one of the conditions is False, then & returns False; otherwise, it returns True.

Note

Each condition should be put in parentheses () when combining them.

Don’t worry, here is an example to make everything clear:


              
1234567891011121314

            
import numpy as np
# Creating an array of integers from 1 to 10 inclusive
array = np.arange(1, 11)
# Retrieving elements greater than or equal to 5 AND less than 9
print(array[(array >= 5) & (array < 9)])
print('-' * 12)
# Retrieving elements less than or equal to 4 AND not equal to 2
print(array[(array != 2) & (array <= 4)])
print('-' * 12)
# Retrieving elements less than 3 OR equal to 8
print(array[(array < 3) | (array == 8)])
print('-' * 12)
# Retrieving elements between 2 inclusive AND 5 inclusive OR equal to 9
print(array[(array >= 2) & (array <= 5) | (array == 9)])
copy

Let's now take a look at the following visualization to understand the code better (purple squares represent the actual retrieved elements):

Task

You are analyzing the ratings of various products collected from customer feedback. The ratings are stored in a 1D NumPy array where each element represents the rating of a product. Your task is to filter out the ratings that are greater than or equal to 3 AND not equal to 5 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 8
toggle bottom row

bookMore about Comparisons

Most conditions you will use are comparisons, so it's important to discuss them in more detail. Comparisons are based on the following comparison operators:

  • > (greater than);
  • < (less than);
  • >= (greater than or equal to);
  • <= (less than or equal to);
  • == (equal to);
  • != (not equal to).

Moreover, you can combine multiple conditions and comparisons using the following logical operators:

  • & (logical and);
  • | (logical or).

If at least one of the conditions is True, then | returns True; otherwise, it returns False. If at least one of the conditions is False, then & returns False; otherwise, it returns True.

Note

Each condition should be put in parentheses () when combining them.

Don’t worry, here is an example to make everything clear:


              
1234567891011121314

            
import numpy as np
# Creating an array of integers from 1 to 10 inclusive
array = np.arange(1, 11)
# Retrieving elements greater than or equal to 5 AND less than 9
print(array[(array >= 5) & (array < 9)])
print('-' * 12)
# Retrieving elements less than or equal to 4 AND not equal to 2
print(array[(array != 2) & (array <= 4)])
print('-' * 12)
# Retrieving elements less than 3 OR equal to 8
print(array[(array < 3) | (array == 8)])
print('-' * 12)
# Retrieving elements between 2 inclusive AND 5 inclusive OR equal to 9
print(array[(array >= 2) & (array <= 5) | (array == 9)])
copy

Let's now take a look at the following visualization to understand the code better (purple squares represent the actual retrieved elements):

Task

You are analyzing the ratings of various products collected from customer feedback. The ratings are stored in a 1D NumPy array where each element represents the rating of a product. Your task is to filter out the ratings that are greater than or equal to 3 AND not equal to 5 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 8
toggle bottom row

bookMore about Comparisons

Most conditions you will use are comparisons, so it's important to discuss them in more detail. Comparisons are based on the following comparison operators:

  • > (greater than);
  • < (less than);
  • >= (greater than or equal to);
  • <= (less than or equal to);
  • == (equal to);
  • != (not equal to).

Moreover, you can combine multiple conditions and comparisons using the following logical operators:

  • & (logical and);
  • | (logical or).

If at least one of the conditions is True, then | returns True; otherwise, it returns False. If at least one of the conditions is False, then & returns False; otherwise, it returns True.

Note

Each condition should be put in parentheses () when combining them.

Don’t worry, here is an example to make everything clear:


              
1234567891011121314

            
import numpy as np
# Creating an array of integers from 1 to 10 inclusive
array = np.arange(1, 11)
# Retrieving elements greater than or equal to 5 AND less than 9
print(array[(array >= 5) & (array < 9)])
print('-' * 12)
# Retrieving elements less than or equal to 4 AND not equal to 2
print(array[(array != 2) & (array <= 4)])
print('-' * 12)
# Retrieving elements less than 3 OR equal to 8
print(array[(array < 3) | (array == 8)])
print('-' * 12)
# Retrieving elements between 2 inclusive AND 5 inclusive OR equal to 9
print(array[(array >= 2) & (array <= 5) | (array == 9)])
copy

Let's now take a look at the following visualization to understand the code better (purple squares represent the actual retrieved elements):

Task

You are analyzing the ratings of various products collected from customer feedback. The ratings are stored in a 1D NumPy array where each element represents the rating of a product. Your task is to filter out the ratings that are greater than or equal to 3 AND not equal to 5 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!

Most conditions you will use are comparisons, so it's important to discuss them in more detail. Comparisons are based on the following comparison operators:

  • > (greater than);
  • < (less than);
  • >= (greater than or equal to);
  • <= (less than or equal to);
  • == (equal to);
  • != (not equal to).

Moreover, you can combine multiple conditions and comparisons using the following logical operators:

  • & (logical and);
  • | (logical or).

If at least one of the conditions is True, then | returns True; otherwise, it returns False. If at least one of the conditions is False, then & returns False; otherwise, it returns True.

Note

Each condition should be put in parentheses () when combining them.

Don’t worry, here is an example to make everything clear:


              
1234567891011121314

            
import numpy as np
# Creating an array of integers from 1 to 10 inclusive
array = np.arange(1, 11)
# Retrieving elements greater than or equal to 5 AND less than 9
print(array[(array >= 5) & (array < 9)])
print('-' * 12)
# Retrieving elements less than or equal to 4 AND not equal to 2
print(array[(array != 2) & (array <= 4)])
print('-' * 12)
# Retrieving elements less than 3 OR equal to 8
print(array[(array < 3) | (array == 8)])
print('-' * 12)
# Retrieving elements between 2 inclusive AND 5 inclusive OR equal to 9
print(array[(array >= 2) & (array <= 5) | (array == 9)])
copy

Let's now take a look at the following visualization to understand the code better (purple squares represent the actual retrieved elements):

Task

You are analyzing the ratings of various products collected from customer feedback. The ratings are stored in a 1D NumPy array where each element represents the rating of a product. Your task is to filter out the ratings that are greater than or equal to 3 AND not equal to 5 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 8
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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