#3 NumPy Indexing, Slicing & Array Functions: Master the Basics
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introduction to numpy - • #1 Introduction to Numpy | how to install ...
numpy part1 - • #2 Master NumPy Arrays: Create, Manage, an...
numpy part2 - • #3 NumPy Indexing, Slicing & Array Functio...
numpy part3 - • #4 Master Array Manipulation in NumPy: Tra...
numpy part4 - • #4 Master Array Manipulation in NumPy: Tra...
numpy part5 - • #6 Save & Load Data with NumPy: Effortless...
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Topics Covered:
Indexing and Slicing NumPy Arrays:
Learn how to access specific elements, slices, and subarrays within a NumPy array using indexing and slicing techniques.
How to Update Array Elements:
Discover how to update individual elements, multiple elements, and entire slices of a NumPy array.
Removing Elements from Arrays:
Explore methods to remove elements by index or condition using functions like np.delete.
Copying Arrays:
Understand the difference between shallow and deep copies, and how to create independent copies of your arrays using the copy method.
Returning Elements Based on Conditions:
Utilize boolean indexing to filter and return elements that meet specific conditions.
Finding Unique Elements:
Use the np.unique function to identify and extract unique elements from a NumPy array.
Sorting Arrays:
Learn how to sort arrays along different axes and with various sorting functions like np.sort and argsort.
Reshaping Arrays:
Master the reshape function to change the shape of your arrays, enabling you to convert between one-dimensional and multidimensional arrays.
Concatenating Arrays:
Combine arrays vertically and horizontally using functions such as np.concatenate, np.vstack, and np.hstack.
Example Code Snippets:
import numpy as np
Indexing and Slicing
arr = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
print("Original Array:\n", arr)
print("Element at [1, 2]:", arr[1, 2])
print("Sliced Array [0:2, 1:3]:\n", arr[0:2, 1:3])
Updating Array Elements
arr[0, 1] = 20
print("Updated Array:\n", arr)
Removing Elements from Arrays
arr = np.array([1, 2, 3, 4, 5])
arr = np.delete(arr, [1, 3])
print("Array after Deletion:\n", arr)
Copying Arrays
arr_copy = arr.copy()
print("Copied Array:\n", arr_copy)
Returning Elements Based on Conditions
arr = np.array([1, 2, 3, 4, 5])
filtered_arr = arr[arr == 2]
print("Filtered Array:\n", filtered_arr)
Finding Unique Elements
arr = np.array([1, 2, 2, 3, 4, 4, 5])
unique_elements = np.unique(arr)
print("Unique Elements:\n", unique_elements)
Sorting Arrays
arr = np.array([[3, 2, 1], [6, 5, 4]])
sorted_arr = np.sort(arr, axis=1)
print("Sorted Array:\n", sorted_arr)
Concatenating Arrays
arr1 = np.array([[1, 2], [3, 4]])
arr2 = np.array([[5, 6], [7, 8]])
concatenated_arr = np.concatenate((arr1, arr2), axis=0)
print("Vertically Concatenated Array:\n", concatenated_arr)
concatenated_arr = np.concatenate((arr1, arr2), axis=1)
print("Horizontally Concatenated Array:\n", concatenated_arr)
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