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Questions and Answers
What is the default starting index in slicing notation?
What is the default starting index in slicing notation?
What is the purpose of advanced indexing?
What is the purpose of advanced indexing?
What is the result of the slice arr[1:5:2]?
What is the result of the slice arr[1:5:2]?
How do you access the first element of a NumPy array arr?
How do you access the first element of a NumPy array arr?
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What is the result of the advanced indexing arr[[1, 3, 5]]?
What is the result of the advanced indexing arr[[1, 3, 5]]?
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What is the purpose of boolean arrays in advanced indexing?
What is the purpose of boolean arrays in advanced indexing?
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Study Notes
Indexing
- NumPy arrays can be indexed using square brackets
[]and integers. - Indexing allows access to individual elements of an array.
- Indexing is 0-based, meaning the first element is at index 0.
- Example:
arr[0]accesses the first element of the arrayarr.
Slicing Notation
- Slicing allows access to a subset of elements in an array.
- Slicing notation:
arr[start:stop:step]-
start: starting index (inclusive), default is 0. -
stop: ending index (exclusive), default is the end of the array. -
step: increment between elements, default is 1.
-
- Examples:
-
arr[1:5]: gets elements at indices 1, 2, 3, and 4. -
arr[1:5:2]: gets elements at indices 1 and 3. -
arr[:5]: gets elements at indices 0, 1, 2, 3, and 4. -
arr[1:]: gets elements at indices 1 to the end of the array.
-
Advanced Indexing
- Advanced indexing allows access to elements using arrays of indices.
- Advanced indexing can be used to access elements in any dimension.
- Examples:
-
arr[[1, 3, 5]]: gets elements at indices 1, 3, and 5. -
arr[[1, 3], [2, 4]]: gets elements at indices (1, 2) and (3, 4) in a 2D array.
-
- Boolean arrays can also be used for advanced indexing.
-
arr[arr > 5]: gets elements that are greater than 5. -
arr[(arr > 5) & (arr < 10)]: gets elements that are greater than 5 and less than 10.
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Indexing
- NumPy arrays utilize square brackets
[]for indexing, enabling access to specific elements. - Indexing starts at 0, where the first element is positioned at index 0.
- Example for accessing the first element:
arr[0].
Slicing Notation
- Slicing is employed to retrieve a range or subset of elements from an array.
- Slicing syntax follows the format
arr[start:stop:step]:-
start: the index to begin from (inclusive), defaults to 0. -
stop: the index to end at (exclusive), defaults to the end of the array. -
step: the interval between indices, with a default value of 1.
-
- Examples of slicing:
-
arr[1:5]retrieves elements at indices 1 through 4. -
arr[1:5:2]accesses elements at index 1 and 3. -
arr[:5]extracts the first five elements (indices 0 to 4). -
arr[1:]yields all elements from index 1 to the end.
-
Advanced Indexing
- Advanced indexing permits selection of elements using multiple indices arrays.
- Applicable to any dimension of arrays, enhancing flexibility.
- Examples of advanced indexing:
-
arr[[1, 3, 5]]collects elements from indices 1, 3, and 5. -
arr[[1, 3], [2, 4]]selects elements from coordinates (1, 2) and (3, 4) in a 2D array.
-
- Boolean arrays can serve for advanced indexing:
-
arr[arr > 5]fetches elements exceeding the value of 5. -
arr[(arr > 5) & (arr < 10)]retrieves elements between 5 and 10, both limits exclusive.
-
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Description
Learn how to access and manipulate individual elements and subsets of NumPy arrays using indexing and slicing notation.
