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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?
- None, it must be specified
- 0 (correct)
- 1
- The end of the array
What is the purpose of advanced indexing?
What is the purpose of advanced indexing?
- To access individual elements of an array
- To access a subset of elements in an array
- To change the data type of an array
- To access elements using arrays of indices (correct)
What is the result of the slice arr[1:5:2]
?
What is the result of the slice arr[1:5:2]
?
- Elements at indices 0, 1, 2, 3, and 4
- Elements at indices 1 and 3 (correct)
- Elements at indices 1, 2, 3, and 4
- Elements at indices 1, 3, and 5
How do you access the first element of a NumPy array arr
?
How do you access the first element of a NumPy array arr
?
What is the result of the advanced indexing arr[[1, 3, 5]]
?
What is the result of the advanced indexing arr[[1, 3, 5]]
?
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.
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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