Rows and Columns Indexes in an Array
- Conclusion: If you want to get the 4th element from an array, you should extract the element that is present at index 3.
- Generalizing: If you want to get the nth element from an array, you should extract element that is present at index (n-1).
Positive Single Indexing in an Array
Say you have an array with elements: [10, 20, 30, 40] in it. You want to get the 3rd element from the array. Use square brackets ([ ]) and pass the index number (2 in this case) in that square brackets as you used to do for Python lists.
Now, what is the dimension of the array? Yep, it's 1!
Remember how we used to extract an element from a nested list in Python? No? No worries. You will remember once you jump to the below part.
Positive Single Indexing in Python Nested List
The below snippet will help you remember how to get one element from a Python nested list.
Positive Single Indexing in a NumPy Array
The array here is of dimension 2. You can compare Python nested list and a NumPy 2D array.
In NumPy 2D array, when you pass a single index in the square bracket, it will give you the entire row present at that index.
You can pass comma-separated values in the square bracket to get one element from a particular row and a particular column.
In the snippet shown here, num_arr[0, 0] will get you the element present at row indexed at 0 and column indexed at 0. Try num_arr[0][0] in your Notebook and see what you get.
Positive Index Intervals in a NumPy Array
You can use semicolon (:) while indexing to get slices of elements from NumPy array.
In the snippet, num_arr[0, 0:2] will get you the row indexed at 0 and the columns indexed from 0 (inclusive) to 2 (exclusive).
This is also known as slicing an array.
You can slice rows and columns as shown in the snippet.
In the snippet, num_arr[1:3, 2:4] will get you the rows starting from index 1 to rows ending at index 3 (exclusive, means excluding 3) i.e. row 1 and row 2, columns starting from index 2 and ending at index 4 (exclusive) i.e. column 2 and column 3.
