Indexing And Slicing In Numpy Array.
Table Of Contents:
- Numpy Indexing
- Numpy Slicing
(1) Numpy Indexing
Syntax:
array[start:end:steps]Parameters:
- Start: Starting position of the element
- End: Ending Position Of The Element
- Steps: Number Of Steps To Jump While Travelling.
Example-1:
data = np.array([1, 2, 3])
dataarray([1, 2, 3])data[0]1Note:
- It will select the value at index position ‘0’ which is ‘1’.
Example-2:
data[0:2]array([1, 2])Note:
- It will select the value from ‘0’ to (end_index -1) = (2 – 1) = 1.
Example-3:
data[1:]array([2, 3])Note:
- Here start index is ‘1’ and we did not mention the end index, hence default will be the last index value.
Example-4:
data[-2:]array([2, 3])Note:
- If we have a negative sign, it will travel from back to front.
- The last element index will be ‘-1’.
(2) Numpy Slicing
- You may want to take a section of your array or specific array elements to use in further analysis or additional operations.
- To do that, you’ll need to subset, slice, and/or index your arrays.
- If you want to select values from your array that fulfil certain conditions, it’s straightforward with NumPy.
Example-1:Numbers That Are Less Than 6.
a = np.array([[1 , 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]])
aarray([[ 1, 2, 3, 4],
[ 5, 6, 7, 8],
[ 9, 10, 11, 12]])print(a[a < 6])Output:
[1 2 3 4 5]Example-2:Numbers that are equal to or greater than 5
five_up = (a >= 5)
print(a[five_up])Output:
[ 5 6 7 8 9 10 11 12]Example-3: You can select elements that are divisible by 2:
divisible_by_2 = a[a%2==0]
print(divisible_by_2)Output:
[ 2 4 6 8 10 12]Example-4: Using Conditional Operator
c = a[(a > 2) & (a < 11)]
print(c)Output:
[ 3 4 5 6 7 8 9 10]Example-5: Using Logical Operator
five_up = (a > 5) | (a == 5)
print(five_up)Output:
[[False False False False]
[ True True True True]
[ True True True True]]Note:
- You can also make use of the logical operators & and | in order to return boolean values that specify whether or not the values in an array fulfil a certain condition.
- This can be useful with arrays that contain names or other categorical values.