- Adding numpy arrays is like adding up all the elements to create a new array. It’s like throwing a party and the sum is the total buzz π.
- Subtracting numpy arrays is like taking away from one array with another to create a new ensemble. It’s like a showdown where one array wins and the other loses π₯.
- Multiplying numpy arrays is like creating a new array from the product of the original arrays. It’s like planting seeds and watching them grow into a beautiful garden π±π·.
- Dividing numpy arrays is like creating a new array from the quotient of the original arrays. It’s like sharing a cake equally among friends π°.
Adding Numpy Arrays
In this video, we will learn how we can easily perform arithmetic operations on NumPy arrays using the sum, subtract, multiply, and divide methods. First, let’s begin with adding NumPy arrays.
- Sum Method – Adds each element of both arrays, displaying the result in a new array.
- Adding Only Column Values – Adds only the column values of both arrays.
- Adding Individual Array Values – Differentiates between row and column values using the AIS parameter.
Example 1: Adding the Elements of NumPy Arrays
| N1 | N2 |
|---|---|
| 15 | 65 |
| 20 | 75 |
| 25 | 85 |
| 30 | 95 |
Example 2: Adding Only Column Values
| Output |
|---|
| 80 |
| 95 |
| 110 |
| 125 |
Example 3: Adding Individual Array Values
| Output |
|---|
| 90 |
| 320 |
Subtracting Numpy Arrays
The subtract method allows you to subtract one array from another and display the output in a new array.
Multiplying Numpy Arrays
By using the multiply method, the result of the multiplication will be displayed in a new array.
Dividing Numpy Arrays
The divide method divides the elements of one array with the elements of another, with the result displayed in a new array.
Key Takeaways
- Adding, subtracting, multiplying, and dividing NumPy arrays using the appropriate methods.
- Understanding the use of AIS parameter for adding individual array values.
In conclusion, this tutorial provides a comprehensive guide on performing arithmetic operations on NumPy arrays. Thank you for watching the video! π₯
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