Uploaded November 2025 | Updated September 2026, 2 weeks ago
#python #coding #programming
00:00:00 zeros()
00:01:29 ones()
00:01:52 full()
00:02:16 eye()
00:03:09 empty()
00:03:59 arange()
00:05:16 linspace()
import numpy as np
# Creates an array with zeros
array = np.zeros((2, 3, 10))
print(array)
# Creates an array with ones
array = np.ones((2, 3, 10))
print(array)
# Creates an array with a given value
array = np.full((2, 3), 9)
print(array)
# Creates an array w/o initializing entries
array = np.empty((2, 3))
print(array)
# Creates an identity matrix with 0s and 1s
array = np.eye(5)
print(array)
# Creates an array with evenly spaced values up to a given range
array = np.arange(0, 100, 0.1) # (start, stop, step)
print(array)
# Creates an array with a set number of values that are evenly spaced
array = np.linspace(0, 10, 5) # (start, stop, num)
print(array)
#python #coding #programming
00:00:00 zeros()
00:01:29 ones()
00:01:52 full()
00:02:16 eye()
00:03:09 empty()
00:03:59 arange()
00:05:16 linspace()
import numpy as np
# Creates an array with zeros
array = np.zeros((2, 3, 10))
print(array)
# Creates an array with ones
array = np.ones((2, 3, 10))
print(array)
# Creates an array with a given value
array = np.full((2, 3), 9)
print(array)
# Creates an array w/o initializing entries
array = np.empty((2, 3))
print(array)
# Creates an identity matrix with 0s and 1s
array = np.eye(5)
print(array)
# Creates an array with evenly spaced values up to a given range
array = np.arange(0, 100, 0.1) # (start, stop, step)
print(array)
# Creates an array with a set number of values that are evenly spaced
array = np.linspace(0, 10, 5) # (start, stop, num)
print(array)

![NumPy aggregate functions are easy! ๐
#coding #python #numpy
import numpy as np
# Aggregate functions = summarize data and typically return a single value
array = np.array([[1, 2, 3, 4, 5],
[6, 7, 8, 9, 10]])
print(np.sum(array)) # Sum of all elements
print(np.mean(array)) # Average of all elements
print(np.std(array)) # Measure of spread
print(np.var(array)) # Square of standard deviation
print(np.min(array)) # Smallest value
print(np.max(array)) # Largest value
print(np.argmin(array)) # Position (flattened) of smallest
print(np.argmax(array)) # Position (flattened) of largest
print(np.sum(array, axis=0)) # sum column-wise (vertically)
print(np.sum(array, axis=1)) # sum row-wise (horizontally) NumPy aggregate functions are easy! ๐](https://i.ytimg.com/vi/8pUBr05OQfs/mqdefault.jpg)

![Learn Java arrays in 9 minutes! ๐
#java #javatutorial #javacourse
import java.util.Arrays;
public class Main {
public static void main(String[] args){
// array = a collection of values of the same data type
// * think of it as a variable that can store more than 1 value *
String[] fruits = {apple, orange, banana, coconut};
//fruits[0] = pineapple;
//int numOfFruits = fruits.length;
//Arrays.sort(fruits);
//Arrays.fill(fruits, pineapple);
for(String fruit : fruits){
System.out.println(fruit);
}
}
} Learn Java arrays in 9 minutes! ๐](https://i.ytimg.com/vi/9dr2mHYYoug/mqdefault.jpg)






