In [1]:
import numpy as np
In [2]:
#Creating Arrays
arr1 = np.array([1, 2, 3, 4, 5])
print("1D Array:", arr1)
arr2 = np.array([[1, 2, 3], [4, 5, 6]])
print("2D Array:\n", arr2)
1D Array: [1 2 3 4 5] 2D Array: [[1 2 3] [4 5 6]]
In [3]:
#Array Operations
a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
print("Addition:", a + b)
print("Multiplication:", a * b)
Addition: [5 7 9] Multiplication: [ 4 10 18]
In [4]:
#Array Slicing
arr = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9])
print("Sliced Array:", arr[2:5])
Sliced Array: [3 4 5]
In [5]:
#Array Reshaping
arr = np.array([1, 2, 3, 4, 5, 6])
reshaped_arr = arr.reshape((2, 3))
print("Reshaped Array:\n", reshaped_arr)
Reshaped Array: [[1 2 3] [4 5 6]]
In [6]:
#Statistical Functions
arr = np.array([1, 2, 3, 4, 5])
print("Mean:", np.mean(arr))
print("Standard Deviation:", np.std(arr))
Mean: 3.0 Standard Deviation: 1.4142135623730951
In [7]:
#Generating Random Numbers
random_arr = np.random.rand(5)
print("Random Array:", random_arr)
random_int_arr = np.random.randint(1, 10, size=5)
print("Random Integers:", random_int_arr)
Random Array: [0.11254985 0.9363435 0.77653911 0.78918305 0.92464688] Random Integers: [4 9 9 8 5]
In [8]:
#Linear Algebra Operations
matrix1 = np.array([[1, 2], [3, 4]])
matrix2 = np.array([[5, 6], [7, 8]])
result = np.dot(matrix1, matrix2)
print("Matrix Multiplication:\n", result)
Matrix Multiplication: [[19 22] [43 50]]