Mathematical operations are one of the biggest advantages of using NumPy arrays. Unlike Python lists, NumPy allows you to perform calculations on entire arrays at once.<\/p>\n\n\n\n
This makes data analysis faster and more efficient.<\/p>\n\n\n\n
First, import NumPy:<\/p>\n\n\n\n
import numpy as np<\/pre>\n\n\n\nCreate an array:<\/p>\n\n\n\n
arr = np.array([1, 2, 3, 4])<\/pre>\n\n\n\nAddition<\/h3>\n\n\n\n
arr + 5<\/pre>\n\n\n\nAdds 5 to each element.<\/p>\n\n\n\n
Subtraction<\/h3>\n\n\n\n
arr - 2<\/pre>\n\n\n\nMultiplication<\/h3>\n\n\n\n
arr * 3<\/pre>\n\n\n\nDivision<\/h3>\n\n\n\n
arr \/ 2<\/pre>\n\n\n\nPower<\/h3>\n\n\n\n
arr ** 2<\/pre>\n\n\n\nSquares each element.<\/p>\n\n\n\n
Array to Array Operations<\/h2>\n\n\n\n
Create another array:<\/p>\n\n\n\n
arr2 = np.array([10, 20, 30, 40])<\/pre>\n\n\n\nAddition:<\/p>\n\n\n\n
arr + arr2<\/pre>\n\n\n\nMultiplication:<\/p>\n\n\n\n
arr * arr2<\/pre>\n\n\n\nDivision:<\/p>\n\n\n\n
arr2 \/ arr<\/pre>\n\n\n\nOperations happen element-wise.<\/p>\n\n\n\n
Mathematical Functions<\/h2>\n\n\n\n
Square Root<\/h3>\n\n\n\n
np.sqrt(arr)<\/pre>\n\n\n\nExponential<\/h3>\n\n\n\n
np.exp(arr)<\/pre>\n\n\n\nLogarithm<\/h3>\n\n\n\n
np.log(arr)<\/pre>\n\n\n\nAbsolute Value<\/h3>\n\n\n\n
np.abs(arr)<\/pre>\n\n\n\nStatistical Operations<\/h2>\n\n\n\n
Mean:<\/p>\n\n\n\n
np.mean(arr)<\/pre>\n\n\n\nSum:<\/p>\n\n\n\n
np.sum(arr)<\/pre>\n\n\n\nMinimum:<\/p>\n\n\n\n
np.min(arr)<\/pre>\n\n\n\nMaximum:<\/p>\n\n\n\n
np.max(arr)<\/pre>\n\n\n\nStandard Deviation:<\/p>\n\n\n\n
np.std(arr)<\/pre>\n\n\n\nVariance:<\/p>\n\n\n\n
np.var(arr)<\/pre>\n\n\n\nMatrix Operations (For 2D Arrays)<\/h2>\n\n\n\n
Create a matrix:<\/p>\n\n\n\n
matrix = np.array([[1, 2], [3, 4]])<\/pre>\n\n\n\nMatrix Transpose:<\/p>\n\n\n\n
matrix.T<\/pre>\n\n\n\nMatrix Multiplication:<\/p>\n\n\n\n
np.dot(matrix, matrix)<\/pre>\n\n\n\nWhy Mathematical Operations Matter<\/h2>\n\n\n\n
In Data Analytics, mathematical operations help you:<\/p>\n\n\n\n
Clean and transform data
Calculate statistics
Normalize values
Perform modeling
Analyze trends<\/p>\n\n\n\nNumPy makes these operations fast and simple.<\/p>\n\n\n\n
Key Takeaway<\/h2>\n\n\n\n
NumPy allows you to perform powerful mathematical and statistical operations on entire datasets efficiently. Mastering these operations is essential for Data Analytics and Data Science.<\/p>\n\n\n