Using Libraries (NumPy, Pandas)

One of Python's greatest strengths is its massive ecosystem of libraries. Libraries are pre-written code that you can use to add advanced features to your programs.

NumPy

NumPy is used for scientific computing and working with large arrays of numbers.

import numpy as np

arr = np.array([1, 2, 3, 4, 5])
print(arr * 2) # Output: [2, 4, 6, 8, 10]

Pandas

Pandas is the go-to library for data analysis and manipulation. It introduces the DataFrame, which is like a spreadsheet for Python.

import pandas as pd

data = {
    'Name': ['Alice', 'Bob', 'Charlie'],
    'Score': [85, 92, 78]
}
df = pd.DataFrame(data)
print(df)