This repository contains a collection of basic to intermediate Python programs for Data Science.
These programs cover essential concepts like NumPy, Pandas, Visualization, NLP, and Python fundamentals.

• Data types
• Operators
• Control structures
• Functions and arguments
• OOP concepts
• File handling

• 1D and 2D array creation
• N-dimensional arrays
• Array properties (shape, size, dtype, dimension)
• Mathematical operations (add, subtract, multiply, divide)
• Matrix operations (reshape, matrix product)
• Functions: arange(), linspace()
• Random functions and string operations

• Creating Series and DataFrames
• Reading and writing CSV files
• Handling missing values
• GroupBy operations
• Concatenation and Join
• Data analysis (mean, max, min)

• Line plots using Matplotlib
• Multiple line plots using Seaborn
• Trigonometric graphs (sin, cos, tan)

• Word Tokenization (NLTK)
• POS Tagging
• Stopwords removal
• Word Frequency Analysis
• Sentiment Analysis using TextBlob

• Practice basic Data Science concepts
• • Useful for college practicals and exams
• • Beginner-friendly programs with simple logic

This file serves as a quick reference for important Data Science programs in Python.

Perfect for revision and building a strong foundation.