A Text Book of Basics of Python Programming for Pharmaceutical Sciences is a student-friendly and application-oriented textbook designed specifically for First Year B. Pharmacy Semester-I students and prepared in accordance with the Pharmacy Council of India (PCI) curriculum and NEP 2020 framework.

As digital technologies, data analytics, and computational methods become increasingly important in pharmaceutical sciences, a basic understanding of programming is becoming an essential skill for pharmacy students. This book introduces Python programming from the fundamentals, making it suitable for students with little or no previous programming experience.

The book presents Python concepts in a simple, systematic, and pharmacy-focused manner, with examples and applications related to pharmaceutical and healthcare data. Instead of concentrating only on programming syntax, emphasis is placed on logical thinking, problem-solving, data handling, analysis, visualization, and practical application.

The book covers the complete five-unit syllabus, including Python fundamentals, variables, data types, operators, string manipulation, conditional statements, loops, functions, lists, tuples, dictionaries, NumPy arrays, file handling, Pandas, data cleaning, data manipulation, and data visualization using Matplotlib.

Pharmaceutical and healthcare-oriented examples are incorporated throughout the book, including dosage calculation, BMI calculation, pharmacokinetic study datasets, adverse drug reaction (ADR) reports, concentration-time curves, ADR reporting rates, and dissolution profiles.

The book also introduces students to Jupyter Notebook, PyCharm, VS Code, pharmaceutical data analysis, structured healthcare datasets, CSV and Excel files, data inspection, handling missing values, filtering, grouping, aggregation, and scientific interpretation of graphical results.

Flowcharts, tables, practical examples, real-world pharmacy scenarios, and pharmacy-focused explanations are included to make programming concepts easier to understand and apply.

The book follows a progressive approach from Python fundamentals to programming logic, data structures, pharmaceutical data handling, and data visualization. It provides students with a strong foundation for further learning in data analytics, artificial intelligence, machine learning, computational pharmacy, and pharmaceutical research.

This textbook is suitable for First Year B. Pharmacy students, pharmacy teachers, beginners in Python, and learners interested in applying Python to pharmaceutical and healthcare data.