Python for Pharmaceutical Sciences: Fundamentals, data handling and visualization for B.Pharm students (English Edition)
Chaturvedi, Dr. Arpana
Synopsis "Python for Pharmaceutical Sciences: Fundamentals, data handling and visualization for B.Pharm students (English Edition)"
Python is increasingly used for scientific computing, data handling, automation, and reproducible analysis. In pharmaceutical sciences, it can support structured work with laboratory observations, formulation data, quality-control records, pharmacokinetic datasets, ADR reports, inventory information, and research data. Python for Pharmaceutical Sciences introduces programming from the beginning for B.Pharm learners and is aligned with the core coverage of BP101T. It covers Jupyter Notebook, variables, data types, input/output, operators, strings, conditions, loops, functions, data structures, NumPy, file handling, Pandas, data cleaning, and Matplotlib. Each concept is supported with pharmacy-focused examples, algorithms, executable code, outputs, interpretations, exercises, and integrated projects. By the end of this book, readers will be able to write basic Python programs, organize and analyze pharmaceutical datasets, automate routine calculations, and communicate findings through tables and visualizations. No prior programming experience is required; examples and datasets are intended for educational use. What you will learn ● Write code using variables, operators, input and output. ● Use conditions and loops to solve pharmacy problems. ● Manage data with lists, tuples, dictionaries and arrays. ● Create reusable functions for common pharmacy calculation tasks. ● Analyze data with NumPy, Pandas and Matplotlib tools. Who this book is for This book is designed for B.Pharm and pharmaceutical science students beginning programming, as well as faculty members, researchers, quality-control trainees, and pharmacy professionals seeking practical Python foundations. No previous coding experience is required; familiarity with basic mathematics and common pharmaceutical terminology is sufficient. Table of Contents 1. Python and Pharmaceutical Sciences 2. Variables, Data Types, Type Casting, Operators and Input/Output Operations 3. Operators and Program Logic 4. Strings and Python Libraries 5. Decision-making with Conditional Statements 6. Loops and Repetitive Operations 7. Functions and Modular Programming 8. Python Data Structures 9. NumPy Arrays and File Handling 10. Data Handling with Pandas 11. Data Cleaning and Basic Analysis 12. Pharmaceutical Data Visualization with Matplotlib 13. Integrated Projects, Question Bank and Model Assessment APPENDICES
