As per NEP 2020, Pharmacy Council of India (PCI) provided new syllabus oriented B.Pharm 1st Semester Basics of Python Programming for Pharmaceutical Sciences – BP101T Book PDF Download link given below.
| Book Name | Basics of Python Programming for Pharmaceutical Sciences Textbook |
|---|---|
| Author’s Name | H. Seikh, M. Mollick |
| Publication Name | TPS Publication |
| Editions | 1st Edition, Sep 2026 |
| Language | English |
| Book Size | 1.50 MB |
Topic to be Covered in this Subjects:
UNIT-1: Introduction to Python programming
- Installing Python and an Integrated Development Environment (IDE) [Jupyter Notebook, PyCharm, VS Code etc.], Advantages of IDEs over text editors.
- Python variables and data types (integers, floats, strings, booleans), Type casting and basic operators (arithmetic, comparison, logical), Input and output operations.
- Basic string operations and manipulation techniques. Introduction to standard libraries and third-party libraries, installing and uninstalling libraries.
UNIT-2: Control Structures & Functions
- Conditional statements (if, if-else, if-elif-else), nested conditions
- Loops (for loop, while loop).
- Break and continue statements.
- Defining and calling functions, passing arguments and returning values.
- Writing modular programs for simple pharmaceutical applications- dosage calculation and BMI calculation.
UNIT-3: Data Structures & File Handling
- Lists, tuples, and dictionaries.
- Indexing and slicing lists, basic operations on lists and dictionaries, string manipulation techniques.
- Introduction to NumPy arrays, basic operations using NumPy (array creation, arithmetic operations).
- Reading and writing CSV files.
- Understanding structured healthcare datasets.
- Importing small pharmaceutical datasets and performing basic data access and manipulation tasks.
UNIT-4: Data Handling with Pandas
- Introduction to Pandas library.
- Pandas Series and DataFrame structures.
- Reading CSV and Excel files-PK study datasets and ADR reports
- Inspecting datasets using functions such as head(), tail(), info(), and describe().
- Data cleaning techniques and handling missing values.
- Filtering and selecting data based on conditions.
- Grouping data and performing aggregation functions.
UNIT-5: Data Visualization with Matplotlib
- Introduction to Matplotlib.
- Creating line plots, histograms, scatter plots, and box plots.
- Labeling axes, titles, and legends.
- Create plots and visualize pharmaceutical datasets – concentration-time curves for oral and IV administration, ADR reporting rates across drugs, dissolution profiles.
- Scientific interpretation of plots.
Subject Objectives:
The objectives of this course are to:
- Introduce the fundamentals of Python programming for pharmaceutical sciences.
- Develop basic programming skills using control structures, functions, and data structures.
- Provide knowledge of data handling techniques for structured dataset management.
- Familiarize students with data analysis tools such as NumPy and Pandas for healthcare datasets.
- Enable students to visualize and interpret pharmaceutical data.
Subject Outcomes:
Upon successful completion of this course, the students will be able to:
- Explain the fundamentals of Python programming, including variables, data types, operators, and libraries.
- Analyze program logic using control structures and functions.
- Organize, manipulate, and retrieve data using data structures and file handling techniques.
- Analyze pharmaceutical datasets using Python libraries.
- Visualize and interpret pharmaceutical data using graphical tools.