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Semester I · PCI syllabus 2026
Basics of Python Programming for Pharmaceutical Sciences
BP101T
2 credits
Theory
Coming soon
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,
- 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
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