BASICS OF PYTHON PROGRAMMING FOR PHARMACEUTICAL SCIENCES UNIT-WISE NOTES – BP101T, B.Pharma 1st Semester
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.