Basics of Python Programming for Pharmaceutical Sciences

Unit 1 · Introduction to Python Programming 6 hrs

Installing Python and an IDE (Jupyter Notebook, PyCharm, VS Code) and the advantages of IDEs over text editors; variables and data types (integers, floats, strings, booleans), type casting and operators (arithmetic, comparison, logical); input and output operations; basic string operations; and installing and using standard and third-party libraries.

Unit 2 · Control Structures & Functions 6 hrs

Conditional statements (if, if-else, if-elif-else and nested conditions); loops (for and while) with break and continue; defining and calling functions, passing arguments and returning values; and writing modular programs for simple pharmaceutical tasks such as dosage and BMI calculation.

Unit 3 · Data Structures & File Handling 6 hrs

Lists, tuples and dictionaries with indexing and slicing; string-manipulation techniques; an introduction to NumPy arrays (creation and arithmetic operations); reading and writing CSV files; and importing and manipulating small, structured healthcare datasets.

Unit 4 · Data Handling with Pandas 6 hrs

The Pandas library — Series and DataFrame structures; reading CSV and Excel files such as PK-study datasets and ADR reports; inspecting data with head(), tail(), info() and describe(); cleaning data and handling missing values; and filtering, selecting, grouping and aggregating data.

Unit 5 · Data Visualization with Matplotlib 6 hrs

Creating line plots, histograms, scatter plots and box plots with labelled axes, titles and legends; and visualising pharmaceutical datasets — concentration–time curves for oral and IV administration, ADR reporting rates, and dissolution profiles — with scientific interpretation of the plots.