Python Programming for Pharmaceutical Sciences

BP101T Basics of Python Programming for Pharmaceutical Sciences | Notes PDF | Noteskarts

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PCI SYLLABUS · NEP 2020 · SEMESTER 1

Basics of Python Programming for Pharmaceutical Sciences Notes PDF

BP101T unit-wise notes for B.Pharm Semester 1 — from Python basics to Pandas & data visualization, explained with pharmaceutical examples. No prior coding background needed.

🧾 BP101T 🎓 2 Credits 📘 5 Units 📝 Theory

Syllabus

Unit-wise topics mapped to the official PCI NEP 2020 syllabus

UNIT1

Introduction to Python Programming

Installing Python; IDEs (Jupyter Notebook, PyCharm, VS Code) and their advantages 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
Standard vs third-party libraries; installing and uninstalling libraries

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UNIT2

Control Structures & Functions

Conditional statements — if, if-else, if-elif-else, and nested conditions
Loops — for loop, while loop; break and continue statements
Defining & calling functions, passing arguments and returning values
Writing modular programs for pharma applications — dosage calculation, BMI calculation

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UNIT3

Data Structures & File Handling

Lists, tuples and dictionaries; indexing & slicing; basic list/dictionary operations
Introduction to NumPy arrays — array creation and arithmetic operations
Reading and writing CSV files; understanding structured healthcare datasets
Importing small pharmaceutical datasets and performing basic data access & manipulation

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UNIT4

Data Handling with Pandas

Introduction to the Pandas library; Series and DataFrame structures
Reading CSV and Excel files — PK study datasets and ADR reports
Inspecting datasets with head(), tail(), info() and describe()
Data cleaning and handling missing values; filtering & selecting data by condition
Grouping data and performing aggregation functions

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UNIT5

Data Visualization with Matplotlib

Introduction to Matplotlib; creating line plots, histograms, scatter plots and box plots
Labeling axes, titles and legends
Visualizing pharmaceutical datasets — concentration-time curves, ADR reporting rates, dissolution profiles
Scientific interpretation of plots

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25 Rapid MCQs

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💡 Pharmacy Fact

Python isn't an optional add-on in the new PCI syllabus — it's a mandatory Semester 1 subject for every B.Pharm student from the 2026 NEP batch onward, and it's designed with zero coding background assumed, building straight up from variables and loops toward real pharma data tasks like ADR analysis and dose calculators.

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