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Basics of Python Programming for Pharmaceutical Sciences (BP101)

₹176.00 ₹220.00 20% OFF
Authors Dr. Harjeet Singh , Dr. Mukta Makhija
ISBN-13 978-81-19781-09-6
Publisher R. Narian Publishers & Distributors
Page Count 176 Pages
Product Type Hard Copy
E-Book N/A
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Book Description

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.