22118 An Introduction to Python
About Course
AN INTRODUCTION TO PYTHON
Welcome to the world of Statistical Programming. Python Software is a Statistical Open Source Software that plays an important key role in statistical computing. Python provides an environment in which you can perform statistical analysis and produce high-quality graphics.
In this short course, the participants will learn to explore Python skills using statistical functions and visualization methods of Python language. The participants will also learn the fundamental programming concepts, fundamentals of Python Syntax, and basics of Python including assigning variables, and simple mathematical operations with one of Python’s most important data structures- vectors. From vectors, the participants will learn about factors, arrays, lists, matrices, and data frames and then also learn about correlation and regression. Finally, the participants will learn how to create data visualizations to showcase insights into data. The aspirants need not have any programming knowledge to enroll in this course.
This course is offered by the Department of Statistics, St Aloysius College (Autonomous), Mangaluru, and the course will begin from November 21st, 2022. The classes will be conducted offline every Saturday between 1:00 pm – 4:00 pm in the Xavier Block.
Course Coordinator: Ms. Sonal Caren D’Souza
Instructors: Ms. Sonal Caren D’souza
Email_Id: [email protected]
An Introduction to Python Syllabus -NOVEMBER – 2022- 2023
| Unit Wise Topics | No of Hours |
| Unit I:
Introduction to Python: Introduction to Python dictionary, Various comments involved in Python, Use of multi-line statements, Quotations in Python, Multiple Assignments. Python Operators: Arithmetic operators, Comparison operators, Assignment operators, String Special operators, String formatting operators. |
10 Hours |
| Unit II:
Built-in Data Types: Variable names, Numeric Data Types- Floating point, Complex, Integers; Boolean data types, Strings, Lists, Tuples, Arrays & Matrices – One Dimensional & Two-Dimensional Arrays, accessing elements of an array, rounding of arrays- round, floor, ceil; Concatenation. Data Type Conversion: Defining a function, Calling a function, Scope of variables, Global v/s Local variables. |
10 Hours
|
| Unit III:
Python for Econometrics, Statistics & Data Analysis: Background, Conventions, Components of Python Scientific Stack- Python, NumPy, SciPy, matplotlib & seaborn, pandas, statsmodels, jupyter notebook. Descriptive Statistics: Mean, Median, Variance, Covariance, Correlation, Linear Regression. Data Visualization in Python: Scatter Pot, Line Chart, Simple Bar Plot, Multiple Bar Plot, Component Bar Plot, Percentage Bar Plot, Pie Chart, Box Plot, Histogram. |
10 Hours |
| Total | 30 Hours |
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