Data Analysis and Visualisation Using Python

Course Code (Credit):

CUTM 1018(0-1-3)

Course Objectives:

How to tell a story from data.
How to marshal the data for storyline.
The ability to develop visualisation to tell the story.
The focus is on analysis of data using visualisation as a tool.

Learning Outcomes:

To create impactful visualisation with good story line.

Course Syllabus:

Module I: STORY BOARD DEVELOPMENT

The objective and flow of the story to be understood through cases

Module II: DATA READING USING PYTHON FUNCTIONS

Python libraries: Pandas, NumPy, Plotly, Matplotlib, Seaborn, Dash Data collection from online data sources, Web scrap, data formats such as HTML, CSV, MS Excel, data compilation, arranging and reading data, data munging

Module III: DATA VISUALSATION USING PYTHON LIBRARIES

Different graphs such as Scatterplot, Line chart, Histogram, Bar chart, Bubble chart, Heatmaps etc. Dashboard Basics – Layout, Reporting, Infographics, Interactive components, live updating

Projects List:

Project No.	Project Name
1	World Development Indicators
2	IPL matches
3	IBM HR Analytics
4	Statewise Analysis Socio Economic Indicators
5	Analysis of Lawn Tennis Tournaments
6	World Cup
7	FIFA cup
8	Status of Micro Small Medium Enterprises in India
9	Crime Against Women
10	Tourism in India
11	Loan/Credit Analysis
12	Indian Budget Analysis
13	Handlooms in India
14	Crimes in India
15	E-commerce
16	NIRF Results
17	Results Analysis of CUTM students (last five year passed out students)
18	Malnutrition
19	Population
20	Performance of Indian Movies
21	Crop Production in India
22	Sales in Super Markets
23	ERP dashboarding (Project-2)
24	Details of Social/ Empowerment schemes of Govt. etc.
25	COVID 19

Text Books:

Advanced Engineering Mathematics by Erwin Kreyszig, 8th Edition
Higher Engineering Mathematics by B.V. Ramana

Reference Books:

J. Sinha Roy & S. Padhy, A Course of Ordinary and Partial Differential Equations
Thomas' Calculus – G.B. Thomas et al.
Introduction to Real Analysis – R.G. Bartle & D.R. Sherbert

Session Plan:

Session	Topic	Reference Link (if any)
1	Course objective, outcome, methodology and assessment. Why data visualisation	YouTube: Data Visualisation YouTube: Data Visualisation 2 PPT: Introduction to Data Analytics & Visualization using Python
2	Story telling using Visuals & Infographics Tips on good visuals Project Groups: Students divided into groups to do two projects	PPT: Story Boarding Infographic Templates Learn Data Visualization Python Storytelling with Data State Dashboard Odisha Data.gov.in YouTube: Tips on Good Visuals
3	Practice: Environmental setup - Anaconda and Jupyter notebook, Anaconda Navigator and Libraries Installation	YouTube: Setup Anaconda & Jupyter PPT: Python Libraries
4 & 5	Practice: Python Fundamentals, Data Analysis use case, Jupyter Notebook assignments Types of Visualization & Basics of Python	Data Visualization in Python Plotting with Python Intro to Data Visualization Types of Visualization Basic of Python (NumPy Arrays)
5 & 6	Project 1: Define study objectives, identify data needed and sources. Group presentations.	No external links
7, 8 & 9	Practice: Data collection/importing CSV, HTML, Excel files Sorting data, Missing values & Munging data	Sample Datasets YouTube: Data Wrangling Wrangling Data with Pandas YouTube: Import HTML Data YouTube: More Pandas YouTube: Sorting Data YouTube: Handling Missing Data YouTube: Data Cleaning Python CSV Module
10 & 11	Project 1: Data collection and sorting	Pandas Tutorial 1: Introduction Pandas Tutorial 2: DataFrame Basics Pandas Tutorial 3: Creating DataFrames Pandas Tutorial 4: Read/Write Excel & CSV Import Excel File Import HTML Data Pandas Tutorial 13: Crosstabs
12 & 13	Practice: Basics of Numpy	YouTube: Numpy Basics Complete Python NumPy Tutorial PPT: Basics of Numpy
14 & 15	Practice: Basics of Pandas	YouTube: Pandas Basics Pandas PDF Tutorial
16 & 17	Practice — Matplotlib Basics	Matplotlib Intro & Installation Format strings in plot Axes labels, Legend, Grid Bar Chart Histograms Pie Chart Save Chart To File Real-time plotting
18 – 21	Project 1 Work — Using Python Libraries (Pandas)	Pandas Intro & Installation Creating DataFrames Read/Write Excel & CSV Read Excel File Import HTML Data Crosstabs in Pandas
22 & 24	Practice — Plotly for Interactive Graphs	Plotly Official Docs Plotly Multi-line Chart Bar and Line Combo Chart Web-based Visualization
25 – 28	Project 1 Work & Interim Presentation	Continue project work and prepare interim presentation
29 & 30	Practice — Seaborn Library	Seaborn Scatter & Bubble Chart Seaborn PDF Tutorial Interactive Data Visualization
31 & 32	Practice — Web Scraping	Web Scraping Basics Export CSV with Pandas Parsing HTML with BeautifulSoup Statistics in Scraping Scraping Dynamic Graphs
33 & 34	Practice — Solve 10 Problems & Submit Group Assignments	Assignments started from session 7, submission as groups (Prof. Ramana’s assignment)
35 & 36	Practice — Dashboard Basics	Dashboard Basics Create Slides from Jupyter Dash Setup Dash Core Components Dash with CSS
37 & 38	Practice — Dash (Plotly) & Jupyter Presentations	Dash Basics Dash in 5 Minutes Jupyter Slideshow IPython Dashboard Real-time Plotting
38 & 39	Practice — Interactive Charts/Maps using Bokeh & Dashboards	Bokeh Interactive Charts Complex Dashboards with Dash
40 & 41	Practice — IPython-Dashboard & Live Graphs	IPython Dashboard (PyPI) Live Graphs with Dash Tutorial
42 & 43	Project Work	Work on Project - 1 to make dashboards
44, 45 & 46	Project	Final presentation of Project - 1
47 & 48	Project - 2	Start Project - 2 (ERP Dashboard) Define the objective and prepare the flow chart
49 & 50	Project	Make presentations on the objective and flow chart of Project - 2
50 & 51	Project	Work on Project - 2
52 & 53	Project	Make interim presentation on Project - 2
54 & 55	Project	Work on Project - 2
56 & 58	Project	Final presentation on Project - 2
59 & 60	Project	Make final changes on Project - 1 & Project - 2 to make ready for External Evaluation