JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD
DATA WRANGLING AND DATA VISUALIZATION LAB
M.Tech I Year I Semester (R22)
Course Objectives:
1. To learn data wrangling techniques
2. To introduce visual perception and core skills for visual analysis
Course Outcomes
Upon completion of the course, the students will be able to
1. Perform data wrangling
2. Explain principles of visual perception
3. Apply core skills for visual analysis
4. Apply visualization techniques for various data analysis tasks
5. Evaluate visualization techniques Implement the following experiments using Python
1. Find missing values and perform data imputation.
2. Find outliers in a chosen dataset.
3. Methods to handle duplicate data.
4. Perform data normalization
5. Explore 2-D charts I. Clustered bar charts II. Connected dot plots III. Pictograms IV. Bubble charts V. Radar charts VI. Polar charts VII. Range chart VIII. Box-and-whisker plots IX. Univariate scatter plots X. histograms word cloud XI. Pie chart XII. Waffle chart XIII. Stacked bar chart XIV. Tree map.
6. Multi-dimensional data visualization
7. Graph data visualization
TEXT BOOKS:
1. Jacqueline Kazil and Katharine Jarmul, Data Wrangling with Python: Tips and Tools to Make Your Life Easier, O’Reilly
2. Andy Kirk, Data Visualization A Handbook for Data Driven Design, Sage Publications, 2016
3. Philipp K. Janert, Gnuplot in Action, Understanding Data with Graphs, Manning Publications, 2010.