This document outlines the course contents for a data wrangling class. It introduces data wrangling and cleaning as the process of converting raw data into a usable format. The course will cover Python programming, Jupyter notebooks, common Python libraries like Pandas and NumPy, and installing packages. Students will learn the steps of data wrangling including importing, merging, standardizing, and exporting data. The instructor will demonstrate working with data in Jupyter notebooks.

1. Data Wrangling
Dr. Ferdin Joe John Joseph
Faculty of Information Technology
Thai – Nichi Institute of Technology, Bangkok

2. Today’s Lesson
• Data Wrangling – Course in Glance
• Data Wrangling or Cleaning
• Introduction to Python
• Jupyter Notebook
• Python Libraries
• Install Packages using pip
• Demonstration
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

3. Today’s Lesson
• Data Wrangling – Course in Glance
• Data Wrangling or Cleaning
• Introduction to Python
• Jupyter Notebook
• Python Libraries
• Install Packages using pip
• Demonstration
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

4. DSA 201 – A Road Map
Attendance
(10%)
Mid Exam
(30%)
Assignments
and
Presentations
(20%)
Final Exam
(40%)
Faculty of Information Technology, Thai - Nichi Institute of
Technology
4

5. Today’s Lesson
• Data Wrangling – Course in Glance
• Data Wrangling or Cleaning
• Introduction to Python
• Jupyter Notebook
• Python Libraries
• Install Packages using pip
• Demonstration
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

6. Why Data Wrangling?
Data Quality
Issues
Bad Data
Incorrect
Analysis
Invalid
Insights
Wrong
Decisions
Poor
Outcomes
Loss in
revenue
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

7. Data Wrangling - Definition
• Data wrangling is the process of converting raw data into data that
can be analyzed to generate valid actionable insights.
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

8. Analogy
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

9. Analogy
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

10. Analogy
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

11. Data Wrangling – Other names
• Data Preprocessing
• Data Preparation
• Data Cleansing
• Data Scrubbing
• Data Munging
• Data Transformation
• Data Fold, Spindle, Mutilate
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

12. Steps in Data Wrangling
Merge data
sets and
Rebuild
missing data
Standardize
and
Normalize
Deduplicate,
Verify and
Enrich
Export Data
and Insights
Import Data
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

13. How are we gonna wrangle data?
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

14. Today’s Lesson
• Data Wrangling – Course in Glance
• Data Wrangling or Cleaning
• Introduction to Python
• Jupyter Notebook
• Python Libraries
• Install Packages using pip
• Demonstration
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

15. Introduction to Python
• Open Source
• Object Oriented
• Preferred language for data science
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

16. Install Miniconda
• Installation of Miniconda needed for Laptops
• https://docs.conda.io/en/latest
• For offline practice
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

17. Today’s Lesson
• Data Wrangling – Course in Glance
• Data Wrangling or Cleaning
• Introduction to Python
• Jupyter Notebook
• Python Libraries
• Install Packages using pip
• Demonstration
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

18. Preferred tool for practice
• Google Colab Notebooks
• Internet is needed to use
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

19. Today’s Lesson
• Data Wrangling – Course in Glance
• Data Wrangling or Cleaning
• Introduction to Python
• Jupyter Notebook
• Python Libraries
• Install Packages using pip
• Demonstration
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

20. Most Common Libraries
• Pandas
• Numpy
• Matplotlib
• Scikit Learn
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

21. Today’s Lesson
• Data Wrangling – Course in Glance
• Data Wrangling or Cleaning
• Introduction to Python
• Jupyter Notebook
• Python Libraries
• Install Packages using pip
• Demonstration
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

22. Install packages using pip
• Numerous packages are available
• Not all packages are installed by default
• Packages can be installed using pip
• Syntax: pip install <library name>
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

23. Today’s Lesson
• Data Wrangling – Course in Glance
• Data Wrangling or Cleaning
• Introduction to Python
• Jupyter Notebook
• Python Libraries
• Install Packages using pip
• Demonstration
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

24. Demonstration
• Get familiar with Colab
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

25. Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

26. Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

27. Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

28. Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

29. Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok

30. Lesson for Next Week
• Basics of Python
• Data Types
• Variables
• Operators and Operands
• Lists
• Demonstration
Faculty of Information Technology, Thai - Nichi Institute of
Technology, Bangkok