Data Visualization With Python
Geodesy and Geoinformation Engineering
Institute of Natural and Applied Sciences
Third Cycle (Doctorate Degree)
| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Data Visualization With Python | JJM620 | Elective | Doctorate degree | 1 | Spring | 8 |
Name of Lecturer(s)
Associate Prof. Dr. Taner ÜSTÜNTAŞ
Learning Outcomes of the Course Unit
1) Learns to read text files
2) Learns NULL data operations
3) Learns data merging, grouping, filtering processes
4) Learns data summary statistical visualization
5) Learns different examples of map drawing
Program Competencies-Learning Outcomes Relation
| Program Competencies | |||||
| 1 | 2 | 3 | 4 | ||
| Learning Outcomes | |||||
| 1 | High | High | High | Low | |
| 2 | Middle | Middle | Middle | Middle | |
| 3 | High | Middle | Low | No relation | |
| 4 | Low | High | High | High | |
| 5 | Middle | No relation | Middle | High | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
Geospatial Programming with Python
Course Contents
They will be able to visualize static and interactive geographic data using open source code numpy, pandas, matplotlib, seaborn, plotly, bokeh, altair, geopandas libraries.
Weekly Schedule
1) Data reading methods2) Missing data processing
3) Data processing (aggregation, grouping, filtering, etc.)
4) Summary statistical visualization expressing the general structure of the data
5) Hexagon, contour, line, heat maps drawings
6) Data summary statistics histogram, box, violin drawings
7) Interactive visualization applications
8) Midterm exam
9) Different examples for interactive visualization
10) Interactive visualization in time series
11) Interactive visualization in time series
12) Interactive visualization of geographic data
13) Choropleth map drawings
14) Geographical map drawings
15) Add scatter, bubble and line drawings on the map
16) Final exam
Recommended or Required Reading
1- Belorkar A. (2019), Interactive Data Visualization with Python, ISBN:1838640002, Packt Publishing
2- Phuong Vo.T.H (2017), Python: Data Analytics and Visualization, ISBN:9781788290098, Packt Pub
3- Embarak, O. (2018). Data Analysis and Visualization Using Python, ISBN:978-1-4842-4109-7
Planned Learning Activities and Teaching Methods
1) Lecture
2) Lecture
3) Lecture
4) Lecture
5) Lecture
6) Question-Answer
7) Question-Answer
8) Question-Answer
9) Question-Answer
10) Question-Answer
11) Self Study
12) Self Study
13) Self Study
14) Self Study
15) Self Study
16) Problem Solving
Assessment Methods and Criteria
Contribution of Midterm Examination to Course Grade |
40% |
|---|---|
Contribution of Final Examination to Course Grade |
60% |
Total |
100% |
Language of Instruction
Turkish
Work Placement(s)
Not Required