CSIT359:553_project1_TablularVisualization
CSIT 359/553 Exploratory Data Analysis and
Visualization
Project 1: Tabular Data Visualization
Instructions: In the project, you need to prepare an idea and a data set from real
world. Convert them to Pandas and apply multiple techniques for data analysis.
Group work: Both individual and group work are allowed in this project. Each group
can include at most 3 students. All the names of group members should be indicated
in the project design report.
About the data set:
You could find the data by your self or select from the following resources:
Don’ts
• Don’t use a standard machine learning dataset (Kaggle, UCI ML Repository). These
are pre-processed and only suitable for analysis, not for the whole DS process
• Don’t pick a dataset where structured data is hard to extract, E.g.,
• text-only, relying on advanced NLP,
• extracting data from collection of PDFs,
• running your own survey (it’s hard to run a good survey)
Project Requirements
The project MUST includes the following techniques:
1. Exploratory Data Analysis
Stanford Large Network Dataset Collection https:
snap.stanford.edu/data
Dataverse Network https:
dataverse.org
Reddit Open Data https:
www.reddit.com
opendata
CDC Data https:
www.cdc.gov/nchs/tools/index.htm?
CDC_AA_refVal=https%3A%2F%2Fwww.cdc.gov%2Fnc
hs%2Fdata_access%2Fdata_tools.htm
World Bank Catalog https:
datacatalog.worldbank.org
Metor Boston Data Common https:
datacommon.mapc.org
COVID-19 Data Repository by Johns
Hopkins University
https:
github.com/CSSEGISandData/COVID-19
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https:
snap.stanford.edu/data
https:
dataverse.org
https:
www.reddit.com
opendata
https:
www.cdc.gov/nchs/tools/index.htm?CDC_AA_refVal=https%3A%2F%2Fwww.cdc.gov%2Fnchs%2Fdata_access%2Fdata_tools.htm
https:
datacatalog.worldbank.org
https:
datacommon.mapc.org
https:
github.com/CSSEGISandData/COVID-19
• Data Loading
• Data Cleaning
• Data Analysis using Descriptive Statistics
• Select at least one of the following techniques in data manipulating:
• Data Wrangling
• Data Aggregation
• Time Series
2. Data Visualization
• Visualization Design
• At least three different designs are required in your project
• You need to implement your visualization in Python
• Description of Data Visualization Design
• Describe the questions your visualization is designed to answer.
• Describe the visualization you created and how its design evolved. (What
marks and channels are used?)
• Describe how the visualization can be used to answer the questions.
Presentation Requirements
A presentation for each team is required. Each team will get approx. 10 min for
presentation. Please plan your talk accordingly. Slides are required during the
presentation with the following contents:
• The description of the project, including the project objectives and the description of
the data set - should be with reference to the data
• Description of the exploratory data analysis
• Data visualization, including the plots and the description of the design
• Live demo/ demo snapshots of execution of your program
• Conclusion from your observation
Project Submission
A final submission should include all the source code, data set and slides for the
presentation.
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CSIT 359/553: Exploratory of Data Analysis and
Visualization
Ru
ic of Project 1
Project Title:
Student Names:
Points out of Total
1. Exploratory Data Analysis XXXXXXXXXX__________/ 10
a. Data Loading (2 points) _____
. Data Cleaning (3 points) _____
c. Data Analysis using descriptive statistics (2 points) _____
d. Other techniques in data manipulating (3 points) XXXXXXXXXX_____
2. Data Visualization XXXXXXXXXX__________/ 20
a. Three different design of data visualization in Python (15 points) XXXXXXXXXX_____
. Description of the design (5 points) XXXXXXXXXX_____
3. Live demo / demo snapshots of execution XXXXXXXXXX__________/ 10
a. The program can be executed successfully (6 points) XXXXXXXXXX_____
. Students can answer the questions about the source code (4 points) _____
3. Project Presentation XXXXXXXXXX__________/ 10
a. Presenters are well-prepared (2 points) XXXXXXXXXX_____
. Slides should present material in an informative manner (2 points) _____
c. Presentation is logically organized and presenters appear
to be fluid (2 points) _____
d. There is a balance between high-level motivational material
& technical detail (2 points) _____
e. Presenters should respond well to questions and critique (2 points) XXXXXXXXXX_____
Total Score XXXXXXXXXX__________/ 50
Graders Comments:
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