Udacity Data Visualization Nanodegree Capstone Project
This is the first blog post in my life, so I want to share that while I was excited about the first one, I was also worried about my shortcomings. Therefore, I need readers’ tolerance and understanding.
In my last project for the Data Visualization Nanodegree Program, it enables me to use what I have learned throughout the program in analyzing and visualizing real data. I am not an expert in data visualization and I attended this program because of my interest. However, thanks to this program and the project, I will be able to discuss an existing visualization like a data visualization expert and share my comments. That is why I prepared this blog and I hope the readers enjoy my posts too.
My task and purpose in this project is to examine the data visualization prepared according to real data from MakeoverMonday, identifying positive and improvable areas and preparing a different dashboard/ data presentation or animated story with improvements. In addition to this, it is to share my project by creating a blog that includes my findings and comments in these processes.
The first step is choosing an existing dataset. While browsing the topics of the data published in 2020, a title about “book” and “reading” caught my attention. As someone living in Turkey; I know that reading habits and interest in the book is less than it should be in my country. In addition; I am also aware of the importance of all kinds of books in a country’s culture. So, I chose “Pick up a book and read!” dataset from Makeover Monday.
I identified the visualization as the first step of the project. You can find the visualization I chose to develop below:
https://ec.europa.eu/eurostat/en/web/products-eurostat-news/-/EDN-20200422-1
For the next step, you will find reviews of mine for the visualization and my improvements. I tried to prepare an Animated Data Story.
What works with the initial visualization?
1) The title is simple and intriguing.
2) For the EU, the time-dependent change of data in two groups and in line graph form is easily perceptible.
3) The colors and line thicknesses used in the line chart allow easy understanding of the changes on the basis of groups and intersections between groups.
4) All descriptions and headings are horizontal and easily readable
5) Reference lines used for the index make it easier for the user to detect
6) Information about the data source is given
How could I make the initial visualization better?
1) It should be clearly stated for which years the analysis was made, this information can be included in the X-axis or in the title.
2) It can be stated which countries are included in the data set. (The data set includes countries that are EU members and candidates)
3) Country filter can be added and interactive graphics can be obtained to see the data of countries on the same graph.
4) Color preferences for graphics can be tailored to people with color blindness.
5) The gaps between the two compared groups can be colored, enabling users to perceive the change more easily at first glance.
Preliminary preparations with data set:
1) Downloaded dataset (Excel file) on
https://data.world/makeovermonday/2020w38
2) Created parameters and necessary calculations > Category indices, date calculations as year and month/year, rankings, etc.
3) Created Tableau file with Animated Data Story > Adding country flags icons, preparing background pictures, creating interactive live plot, waterfall plot, animated scatter plots.
What improvements have I tried to implement?
1) The information on which years of data are used was stated in the title.
2) Colors were used according to people with color blindness.
3) It is designed to be used for interactive inquiries according to the country flags table. In this way, country-specific examination can also be done.
4) The spaces between the lines have been colored, making the situation between groups easier to perceive. Gray background was used to achieve this.
As a result, you can find screenshots of my data story visualizations that I designed as a book concept:
· First page: The title of the project, a subtitle in the form of ask and other information were added on the cover of the book.
· Second page: On the page where the interactive version of the initial visualization was located, information was shared according to the original article.
· Third page: The index change of the countries by years was examined in the waterfall plot and outliers were detected.
· Fourth-fifth-sixth-seventh-eighth pages: Scatter plot where the countries are symbolized by flags and the indexes of all goods and books are compared. For this graph, the change in 5-year periods has been analyzed and the findings are shared.
· Ninth page: With the animated version of the same scatter plot, changes can be seen in the monthly changes in the indices on the basis of countries. Turkey has the largest change to the line were showed as historical data.
· Tenth page: The previous monthly based scatter plot was evaluated on an annual basis and country groups were created according to the average of 2020.
· Eleventh page: Final findings and recommendations were shared.
Twelfth page: Limitations and biases were shared
· Last page: “Thank you” on the book cover
You can find my Tableau file below:
Thanks again to the Udacity Data Visualization Nanodegree Program that gave me the opportunity to write this article. I hope this is an enjoyable article for you readers. :))
All of the project links used on the blog and tableau project file:
1) Initial dataset link / Makeover Monday:
https://data.world/makeovermonday/2020w38
2) Makeover Monday Source article link :
https://ec.europa.eu/eurostat/en/web/products-eurostat-news/-/EDN-20200422-1
3) Tableau project file link:
4) Blog top picture and Tableau story book cover picture link:
https://www.inploid.com/embedded/images/525/a203acef-df4b-4581-b784-1d9399e5b18e.jpg
5) Background picture > Book cover link:
https://images-na.ssl-images-amazon.com/images/I/617LYNQsELL.jpg
6) Background picture > open book link:
7) Harmonized Index of Consumer Prices (HICP) link:
8) European Union (EU) description link:
https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Glossary:European_Union_(EU)
