Visualizing data is one of the most important aspects of data science. It correlates with the storytelling skill that I mentioned in another post. It's essential to data science because it allows you to transfer information in a simple way that non data scientists can understand, for example, putting a data set into a line graph, map, or a pie chart, so that someone who has no knowledge on a topic can interpret that visualization and make conclusions based on the information given.
In my Advanced Placement Computer Science Principles class, we recently started a chapter dedicated to all things data. Additionally, the other day we did a data visualization project. For this, we were guided by an essential question:
"How do I summarize a set of data and describe what information can be extracted from it?"
Using this question, all of the students were assigned to find a data set on the Internet and make our own graph and other statistics we found to create an eye-catching and informative data visualization poster. I found a data set on kaggle.com with loads of statistics on the average number of hours of sleep different demographics get over the years. More specifically, it had data on the differences of sleep patterns between men and women, people of distinct ages, and different kinds of days (all days, non holiday weekdays, and weekends & holidays).
I created my own graph using Google Sheets that showed the distribution of the average number of hours men and women of all ages on all days get as of 2017. This visualization could allow anyone to interpret how much sleep the average person gets. In my final poster, I also included a chart made on another website that showed the increase in Melatonin pills over the years. This chart showed how more and more people started to need sleeping aids. In addition, I used a chart I found on the percent of people that get a certain number of hours of sleep. The last few things on my poster were quotes on different statistics relating to my topic.
Overall, using my basic example that I made for my APCSP class, you can better understand the significance of data visualization in data science. More specifically, how putting your data into simple terms and in a compelling format can help people interpret data. Whether it's with graphs or charts, conveying your findings with the intention of informing others requires proper data visualization.
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