Introduction
This data set pulls information from Apple Maps users across the globe to see how their mobility changed due to the pandemic. Using this I have zoned in on New York State and City to showcase January of 2020’s trend in mobility, perhaps when people had first begun to hear about the pandemic and begin to react. The data set used January 13th, 2020 as a baseline. Using this baseline we are able to see the progression in reaction to the pandemic.
On a line chart, the average mobility of each transportation type follows extremely similar patterns, but it is able to showcase that transit transportation had lower average mobility in comparison to walking or driving. Perhaps an indication that people were already beginning to react to news of Covid by finding ways to socially distance themselves.
Inspirations
I was inspired to utilize this data set and create a GIF from an infographic GIF such as the one below. I believe they are a great way to portray trends and information in a quick and eye-catching way.
Materials
For this map dashboard in Tableau, I utilized a data set from Kaggle titled, “Covid 19 – Apple Mobility Trends”. This data was collected from Apple Maps in order to analyze mobility trends and how they were transformed by Covid-19.
To transform to file from CSV to XLSX, clean up and organize the data I used Excel.
In order to create the maps, I utilized Tableau Public.
And to create the GIF I used an App on the iPad called Procreate.
Method and Process
- Filtering the Data
For this project, I chose to include only the data from January 13th, 2020-February 13th, 2020 in New York State. This allowed me to focus on trends in a specific area, over a shorter period of time.
2. Cleaning & Formatting the Data
In order to best showcase the data, I needed to transform the data. The mobility ratings were placed in a table that had the date labels at the top of each column.
I created a Date column and reorganized the data so that the dates corresponded with the mobility in two columns instead of having a separate column for each date.
Results
Through mapping Apple’s mobility data we are able to see that often increases in mobility occurred similarly across New York State in regards to driving and across New York City in regards to walking and transit. Although individually mobility seemed to coordinate across state or city, higher transit or driving didn’t necessarily reflect higher walking trends. This could be due to weather, which would lead someone to choose to drive or take transit, over walking.
Reflections
Looking to the future, I would like to utilize this data set and connect it to data regarding the weather in the New York locations on each specific data to see if there was any correlation to the mode of transportation chosen or the level of mobility on that day. I would also like tp convert all of the graphs into GIF infographics so that the changes over time are clear to the viewer. I believe that the scrolling on Tableau provides a nice timeline, but the GIF display is a little more engaging for the topic.