How I Leveraged my Photoshop Skills to Communicate Data Science Ideas.

Through out my time at Bellevue university I have used photoshop to express my ideas.

My very first semester I built an 80s themed poster. The teacher had stated in the assignment "no pink titles" and I smiled and said to myself challenge accepted. The computer vision words were modeled after the at the time popular Stranger Things Netflix series logo. If you are wondering the teacher had nothing but nice things to say about the poster I had created. The neural network I built with paths in photoshop and I altered the Bellevue university logo to glow with a golden theme. The intense image in the middle I purchased on adobe stock and cut out words that pertained to our project.

In the following project we were tasked with building graphs that we could use to explain a concept idea to a data science team. Again I went with an 80s theme but abandoned the theme for a light color scheme in later projects.

In this project we were making safety comparisons to Airline travel vs Automotive.

The interesting thing is that when building my graphs in python I would often default to less detail then chose to fill in the details later using photoshop.

An example is the bottom left chart is in fact two overlayed charts with transparent backgrounds.

I used similar strategies on the top middle chart and then added visual aids that point out key datapoints that help bring my points home for the user.

“I personally love dark 80s themed photoshop images but often my peers prefer light schemes. So I usually default towards light themes.”

When I switched my focus to a light color scheme I decided to use gradients to guide how my users would interact with my data.

Don't be fooled by the dark background it is transparent I just happen to program in a dark theme environment as you can see here.

The gradients were used to help people decide which direction to follow when looking at the graphs.

I accomplished this by choosing colors that were next to each other on a color wheel. In this case blue and green. Then found the gradient colors in between the chosen colors.

The beauty of photoshop is that we can then add embellishments to the graphs pointing out important features as you can see above.

I was able to set defaults that cleaned up my graphs and got them ready for photoshop as follows.

I would then build a list of gradients for my given datapoints as follows using the colour library.

I started by counting the number of datapoints that I wanted to apply color to.

Then I fed it into my color stepper library and it filled in the hex values of the colors.

This allowed me to explicitly color the datapoints on my graphs using my generated color list.

I think that the choices we make can help us tell a better story.