Make over Monday Week 5

Trying to get caught up on the Makeover Monday exercises from the last couple of weeks. I just finished week 5 which was on employment in the G7 countries. The original viz showed two pie charts on employment share and net employment growth in the G7 countries from 2010 – 2016

g7original

From reading the article the more important data point appeared to be the share of net employment growth in the US. I decided to turn that pie chart into a bar chart because I find it easier to see the differences in values with a bar chart than in a pie chart. I also adjusted the thickness of the bar to correspond to the measure. I kept the share of total employment in my remake as a reference point – I wanted the focus to be on the net share of employment so I added the share of total employment as a table. You can view the workbook on my Tableau public site.

g7mom

In both my MOM and work dashboards I am starting to use the same theme. I like the clean look and find it easier to read dashboards on a light background. I think the darker backgrounds can be beautiful when they are done right but I have a hard time reading them and sometimes find them distracting. I’m getting new glasses in a few weeks and maybe when I get my progressives I’ll change my mind but for now I’m sticking with the light background!

New Zealand RTI Makeover Monday

Back from vacation and catching up on the last two Makeover Monday exercises. I tried the New Zealand RTI one from week 4 first.

The first thing I created was a line chart that showed the RTI by visitor type by period. I filtered the dashboard to just the Total Region and excluded 2008 from the chart. The definitions listed RTI as the change in expenditure by Region comparing the month to the average month in 2008, so, I figured 2008 didn’t need to be included.

There were a lot of options with this data set and I spent longer than it may seem on this one. The thing I kept coming back to was the difference in the RTI in Winter between domestic and international visitors. So after reading a lot about New Zealand weather I decided to go with that.

The viz itself is simple – a line chart to show the RTI trends by visitor type and a list of the 10 Regions with the largest difference in RTI between domestic and international visitors during the winter months.

nzmom

Let me know if you think I missed the mark here or have any suggestions or feedback!

 

make over Monday week 3

This week’s MakeOverMonday was the first time I have used Twitter data. The objective was to rebuild a Buzz Feed depiction of Trump’s retweets. The thing I love about MakeOverMonday is that it pushes me outside of the data sets I use in work – I’m not sure I got everything right this week but because this is my “Tableau play time” I’m going with what I built.

This is the dashboard I ended up with:trumptweetsThe retweets by day chart is a Gantt chart and I’m not sure that it is the best visualization but I thought it looked like a city skyline and thought that fit into the Trump theme. I think it conveys the point that the number of Tweets Trump is retweeting has decreased since he announced his candidacy in June 2015.

The original data set looked at the users Trump was retweeting and I wanted to keep with that so I created the bar chart that shows the number of times he has retweeted that user with a color coding for before and after. I filtered this to people he retweeted 10 or more times. I thought it was interesting that the only person in his inner circle who met that criteria and who he retweeted before the announcement was @danscavino. I don’t have enough time or information to figure out why that is but I thought it was interesting.

I exceeded the time limit I set for myself this week so I’m going with what I built.