For day 4 of dashboard week, the datasets were from the movie database IMDb (insert link). However, the requirement was for the team to retrieve the data through APIs. The core dataset I retrieved was the ‘Top 250 Movies’ and supplementary data from IMDB. I want to provide a brief explanation as to how I approached this in Alteryx and my insight from Tableau (link to my dashboard).
In Alteryx almost all my workflows have started with something like the above. A short explanation of this is that the Download tool reads the API link from the text input which outputs JSON formatted information from the API and is parsed nicely into different columns.
The container downloads information that looks like this,
Which my workflow processes and Produces something readily that looks like so,
I’ve repeated this several times to obtain all the data I need and uploaded it into Tableau.
The main interest in this dataset I’ve created was Is there a difference between reviewer site scores for movies? Overall, I found two things after creating my dashboard.
- The first was that there were visible differences in different reviewer site scores for movies. Trendlines for scores differed quite dramatically between some films, suggesting that on one site films are rated highly but low on others. An example of this comparison between Rotten Tomatoes and every other review site. Rotten Tomatoes scores have higher variance between different sites as they might be using more of their scoring scale compared to other sites. This could mean that reviewers of other sites are stricter on their scoring compared to Rotten Tomatoes.
- The second thing I found was the distribution of demographics. The demographics of IMDB movie reviewers are dominated by men between 30-44.