Please see the interactive version in Tableau here.
- the “Button Filter”, developed by Biztory;
- and the “Brush Filter”, developed by Starschema;
- fast filtering
- it’s highly intuitive for any user
- and it is appealing for reporting
What is an extension?
An extensions in Tableau is an external development that can be used inside the application.
The use of it is not narrow at all, from custom visualization to narrative data summarization to excel 1:1 export up to ERP input integration.
So, basically, we can use them to do everything we want (or almost).
On the Tableau webpage, we can find 23 free extensions. See here the list.
Tested and recommendations
In the last period, I was a bit skeptic about the usage of the extensions in real life cases. Mainly because I wasn’t sure where to use them.
After browsing the extension library on the Tableau web page 2 of them popped out:
Extensions in Tableau – Button Filter from Biztory
For the ones that are used with Excel this more or less the same as the slicer.
Even though you can obtain the same functionality using a workaround with shapes in Tableau. This is a quite simple way of for a beginner to start using the buttons in his reports.
Some improvements that I would consider for this functionality is to add some custom shapes for the buttons and functionality to change the color of the buttons.
See the extension in action:
Extensions in Tableau – Brush Filter from Starschema
The second extension that has caught my attention is the Brush Filter, a filtering tool for dates only.
This is a cool feature in Tableau and I would consider this as a build in function, not as an add-in on top of the app.
I see three advantages of using a brush filter:
A disadvantage of the brush filter is mainly the fact that is quite inaccurate. I mean, you do know exactly the starting and ending point. But, this can be solved with some workarounds directly in dashboards.
The development from Starschema has a single minus on top of all of the many pluses. I could not get off the scrollbar from the bottom.
See the extension in action:
As a conclusion, I can say that I see a lot of potential for development and making good reporting experience using the extensions in Tableau.
This article is not about re-inventing any pie chart or to give it another shape. It’s about a list of a few articles that helped me during the time.
The story of the pie chart for me has started once I read one of the books written by Stephen Few. Even though, I had some background stories about the usage of the pie chart I didn’t stop using them by the end of the book (around 2016). And the reason why I was using it is just that the business people were still asking for it.
Anyway, during the past years, the usage of the pie chart is smaller and smaller.
Recommendations
One of the first articles that I would ever recommend is about the pie chart and some data visualization tips and tricks. The article belongs to Stephen Few and it has been published in August 2007 – Save the Pies for Dessert.
“Despite the obvious nature of a pie charts message, bar graphs provide a much better means to compare the magnitudes of each part.” – and this is the main idea that needs to be in your mind when you start designing
Even if the size of the paper is not a 5 minutes read I strongly recommend reading it with attention.
My second recommendation on this topic is a new article from the guys from datarevelations.com that has been published a few days ago – “A Bar Chart and a Pie Chart Living in Harmony“.
Here we have a cool article that summarizes the best practices of this field really briefly.
Also, there you can find the best short presentation about the pie chart approach. That can be used as a breaking point for any data visualization presentation or even as an argument when you deal with this issue.
DataViz.ro, Tableau
Land use per gram of protein – Anything but bars – #MakeoverMonday
decembrie 10, 2018The MakeoverMonday in this week has come with a dataset representing the use of land per protein gram.
The scope of the below dataset is to raise the awareness of meat consumption.
If you’re at a healthy weight, don’t lift weights and don’t exercise much, then aiming for 0.36–0.6 grams per pound (0.8–1.3 gram per kg) is a reasonable estimate.
This amounts to:
• 56–91 grams per day for the average male.
• 46–75 grams per day for the average female.
This means that if we consider the below stats – 1 gram of beef protein needs 1.02 sqm:
• an average man can use up to 92.82 sqm per day
• an average female can use up to 76.50 sqm per day
My own makeover
The original chart is a bar chart, so I had to look over some alternatives in order to emphasize the land area and the differences between the beef ant the other types of food.
So I have made a dot matrix.
Why? Because it can highlight both: the size (like 1 square meter of land) and the comparison between dimensions:
Thanks for the inspiration to hypsypops.com and tableaumagic.com.
Tableau
Makeover Monday week 49: How many women have constructed crossword puzzles in the Shortz Era
decembrie 4, 2018Will Shortz (born August 26, 1952 in Crawfordsville, Indiana) is an American puzzle creator and editor, and crossword puzzle editor for The New York Times.
Shortz is the author or editor of more than 100 books and owns over 20,000 puzzle books and magazines dating back to 1545, reportedly the world’s largest private library on the subject. He is a member and historian of the National Puzzlers’ League.
Shortz provided the puzzle clues which The Riddler (Jim Carrey) leaves for Batman (Val Kilmer) in the film Batman Forever.
How many women have constructed crossword puzzles in the Shortz Era
The makeover proposed by the authors of the book #MakeoverMonday was about “How many women have constructed crossword puzzles in the Shortz Era”.
The original viz it’s a spaghetti chart
The original viz has been posted by XWord Info.
And this it is something that the specialists of data visualization are calling a spaghetti chart.
A spaghetti chart it is considered a bad practice in data visualization because it is difficult to follow the path of a single line and you can not see the general trend.
My own makeover
In the below visualization I tryed to emphasise the contribution of the female constructurs of crossword puzzles per year and per weekday.
