By clicking on the “R transformation” a new windows will show up. This windows is a R editor that you can past your code here. however there are couple of things that you should consider.
1. there is a error message handling but always recommended to run and be sure your code work in R studio first (in our example we already tested it in Part 1).
2. the all data is holding in variable “dataset”.
3. you do not need to write “install.packages” to get packages here, but you should first install required packages into your R editor and here just call “library(package name)”
Leila takes this step-by-step, leading to a Power BI visual with drill-down.
In this module you will learn how to use the Gantt Power BI Custom Visual. Using the Gantt chart you can easily visualize project timelines and deliverable completion.
Gantt charts have a bad rep in IT mostly because GIGO applies to timelines too. But with that said, I think this is a nicely implemented visual.
Expand, Collapse, Drill and Filter
Expand and collapse behaves just like a pivot table however with a slightly different UI. The new matrix experience is however entirely consistent with the chart drill experience so it is very intuitive.
The new cross filter behaviour is of course not possible in a regular pivot table in Excel (without VBA). You can select any column, row or cell in the matrix and it will cross drill the other visuals on the canvas as can be seen above.
This looks like an interesting change, and Matt shows how to enable the preview.
If you have heard my “Data Visualization: How to truly tell a great story!” presentation, you will have heard me mention about using a storyboard to get a better understanding of the problem. Cole Nussbaumer Knaflic does a great job of introducing this concept in her book “Storytelling with Data” which is a great read and an excellent reference tool for anyone in the data viz world.
I have adapted to using her basic storyboard as my basis for my development and we will use it today as the foundation of our series.
Jonathan ends with a set of sample questions to ask. These are just starter questions, but they’ll help uncover important but hidden business requirements.
The Stars visual has the ability to use symbols instead of the star.
If you have multiple rows in your dataset then you may need to use a Slicer to toggle back and forth between each record.
I haven’t used the stars visual, but it seems that it’d make intuitive sense, given how many major sites use stars for ratings.
Musical purists always reproached the Ramones for knowing a couple of chords only and making an excessive use of them. Data show that the band knew at least… 11 different chords (out of too-many-to-bother-counting possibilities) although 80% of their songs were built on no more than 6. And there is no evidence of a sophistication of the Ramones’ compositions over time.
It’s a fun analysis with all the R code attached. This fun analysis, however, includes n-gram analysis, sentiment analysis, and token distribution analysis.
I have previously written some blog posts about Map visuals in Power BI. One of them was specifically about Filled Map, titled as Filled Map; the Good, the Bad, the Ugly! Why? you need to read that post to find the reason. In this post I want to explain the power of Shape Map which is one of the visuals Power BI team published recently. This visual is still at preview mode at the time of writing this post. This visual is much more powerful than what it looks. The actual power behind it is that you can have your own map added to it. Let’s take a closer look at this visual with an example. If you want to learn more about Power BI; read Power BI from Rookie to Rock Star.
It’s an interesting look at a new visual.
The first step was to create a list of all the places I have flown between at least once. Paging through my travel photos and diaries, I managed to create a pretty complete list. The structure of this document is simply a list of all routes (From, To) and every flight only gets counted once. The next step finds the spatial coordinates for each airport by searching Google Maps using the geocode function from the ggmap package. In some instances, I had to add the country name to avoid confusion between places.
The end result is imperfect (as Peter mentions, ggmap isn’t wrapping around), but does fit the bill for being eye-catching.
In this module you will learn how to use the Image Viewer Power BI Custom Visual. The Image Viewer visual helps in displaying images based on an image URL stored in your data.
This is an interesting visual.
The March 2017 update of Power BI Desktop comes with a preview of Themes. Right now it is in its simplest of forms: You manually create a JSON file that has a very few attributes that can set basic color themes to your reports. So all you have to do is create file that looks like this:
Click through for an example. This isn’t a true fix for the lack of Color Vision Deficiency support, but you can plug in safe colors (for example, this article includes some) and skirt the issue until there’s real support.