Allows you to visualize a data point on each date on the calendar.
- The darker the color, the higher the value or density of values.
If you have multiple rows on the same date they are aggregated together
The Calendar Visualization can be used for cross filtering. Meaning you can select a square in the calendar and it will filter other visuals down to the date you picked.
This is an interesting visual. It’s dense, but not difficult to understand.
Note the use of an attractive colour pallette, style-compatible fonts, and even the official Olympic icons for the sports. I just took a screenshot here, but if you click through to the actual site you’ll notice that these graphics are also scale-independent (you can zoom in on your browser and they’ll look better, not worse) and even interactive (pop-ups appear with country-specific data when you hover over a bar).
Duc-Quang has been generous enough to provide the R code behind these charts if you’d like to try your hand at something similar. The data themselves were scraped from the official Rio 2016 site. The bar charts were created using a standard geom_bar plot using ggplot2, with a custom theme to set the font to OpenSans Condensed. The interactive elements were added using the ggiraph package and the geom_bar_interactive function. The chart titles (including the icons) were created as HTML headers directly, which was then exported along with the interactive charts using the save_html function.
I’m impressed that this all comes from R. There’s a good bit of work involved in getting this going, but you can get professional-grade graphics quality with R, and that’s pretty cool.
Allows you to bind performance measures to 3 states.
The thresholds for these 3 stages can be set manually or be data driven.
It can visualize one measure while using a different one for the indicator value
This is a pretty small visualization, but it could be useful as part of a larger dashboard.
Scatter chart is a built-in chart in Power BI that you can show up to three measure with a categorization in it. Three measures can be visualized in position of X axis, Y axis, and size of bubbles for scatter chart. You can also set up a date field in play axis, and then scatter chart will animate how measure values are compared to each other in each point of a time. Let’s start building something simple with this chart and see how it is working in action. At the end of example you will see a summary chart as below;
This is primarily for viewing changes in groups of data over time. You don’t want too many data points on the map or it gets too confusing.
This time, amit suggested I do some hierarchical clustering of the votes. So here goes a very dirty first attempt…
Check this out as a case study in data analysis.
Monte Carlo analysis is a great way to explore the impact of input variable uncertainty on the results of engineering equations, and with vector variables and distribution and sampling functions at its core, R is a natural platform for this analysis.
Check out his app, which has a link to the code. Amazingly, this is only 107 lines of code.
In this module you will learn how to use the Chord Power BI Custom Visual. Chord diagrams show directed relationships among a group of entities using colored lines (chords); this allows for an easy representation of correlating data.
Chord diagrams, when done right, can be extremely informative. The problem is that they’re also really confusing to the uninitiated.
Heatmaps are good for mapping out gradients, but we’ll want something with more structure to plot out differences in SAT score across the city. School districts are a good way to visualize this information, as each district has its own administration. New York City has several dozen school districts, and each district is a small geographic area.
We can compute SAT score by school district, then plot this out on a map. In the below code, we’ll:
Group full by school district.
Compute the average of each column for each school district.
Convert the school_dist field to remove leading 0s, so we can match our geograpghic district data.
Also check out part 1 if you missed it.
The USGS has a website called EarthExplorer that lets you search through decades of satellite data. I limited my search to Landsat 8 data with less than 10% cloud cover.
(you can do this search on the command line with landsat-util too but i prefer the web interface. In the future I will probably use this online toolfrom Development Seed)
Hat tip to Nathan Yau.
In this module you will learn how to use the Dot Plot Power BI Custom Visual. The Dot Plot is often used when visualizing a distribution of values or a count of an occurrence across different categorical data you may have. Watch this module to learn more!
This particular visualization seems a bit distracting for my tastes, but check out Devin’s video.