Press "Enter" to skip to content

Category: Visualization

Scatterplot Matrices

Published 2018-06-08 by Kevin Feasel

The Plotly folks show off scatterplot matrices in Python:

The scatterplot matrix, known acronymically as SPLOM, is a relatively uncommon graphical tool that uses multiple scatterplots to determine the correlation (if any) between a series of variables.

These scatterplots are then organized into a matrix, making it easy to look at all the potential correlations in one place.

SPLOMs, invented by John Hartigan in 1975, allow data aficionados to quickly realize any interesting correlations between parameters in the data set.

In this post, we’ll go over how to make SPLOMs in Plotly with Python. For extra insights, check out our SPLOM tutorial in Python and R.

fff

Comments closed

Why Nobody Is Reading Your Report

Published 2018-05-30 by Kevin Feasel

Stephanie Evergreen really cuts to the chase:

Here’s the hard truth: Your report probably sucks. Mine sure did. The heart of your content is likely fine, maybe even helpful. But, if you are anything like the hundreds of reports I see every year, the entire set of cultural norms we have somehow developed around reporting is just setting us up for failure, writing a destiny where no one is reading the report.

Why? Let me lay out the most common issues I see and propose some strategic solutions.

There’s an emphasis here on academic papers but it also applies to corporate work too.

Comments closed

Taking Screenshots With R

Published 2018-05-29 by Kevin Feasel

Abdul Majed Raja shows us how to take screenshots of webpages using R:

webshot package provides one simple function webshot() that takes a webpage url as its first argument and saves it in the given file name that is its second argument. It is important to note that the filename includes the file extensions like ‘.jpg’, ‘.png’, ‘.pdf’ based on which the output file is rendered. Below is the basic structure of how the function goes:

library(webshot)

#webshot(url, filename.extension)
webshot(“https://www.listendata.com/”, “listendata.png”)

If no folder path is specified along with the filename, the file is downloaded in the current working directory which can be checked with getwd().

Now that we understood the basics of the webshot() function, It is time for us to begin with our cases – starting with downloading/converting a webpage as a PDFcopy.

This isn’t something I’d expect to do every day, but I could see it being useful as part of a notebook to give the user a sanity check, like if a webpage or data set has a last updated timestamp that you want to check.  H/T R-Bloggers

Comments closed

WVPlots 1.0.0

Published 2018-05-29 by Kevin Feasel

John Mount announces WVPlots 1.0.0:

Nina Zumel and I have been working on packaging our favorite graphing techniques in a more reusable way that emphasizes the analysis task at hand over the steps needed to produce a good visualization. We are excited to announce the WVPlots is now at version 1.0.0 on CRAN!

The idea is: we sacrifice some of the flexibility and composability inherent to ggplot2 in R for a menu of prescribed presentation solutions. This is a package to produce plots while you are in the middle of another task.

I like this idea:  I know the kind of plot I need and just want to throw something together for myself to give me an idea of the underlying data.

Comments closed

Power BI Color Palattes

Published 2018-05-29 by Kevin Feasel

Meagan Longoria helps us choose a color palette for Power BI reports:

A color palette is simply a collection of colors applied to the visual elements in your report. What we typically refer to as color is a combination of three main properties: hue (base color on the color wheel), intensity (brightness or gray-ness) and value (lightness or darkness). You can build an engaging and professional looking report with just 6 colors. It’s possible to have fewer colors or more colors, but 6 should cover many common visualization needs. If you are using more than 6 colors, you might want to check that you are optimizing engagement and cognitive load.

  1. Main color – default color on graphs

  2. Color 2 – used when multiple colors are needed in a graph or report

  3. Color 3 – used when multiple colors are needed in a graph or report and Color 2 has already been used

  4. Highlight color – a color used to highlight important data points to make them stand out from other points on the page

  5. Border color – a light color used for borders on tables and KPIs where necessary

  6. Title color – color used for visual titles and axis labels as appropriate

There’s a lot of good advice in here.

Comments closed

Visualization Over Kafka And KSQL

Published 2018-05-24 by Kevin Feasel

Shant Hovsepian shows off a data visualization tool which can read Kafka Streams data:

KSQL is a game-changer not only for application developers but also for non-technical business users. How? The SQL interface opens up access to Kafka data to analytics platforms based on SQL. Business analysts who are accustomed to non-coding, drag-and-drop interfaces can now apply their analytical skills to Kafka. So instead of continually building new analytics outputs due to evolving business requirements, IT teams can hand a comprehensive analytics interface directly to the business analysts. Analysts get a self-service environment where they can independently build dashboards and applications.

Arcadia Data is a Confluent partner that is leading the charge for integrating visual analytics and BI technology directly with KSQL. We’ve been working to combine our existing analytics stack with KSQL to provide a platform that requires no complicated new skills for your analysts to visualize streaming data. Just as they will create semantic layers, build dashboards, and deploy analytical applications on batch data, they can now do the same on streaming data. Real-time analytics and visualizations for business users have largely been a misnomer until now. For example, some architectures enabled visualizations for end users by staging Kafka data into a separate data store, which added latency. KSQL removes that latency to let business users see the most recent data directly in Kafka and react immediately.

Click through for a couple repos and demos.

Comments closed

Creating Choropleths With ggcounty

Published 2018-05-21 by Kevin Feasel

Sebastian Sauer has a quick example of using ggcounty to plot data on a map of US counties:

This posts shows how easy it can be to build an visually pleasing plot. We will use hrbrmster’s ggcounty, which is an R package at this Github repo. Graphics engine is as mostly in my plots, Hadley Wickhams ggplot. All build on R. Standing on shoulders…

Disclaimer: This example heavily draws on hrbrmster example on this page. All credit is due to Rudy, and those on whose work he built up on.

In just a few lines of code, you can have a pretty nice map.

Comments closed

Overlaying Visuals In Power BI

Published 2018-05-21 by Kevin Feasel

Annie Xu gives us two methods for being able to jump between two visuals in the same space:

Disconnected Table method:

This method is more towards PowerBI modelers. Basically, the idea is to have a Field in a independent table (no relationship to other tables) as Slicer with your measure choice and then create a measure using SELECTEDVALUE function to have the measure dynamically switch referring measures based on the choice made on the slicer.

Click through for both methods.

Comments closed

Building Flow Charts In R

Published 2018-05-10 by Kevin Feasel

Alan Haynes shows how to build flow charts in R using the grid Gmisc packages:

Flow charts are an important part of a clinical trial report. Making them can be a pain though. One good way to do it seems to be with the grid and Gmisc packages in R. X and Y coordinates can be designated based on the center of the boxes in normalized device coordinates (proportions of the device space – 0.5 is this middle) which saves a lot of messing around with corners of boxes and arrows.

A very basic flow chart, based very roughly on the CONSORT version, can be generated as follows…

Click through for sample code and a resulting image.  H/T R-bloggers

Comments closed

Building Palettes From Pictures In R

Published 2018-05-10 by Kevin Feasel

Andrea Cirillo takes inspiration from the great works to build palettes:

If you see this painting you will find a profound of colours with a great equilibrium between different hues, the hardy usage of complementary colours and the ability expressed in the “chiaroscuro” technique. While I was looking at the painting I started, wondering how we moved from this wisdom to the ugly charts you can easily find within today’s corporate reports ( find a great sample on the WTF visualization website)

This is where Paletter comes from: bring the Renaissance wisdom and beauty within the plots we produce every day.

Introducing paletter

PaletteR is a lean R package which lets you draw from any custom image an optimized palette of colours. The package extracts a custom number of representative colours from the image. Let’s try to apply it on the “Vergine con il Bambino, angeli e Santi” before looking into its functional specification.

It’s an interesting package.  I’ll have to play around with it.

Comments closed