Introducing the "Change plot"

A common issue I've seen is how to visually represent percentage change and current values for a high number of categories at the same time. To solve for this, I created a new chart type called the "Change plot." 

Read and click through the Tableau story below to learn more about it. Click on the far right of the Tableau toolbar to view in full screen. Another new chart type I invented is the Polyarea chart, which you can read about here.

Building and modifying Tufte boxplots in R

In this post, I included an example of how to build and modify Tufte boxplots in R. The data is from DataSF through the open data initiative and relates to SF Police Department crime incidents. Here is what the final product looks like (click the image to increase the size):

For more unique data visualizations, checkout out my posts on the Polyarea chart and Change plot. 

How to create a Polyarea chart

I was interested in displaying the percent of total for many categories over time. However, I didn’t want to use a stacked bar chart or stacked area chart. This is primarily because it can be difficult to determine if the categories in the middle of these charts are increasing or decreasing over time since there is no common baseline. I created a new way to visualize this data in Tableau that combines many area charts (hence the name Polyarea chart). This can be built in less than a few minutes. This chart has been internationally recognized and can also be created using D3.js. 

Using embedded extracts to edit published data sources on Tableau Server

There are advantages to using a published data source, but there is one downside to using them. As mentioned in this link, it is not possible to edit a published data source directly on Tableau Server and requires that the developer make a local copy of the data source. The method described in the link is not ideal for the following reasons:

Response to specific date functionality question

I've received some great feedback from the Tableau community regarding my blog post about How to default your Tableau dashboard to yesterday (quadrupled my Total Site Pageviews!) so I thought I would answer a question that I received on Linkedin about a specific date functionality: 

Next Level Popping Parameters, Part 2

This is Part 2 of the Next Level Popping Parameters series. Part 1 of this series describes how to make horizontal Next Level Popping Parameters and Part 2 describes how to make them vertically. The methods that I’ve developed build upon the work that has been done by The Information Lab involving Popping Parameters.

Next Level Popping Parameters, Part 1

Before we get started, I thought it would be good to answer the following question: What are popping parameters and why should you use them? "Popping Parameters" is a term created by The Information Lab that refers to the idea of limiting what parameters are displayed to the user based on what the user has selected.

How to default your Tableau dashboard to yesterday

A common request when building a Tableau dashboard is to have the dashboard default to a specific time frame (e.g. yesterday or the last 7 days), but also allow for the ability to select a custom date range. This post focuses on how to build this functionality.