VizWiz

Launch, grow, and unlock your career in data
Showing posts with label cycle plot. Show all posts

May 3, 2024

How to Make Your Cycle Plots Actionable in Tableau

, , , , , , , , No comments

Cycle plots are a fantastic way to identify seasonality in a data set. And you can make them even more useful by adding indicators for whether they are above or below the average.

Here's how you can do that in Tableau in only 2 minutes.

Like this? You'll love Next-Level Tableau. Learn more at nextleveltableau.com.

May 1, 2024

How to Create a Cycle Plot in Tableau

, , , , , , , , , No comments
A cycle plot is used to display cyclical patterns or trends over time, such as days of the week or months, to identify patterns, compare groups, and visualize seasonality in data.

March 8, 2024

Visualizing Time Series Data in Tableau

, , , , , , , , , , , , , , , , , , No comments

Last night I was invited to speak at the Chicago Tableau User Group about visualizing time series data. Other than spatial data, time series data is my favorite to visualize. 

There seem to be endless methods for making time series data useful for analysis. Check out this video for 60ish ways to visualize time.

I had a 20 minute slot to present and, of course, I ran over time. I seem to do this with every session I run lately. Be it training for Next-Level Tableau, presenting at events, or running a livestream, I get into a groove and don't want to stop.

I was able to create 14 vizzes in 20+ minutes. I added an extra in this workbook to make the dashboard format nicely.

Click on the image below to download the workbook and dissect it. Get the data here to follow along. 

Have fun! 

August 17, 2022

Analyzing Seasonality with Cycle Plots

, , , , , , , , , , , , , , , No comments
Cycle plots are exceptionally useful for analyzing seasonality in time series data. In this video, I walk you through two examples that show the limitations of traditional time series analysis and two examples of how cycle plots overcome these problems. 

Inspired by: Jon Schwabish
Download the workbook here.

August 4, 2021

#MakeoverMonday Week 31 - Bicycle Collisions in London

, , , , , , , , , , , , , , , No comments
This week's data set was pretty straightforward. During #WatchMeViz I iterated through some maps, including joining to spatial files for London, and also lots of time series charts. Below are links to the resources, the video, and the final viz.

Resources:


June 19, 2017

Makeover Monday: Is America Improving Its Ozone Air Quality?

, , , , , , , , , , 2 comments
Eva and I are hosting another BrightTalk webinar this Friday titled "Visualizing Smart Cities: How Data can help shape our communities". This is part of an Internet of Things week for BrightTalk so when deciding what data set to pick for this week, I got to thinking about air quality sensors. A quick google search turned up a treasure trove of data on the EPA website. Thanks for my friends over at Exasol, I was able to create a place for all of us to play with all 202 million hourly measurements. If you want to play with the live connection to all 202M records, you will need a login which you can create via this registration if you do not already have one.

The EPA website also contained some basic reporting, which is the focus for this week's makeover.


What works well?

  • Simple layout. It's easy to see you have days within months going left to right and years going down.
  • Colors match the official EPA colors for the AQI categories
  • Including the ranges we know what constitutes a good reading vs. a bad reading
  • The title tells me what I'm looking. Including the date range is a nice touch too.
  • Using a strip plot along with the colors helps reveal seasonal patterns
  • Including the source in the footer

What could be improved?

  • Make the colors color-blind friendly
  • It's difficult to see how a month has changed across the years.
  • I can't hover to see the values.
  • It says each “tile” represents one day of the year and is color-coded based on the AQI level for that day, but I think it's actually showing the max measurement for each day. It should be more clear what they are representing.
  • There's very little context. How does one county compare to others? How does one county compare to the national average? 

What were my goals?

  • Last year I challenged The Data Duo to visualise an almost identical data set. Pooja created a pretty amazing viz (of course), so I wanted to pick some parts off of it. Particularly, the State selectors on each site and the dot plot.
  • I wanted to understand how each month changed across the years, which is pretty much exactly what a cycle plot was created for. I used a trend line instead of an average though because that seemed to show the patterns better.
  • I wanted to add context for comparisons to the national average and to the state average (which appears when you click on a state).
  • I wanted to use color-blind friendly colors.
  • I wanted a small sparkline-type chart to show how things have changed since 1990.

With these goals in mind, here is my Makeover Monday week 25 submission. Click on the image for the interactive version.

Subscribe to: Posts ( Atom )