2023 Week 03 | Power BI: Vertical Area Chart

2 Comments / Power BI, Workout Wednesday / By

Introduction

Howdy All!

We’re all topsy-turvey this week turning line charts on their side! ⇩🙃

This weeks challenge was inspired by Nick Desbarats article Are Vertical Line Charts Ever a Good Idea?

Can you find some other examples where vertical line charts may be a good idea?

⋟^◕ܫ◕^⋞ Happy Vizzing

Requirements

Power Query
  1. Obtain the voteview_polarization_data.csv dataset from Voteview | Polarization in Congress
  2. Save locally
  3. From Power BI Desktop, get data from step 2
  4. Select chamber, congress, year, rep.mean.d1, dem.mean.d1 fields and remove all others
  5. Unpivot rep.mean.d1, dem.mean.d1 fields
  6. Load
Power BI Desktop
  1. Import Plotly.JS Custom Visual found in AppSource
  2. Place fields in Field Well
  3. From the ellipsis of the custom visual header, select edit visual
  4. Add Area Trace
  5. Add Transform, Split By, then split by category (Republican/Democrat)
  6. Add Transform, Sort, then sort by year
  7. Style of Trace:
    1. Set Stack to None
    2. Set Area Fill to X = 0
  8. In the JSON set autorange = “reversed”, to reverse the Y-Axis, hit save
  9. Format as desired.

Dataset

The dataset this week can be viewed here: https://voteview.com/articles/party_polarization

Ensure you cite the sources before sharing:

Pew Research Centre : https://www.pewresearch.org/fact-tank/2022/03/10/the-polarization-in-todays-congress-has-roots-that-go-back-decades/
Source : Data Lewis, Jeffrey B., Keith Poole, Howard Rosenthal, Adam Boche, Aaron Rudkin, and Luke Sonnet (2023). Voteview: Congressional Roll-Call Votes Database. https://voteview.com/

Share

After you finish your workout, share on Twitter using the hashtags #WOW2022 and #PowerBI, and tag @JSBaucke, @MMarie, @shan_gsd, @KerryKolosko, @NerdyWithData. Also make sure to fill out the Submission Tracker so that we can count you as a participant this week in order to track our participation throughout the year.

Solution

Solution File available for download via Data Stories Gallery