#workoutwednesday | Data Visualization | Tableau

#WorkoutWednesday Week 10 – KEEP AN EYE ON SALES (Radial Chart)

This week’s #workoutwednesday was about creating radial chart with lines equally spaced on the percent of the year completed.

Requirements

  • Use sales for 2017.
  • The size of the dashboard 500px x 600px.
  • If you think of the segments as a clock, Week 1 should be at the 12:00 position.
  • The weeks should be evenly spaced based on the week number.
  • You’ll be using geometry. The minimum radius is 1. The maximum radius is 2.3. (Spoilers provide some math help.)
  • The space between the segments is .15.
  • Note the tooltips to get some assistance on your math.

Here is my radial chart using LOD functions and bit of trigonometry functions to generate chart:

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#MakeoverMonday | Data Visualization | Tableau

#MakeoverMonday: Equal Measures 2030 (International Womens Day)

#Makeovermonday partnered with Equal Measures 2030 for week 10 as we approach International Women’s day. This week we will be seeing how good or bad policymakers for 5 different countries are and how much awareness they have with women welfare in the country.

Here is the original dashboard:

I started with playing around with the survey data and create dashboard in simplified way to understand the responses and how well policymakers know the state of women in their respective countries. The requirement and data was share on http://www.makeovermonday.co.uk/data/ for week 10.

Below is my dashboard for #makeovermonday:

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#MakeoverMonday | Data Visualization | Tableau

How to make Bump Chart in Tableau

In today’s blog, we will learn about Bump Chart in Tableau. A Bump chart is used to visualize changes in rank over a period of time. Bump chart have very simple use and application in Tableau:

For this chart, I have used the world economic freedom data shared for #makeovermonday on http://www.makeovermonday.co.uk/data/ for last week makeover.

Step 1: Import the world economic freedom data into Tableau which I transformed into following format:

Step 2: Create a calculated field called rank on the score field using rank() function of Tableau:

Step 3: Drag Year (convert the Year to date format) to column shelf (I filtered the year from 2006 to 2015) and convert Year into discrete form and drag rank twice into rows. Then drag Index type column into filter and filter for “overall” Type and drag countries column into colors under marktype.

Step 4: For both the rank, change the calculation type by clicking on compute by and selecting countries and change the graph type to dual axis and use synchronise axis to have axis in sync

Step 5: Reverse the axis using edit axis option and change the graph type from automatic to circle for second Rank column:

Step 6: I set the filter for countries as well to display top 10 ranks and few changes in formatting then it will look like below:

That’s it our bump chart is ready

Final output is shared on Tableau public path here

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Data Visualization | Tableau

ICC top 20 ODI rankings – Sankey chart in Tableau

In today’s blog, I will guide you through how to use sigmoid function and create an Sankey chart using Tableau. Sankey diagrams are specific type of flow diagram in which the width of the arrows is shown proportionally to the flow quantity. Sankey diagram put a visual emphasis on the major transfers or flows within a system.

Below is the illustration of how sankey diagram looks:

This chart has 3 components:

1- Country on left side in stack bar format

2- Flow diagram in center showing the flow

3- Players name on the right side in stack bar

This graph shows depicts the Cricket players and the country where they belong.

Below is the final output of my Sankey chart using Tableau:

Since we have fair idea of Sankey diagram and what it shows lets get going and learn how to make one:

Step 1:

In our example we will consider top 20 ranked ICC cricketers for One day internationals for 2016 and 2017. Import the excel file into Tableau (Below screenshot of data)

Step 2:

Once data is imported we need to define the number of points to draw a smooth sigmoid curve. We will now create a calculated field “Point” and assign 1 for 2016 records and 49 for 2017 records:

Step 3:

For sigmoid curve, the coordinate values should be in between -6 and +6. To generate that curve we will create following calculated fields which we will use to create the curve:

Index = index()

X = 0.25*[Index]-6.25

Sigmoid = 1/(1+EXP(-[X]))

Curve = WINDOW_MIN(IF FIRST()=0 THEN MIN([Rank]) END)+[Sigmoid]*[Change]

Step 4:

Next is to create a bins (padded) based on Point. This will create additional 47 points which we need to create the curve through data densification

Step 5:

Drag Padded into rows and right click –> select show missing values then drag padded to details and then drag index into details as well and make it compute using Padded and similarly drag X into columns and curve into Rows in the sheet then make them compute using padded for both X & Curve as shown in below screen shot:

After bit of formatting, the chart will look like this with sigmoid curve with 2016 vs 2017 rankings of top 20 ODI batsmen:

 

Our sigmoid curve for Sankey graph is ready. Now, our next step should be to create one worksheet with all the countries and other stack bar with names of the players. Then we can add all sheets in dashboard to get desired Sankey flow chart output.

you can find tableau workbook here

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