#workoutwednesday | Data Visualization | Tableau

#WorkoutWednesday wk29: Connected Scatter Plot over hover

This week #workoutwednesday challenge was set up by Rody Zakovich, it was about creating a connected scatter plot on hover which allows user experience (UX) feature not available in natively available in product.

Requirements

  • Dashboard size is 600 x 600
  • The Scatter Plot has Sales by Profit for each Category and Year
  • When a user hovers over any category, all years for the category will be connected by a line
  • The line connects the categories by year in ascending order

Data for the workout can be downloaded from here

Here is my output for the challenge (Click on Image for interactive version):

The Challenge seems to be simple but the actual challenge is to create the effect without affecting other categories i.e. they should still be visible and not disappear

Let me share the steps I performed to achieve this effect which I think is cool way to showcase scatter plot for user experience:

Step 1: Data Preparation

Since dataset has 3 categories, we will union the orders sheet twice with original data with required fields of Order_date, Category, sales and profit.

This union of dataset will help us to create the action filter in further steps.

Step 2: Calculated Fields

CalcProfit: we will use LOD function to create average of profit values on the basis of Category, Table Name, year of Order date) since we have duplicated the numbers average will help us get original values

CalcSales: we will use LOD function to create average of sales values on the basis of Category, Table Name, year of Order date) since we have duplicated the numbers average will help us get original values

SalesCategorywisesales: This field is to aggregate the data on each category using the Table name field

SalesCount: This field is conditional field to show the line chart in our next chart

CalcCategory: Final field of mapping each category to table name for Action Filter

Step 3: Create the visualisation

Replicate the below Visualisation with relevant fields into rows and column shelf then create the dual axis. Post this add required field into Marks shelf for both CalcSales and SalesCount field.

 

Step 4: Add Action Filter

Last but the most important step, create an dashboard and import the sheet into dashboard. Then select the Dashboard –> Action Filter

set the action on hover on the basis of CalcCategory to Table Name

Do few changes in format and tooltip

Now we are ready with visualization with user experience which we wanted to show.

Click here for Tableau file

Thanks Rody Zakovich for this workout.

Happy Data Visualisation!!!!

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#workoutwednesday | Data Visualization | Tableau

#WorkoutWednesday wk24: Do customers spend more on their First or Second Purchase

This week’s #workoutwednesday by Ann Jackson was to prepare dataset using Tableau Prep then to design visualisation to show customers spend more on their first or second purchase.

The list of full requirements can be found here but on a high level:

  • Create a dataset using Tableau prep which will return customer level first and second order information with regards to sales, no. of categories and no. of products sold in the order
  • Dataset will have 9 columns i.e. Customer id, 1st Purchase Date, 2nd Purchase Date, 1st Purchase Sum Sales, 2nd Purchase Sum Sales, 1st Purchase # Categories, 2nd Purchase # Categories, 1st Purchase # Products, 2nd Purchase # Products
  • Create scatter plot with First purchase sales vs second purchase sales with 2 strip plots
  • Sheets aligned in dashboard using float method

It was good reason to try out Tableau prep for first time and create the dataset for the challenge. Here is how my workflow looked like in Tableau prep:

developing the viz was pretty straight forward with scatter and strip plot but the tricky part was to arrange all the sheets into float order with pixel perfect output. Took a bit of time to arrange but was able to make it at last. Overall, enjoyed working on Tableau Prep. I will be writing on Tableau prep in coming days to explain how it works.

Here is my output for the challenge (Click on Image for interactive version)

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