For #MakeoverMonday week 31, this week’s makeover viz was about The Big Mac Index by The Economist. This index was based on “Big Mac Hamburger” price across various countries where it is sold to analyse the purchasing power parity.

Here is the original viz :

Data is available on data.world and source of data was The Economist

Whats good?

  • Clear Legends showing price of Jul’17 and Jan’18 along with Price of Big Mac price in US Dollar
  • Zero reference line to see the difference and sorting the countries with latest prices
  • Sub-titles explaining the overvalued and undervalued with signs along with caveats

Here is what I did:

  • Rather then using price of last 2 years, I selected price of last 10 years starting Jul’2009 and used only July prices for all the years
  • Designed an jitter plot to show the plot the country wise price variation in comparison to US price
  • Interactive tooltip to show Big Mac price in various countries with there overvalued and undervalued against US dollar and highlight option to select a country for trend

Here is the Image of the visualisation I created (Click on image to get interactive version):

Click here for Tableau file

Thanks Eva Murray & Andy Kriebel for this workout.

Happy Data Visualisation!!!!

Thanks for visiting this post. Please do let me know your feedback or if you have any questions about the blog do not hesitate to contact me on twitter (@Desaimithun)

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This week #workoutwednesday challenge was set up by Ann Jackson. It was slightly difficult challenge as this week it was about finding signals or patterns in data with use of control chart. It was more about finding statistical signals using standard deviations and mean/ medians with signals to indicate change in pattern or trend or finding an outlier within the dataset. This is good way to analyze the data and get statistical insights/ signals from the data about pattern and behavior.

Requirements: 

Available here

Data for the workout can be downloaded from here

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

It took me time to understand the requirement and figure out the way to design the visualisation. lookup() & windows functions did help a lot to build this requirement

Let me share the steps required to create this visualisation post data is imported into Tableau:

Step 1: Create 2 parameters for the requirement

Select a Middle line: This parameter to provide drop down option for either median or mean

Select A Test: This parameter to select the type of test we want to perform (outliers, Trend or change)

Step 2: Create the calculated fields required for the visualisation

Middle Line: This field is based on parameter “SELECT A MIDDLE LINE” and based on selection we will have either median or mean of sales

 

+3SD: This field is to calculate + 3 standard deviation based on middle line

-3SD: This field is to calculate – 3 standard deviation based on middle line

TEST – Outliers: Boolean field to highlight the outliers in the dataset i.e. if the sales value is either above +3SD or -3SD

 

TEST – TREND: Boolean field to highlight the trend whether current sales > previous month > previous to previous month or current sales < previous month < previous to previous month.

TEST – CHANGE: Boolean field to highlight whether 3 consecutive fields are below or above middle line.

TEST – SELECTION: This field is based on “SELECT A TEST” Parameter and uses above 3 calculated field to show the required value.

Tooltip – Signal: Tooltip to show signal if the sales value matches with any of the parameter selection criteria

Show Text: This is the field to show the necessary text based on parameter selection

STEP 3: There are 3-4 more fields which we need to create but lets start creating data visualisation for first 2 sheets

Drag Order date to column shelf (convert to month)

Drag Sum(sales) and TEST Selection to rows shelf then change it to dual axis followed by sync axis

Drag Middle line, +3SD, -3SD to details in Marks Area

Add a 3 reference lines on the basis of Middle line, +3SD and -3SD

Add Parameter control for Parameters “Select a Middle line” and “Select A TEST”

Then format the sheet as per requirement with tooltips and it will look like following:

Create an new sheet for Text data and drag Show text field to Text

Step 4: Final sheet for Monthly strip chart

For Strip chart, we will need to add following fields into the dataset

TREND: This is boolean field which we will use to highlight the pattern for Trend

CHANGE:This is boolean field which we will use to highlight the pattern for Change

SymbolCOLOR: Based on Parameter selected for the test, this is will return values for the test select and we will use this as also to segregate data into 3 color bucket of blue, amber and orange to show following:

  • Meets the test criteria
  • Part of test pattern

Finally, we will create 3rd sheet with strip chart:

Drag Order date to column shelf (convert to month)

Then Drag symbolColor to color and shape area under Marks area then create the tooltip to show the values

Step 5: Create the Dashboard

Add all 3 sheets into dashboard as per below image:

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

Click here for Tableau file

Thanks Ann Jackson for this workout.

Happy Data Visualisation!!!!

Thanks for visiting this post. Please do let me know your feedback or if you have any questions about the blog do not hesitate to contact me on twitter (@Desaimithun)

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For #MakeoverMonday week 30 and this is my 50th Post, Eva shared the viz on paid maternity leave for various countries including the OECD. This viz shows the weeks of paid maternity leave and average payment rate across maternity leave.

Here is the original viz :

Original Visualization

Data is available on data.world and source of data was OECD

Whats good?

  • Clear sub-titles with explanation what each chart represents
  • Sorted on number of paid weeks of maternity leave
  • Showing how much each country pays for Maternity leave in %

Here is what I did:

  • First thing I observed was that non-european countries has lower paid maternity weeks than european countries. Hence I filtered for non-european countries and remove all european countries
  • Create Ring chart to show the values on Paid maternity weeks of leave and simple one chart solution to display results.
  • Selected hue-circle color palette to show countries with different colors

Here is the Image of the visualisation I created (Click on image to get interactive version):

Click here for Tableau file

Thanks Eva Murray for this workout.

Happy Data Visualisation!!!!

Thanks for visiting this post. Please do let me know your feedback or if you have any questions about the blog do not hesitate to contact me on twitter (@Desaimithun)

Do subscribe to Tabvizexplorer.com to keep receive regular updates.

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!!!!

Thanks for visiting this post. Please do let me know your feedback or if you have any questions about the blog do not hesitate to contact me on twitter (@Desaimithun)

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For #MakeoverMonday week 29, Andy shared the viz from What’s the Cap? and it was designed by whatsthecapIt was about NBA Team salaries and Salary cap since 1985-86. 

Here is the original viz :

Screen Shot 2018-07-15 at 12.46.55 pm.png

Data is available on data.world and source of data was Celtics Hub

Whats good?

  • Interactive tooltips to know the max, min and average salaries and actual salary cap
  • Clean time-series data with 3 distinct lines for highest, average and lowest payroll with bar chart to plot the salary cap which depicts the trend over last 32 seasons
  • Clear Y-axis labeling
  • Use of different colors for each line and bar with legend to distinguish each other

Here is what I did:

  • First of all I used the Andy’s Franchise mapping, since the teams have moved cities and changed their names over last 30 years.
  • I wanted to show all the teams which helps in comparisons and I finalized on bar chart.
  • Added indicator line for salary cap to see how many franchises adhere to salary cap and how many spent above salary cap
  • I wanted to compare franchises salary vs salary cap each season hence I introduced the filter for season
  • Added tooltip and text label to show the variance in Teams salary vs salary cap

Here is the Image of the visualisation I created (Click on image to get interactive version):

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