This is Part III of a four-part post. Part I talks about scraping data from a website (bookdepository.com, in this case) while Part II discusses data cleaning/ preparation. Part III outlines the process of presenting the data using Tableau and Part IV delves into insights from the analysis.
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Capabilities of Tableau:
- Calculating average on the fly and assigning colors to values above/ below average via a calculated field.
IF AVG([Rating]) > WINDOW_AVG(AVG([Rating])) THEN "Above average" ELSEIF AVG([Rating]) < WINDOW_AVG(AVG([Rating])) THEN "Below average" ELSE "Average"
END
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- Treemap. The size and intensity of color of each box reflects the number of records. With the sparse book categories, there is a large number of boxes with only one record. We can use this chart as a filter as well, where clicking on one/ many boxes will filter the rest of the charts to focus on the selected book categories.
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- As there are repeated book titles but with different materials/ year of published and ISBN13 number, trying to show the ISBN13 number under tooltip is not possible. An * sign will be shown instead for repeated book titles. With the new capability of using viz in tooltip, this challenge can be overcome.
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Alternatively, the interactive dashboard can be found here.
The dataset can be found here.