The visualization required a critical data source from Rotten Tomatoes that was used to create the the scatter plot, Critics Score callout, and Audience Score callout. Tableau Prep was used to shape, combine, and clean 50 different data sources into one consolidated data connection! This flow was needed to prepare the data source to create my recent BLOCKBUSTER visualization. Using Tableau Prep to Shape, Combine, and Clean Dataīy the end of this post, you will be able to recreate this flow in Tableau Prep that pivots some columns to rows, then some rows to columns: This post uses the Rotten Tomatoes data source used to create my BLOCKBUSTER visualization to show you how to pivot columns to rows (pivot), rows to columns (unpivot), or both, in Tableau Prep 2019.1 or later. As long as you are a Tableau Desktop user with a Tableau Creator license, you can install Tableau Prep and do this yourself! You have been able to pivot columns to rows for a long time in both Tableau Desktop and Tableau Prep, but now it is even easier to quickly restructure an existing Excel report so you can start exploring it in Tableau right away. That’s why I was so excited to see that a new feature in Tableau Prep version 2019.1 is the ability to pivot rows to columns – or unpivot the fields. When used as a data connection, all these aspects of the data layout can be problematic for how Tableau interprets the data source and prevents you from easily exploring the data as Tableau was designed to do. These traditional reports often have dates in the column headers, measures in the rows instead of the columns, and subtotals, among other potential pitfalls. Forming one column for Sales and one for Profit would enable these two columns to be Measures when analysing the data in Tableau.One of the first topics I cover during my live Tableau training events is what I view as the single biggest barrier to Tableau adoption: connecting to a data source that was structured to be human-friendly in Excel. The Measures that are named in the Measure Column would be much easier to analyse if they were individual columns. Therefore, in this case, the Dates listed as headers at the moment will need to be pivoted. To analyse data over time in Tableau, one column containing all of the different dates would be more preferable and easier to use. The Measure Header is in the correct location, but is it necessary? The Measures are listed under each individual month. The Header for the Dimension is at the top of the column that contains all the relevant values. In this example, we can see Category is in the correct state. The data field can be set as a String but the Geographic Role will need to be allocated in Desktop. Geographic Roles - currently a geographic role can not be set and then carried over in to Tableau Desktop. Therefore, there is no need to order the columns Order of columns - Tableau Desktop and Server will absorb a dataset and order the fields shown in the Data Pane in Alphabetical Order. There are a few aspects that do not matter as well: For measures, if they are not numeric, they they will not be present in the list of measures. Is it a Dimension or Measure? Tableau will divide all data fields in to Dimensions (aspect to split the data up by) and Measures (the data fields to analyse).Ī single data type for each data field - a data field in Tableau (and most other tools) require a single data type. Here are the key aspects to consider when structuring data for Tableau:Ī single column for data field - these will form the data fields that are then dragged & dropped in Tableau When loading data in to Tableau Desktop, the software takes the first row of data as the headers for the columns and all subsequent rows as the data points for those headers. What shape is best for analysis in Tableau? By drawing out the structure of the input dataset, it becomes clear what alterations need to be made once you have an understanding on how data should be structured for analysis.
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