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Comment: Published by Scroll Versions from space DEV and version next


You can download the Dataset-TestScores.csv dataset.Most calculations, such as standard deviation, work for a single column of data. To perform analysis across all three columns, you must reshape the above dataset to look like the following:


  1. Load the TestScores dataset into the Transformer page. It should already be split out into five separate columns.
  2. The three columns listed side by side are data that has been organized in a pivot table. To break down this data, you must unpivot the data, which breaks down the data into a key column (containing TestScore1, TestScore2, TestScore1) and a value column, which contains individual test scores.

    D trans
    p02NameGroup size
    SearchTermUnpivot columns

  3. Rename the generated column of test scores to TestScore.
  4. The numeric information in the key column values can be extracted using the following:

    D trans
    p01NameColumn to extract from
    p02ValueCustom text or pattern
    p03NameText to extract
    SearchTermExtract text or pattern

  5. The key2 column contains just the numeric data now. Rename this column to TestNumber. You can drop delete the key column now.
  6. The dataset does not contain a primary key, which field containing a unique identifier for each row. The combination of last name, first name, and test number is a unique identifier for each row in the dataset:

    D trans
    SearchTermMerge columns

  7. Rename the new column to TestID. Typically, primary keys are listed as the first field in a dataset. You might want to move the column before the LastName column.
  8. You may have noticed that the data is still organized by name (first and last) and test number, so that an individual's tests are scattered throughout the dataset. To reorganize the information, you can re-aggregate the data using the following:

    D trans
    p01NameRow labels
    p03NameMax number of columns to create
    SearchTermPivot table


    Tip: The above retains all instances of tests that have been taken. If you are only interested in the average test score, you can remove the TestNumber and TestID groupings and the change the SUM function to AVERAGE. In the results, you have one average for each test taker.

  9. You may want to rename the aggregation column. Your final dataset should look like the following: