Easy Data Transform v1.13.1
For Windows and Mac

This release adds bug fixes and improvements to v1.13.0. The download links are at the bottom of the page.

We recommend that you back-up important transform files before installing any new release. Please let us know of any problems or issues you encounter with the release.

You can uninstall old releases after you have successfully installed this version.

Windows and Mac

1. Easy Data Transform can now read larger delimited files. In testing we were able to read in a 1.6 GB CSV file with 20 million rows and 10 columns.

2. Easy Data Transform is now approximately 10% faster at reading in delimited files. In testing we were able to read a 60 MB CSV file with 500,000 rows and 14 columns in just 2.3 seconds.

3. The Sort transform has been significantly speeded up for sorting by date and numeric columns. In testing:

• Sorting a 500,000 row dataset by a date column was approximately 20 times faster.
• Sorting a 500,000 row dataset by a numeric column was approximately 2 times faster.

Thanks to Mark S. for reporting the slow performance with dates.

4. The Sample transform now has an option to sample Randomly. This uses a pseudo-random number generator to select rows from the input data. The pseudo-random number generator should always give the same results with the same Random seed, even across Windows and Mac versions of Easy Data Transform.

5. In the Summary transform:

• An Integer values row has been added.
• The Unique values row has been renamed to Distinct values.
• A Unique values row has been added to show the number of values that occur only once in a column.
• A Duplicated values row has been added to show the number of values that occur more than once in a column.

6. The automatic layout has been improved when inserting transforms between existing items in the Center pane.

7. Processing no longer starts while drop-down lists are open in the Right pane.

8. Fixed a bug in the Unique transform which could occur when adding a Count column to a dataset with no column headers.

9. Fixed a bug in the Split Rows transform which could occur for datasets with no column headers.

10. Fixed a bug in the Slice transform.