Tag Archives: data munging

Easy Data Transform v1.1.0

I released v1.1.0 of Easy Data Transform this week. It is a big upgrade, with some major new features.


There is a new Javascript transform. This allows you to create custom transforms for anything that is too specialist to do with the other 37 built-in transforms. I’m not a fan of Javascript, with its horrible scoping and typing, and I would have preferred Python or Lua. But there is a Javascript engine built into Qt, so this was the easiest way to add scripting. Now if you want to multiply two columns of your data together in Easy Data Transform, you can just do this:


You can also access Javascript maths, date and string functions. So you can do some pretty complicated stuff. Hopefully the built-in transforms are enough to cover 95% of data transformations. But the new Javascript transform adds some serious flexibility for the remainder. The Qt Javascript engine is also pretty fast. In testing I was able to multiply values from 2 columns together across 10,000 rows in less than 0.03 seconds.

There is a new Lookup transform. This allows you to lookup values for one dataset in another dataset. For example, if you have a dataset with a column for country code and another dataset with columns for the country code and tax rate, you can look up the tax rate by country code.

Previously you could only output your data in Excel and delimited text formats (including CSV and TSV). The new release also adds output to JSON, HTML, Markdown, vCard, YAML and XML formats.

I have improved the speed of the Join transform significantly using hashing. This makes a big difference with large datasets.

To save time, Easy Data Transform guesses the likely columns you want to use as keys when you Join, Intersect, Lookup or Subtract two datasets. For example if 2 datasets both have colummns called ‘ID’ with lots of unique values that are common to both columns, it will choose those two columns as the default key columns. I have improved the heuristic used to set the default columns.

You can now add comments to input, transform and output nodes as a note to a colleague or your future self.

You can now snap your input, transform and output nodes to a grid, so you can keep your layout all lovely and neat.

I have also made some bug fixes and minor improvements.

Haven’t tried Easy Data Transform yet? Got some table or list data that you need to wrangle into a more useful form? Take the free trial for a spin.


Easy Data Transform v1.0.0 released


I finally released a paid version of Easy Data Transform today, for both Windows and Mac. I am very pleased with how it has turned out. Obviously it is only v1.0.0, so there is plenty of additional features I could add, including:

  • Batch processing
  • Support for JSON, XML, SQLite input/output
  • More transforms
  • A 64 bit version for Windows
  • A Linux version

But I need to listen carefully to prospective customers to decide which additional features to prioritize in future releases. It might be something I haven’t even thought of.

But v1.0.0 already has a really useful core of features. And, if you aren’t embarrassed by v1.0, you didn’t release it early enough. That said, I haven’t cut corners on quality. It has proper documentation and has been through extended beta testing, dogfooding and several rounds of usability and third party testing.

The product has a fully-functional 7 (non-consecutive) day free trial. I think that is enough for prospective customers to decide if it does what they need. I also have a 60 day money-back guarantee.

I have decided to go with a subscription model: $99 / €90 / £75 + tax per person per year. Which covers up to 3 computers. At this price point I can afford some paid promotion and to provide a decent level of support. I am not offering a monthly subscription, as I don’t really want people who are going to pay for 1 month (to do their annual TPS reports) and then cancel.

Have you got some data you need to merge, clean, reformat or de-dupe? Give it a try. You can get a 25% discount if you buy a subscription by the 27th December 2019 using this link.