Grroom is a data clean-up tool to prepare your data sets for analysis and usage.
On the initial screen, open your CSV file to edit with the "Upload" button to get started. The list of changes you can make are to the right side of the screen. The lower portion of that section are some suggestions detected by Grroom to jump start your data-cleanup efforts.
You can make your own modifiers to apply to your data set. See Custom Modifiers.
Modifiers are actions you can apply to your data set to change in the way you desire. Grroom suggests some actions you can take once you upload a data set. You can select "Preview" on any modifier to show exactly how it would modify your data and the specific rows it would affect.
If Grroom does not come up with a modifier that you need, you can make your own with JavaScript! This can be handy if you want to transform the data is a specific column in every row or even accumulate to fix an indexing issue.
Custom modifiers can be written with ES5 (ES6 and onward coming soon). You can trust that Grroom does not eval() your code or make you vulnerable to XSS and injection attacks: The code you write is executed using JS-Interpreter, an amazing library written for exactly this reason: to be used in isolation and safety.
When you select the "+ New Modifier" button, an example is used a a template to work with. It is recommended that you maintain the row reference when mapping through the data set. The wrapping modify function is what will be called when your modifier is executed, and it's argument must be a function with the arguments rows, columnNames. This function must return a row array in the same structure as it was given as input. Writing code outside of the modify function may result in unexpected behavior.
To export your data set, simply click "Export" to the right of the file name input bar.
In the project directory, you can run npm start
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