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- #HOW TO USE TES5EDIT TO AUTOMATICALLY CLEAN SERIES#
- #HOW TO USE TES5EDIT TO AUTOMATICALLY CLEAN DOWNLOAD#
#HOW TO USE TES5EDIT TO AUTOMATICALLY CLEAN SERIES#
If we want to categorize a big set of beer types at once, we nest a series of if statements inside each other. If statements here are straightforward: If the first part is true, transform the whole value to "lager " otherwise, replace the cell value with itself (or, do nothing). To look for "lager" and replace the entirety of the Beer types value with "lager" where applicable, we use an if statement: Start by clicking on "Manufacturer’s Brand." Select Edit Column then choose Create column based on this column. A Custom Text Facet on the Manufacturer’s Brand column brings up this window, into which we enter a filter: We’ll look for all cell values that contain "Porter" (this is also case-sensitive, but now that we’ve put everything in titlecase, the capital P should catch everything). We can do a quick check for one type of beer using a Custom Text Facet. We don’t want to manually label each entry, so let’s save some time by identifying beer types from the beers’ names. Let’s pretend these beers are our product data, and we want to add categories of beer to our catalogue. The next step is to do clever things with all this data. Categorize Data Automatically in OpenRefine Click again on the dropdown menu for the column, go to Edit cells, and read through all the possibilities. Let’s also get rid of all the uppercase brewery names by transforming the whole column to Titlecase. There are also some common transform tools you can use to clean stuff up, like eliminating all the spaces before and after text. It can also take XML and JSON files, if that’s your jam. You'll need some data for OpenRefine to work with-and it open any data in a spreadsheet format: CSV, XLS, or even a Google Sheets spreadsheet online. It’ll open up a browser tab that looks much like other Google Apps, and will ask you to create a project, or open a project you’ve already started.
#HOW TO USE TES5EDIT TO AUTOMATICALLY CLEAN DOWNLOAD#
Just download OpenRefine-it works on Windows, Mac, and Linux-and start the program. It may just be what you need to finally finish that data project you’ve been putting off. OpenRefine was built especially with those types of bulk operations in mind. Maybe your survey results are messy, your app exports are confusing, or your analytics data needs combined from multiple sources. Your PR staff could have multiple email lists from campaigns past you want to merge, modify, or de-duplicate. Your accounting staff might have legacy data floating around from years ago. You sales team could want to export old store data, reorganize it, and import it into a new eCommerce app. To you, this could mean a number of things. Today it's a community-run, open-source project to, well, refine your data. OpenRefine bills itself, simply, as "a powerful tool for working with messy data." Originally released 2010 as " Freebase Gridworks," it was later called "Google Refine" after being acquired by the search giant. My favourite tool for this is called OpenRefine, and its specialty is "reconciling" or "normalizing"-making it easy to find typos, variations on phrases, formatting errors, extra spaces, and other things that are hard to spot in rows upon rows of information. The good news is, if you can get your messy data into a spreadsheet, you can clean up and reformat it. It was quite the chore-a chore many of us face when trying to organize data. My job was transferring everything to yet another contractor-which meant cleaning up thousands of records to play nice with the new vendor’s fancy online inventory. Add in the random mistakes that added up over time, and you had quite a mess. Storage contracts changed several times-so the box codes and vendor receipts varied over time. Most records had a box number, storage date, storage vendor receipt number, and a rough idea of the contents. Materials were indexed in a document table. I once worked for a company that stored paperwork offsite for 60 years. Ever had to manually edit dusty, messy, years-old information from some obsolete software?