{"id":660,"date":"2016-06-06T08:56:38","date_gmt":"2016-06-06T13:56:38","guid":{"rendered":"http:\/\/dataabinitio.com\/?p=660"},"modified":"2016-06-06T08:51:14","modified_gmt":"2016-06-06T13:51:14","slug":"these-are-a-few-of-my-favorite-tools","status":"publish","type":"post","link":"https:\/\/dataabinitio.com\/?p=660","title":{"rendered":"These are a Few of My Favorite Tools"},"content":{"rendered":"

If you follow me on twitter<\/a>, you may have noticed a small rant<\/a> the other day about how much I dislike how Excel handles dates (it’s a proven fact<\/a> that Excel is terrible with dates<\/a>). My beef with Excel got me thinking more about the programs I actually like to use for data processing and clean up. These are tools that I’d only stop using if you paid me serious money. And maybe even not then.<\/p>\n

Since I love these tools so much and since I’m mistress of my own blog, I’m going to spend this post proselytizing about them to you because I want you to love them too. So here are my top 4 you-might-not-know-about-them-but-really-should tools for hacking at your data. Some of them only do a small job, but they do it incredibly well and are just what you need in a specific instance.<\/p>\n

 <\/p>\n

Regular Expressions<\/strong><\/p>\n

<\/strong>Regular expressions<\/a> (or regex) are a somewhat obscure little tool for search and replace but I’ve found nothing better for cleaning up text. Regular expressions work by pattern matching text and have a lot of flexibility. Need to find every phone number in a document? Want to clean up dates? Have to reformat a document while keeping the text the same? Regex is the tool for you.\u00a0Regex isn’t a standalone program but rather plugs into other tools (including all of the tools below, as well as some programming languages). I recommend this tutorial<\/a> for getting started.<\/p>\n

Notepad++<\/strong><\/p>\n

<\/strong>While not as dazzling as the other players on this list, Notepad++<\/a>\u00a0is my go-to text editor and the main platform I use for leveraging regular expressions. It’s always good to have an open source text editor around and this one is my particular workhorse.<\/p>\n

OpenRefine<\/strong><\/p>\n

OpenRefine<\/a>\u00a0(formerly Google Refine) in an open source tool for cleaning up spreadsheet data. This tool allows you to dig into your data by faceting it across any number of variables. I find it particularly handy for generating counts; for example, it’s incredibly easy to find out how many times {variable1=X AND variable2=Y} versus {variable1=X AND variable2=Z}. Faceting also allows for editing of select subsets of data. You can also do stronger data manipulations, such as streamlining inconsistent spelling and formatting or breaking multi-component cells apart\/collapsing columns together. I recommend this tutorial<\/a> for getting started.<\/p>\n

Bulk Rename Utility<\/strong><\/p>\n

<\/strong>Need to rename a number of files? Bulk Rename Utility<\/a>\u00a0is the tool for you! This software allows you to rename files in very specific ways such as: adding characters to the ending, removing characters from the name beginning, changing something at a specific position in the name, and much more. You can also add numbering and dates to file names or do a custom search and replace with regular expressions. I don’t use Bulk Rename Utility a lot, but it saves me a ton of time and energy when I do.<\/p>\n","protected":false},"excerpt":{"rendered":"

If you follow me on twitter, you may have noticed a small rant the other day about how much I dislike how Excel handles dates (it’s a proven fact that Excel is terrible with dates). My beef with Excel got … Continue reading →<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[],"class_list":["post-660","post","type-post","status-publish","format-standard","hentry","category-dataanalysis"],"_links":{"self":[{"href":"https:\/\/dataabinitio.com\/index.php?rest_route=\/wp\/v2\/posts\/660","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dataabinitio.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/dataabinitio.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/dataabinitio.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/dataabinitio.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=660"}],"version-history":[{"count":10,"href":"https:\/\/dataabinitio.com\/index.php?rest_route=\/wp\/v2\/posts\/660\/revisions"}],"predecessor-version":[{"id":670,"href":"https:\/\/dataabinitio.com\/index.php?rest_route=\/wp\/v2\/posts\/660\/revisions\/670"}],"wp:attachment":[{"href":"https:\/\/dataabinitio.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=660"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/dataabinitio.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=660"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/dataabinitio.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=660"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}