{"id":3642,"date":"2015-08-24T12:51:05","date_gmt":"2015-08-24T17:51:05","guid":{"rendered":"http:\/\/rud.is\/b\/?p=3642"},"modified":"2018-03-07T16:43:28","modified_gmt":"2018-03-07T21:43:28","slug":"new-pacakge-docxtractr-easily-extract-tables-from-microsoft-word-docs","status":"publish","type":"post","link":"https:\/\/rud.is\/b\/2015\/08\/24\/new-pacakge-docxtractr-easily-extract-tables-from-microsoft-word-docs\/","title":{"rendered":"New Pacakge “docxtractr” – Easily Extract Tables From Microsoft Word Docs"},"content":{"rendered":"

UPDATE<\/strong>: `docxtractr` is now [on CRAN](https:\/\/cran.rstudio.com\/web\/packages\/docxtractr\/index.html)<\/p>\n

———————<\/p>\n

This is more of a follow-up from [yesterday’s post](http:\/\/rud.is\/b\/2015\/08\/23\/using-r-to-get-data-out-of-word-docs\/). The hack and function in said post was fine, but it was limited to uniform tables and made you do more work than you had to. So, there’s now a `devtools`-installable package [on github](https:\/\/github.com\/hrbrmstr\/docxtractr) that makes it way easier to get information about the tables in a Word document and extract them—uniform or not.<\/p>\n

There are plenty of examples in the GitHub README and also in the package examples. But, I will show the basic functionality here.<\/p>\n

The package ships with four example Word documents, but we’ll work with the last one: `complex.doc`. It has five tables and the last two have varying columns and rows and look like:<\/p>\n

\"complex\"<\/p>\n

Let’s read those two in:<\/p>\n

complx <- read_docx(system.file("examples\/complex.docx", package="docxtractr"))\r\n\r\ndocx_tbl_count(complx)\r\n#> [1] 5\r\n\r\ndocx_describe_tbls(complx)\r\n#> Word document [\/Library\/Frameworks\/R.framework\/Versions\/3.2\/Resources\/library\/docxtractr\/examples\/complex.docx]\r\n#> \r\n#> Table 1\r\n#>   total cells: 16\r\n#>   row count  : 4\r\n#>   uniform    : likely!\r\n#>   has header : likely! => possibly [This, Is, A, Column]\r\n#> \r\n#> Table 2\r\n#>   total cells: 12\r\n#>   row count  : 4\r\n#>   uniform    : likely!\r\n#>   has header : likely! => possibly [Foo, Bar, Baz]\r\n#> \r\n#> Table 3\r\n#>   total cells: 14\r\n#>   row count  : 7\r\n#>   uniform    : likely!\r\n#>   has header : likely! => possibly [Foo, Bar]\r\n#> \r\n#> Table 4\r\n#>   total cells: 11\r\n#>   row count  : 4\r\n#>   uniform    : unlikely => found differing cell counts (3, 2) across some rows \r\n#>   has header : likely! => possibly [Foo, Bar, Baz]\r\n#> \r\n#> Table 5\r\n#>   total cells: 21\r\n#>   row count  : 7\r\n#>   uniform    : likely!\r\n#>   has header : unlikely\r\n\r\n\r\ndocx_extract_tbl(complx, 4, header=TRUE)\r\n#> Source: local data frame [3 x 3]\r\n#> \r\n#>   Foo  Bar Baz\r\n#> 1  Aa BbCc  NA\r\n#> 2  Dd   Ee  Ff\r\n#> 3  Gg   Hh  ii\r\n\r\ndocx_extract_tbl(complx, 5, header=TRUE)\r\n#> Source: local data frame [6 x 3]\r\n#> \r\n#>    Foo Bar Baz\r\n#> 1   Aa  Bb  Cc\r\n#> 2   Dd  Ee  Ff\r\n#> 3   Gg  Hh  Ii\r\n#> 4 Jj88  Kk  Ll\r\n#> 5       Uu  Ii\r\n#> 6   Hh  Ii   h<\/code><\/pre>\n
It reads in “uniform” tables properly and will warn you if there is a header marked in Word but not asked for in the extraction.<\/p>\n
Next steps are to both allow specifying column types and try to guess column types (`readr` has some nice functions for this) and perhaps return more metadata (if possible).<\/p>\n
Feature requests & bug reports are most welcome [on GitHub](https:\/\/github.com\/hrbrmstr\/docxtractr\/issues).<\/p>\n","protected":false},"excerpt":{"rendered":"
UPDATE: `docxtractr` is now [on CRAN](https:\/\/cran.rstudio.com\/web\/packages\/docxtractr\/index.html) ——————— This is more of a follow-up from [yesterday’s post](http:\/\/rud.is\/b\/2015\/08\/23\/using-r-to-get-data-out-of-word-docs\/). The hack and function in said post was fine, but it was limited to uniform tables and made you do more work than you had to. So, there’s now a `devtools`-installable package [on github](https:\/\/github.com\/hrbrmstr\/docxtractr) that makes it way easier […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":true,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"activitypub_content_warning":"","activitypub_content_visibility":"","activitypub_max_image_attachments":3,"activitypub_interaction_policy_quote":"anyone","activitypub_status":"","footnotes":""},"categories":[91,732],"tags":[810],"class_list":["post-3642","post","type-post","status-publish","format-standard","hentry","category-r","category-xml","tag-post"],"yoast_head":"\nNew Pacakge "docxtractr" - Easily Extract Tables From Microsoft Word Docs - rud.is<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/rud.is\/b\/2015\/08\/24\/new-pacakge-docxtractr-easily-extract-tables-from-microsoft-word-docs\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"New Pacakge "docxtractr" - Easily Extract Tables From Microsoft Word Docs - rud.is\" \/>\n<meta property=\"og:description\" content=\"UPDATE: `docxtractr` is now [on CRAN](https:\/\/cran.rstudio.com\/web\/packages\/docxtractr\/index.html) ——————— This is more of a follow-up from [yesterday’s post](http:\/\/rud.is\/b\/2015\/08\/23\/using-r-to-get-data-out-of-word-docs\/). 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Also: docxtractr is now on CRAN This was asked on twitter recently: Is it possible to import data entered in MS Word into R - I have\u2026","rel":"","context":"In "R"","block_context":{"text":"R","link":"https:\/\/rud.is\/b\/category\/r\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":4547,"url":"https:\/\/rud.is\/b\/2016\/07\/24\/mid-year-r-packages-update-summary\/","url_meta":{"origin":3642,"position":1},"title":"Mid-year R Packages Update Summary","author":"hrbrmstr","date":"2016-07-24","format":false,"excerpt":"I been updating some existing packages and github-releasing new ones (before a CRAN push). Most are \"cyber\"-related, but there are some general purpose ones. Here's a quick overview: docxtractr (CRAN, now, v0.2.0) was initially designed to make it easy to get data tables out of MS Word (docx) documents. The\u2026","rel":"","context":"In "R"","block_context":{"text":"R","link":"https:\/\/rud.is\/b\/category\/r\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":6491,"url":"https:\/\/rud.is\/b\/2017\/09\/28\/sodd-stackoverflow-driven-development\/","url_meta":{"origin":3642,"position":2},"title":"SODD \u2014 StackOverflow Driven-Development","author":"hrbrmstr","date":"2017-09-28","format":false,"excerpt":"I occasionally hang out on StackOverflow and often use an answer as an opportunity to fill a package void for a particular need. docxtractr and qrencoder are two (of many) packages that were birthed from SO answers. I usually try to answer with inline code first then expand the functionality\u2026","rel":"","context":"In "R"","block_context":{"text":"R","link":"https:\/\/rud.is\/b\/category\/r\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":11746,"url":"https:\/\/rud.is\/b\/2019\/01\/10\/waffle-geoms-other-miscellaneous-in-development-package-updates\/","url_meta":{"origin":3642,"position":3},"title":"Waffle Geoms & Other Miscellaneous In-Development Package Updates","author":"hrbrmstr","date":"2019-01-10","format":false,"excerpt":"More than just sergeant has been hacked on recently, so here's a run-down of various ? updates: waffle The square pie chart generating waffle? package now contains a nascent geom_waffle() so you can do things like this: library(hrbrthemes) library(waffle) library(tidyverse) tibble( parts = factor(rep(month.abb[1:3], 3), levels=month.abb[1:3]), values = c(10, 20,\u2026","rel":"","context":"In "R"","block_context":{"text":"R","link":"https:\/\/rud.is\/b\/category\/r\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2019\/01\/fwg.png?fit=900%2C1200&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2019\/01\/fwg.png?fit=900%2C1200&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2019\/01\/fwg.png?fit=900%2C1200&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2019\/01\/fwg.png?fit=900%2C1200&ssl=1&resize=700%2C400 2x"},"classes":[]},{"id":8230,"url":"https:\/\/rud.is\/b\/2018\/02\/16\/pym-js-library-vulnerability-in-widgetframe-package\/","url_meta":{"origin":3642,"position":4},"title":"Pym.js Library Vulnerability in widgetframe Package","author":"hrbrmstr","date":"2018-02-16","format":false,"excerpt":"What's Up? The NPR Visuals Team created and maintains a javascript library that makes it super easy to embed iframes on web pages and have said documents still be responsive. The widgetframe R htmlwidget uses pym.js to bring this (much needed) functionality into widgets and (eventually) shiny apps. NPR reported\u2026","rel":"","context":"In "Cybersecurity"","block_context":{"text":"Cybersecurity","link":"https:\/\/rud.is\/b\/category\/cybersecurity\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":3460,"url":"https:\/\/rud.is\/b\/2015\/06\/15\/metricsgraphics-0-8-5-is-now-on-cran\/","url_meta":{"origin":3642,"position":5},"title":"metricsgraphics 0.8.5 is now on CRAN!","author":"hrbrmstr","date":"2015-06-15","format":false,"excerpt":"I'm super-pleased to announce that the Benevolent CRAN Overlords [accepted the metricsgraphics package](http:\/\/cran.r-project.org\/web\/packages\/metricsgraphics\/index.html) into CRAN over the weekend. Now, you no longer need to rely on github\/devtools to use [MetricsGraphics.js](http:\/\/metricsgraphicsjs.org\/) charts from your R scripts. If you're not familiar with `htmlwidgets`, take a look at [the official site for them](http:\/\/www.htmlwidgets.org\/).\u2026","rel":"","context":"In "d3"","block_context":{"text":"d3","link":"https:\/\/rud.is\/b\/category\/d3\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]}],"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/posts\/3642","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/comments?post=3642"}],"version-history":[{"count":0,"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/posts\/3642\/revisions"}],"wp:attachment":[{"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/media?parent=3642"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/categories?post=3642"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/rud.is\/b\/wp-json\/wp\/v2\/tags?post=3642"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}