#Codec pack for mac 2013 mac os#
#Codec pack for mac 2013 update#
#Codec pack for mac 2013 code#
#Codec pack for mac 2013 plus#

New capabilities for email and compliance Access and edit project-related email stored in Exchange andДocuments stored in SharePoint directly from Outlook using siteДЄvoid mistakenly sending email with sensitive information to Plus, Access, Skype for Business, and InfoPath are

#Codec pack for mac 2013 plus#

Office Professional Plus 2013 enables you to work together evenД«etter by giving you more control over compliance, new tools forДЄnalyzing and sharing data, and more possibilities forД¬ommunication. Empower your employees with the latest productivity tools and theДЄbility to work from virtually anywhere.

#Codec pack for mac 2013 mac os#

It will not be plotted.Genuine Microsoft Office Home & Business 2013 / 2016 for MacД¬ompatible only with Windows 7, 8, 8.1, 10Дoes not run on Windows XP or Vista or Mac OS or ChromebookД¬ompatible with Windows 8.1,Windows 8, Windows 7, Windows ServerДў008 R2, or Windows Server 2012. Usemethod('removewords', could not be fit on page. In order not get an error message about the cores in the following way:ДЎ: In mclapply(x$content, function(d) tm_reduce(d, x$lazy$maps)) :ДЄll scheduled cores encountered errors in user codeД«ut when everything goes without error meassages i get(using the r_stats_text_corpus <- tm_map(r_stats_text_corpus, PlainTextDocument)) : R_stats_text_corpus <- tm_map(r_stats_text_corpus, content_transformer(tolower), lazy=TRUE) Trend <- getTrends(1, cainfo='cacert.pem') Trend <- availableTrendLocations(cainfo='cacert.pem')

Me <- getUser('davetang31', cainfo='cacert.pem') There are many other uses of the R twitteR package, for example you could run a daily cron job to check which of your followers have unfollowed you and so on. There are several posts on the web already on using the R twitteR package for text mining I found them after I had the idea of making a word cloud using peopleвЂ™s tweets that had a particular hash tag. Good to see that people are tweeting on training, workshops and resources for bioinformatics. I guess bioinformatics and genomics go hand in hand. Wordcloud(bioinformatics_text_corpus,min.freq=2,max.words=100, random.order=T, colors=pal2) Wordcloud with less words, minimum frequency and in colour I had a small chuckle on finding the word вЂњultratrickyвЂќ on the far left towards the top #wordcloud(bioinformatics_text_corpus, scale=c(2,0.2)) I learned who Hadley Wickham is after seeing thisД«ioinformatics <- searchTwitter('#bioinformatics', n=1500, cainfo='cacert.pem')Д«ioinformatics_text <- sapply(bioinformatics, function(x) x$getText())Д«ioinformatics_text_corpus <- Corpus(VectorSource(bioinformatics_text))Д«ioinformatics_text_corpus <- tm_map(bioinformatics_text_corpus,Д«ioinformatics_text_corpus <- tm_map(bioinformatics_text_corpus, content_transformer(tolower), mc.cores=1)Д«ioinformatics_text_corpus <- tm_map(bioinformatics_text_corpus, removePunctuation, mc.cores=1)Д«ioinformatics_text_corpus <- tm_map(bioinformatics_text_corpus, function(x)removeWords(x,stopwords()), mc.cores=1) R_stats_text_corpus <- tm_map(r_stats_text_corpus, function(x)removeWords(x,stopwords()), mc.cores=1) R_stats_text_corpus <- tm_map(r_stats_text_corpus, removePunctuation, mc.cores=1) R_stats_text_corpus <- tm_map(r_stats_text_corpus, content_transformer(tolower), mc.cores=1) R_stats_text_corpus <- tm_map(r_stats_text_corpus,Д¬ontent_transformer(function(x) iconv(x, to='UTF-8-MAC', sub='byte')),

#Codec pack for mac 2013 code#

# all scheduled cores encountered errors in user code

R_stats<- searchTwitter('#Rstats', n=1500, cainfo='cacert.pem') #alternative steps if you're running into problems R_stats_text_corpus <- tm_map(r_stats_text_corpus, function(x)removeWords(x,stopwords())) R_stats_text_corpus <- tm_map(r_stats_text_corpus, removePunctuation) R_stats_text_corpus <- tm_map(r_stats_text_corpus, content_transformer(tolower)) R_stats_text_corpus <- Corpus(VectorSource(r_stats_text)) R_stats_text <- sapply(r_stats, function(x) x$getText()) R_stats <- searchTwitter('#Rstats', n=1500, cainfo='cacert.pem') #the cainfo parameter is necessary only on Windows #to get your consumerKey and consumerSecret see the twitteR documentation for instructions Please enter your values in the code below.Дownload.file(url='', destfile='cacert.pem') In addition, I have included a screenshot below from my Twitter Apps Keys and Access Tokens page to indicate where to get the consumer_key, consumer_secret, access_token, and access_secret values.

#Codec pack for mac 2013 update#

IвЂ™ve updated the code due to changes in the recent update of the twitteR package. I did this on my Windows machine, which has this problem.

Updated 2015 February 18th to reflect changes in the twitteR packageДЄ short post on using the R twitteR package for text mining and using the R wordcloud package for visualisation.

Updated 2014 November 26th to reflect changes in the tm package.