wordCloudIt: Generate a word cloud with a given subset of patent data...

In kamilien1/patentR: A Toolbox for Analyzing Patent Data

Description

Create a word cloud from a patent data set.

Usage

wordCloudIt(file, rmwords, minfreq = 20, maxwords = 150, ...)

Arguments

file	The data frame you want word cloud, typically the abstract, title, and claims subset.
rmwords	A character vector of words you exclude from your analysis. Default is excludeWords.
minfreq	From wordcloud, the min frequency to include a word. Default is 10.
maxwords	From wordcloud, the max number of words to show. Default is 150.
...	wordcloud options

Value

NULL, prints out a wordcloud

Examples

sumo <- cleanPatentData(patentData = patentr::acars, columnsExpected = sumobrainColumns,
cleanNames = sumobrainNames,
dateFields = sumobrainDateFields,
dateOrders = sumobrainDateOrder,
deduplicate = TRUE,
cakcDict = patentr::cakcDict,
docLengthTypesDict = patentr::docLengthTypesDict,
keepType = "grant",
firstAssigneeOnly = TRUE,
assigneeSep = ";",
stopWords = patentr::assigneeStopWords)

# df <- dplyr::select(sumo, title, abstract)
df <- sumo[,c("title","abstract")]
wordCloudIt(df, excludeWords, minfreq = 20, 
random.order = FALSE, rot.per = 0.25)

kamilien1/patentR documentation built on May 20, 2019, 7:19 a.m.