pythonpandastableau-apitabpy

Word Clouds using TabPy

I want to create some code in TabPy that will count the frequency of words in a column and remove stop words for a word cloud in Tableau.

I'm able to do this easily enough in Python:

other1_count = other1.answer.str.split(expand=True).stack().value_counts()
other1_count = other1_count.to_frame().reset_index()
other1_count.columns = ['Word', 'Count']

### Remove stopwords
other1_count['Word'] = other1_count['Word'].apply(lambda x: ' '.join([word for word in x.split() if word not in (stop)]))
other1_count['Word'].replace('', np.nan, inplace=True)
other1_count.dropna(subset=['Word'], inplace=True)
other1_count = other1_count[~other1_count.Word.str.contains("nan")]

But less sure how to run this through TabPy. Anyone familiar with TabPy and how I can make this run?

Thanks in advance.

Solution

  • I worked on a project that accomplished something very similar a while back in R. Here's a video example showing the proof-of-concept (no audio). https://www.screencast.com/t/xa0yemiDPl

    It essentially shows the end state of using Tableau to interactively examine the description of wines in a word-cloud for the selected countries. The key components were:

    High-Level Overview overview

    Tableau Calculated Field - [R Words+Freq]:

    Script_Str('
print("STARTING NEW SCRIPT RUN")
print(Sys.time())
print(.arg2) # grouping
print(.arg1) # selected country


# TEST VARIABLE (non-prod)
.MaxSourceDataRecords = 1000 # -1 to disable

# TABLEAU PARAMETER VARIABLES 
.country = "' + [Country Parameter] + '"
.wordsToReturn = ' + str([Return Top N Words]) + '
#^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#

# VARIABLES DERIVED FROM TABLEAU PARAMETER VALUES
.countryUseAll = (.country == "All")
print(.countryUseAll)
#^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^#

#setwd("C:/Users/jbelliveau/....FILL IN HERE...")
.fileIn = ' + [Source Data Path] + '
#.fileOut = "winemag-with-DTM.csv"

#install.packages("wordcloud")
#install.packages("RColorBrewer") # not needed if installed wordcloud package

library(tm)
library(wordcloud)
library(RColorBrewer) # color package (maps or wordclouds)

wineAll = read.csv(.fileIn, stringsAsFactors=FALSE)

# TODO separately... polarity 

# use all the data or just the parameter selected
print(.countryUseAll)

if ( .countryUseAll ) {
  wine = wineAll # filter down to parameter passed from Tableau
}else{
  wine = wineAll[c(wineAll$country == .country),] # filter down to parameter passed from Tableau
}

# limited data for speed (NOT FOR PRODUCTION)
if( .MaxSourceDataRecords > 0 ){
  print("limiting the number of records to use from input data")
  wine = head(wine, .MaxSourceDataRecords)  
}


corpus = Corpus(VectorSource(wine$description))
corpus = tm_map(corpus, tolower)
#corpus = tm_map(corpus, PlainTextDocument) # https://stackoverflow.com/questions/32523544/how-to-remove-error-in-term-document-matrix-in-r/36161902
corpus = tm_map(corpus, removePunctuation)
corpus = tm_map(corpus, removeWords, stopwords("English"))
#length(corpus)

dtm = DocumentTermMatrix(corpus)

#?sample
mysample = dtm # no sampling (used Head on data read... for speed/simplicity on this example)
#mysample <- dtm[sample(1:nrow(dtm), 5000, replace=FALSE),]
#nrow(mysample)
wineSample = as.data.frame(as.matrix(mysample))

# column names (the words)
# use colnames to get a vector of the words
#colnames(wineSample)

# freq of words
# colSums to get the frequency of the words
#wineWordFreq = colSums(wineSample)

# structure in a way Tableau will like it
wordCloudData = data.frame(words=colnames(wineSample), freq=colSums(wineSample))
str(wordCloudData)

# sort by word freq
wordCloudDataSorted = wordCloudData[order(-wordCloudData$freq),]

# join together by ~ for processing once Tableau gets it
wordAndFreq = paste(wordCloudDataSorted[, 1], wordCloudDataSorted[, 2], sep = "~")

#write.table(wordCloudData, .fileOut, sep=",",row.names=FALSE) # if needed for performance refactors

topWords = head(wordAndFreq, .wordsToReturn)
#print(topWords)

return( topWords )

',
Max([Country Parameter])
, MAX([RowNum]) // for testing the grouping being sent to R
)

    Tableau Calculated Field for the Word Value:

    // grab the first token to the left of ~
Left([R Words+Freq], Find([R Words+Freq],"~") - 1)

    Tableau Calculated Field for the Frequency Value:

    INT(REPLACE([R Words+Freq],[Word]+"~",""))

    If you're not familiar with Tableau, you'll likely want to work alongside a Tableau analyst at your company that is. They'll be able to help you create the calculated fields and configure Tableau to connect to TabPy.