R/estrutura_list.dics3.R
In Fidelalencar/LCtestcontentR: Functionalities and objects for content production to the website.
##########################################
###### (1) Synonyms - dados para formar a lista de sinônimos ----
# é feito trabalhando 10 planilhas, sendo 2 delas parte da sessão "tratamento da informação
##########################################
# if(require(tm) == F) install.packages("tm"); require(tm)
# if(require(qdap) == F) install.packages("qdap"); require(qdap) # alista grande vem do qdap dictionaires
# if(require(tidyverse) == F) install.packages("tidyverse"); require(tidyverse)
# if(require(xlsx) == F) install.packages("xlsx"); require(xlsx)
# ## (1.1) carregando as sheets para formar a lista de sinônimos
# Syn1 <-
# read.csv2("C:/Users/Paren/Dropbox/Udacity/LearningCommunityConteudo/listas_palavras/ResourcesData/Synonym/Word Search Lists 1 - Synonyms1.csv",
# sep = ",",
# header = T)
# colnames(Syn1) <- Syn1[1,]
# Syn1 <- Syn1[-1,]
#
# Syn2 <-
# read.csv2("C:/Users/Paren/Dropbox/Udacity/LearningCommunityConteudo/listas_palavras/ResourcesData/Synonym/Word Search Lists 1 - Copy of Synonyms2.csv",
# sep = ",",
# header = T)
# colnames(Syn2) <- Syn2[1,]
# Syn2 <- Syn2[-1,]
#
# Syn3 <-
# read.csv2("C:/Users/Paren/Dropbox/Udacity/LearningCommunityConteudo/listas_palavras/ResourcesData/Synonym/Word Search Lists 1 - Synonyms3.csv",
# sep = ",",
# header = T)
# colnames(Syn3) <- c("Word", "Synonym")
# Syn3 <- Syn3[-1,]
#
# Syn4 <-
# read.csv2("C:/Users/Paren/Dropbox/Udacity/LearningCommunityConteudo/listas_palavras/ResourcesData/Synonym/Word Search Lists 1 - Copy of Synonyms4.csv",
# sep = ",",
# header = T)
# Syn4 <- Syn4[c(4,5)]
# colnames(Syn4) <- c("Word", "Synonym")
# Syn4 <- Syn4[-c(1,2),]
#
# Syn5 <-
# read.csv2("C:/Users/Paren/Dropbox/Udacity/LearningCommunityConteudo/listas_palavras/ResourcesData/Synonym/Word Search Lists 2 - Copy of Synonyms5.csv",
# sep = ",",
# header = T)
# Syn5 <- Syn5[c(1,3)]
# colnames(Syn5) <- c("Word", "Synonym")
# Syn5 <- Syn5[-c(1,2),]
#
# Syn6 <-
# read.csv2("C:/Users/Paren/Dropbox/Udacity/LearningCommunityConteudo/listas_palavras/ResourcesData/Synonym/Word Search Lists 2 - Synonyms6.csv",
# sep = ",",
# header = T)
# colnames(Syn6) <- c("Word", "Synonym")
# Syn6 <- Syn6[-1,]
#
# Syn7 <- # vem do arquivo Word Search Lists 1 - Copy of Syns+Antonys.csv
# read.csv2("C:/Users/Paren/Dropbox/Udacity/LearningCommunityConteudo/listas_palavras/ResourcesData/Synonym/Word Search Lists 1 - Copy of Syns+Antonys.csv",
# sep = ",",
# header = T)
# Syn7 <- Syn7[c(2,3)]
# colnames(Syn7) <- c("Word", "Synonym")
# Syn7 <- Syn7[-1,]
#
#
#
# Syn8 <- # vem do arquivo Word Search Lists 2 - Copy of Synonyms Categories
# read.csv2("C:/Users/Paren/Dropbox/Udacity/LearningCommunityConteudo/listas_palavras/ResourcesData/Synonym/Word Search Lists 2 - Copy of Synonyms Categories.csv",
# sep = ",",
# header = T)
# colnames(Syn8) <- c("Word", "Synonym")
# Syn8 <- Syn8[-1,]
#
#
# # sheet ??? # vem das listas de tratamento da informacao
# trat_infoS1 <-
# read.csv2("C:/Users/Paren/Dropbox/Udacity/LearningCommunityConteudo/listas_palavras/ResourcesData/TratamentoInformacao/Tratamento Informação - Sheet1.csv",
# sep = ",",
# header = T)
######## primeiro usamos essas base, mas depois retiramos pq tinha muito ruido
#### trat_infoS1 <- trat_infoS1[c(1,2)]
#### colnames(trat_infoS1) <- c("Word", "Synonym")
#### trat_infoS1$Synonym <- str_to_lower(trat_infoS1$Synonym)
#### trat_infoS1 <- trat_infoS1 %>% filter(Synonym != "")
####
#### #Sheet ???? ####vem das listas de tratamento da informacao
#### trat_infoS5 <-
#### read.csv2("C:/Users/Paren/Dropbox/Udacity/LearningCommunityConteudo/listas_palavras/ResourcesData/TratamentoInformacao/Tratamento Informação - Sheet5.csv",
#### sep = ",",
#### header = T)
#### trat_infoS5 <- trat_infoS5[c(1,3)]
#### colnames(trat_infoS5) <- c("Word", "Synonym")
#### trat_infoS5$Synonym <- str_to_lower(trat_infoS5$Synonym)
#### trat_infoS5 <- trat_infoS5 %>% filter(Synonym != "")
# #
# Syn <- rbind(Syn1, Syn2, Syn3, Syn4, Syn5, Syn6, Syn7, Syn8)
# ## rm("Syn1", "Syn2", "Syn3", "Syn4", "Syn5", "Syn6", "Syn7", "Syn8", "trat_infoS1", "trat_infoS5")
#
# Syn$Word <- str_to_lower(Syn$Word)
# Syn$Synonym <- str_to_lower(Syn$Synonym)
# Syn <- unique(Syn)
# Syn <- Syn[order(Syn$Word),]
# Syn <- Syn[-1,]
# rownames(Syn) <- NULL
### (1.2) limpando
# Syn$Word <- sub("to ", "", Syn$Word)
# Syn$Synonym <- sub("to ", "", Syn$Synonym)
# Syn$Word <- sub("a ", "", Syn$Word)
# Syn$Word <- sub("few determiner,", "few", Syn$Word)
# Syn <- Syn[-c(grep("wearisome. irksome", Syn$Synonym)),]
# Syn <- rbind(Syn, data.frame(Word=c("tedious", "tedious"), Synonym=c("wearisome", "irksome")))
# Syn <- Syn[-c(grep("valid, lega", Syn$Synonym)),]
# Syn <- rbind(Syn, data.frame(Word=c("legitimate", "legitimate"), Synonym=c("valid", "legal")))
# Syn$Word <- sub("zig -zag", "zig-zag", Syn$Word)
# Syn$Word <- sub("busy ", "busy", Syn$Word)
# Syn$Word <- sub("construction ", "construction", Syn$Word)
# def <- Syn[grep(".* .* .* .*", Syn$Synonym),] # <----------------- Incluir na lista de definições !!!!!!!
# Syn <- Syn[-c(grep(".* .* .* .*", Syn$Synonym)),]
#
# ########### erros que não existem mais pela remoção das ultimas bases
# ###### Syn <- Syn[-c(grep("in questions", Syn$Synonym)),]
# ###### Syn$Synonym[grep(", determiner ", Syn$Synonym)[[1]]] <- "remaining"
# ###### Syn$Synonym[grep(", determiner", Syn$Synonym)[[1]]] <- "twelve"
# ###### coloc <- Syn[(grep("etc\\.", Syn$Synonym)),] # <----------------- Incluir na lista de colocations !!!!!
# ###### Syn <- Syn[-c(grep("etc\\.", Syn$Synonym)),]
#
# Syn$Synonym <- sub(",", "", Syn$Synonym)
# Syn <- unique(Syn)
# Syn <- Syn[-c(grep("premiss", Syn$Synonym)),]
# Syn <- Syn[Syn$Word != Syn$Synonym,]
#
# Syn <- Syn[-c(grep("say/tell", Syn$Word)),]
# x <- data.frame(Word=c(rep("say", 4), rep("tell", 4)), Synonym=rep(c("recount", "narrate", "explain", "reveal"), 2))
# Syn <- rbind(Syn, x)
###############limpando stopwords - Nao limpamos stopwords apos retirada das bases
#####stop <- tm::stopwords(kind = "en")
#####N <- c()
#####M <- c()
#####for(i in 1:length(stop)) {
##### n <- grep(paste0("^", stop[i], "$") , Syn$Word)
##### N <- c(N,n)
##### m <- grep(paste0("^", stop[i], "$") , Syn$Synonym)
##### M <- c(M,m)
#####}
#####x <- unique(c(N,M))
#####SSS <- Syn[x,] #####<-------------------- Sinonimos de stop words
#
#####Syn <- Syn[-x,]
#####rm("N", "n", "M", "m", "stop", "i", "x", "SSS")
#
#
##########o que fazer com as linas q tem / na 2a coluna ??? algumas sao por causa de preposição
#####syn.with.bar <- Syn[grep("/", Syn$Synonym),] #####<------------ enviado para limpeza manual
#########################write.csv2(syn.with.bar, file= "syn.with.bar.csv")
#
#####Syn <- Syn[-grep("/", Syn$Synonym),]
# ##### (1.3) Colocando o Level na lista de sinônimos
#
# setwd("C:/Users/Paren/Dropbox/Learning_Community/LCtestcontentR/data")
# load(file="trat.Info.1.0.RData")
#
# trat.Info.1.0 <- trat.Info.1.0[order(trat.Info.1.0$Level),]
#
# trat_ref <- data.frame(ref=trat.Info.1.0$Base.Word)
# trat_ref <- unique(trat_ref)
# trat_ref <- data.frame(index=rownames(trat_ref), ref=trat_ref$ref)
# trat_ref$index <- as.numeric(trat_ref$index)
#
# trat_level <- data.frame(Level=trat.Info.1.0$Level, index=1:length(trat.Info.1.0$Level))
# trat_level$index <- as.numeric(trat_level$index)
# trat_limpo <- left_join(trat_ref, trat_level, by="index")
#
# rm("trat_level", "trat_ref", "def", "coloc")
#
# Syn.Words <- data.frame(indexS=1:length(Syn$Word), ref=Syn$Word, syn_base=Syn$Word)
# SynW_L <- left_join(Syn.Words, trat_limpo, by="ref")
# SynW_L <- SynW_L[c(1,3,5)]
# # # SynW_L <- na.omit(SynW_L)
# SynW_L$indexS <- as.numeric(SynW_L$indexS)
#
#
# Syn.Synonyms <- data.frame(indexS=1:length(Syn$Synonym), ref=Syn$Synonym, syn_syn=Syn$Synonym)
# SynS_L <- left_join(Syn.Synonyms, trat_limpo, by="ref")
# SynS_L <- SynS_L[c(1,3,5)]
# # # SynS_L <- na.omit(SynS_L)
# SynS_L$indexS <- as.numeric(SynS_L$indexS)
#
#
# Syn_leveled <- full_join(SynW_L, SynS_L, by="indexS")
# Syn_leveled <- Syn_leveled[c(2,3,4,5)]
#
# Syn_leveled <- Syn_leveled %>%
# mutate(Level.x = case_when(Level.x == "A1" ~ 1,
# Level.x == "A2" ~ 2,
# Level.x == "B1" ~ 3,
# Level.x == "B2" ~ 4,
# Level.x == "C1" ~ 5,
# Level.x == "C2" ~ 6),
# Level.y = case_when(Level.y == "A1" ~ 1,
# Level.y == "A2" ~ 2,
# Level.y == "B1" ~ 3,
# Level.y == "B2" ~ 4,
# Level.y == "C1" ~ 5,
# Level.y == "C2" ~ 6))
#
#
#
# N <- c()
# for(i in 1:length(Syn_leveled$syn_base)){
# if(grepl(" ", Syn_leveled$syn_base[i]) == T & grepl(" ", Syn_leveled$syn_syn[i]) == T){
# N <- c(N, i)
# }
# }
#
# a <- Syn_leveled[N,] # <------------- RESGATAR: synonymos bigramas dos dois lados
#
# Syn_leveled <- Syn_leveled[-N,]
#
# for(i in 1:length(Syn_leveled$syn_base)){
# if(grepl(" ", Syn_leveled$syn_base[i]) == F & is.na(Syn_leveled$Level.x[i])){
# Syn_leveled$Level.x[i] <- 7
# }
# }
# for(i in 1:length(Syn_leveled$syn_syn)){
# if(grepl(" ", Syn_leveled$syn_syn[i]) == F & is.na(Syn_leveled$Level.y[i])){
# Syn_leveled$Level.y[i] <- 7
# }
# }
#
#
# Syn_leveled[is.na(Syn_leveled)] <- .5 # atribuindo o .5 às expressões com espaços
#
#
# # organizando para que na primeira coluna estejam as palavras mais dificeis do par
# maior <- Syn_leveled[Syn_leveled$Level.x > Syn_leveled$Level.y,]
# menor <- Syn_leveled[Syn_leveled$Level.x < Syn_leveled$Level.y,]
# igual <- Syn_leveled[Syn_leveled$Level.x == Syn_leveled$Level.y,]
# menor <- menor[c(3,4,1,2)]
# colnames(menor) <- colnames(maior)
# igual1 <- igual[c(3,4,1,2)]
# colnames(igual1) <- colnames(maior)
#
# Syn_organized <- rbind(maior, menor, igual, igual1)
# colnames(Syn_organized) <- c("B.word_dif", "lvl.base", "Syn_easy", "lvl.syn")
# #
# #
# # rm("igual", "igual1", "maior", "menor", "Syn.Synonyms", "Syn.Words", "SynW_L", "SynS_L", "r", "Syn_leveled_NoNA", "a", "x")
#
# Syn_organized <- unique(Syn_organized)
# setwd("C:/Users/Paren/Dropbox/Learning_Community/LCtestcontentR/data")
# # # # save(Syn_organized, file= "Syn.1.0.Rdata")
############# CONCLUIMOS
### adicional:
# # o pacote qdap tem um retornador de sinonimos
# qdap::synonyms("strange")
# synonym.frame = qdapDictionaries::key.syn # https://cran.r-project.org/web/packages/qdapDictionaries/qdapDictionaries.pdf
#
##################################
### Para testar e executar o exercicio de sinonimos, ir para o script Syn&Ant
############## ----
########## EXPANDIDO O lemmasDF.2.0 -> Criando lemmasDF.2.1
#
# O lemmatizador lemmasDF.2.1 é a expansão do lemmasDF.2.0
# em que se adiciona todas as variações das palavras da lista
# dos sinonimos que não estavam na lista com niveis ("trat.Info.1.0").
#
# x <- Syn_organized[Syn_organized$lvl.base =="7",]
# y <- x$B.word_dif
#
# i=1
# N <- c()
# for(i in 1:length(y)) {
# print(i)
# n <- grep(paste0("^", y[i], "$"), lemmat300m$words)
# N <- c(N, n)
# }
#
# N1 <- unique(N)
#
# view(lemmat300m[N1,])
#
# expansao_syn <- lemmat300m[N1,]
# expansao_syn_lista <- expansao_syn$lemma
#
# i=1
# M <- c()
# for(i in 1:length(expansao_syn_lista)) {
# print(i)
# n <- grep(paste0("^", expansao_syn_lista[[i]], "$"), lemmat300m$lemma)
# M <- c(M, n)
# }
# M1 <- unique(M)
#
# view(lemmat300m[M1,])
#
#
# complemento <- lemmat300m[M1,]
# complemento <- complemento[c(3,1,2)]
# original <- lemmasDF.2.0
# colnames(complemento) <- colnames(original)
# lemmasDF.2.1 <- rbind(original, complemento)
# lemmasDF.2.1 <- unique(lemmasDF.2.1)
# setwd("C:/Users/Paren/Dropbox/Learning_Community/LCtestcontentR/data")
# # # # save(lemmasDF.2.1, file= "lemmasDF.2.1.Rdata")
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##########################################
###### (1) Synonyms - dados para formar a lista de sinônimos ----
# é feito trabalhando 10 planilhas, sendo 2 delas parte da sessão "tratamento da informação
##########################################
# if(require(tm) == F) install.packages("tm"); require(tm)
# if(require(qdap) == F) install.packages("qdap"); require(qdap) # alista grande vem do qdap dictionaires
# if(require(tidyverse) == F) install.packages("tidyverse"); require(tidyverse)
# if(require(xlsx) == F) install.packages("xlsx"); require(xlsx)
# ## (1.1) carregando as sheets para formar a lista de sinônimos
# Syn1 <-
# read.csv2("C:/Users/Paren/Dropbox/Udacity/LearningCommunityConteudo/listas_palavras/ResourcesData/Synonym/Word Search Lists 1 - Synonyms1.csv",
# sep = ",",
# header = T)
# colnames(Syn1) <- Syn1[1,]
# Syn1 <- Syn1[-1,]
#
# Syn2 <-
# read.csv2("C:/Users/Paren/Dropbox/Udacity/LearningCommunityConteudo/listas_palavras/ResourcesData/Synonym/Word Search Lists 1 - Copy of Synonyms2.csv",
# sep = ",",
# header = T)
# colnames(Syn2) <- Syn2[1,]
# Syn2 <- Syn2[-1,]
#
# Syn3 <-
# read.csv2("C:/Users/Paren/Dropbox/Udacity/LearningCommunityConteudo/listas_palavras/ResourcesData/Synonym/Word Search Lists 1 - Synonyms3.csv",
# sep = ",",
# header = T)
# colnames(Syn3) <- c("Word", "Synonym")
# Syn3 <- Syn3[-1,]
#
# Syn4 <-
# read.csv2("C:/Users/Paren/Dropbox/Udacity/LearningCommunityConteudo/listas_palavras/ResourcesData/Synonym/Word Search Lists 1 - Copy of Synonyms4.csv",
# sep = ",",
# header = T)
# Syn4 <- Syn4[c(4,5)]
# colnames(Syn4) <- c("Word", "Synonym")
# Syn4 <- Syn4[-c(1,2),]
#
# Syn5 <-
# read.csv2("C:/Users/Paren/Dropbox/Udacity/LearningCommunityConteudo/listas_palavras/ResourcesData/Synonym/Word Search Lists 2 - Copy of Synonyms5.csv",
# sep = ",",
# header = T)
# Syn5 <- Syn5[c(1,3)]
# colnames(Syn5) <- c("Word", "Synonym")
# Syn5 <- Syn5[-c(1,2),]
#
# Syn6 <-
# read.csv2("C:/Users/Paren/Dropbox/Udacity/LearningCommunityConteudo/listas_palavras/ResourcesData/Synonym/Word Search Lists 2 - Synonyms6.csv",
# sep = ",",
# header = T)
# colnames(Syn6) <- c("Word", "Synonym")
# Syn6 <- Syn6[-1,]
#
# Syn7 <- # vem do arquivo Word Search Lists 1 - Copy of Syns+Antonys.csv
# read.csv2("C:/Users/Paren/Dropbox/Udacity/LearningCommunityConteudo/listas_palavras/ResourcesData/Synonym/Word Search Lists 1 - Copy of Syns+Antonys.csv",
# sep = ",",
# header = T)
# Syn7 <- Syn7[c(2,3)]
# colnames(Syn7) <- c("Word", "Synonym")
# Syn7 <- Syn7[-1,]
#
#
#
# Syn8 <- # vem do arquivo Word Search Lists 2 - Copy of Synonyms Categories
# read.csv2("C:/Users/Paren/Dropbox/Udacity/LearningCommunityConteudo/listas_palavras/ResourcesData/Synonym/Word Search Lists 2 - Copy of Synonyms Categories.csv",
# sep = ",",
# header = T)
# colnames(Syn8) <- c("Word", "Synonym")
# Syn8 <- Syn8[-1,]
#
#
# # sheet ??? # vem das listas de tratamento da informacao
# trat_infoS1 <-
# read.csv2("C:/Users/Paren/Dropbox/Udacity/LearningCommunityConteudo/listas_palavras/ResourcesData/TratamentoInformacao/Tratamento Informação - Sheet1.csv",
# sep = ",",
# header = T)
######## primeiro usamos essas base, mas depois retiramos pq tinha muito ruido
#### trat_infoS1 <- trat_infoS1[c(1,2)]
#### colnames(trat_infoS1) <- c("Word", "Synonym")
#### trat_infoS1$Synonym <- str_to_lower(trat_infoS1$Synonym)
#### trat_infoS1 <- trat_infoS1 %>% filter(Synonym != "")
####
#### #Sheet ???? ####vem das listas de tratamento da informacao
#### trat_infoS5 <-
#### read.csv2("C:/Users/Paren/Dropbox/Udacity/LearningCommunityConteudo/listas_palavras/ResourcesData/TratamentoInformacao/Tratamento Informação - Sheet5.csv",
#### sep = ",",
#### header = T)
#### trat_infoS5 <- trat_infoS5[c(1,3)]
#### colnames(trat_infoS5) <- c("Word", "Synonym")
#### trat_infoS5$Synonym <- str_to_lower(trat_infoS5$Synonym)
#### trat_infoS5 <- trat_infoS5 %>% filter(Synonym != "")
# #
# Syn <- rbind(Syn1, Syn2, Syn3, Syn4, Syn5, Syn6, Syn7, Syn8)
# ## rm("Syn1", "Syn2", "Syn3", "Syn4", "Syn5", "Syn6", "Syn7", "Syn8", "trat_infoS1", "trat_infoS5")
#
# Syn$Word <- str_to_lower(Syn$Word)
# Syn$Synonym <- str_to_lower(Syn$Synonym)
# Syn <- unique(Syn)
# Syn <- Syn[order(Syn$Word),]
# Syn <- Syn[-1,]
# rownames(Syn) <- NULL
### (1.2) limpando
# Syn$Word <- sub("to ", "", Syn$Word)
# Syn$Synonym <- sub("to ", "", Syn$Synonym)
# Syn$Word <- sub("a ", "", Syn$Word)
# Syn$Word <- sub("few determiner,", "few", Syn$Word)
# Syn <- Syn[-c(grep("wearisome. irksome", Syn$Synonym)),]
# Syn <- rbind(Syn, data.frame(Word=c("tedious", "tedious"), Synonym=c("wearisome", "irksome")))
# Syn <- Syn[-c(grep("valid, lega", Syn$Synonym)),]
# Syn <- rbind(Syn, data.frame(Word=c("legitimate", "legitimate"), Synonym=c("valid", "legal")))
# Syn$Word <- sub("zig -zag", "zig-zag", Syn$Word)
# Syn$Word <- sub("busy ", "busy", Syn$Word)
# Syn$Word <- sub("construction ", "construction", Syn$Word)
# def <- Syn[grep(".* .* .* .*", Syn$Synonym),] # <----------------- Incluir na lista de definições !!!!!!!
# Syn <- Syn[-c(grep(".* .* .* .*", Syn$Synonym)),]
#
# ########### erros que não existem mais pela remoção das ultimas bases
# ###### Syn <- Syn[-c(grep("in questions", Syn$Synonym)),]
# ###### Syn$Synonym[grep(", determiner ", Syn$Synonym)[[1]]] <- "remaining"
# ###### Syn$Synonym[grep(", determiner", Syn$Synonym)[[1]]] <- "twelve"
# ###### coloc <- Syn[(grep("etc\\.", Syn$Synonym)),] # <----------------- Incluir na lista de colocations !!!!!
# ###### Syn <- Syn[-c(grep("etc\\.", Syn$Synonym)),]
#
# Syn$Synonym <- sub(",", "", Syn$Synonym)
# Syn <- unique(Syn)
# Syn <- Syn[-c(grep("premiss", Syn$Synonym)),]
# Syn <- Syn[Syn$Word != Syn$Synonym,]
#
# Syn <- Syn[-c(grep("say/tell", Syn$Word)),]
# x <- data.frame(Word=c(rep("say", 4), rep("tell", 4)), Synonym=rep(c("recount", "narrate", "explain", "reveal"), 2))
# Syn <- rbind(Syn, x)
###############limpando stopwords - Nao limpamos stopwords apos retirada das bases
#####stop <- tm::stopwords(kind = "en")
#####N <- c()
#####M <- c()
#####for(i in 1:length(stop)) {
##### n <- grep(paste0("^", stop[i], "$") , Syn$Word)
##### N <- c(N,n)
##### m <- grep(paste0("^", stop[i], "$") , Syn$Synonym)
##### M <- c(M,m)
#####}
#####x <- unique(c(N,M))
#####SSS <- Syn[x,] #####<-------------------- Sinonimos de stop words
#
#####Syn <- Syn[-x,]
#####rm("N", "n", "M", "m", "stop", "i", "x", "SSS")
#
#
##########o que fazer com as linas q tem / na 2a coluna ??? algumas sao por causa de preposição
#####syn.with.bar <- Syn[grep("/", Syn$Synonym),] #####<------------ enviado para limpeza manual
#########################write.csv2(syn.with.bar, file= "syn.with.bar.csv")
#
#####Syn <- Syn[-grep("/", Syn$Synonym),]
# ##### (1.3) Colocando o Level na lista de sinônimos
#
# setwd("C:/Users/Paren/Dropbox/Learning_Community/LCtestcontentR/data")
# load(file="trat.Info.1.0.RData")
#
# trat.Info.1.0 <- trat.Info.1.0[order(trat.Info.1.0$Level),]
#
# trat_ref <- data.frame(ref=trat.Info.1.0$Base.Word)
# trat_ref <- unique(trat_ref)
# trat_ref <- data.frame(index=rownames(trat_ref), ref=trat_ref$ref)
# trat_ref$index <- as.numeric(trat_ref$index)
#
# trat_level <- data.frame(Level=trat.Info.1.0$Level, index=1:length(trat.Info.1.0$Level))
# trat_level$index <- as.numeric(trat_level$index)
# trat_limpo <- left_join(trat_ref, trat_level, by="index")
#
# rm("trat_level", "trat_ref", "def", "coloc")
#
# Syn.Words <- data.frame(indexS=1:length(Syn$Word), ref=Syn$Word, syn_base=Syn$Word)
# SynW_L <- left_join(Syn.Words, trat_limpo, by="ref")
# SynW_L <- SynW_L[c(1,3,5)]
# # # SynW_L <- na.omit(SynW_L)
# SynW_L$indexS <- as.numeric(SynW_L$indexS)
#
#
# Syn.Synonyms <- data.frame(indexS=1:length(Syn$Synonym), ref=Syn$Synonym, syn_syn=Syn$Synonym)
# SynS_L <- left_join(Syn.Synonyms, trat_limpo, by="ref")
# SynS_L <- SynS_L[c(1,3,5)]
# # # SynS_L <- na.omit(SynS_L)
# SynS_L$indexS <- as.numeric(SynS_L$indexS)
#
#
# Syn_leveled <- full_join(SynW_L, SynS_L, by="indexS")
# Syn_leveled <- Syn_leveled[c(2,3,4,5)]
#
# Syn_leveled <- Syn_leveled %>%
# mutate(Level.x = case_when(Level.x == "A1" ~ 1,
# Level.x == "A2" ~ 2,
# Level.x == "B1" ~ 3,
# Level.x == "B2" ~ 4,
# Level.x == "C1" ~ 5,
# Level.x == "C2" ~ 6),
# Level.y = case_when(Level.y == "A1" ~ 1,
# Level.y == "A2" ~ 2,
# Level.y == "B1" ~ 3,
# Level.y == "B2" ~ 4,
# Level.y == "C1" ~ 5,
# Level.y == "C2" ~ 6))
#
#
#
# N <- c()
# for(i in 1:length(Syn_leveled$syn_base)){
# if(grepl(" ", Syn_leveled$syn_base[i]) == T & grepl(" ", Syn_leveled$syn_syn[i]) == T){
# N <- c(N, i)
# }
# }
#
# a <- Syn_leveled[N,] # <------------- RESGATAR: synonymos bigramas dos dois lados
#
# Syn_leveled <- Syn_leveled[-N,]
#
# for(i in 1:length(Syn_leveled$syn_base)){
# if(grepl(" ", Syn_leveled$syn_base[i]) == F & is.na(Syn_leveled$Level.x[i])){
# Syn_leveled$Level.x[i] <- 7
# }
# }
# for(i in 1:length(Syn_leveled$syn_syn)){
# if(grepl(" ", Syn_leveled$syn_syn[i]) == F & is.na(Syn_leveled$Level.y[i])){
# Syn_leveled$Level.y[i] <- 7
# }
# }
#
#
# Syn_leveled[is.na(Syn_leveled)] <- .5 # atribuindo o .5 às expressões com espaços
#
#
# # organizando para que na primeira coluna estejam as palavras mais dificeis do par
# maior <- Syn_leveled[Syn_leveled$Level.x > Syn_leveled$Level.y,]
# menor <- Syn_leveled[Syn_leveled$Level.x < Syn_leveled$Level.y,]
# igual <- Syn_leveled[Syn_leveled$Level.x == Syn_leveled$Level.y,]
# menor <- menor[c(3,4,1,2)]
# colnames(menor) <- colnames(maior)
# igual1 <- igual[c(3,4,1,2)]
# colnames(igual1) <- colnames(maior)
#
# Syn_organized <- rbind(maior, menor, igual, igual1)
# colnames(Syn_organized) <- c("B.word_dif", "lvl.base", "Syn_easy", "lvl.syn")
# #
# #
# # rm("igual", "igual1", "maior", "menor", "Syn.Synonyms", "Syn.Words", "SynW_L", "SynS_L", "r", "Syn_leveled_NoNA", "a", "x")
#
# Syn_organized <- unique(Syn_organized)
# setwd("C:/Users/Paren/Dropbox/Learning_Community/LCtestcontentR/data")
# # # # save(Syn_organized, file= "Syn.1.0.Rdata")
############# CONCLUIMOS
### adicional:
# # o pacote qdap tem um retornador de sinonimos
# qdap::synonyms("strange")
# synonym.frame = qdapDictionaries::key.syn # https://cran.r-project.org/web/packages/qdapDictionaries/qdapDictionaries.pdf
#
##################################
### Para testar e executar o exercicio de sinonimos, ir para o script Syn&Ant
############## ----
########## EXPANDIDO O lemmasDF.2.0 -> Criando lemmasDF.2.1
#
# O lemmatizador lemmasDF.2.1 é a expansão do lemmasDF.2.0
# em que se adiciona todas as variações das palavras da lista
# dos sinonimos que não estavam na lista com niveis ("trat.Info.1.0").
#
# x <- Syn_organized[Syn_organized$lvl.base =="7",]
# y <- x$B.word_dif
#
# i=1
# N <- c()
# for(i in 1:length(y)) {
# print(i)
# n <- grep(paste0("^", y[i], "$"), lemmat300m$words)
# N <- c(N, n)
# }
#
# N1 <- unique(N)
#
# view(lemmat300m[N1,])
#
# expansao_syn <- lemmat300m[N1,]
# expansao_syn_lista <- expansao_syn$lemma
#
# i=1
# M <- c()
# for(i in 1:length(expansao_syn_lista)) {
# print(i)
# n <- grep(paste0("^", expansao_syn_lista[[i]], "$"), lemmat300m$lemma)
# M <- c(M, n)
# }
# M1 <- unique(M)
#
# view(lemmat300m[M1,])
#
#
# complemento <- lemmat300m[M1,]
# complemento <- complemento[c(3,1,2)]
# original <- lemmasDF.2.0
# colnames(complemento) <- colnames(original)
# lemmasDF.2.1 <- rbind(original, complemento)
# lemmasDF.2.1 <- unique(lemmasDF.2.1)
# setwd("C:/Users/Paren/Dropbox/Learning_Community/LCtestcontentR/data")
# # # # save(lemmasDF.2.1, file= "lemmasDF.2.1.Rdata")
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