diff --git a/DESCRIPTION b/DESCRIPTION index ad9106d..b002ddb 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -9,7 +9,7 @@ License: `use_mit_license()`, `use_gpl3_license()` or friends to pick a license Encoding: UTF-8 Roxygen: list(markdown = TRUE) -RoxygenNote: 7.2.1 +RoxygenNote: 7.2.3 Imports: mvbutils, tools diff --git a/TextAnalysis/top10_analysis.R b/TextAnalysis/top10_analysis.R index 99c1b5f..26aa218 100644 --- a/TextAnalysis/top10_analysis.R +++ b/TextAnalysis/top10_analysis.R @@ -3,20 +3,20 @@ library(here) library(pdftools) library(tm) library(stringr) -library(xlsx) -library(ggplot2) -library(patchwork) #devtools::install_github("thomasp85/patchwork") library(wordcloud) library(RColorBrewer) +library(ggplot2) +library(scales) +library(viridis) # Define keyword --------------------------------------------------------------- -z <- data.frame( - keyword = c( - "instantaneous mortality rate|z" - ), - group = "instantaneous mortality rate" -) +# z <- data.frame( +# keyword = c( +# "instantaneous total mortality rate|z" +# ), +# group = "instantaneous mortality rate" +# ) spawning_biomass <- data.frame( keyword = c( @@ -33,10 +33,8 @@ cpue <- data.frame( "catch per unit effort|cpue", "catch rate", "index of abundance", - "standardized fishery catch time series", "catch per effort", - "fishing success", - "availability" + "fishing success" ), group = "catch per unit effort" ) @@ -44,7 +42,8 @@ cpue <- data.frame( catch <- data.frame( keyword = c( "catch", - "total mortality" + "total mortality", + "harvest" ), group = "catch" ) @@ -52,8 +51,7 @@ catch <- data.frame( landings <- data.frame( keyword = c( "landings", - "retained catch", - "wanted catch" + "retained catch" ), group = "landings" ) @@ -75,13 +73,13 @@ sex <- data.frame( group = "sex" ) -spr <- data.frame( - keyword = c( - "spawner per recruit|spr", - "30%spr|spr30%|30spr|spr30" - ), - group = "spawner per recruit" -) +# spr <- data.frame( +# keyword = c( +# "spawner per recruit|spr", +# "spawning potential ratio" +# ), +# group = "spawner per recruit" +# ) weight <- data.frame( keyword = c( @@ -102,8 +100,8 @@ lnr0 <- data.frame( group = "natural log of unfished recruitment" ) -keyword_map <- rbind(z, spawning_biomass, cpue, catch, landings, - projection, sex, spr, weight, lnr0) +keyword_map <- rbind(catch, cpue, landings, + lnr0, projection, sex, spawning_biomass, weight) keyword_map$keyword_id <- as.factor(1:nrow(keyword_map)) keyword <- keyword_map$keyword @@ -114,7 +112,7 @@ subfolder_path <- list.dirs(path = working_path, full.names = TRUE, recursive = subfolder_name <- list.dirs(path = working_path, full.names = FALSE, recursive = FALSE) # Create keyword database -col_name <- c("ID", "Science_Center", "File_Path", keyword) +col_name <- c("ID", "Source", "File_Path", keyword) frequency_database <- presence_database <- proportion_database <- data.frame(matrix(NA, ncol = length(col_name))) colnames(frequency_database) <- colnames(presence_database) <- colnames(proportion_database) <- @@ -216,47 +214,60 @@ proportion_database <- rbind( ) proportion_database[nrow(proportion_database), "ID"] <- "Sum" -xlsx_path <- here::here("TextAnalysis", "top10_analysis.xlsx") -xlsx::write.xlsx(frequency_database, file=xlsx_path, sheetName="frequency", row.names=FALSE) -xlsx::write.xlsx(presence_database, file=xlsx_path, sheetName="presence", append=TRUE, row.names=FALSE) -xlsx::write.xlsx(proportion_database, file=xlsx_path, sheetName="proportion", append=TRUE, row.names=FALSE) +write.csv(frequency_database, file=here::here("TextAnalysis", "top10_frequency.csv"), row.names=FALSE) +write.csv(presence_database, file=here::here("TextAnalysis", "top10_presence.csv"), row.names=FALSE) +write.csv(proportion_database, file=here::here("TextAnalysis", "top10_proportion.csv"), row.names=FALSE) # Upload xlsx to Google Drive -# Google Drive folder id -id_googledrive <- "1BUsYYd11lE2TECqHru5tX6LwkMniVnKv" -googledrive::drive_upload(media = xlsx_path, path = as_id(id_googledrive), overwrite = TRUE, type="spreadsheet") +authorize_GoogleDrive <- FALSE +if (authorize_GoogleDrive) { + # Google Drive folder id + id_googledrive <- "1BUsYYd11lE2TECqHru5tX6LwkMniVnKv" + googledrive::drive_upload(media = xlsx_path, path = as_id(id_googledrive), overwrite = TRUE, type="spreadsheet") +} # Plot results ------------------------------------------------------------ -xlsx_path <- here::here("TextAnalysis", "top10_analysis.xlsx") -frequency_database <- xlsx::read.xlsx(file=xlsx_path, sheetName="frequency") -presence_database<-xlsx::read.xlsx(file=xlsx_path, sheetName="presence") -proportion_database<-xlsx::read.xlsx(file=xlsx_path, sheetName="proportion") +frequency_database <- read.csv(file=here::here("TextAnalysis", "top10_frequency.csv")) +presence_database<-read.csv(file=here::here("TextAnalysis", "top10_presence.csv")) +proportion_database<-read.csv(file=here::here("TextAnalysis", "top10_proportion.csv")) colnames(presence_database) <- col_name data_reshape <- reshape2::melt( presence_database[, c(2, 4:ncol(presence_database))], - id = c("Science_Center") + id = c("Source") ) -colnames(data_reshape) <- c("Science_Center", "keyword", "value") +colnames(data_reshape) <- c("Source", "keyword", "value") data_merge <- merge(data_reshape, keyword_map, by= "keyword") -sum_by_group <- aggregate(value ~ keyword+keyword_id+group+Science_Center, data = data_merge, sum) +sum_by_group <- aggregate(value ~ keyword+keyword_id+group+Source, data = data_merge, sum) sum_by_group <- sum_by_group[order(sum_by_group$keyword_id),] group <- unique(sum_by_group$group) -figure <- vector(mode="list", length=length(group)) -for (i in 1:length(group)){ - figure[[i]] <- ggplot(data = sum_by_group[sum_by_group$group==group[i], ], aes(x=keyword_id, y=value, fill=Science_Center)) + - geom_bar(position='dodge', stat='identity') + - labs( - x = group[i], - y = "Frequency" - )+ - theme_bw() -} +jpeg(filename = here::here("TextAnalysis", "top10_barplot_sum.jpg"), width=200, height=150, units="mm", res=1200) +ggplot(sum_by_group, aes(fill=Source, y=value, x=keyword_id)) + + geom_bar(position="dodge", stat="identity") + + facet_wrap(~group, scales = "free_x") + + labs( + x = "Term ID", + y = "Frequency" + ) + + scale_fill_viridis(discrete = TRUE) + + theme_bw() +dev.off() + +mean_by_group <- aggregate(value ~ keyword+keyword_id+group+Source, data = data_merge, mean) +mean_by_group <- mean_by_group[order(mean_by_group$keyword_id),] +group <- unique(mean_by_group$group) -jpeg(filename = here::here("TextAnalysis", "top10_barplot.jpg"), width=300, height=270, units="mm", res=1200) -(figure[[1]] + figure[[2]] + figure[[3]] + figure[[4]] + figure[[5]])/ - (figure[[6]] + figure[[7]] + figure[[8]] + figure[[9]] + figure[[10]]) +jpeg(filename = here::here("TextAnalysis", "top10_barplot_mean.jpg"), width=200, height=150, units="mm", res=1200) +ggplot(mean_by_group, aes(fill=Source, y=value*100, x=keyword_id)) + + geom_bar(position="dodge", stat="identity") + + facet_wrap(~group, scales = "free_x") + + labs( + x = "Term ID", + y = "Presence (%)" + ) + + scale_fill_viridis(discrete = TRUE) + + theme_bw() dev.off() diff --git a/TextAnalysis/top10_analysis.xlsx b/TextAnalysis/top10_analysis.xlsx deleted file mode 100644 index af9264a..0000000 Binary files a/TextAnalysis/top10_analysis.xlsx and /dev/null differ diff --git a/TextAnalysis/top10_barplot.jpg b/TextAnalysis/top10_barplot.jpg deleted file mode 100644 index aba27f7..0000000 Binary files a/TextAnalysis/top10_barplot.jpg and /dev/null differ diff --git a/TextAnalysis/top10_barplot_mean.jpg b/TextAnalysis/top10_barplot_mean.jpg new file mode 100644 index 0000000..4f1208a Binary files /dev/null and b/TextAnalysis/top10_barplot_mean.jpg differ diff --git a/TextAnalysis/top10_barplot_sum.jpg b/TextAnalysis/top10_barplot_sum.jpg new file mode 100644 index 0000000..9b46845 Binary files /dev/null and b/TextAnalysis/top10_barplot_sum.jpg differ diff --git a/TextAnalysis/top10_frequency.csv b/TextAnalysis/top10_frequency.csv new file mode 100644 index 0000000..2048c70 --- /dev/null +++ b/TextAnalysis/top10_frequency.csv @@ -0,0 +1,105 @@ +"ID","Source","File_Path","catch","total mortality","harvest","catch per unit effort|cpue","catch rate","index of abundance","catch per effort","fishing success","landings","retained catch","natural log of unfished recruitment|lnr0","logr0","logr_0","log(r0)","r0","projection","forecast","prediction","sex","gender","spawning biomass|sb","spawning stock biomass|ssb","spawning output","spawning stock output|sso","weight","mass" +"1","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/blue-warehou-rebuilding-strategy-2022.pdf",83,0,14,14,0,12,0,0,2,0,0,0,0,0,0,0,0,0,2,0,6,0,0,0,2,0 +"2","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/frr276.pdf",435,18,1,1,6,6,0,0,0,0,0,0,0,0,0,0,0,0,38,0,4,7,0,0,12,0 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2019.pdf",0.05,0,0,0.01,0,0.02,0,0,0,0.01,0,0,0,0,0,0,0,0,0,0,0.03,0,0,0,0.01,0 +"103","NOAA-SWFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SWFSC/SC14-SA-WP-11 ISC18 Shortfin Mako Stock Assessment.pdf",0.1,0,0,0.07,0,0,0,0,0,0,0,0.01,0,0.01,0.01,0,0.01,0,0.01,0,0,0,0,0,0.01,0 +"Sum",NA,NA,8.31,0.03,1.23,1.65,0.21,0.18,0,0,2.69,0.12,0.05,0.01,0,0.01,0.1,0.47,0.11,0.03,0.26,0.03,2.31,1.79,0.29,0,0.99,0.02 diff --git a/TextAnalysis/top20_analysis.R b/TextAnalysis/top20_analysis.R index c722810..eb2a6c8 100644 --- a/TextAnalysis/top20_analysis.R +++ b/TextAnalysis/top20_analysis.R @@ -3,268 +3,298 @@ library(here) library(pdftools) library(tm) library(stringr) -library(xlsx) library(wordcloud) library(RColorBrewer) # Download stock assessment reports from Google Drive ------------- -# googledrive set-up: https://github.com/nmfs-openscapes/GoogleDrive1 -download_assessments <- function(googledrive_url, folder_name, subfolder_name) { +## If authorize_GoogleDrive <- TRUE: +## Users need to authorize googledrive package to access your Google Drive +## Please follow the instructions from https://googledrive.tidyverse.org/reference/drive_auth.html and https://github.com/nmfs-openscapes/GoogleDrive1 to +## authorize googledrive - # Get the files in the folder - dir_files <- googledrive::drive_ls(path = googledrive_url) - file_name <- dir_files$name +## If authorize_GoogleDrive <- FALSE: +## Users need to manually download stock assessment reports from the +## Assessment Docs Google Drive folder (https://drive.google.com/drive/folders/1uyLVjf7Xu2iMY6dhEjAAkB4l2vtSDMw9?usp=share_link) to fishdictionary/StockAssessment folder +## The folder structure looks - # Create folders to save downloaded files - if (!dir.exists(here::here(folder_name))) dir.create(here::here(folder_name)) - if (!dir.exists(here::here(folder_name, subfolder_name))) dir.create(here::here(folder_name, subfolder_name)) +authorize_GoogleDrive <- FALSE +if (authorize_GoogleDrive) { + # googledrive set-up: https://github.com/nmfs-openscapes/GoogleDrive1 + download_assessments <- function(googledrive_url, folder_name, subfolder_name) { - # Download files from Google Drive - for (i in 1:length(dir_files$id)) { - googledrive::drive_download(file = dir_files$id[i], overwrite = TRUE, path = here::here(folder_name, subfolder_name, file_name[i])) - } -} - -# Download AFSC stock assessment reports -download_assessments( - googledrive_url = "https://drive.google.com/drive/folders/1vbxiADIsjnCPGyOf-v4zTexOUSTidMTA", - folder_name = file.path("StockAssessment"), - subfolder_name = "AFSC" -) + # Get the files in the folder + dir_files <- googledrive::drive_ls(path = googledrive_url) + file_name <- dir_files$name -# Download NEFSC stock assessment reports -download_assessments( - googledrive_url = "https://drive.google.com/drive/folders/1edP73M7Bd4SpGLsgXIS8-jlqclA1QTZ9", - folder_name = file.path("StockAssessment"), - subfolder_name = "NEFSC" -) - -# Download NWFSC stock assessment reports -download_assessments( - googledrive_url = "https://drive.google.com/drive/folders/1UHv3f7JDkz3T6OUFNGiurBZIWR_EzyQq", - folder_name = file.path("StockAssessment"), - subfolder_name = "NWFSC" -) + # Create folders to save downloaded files + if (!dir.exists(here::here(folder_name))) dir.create(here::here(folder_name)) + if (!dir.exists(here::here(folder_name, subfolder_name))) dir.create(here::here(folder_name, subfolder_name)) -# Download PIFSC stock assessment reports -download_assessments( - googledrive_url = "https://drive.google.com/drive/folders/11I-3gwehVMEK_0aAkuytijNs7PXsu_e-", - folder_name = file.path("StockAssessment"), - subfolder_name = "PIFSC" -) - -# Download SEFSC stock assessment reports -download_assessments( - googledrive_url = "https://drive.google.com/drive/folders/12-09nqC7CvKfL2j1JX8ooi_bgMob2c1I", - folder_name = file.path("StockAssessment"), - subfolder_name = "SEFSC" -) + # Download files from Google Drive + for (i in 1:length(dir_files$id)) { + googledrive::drive_download(file = dir_files$id[i], overwrite = TRUE, path = here::here(folder_name, subfolder_name, file_name[i])) + } + } -# Download SWFSC stock assessment reports -download_assessments( - googledrive_url = "https://drive.google.com/drive/folders/1IqbncWlwbSwmBKroIfo-C9ckI_uGe6NG", - folder_name = file.path("StockAssessment"), - subfolder_name = "SWFSC" -) + # Download AFSC stock assessment reports + download_assessments( + googledrive_url = "https://drive.google.com/drive/folders/1vbxiADIsjnCPGyOf-v4zTexOUSTidMTA", + folder_name = file.path("StockAssessment"), + subfolder_name = "AFSC" + ) + + # Download NEFSC stock assessment reports + download_assessments( + googledrive_url = "https://drive.google.com/drive/folders/1edP73M7Bd4SpGLsgXIS8-jlqclA1QTZ9", + folder_name = file.path("StockAssessment"), + subfolder_name = "NEFSC" + ) + + # Download NWFSC stock assessment reports + download_assessments( + googledrive_url = "https://drive.google.com/drive/folders/1UHv3f7JDkz3T6OUFNGiurBZIWR_EzyQq", + folder_name = file.path("StockAssessment"), + subfolder_name = "NWFSC" + ) + + # Download PIFSC stock assessment reports + download_assessments( + googledrive_url = "https://drive.google.com/drive/folders/11I-3gwehVMEK_0aAkuytijNs7PXsu_e-", + folder_name = file.path("StockAssessment"), + subfolder_name = "PIFSC" + ) + + # Download SEFSC stock assessment reports + download_assessments( + googledrive_url = "https://drive.google.com/drive/folders/12-09nqC7CvKfL2j1JX8ooi_bgMob2c1I", + folder_name = file.path("StockAssessment"), + subfolder_name = "SEFSC" + ) + + # Download SWFSC stock assessment reports + download_assessments( + googledrive_url = "https://drive.google.com/drive/folders/1IqbncWlwbSwmBKroIfo-C9ckI_uGe6NG", + folder_name = file.path("StockAssessment"), + subfolder_name = "SWFSC" + ) +} # Define keyword --------------------------------------------------------------- keyword <- c( "biomass|b|abundance", - "spawning biomass|sb|spawning stock biomass|ssb|spawning stock output|sso|spawning output", + "spawning biomass|sb|spawning stock biomass|ssb|spawning stock output|sso|mature biomass|spawners", "unfished|virgin|initial|equilibrium|unfished equilibrium", - "recruits|age-0 fish", - "catch|total mortality", - "landings|retained catch|wanted catch", - "catch per unit effort|cpue|catch rate|index of abundance|standardized fishery catch time series|catch per effort|fishing success|availability", - "maximum sustainable yield|msy|msyproxy", - "instantaneous mortality rate|z", - "instantaneous fishing mortality rate|f|harvest rate|exploitation rate|finite fishing mortality|apical f", - "fishing mortality at maximum sustainable yield|fproxy|f_msy|fmsy", - "spawning per recruit|spr|spr30%|30%spr", - "weight|kg|mass", + "recruitment", + "recruits|recruit|age-0 fish|age-1 fish", + "catch|total mortality|harvest", + "catch per unit effort|cpue|catch rate|index of abundance|catch per effort|fishing success", + "landings|retained catch", + "spawning per recruit|spawning potential ratio|spr", + "maximum sustainable yield|msy", + "instantaneous total mortality rate|z", + "fishing mortality rate|f|instantaneous fishing mortality rate|harvest rate|exploitation rate|finite fishing mortality|apical f", + "fishing mortality at maximum sustainable yield|fmsy", + "weight|mass", "length composition|length frequency|length observation", "age composition|age frequency|age observation", "projection|forecast|prediction", "sex|gender", - "natural log of unfished recruitment|logr0|lnr0|r0|log(r0)", - "plus group", - "cohort|recruit" + "natural log of unfished recruitment|lnr0|logr0|logr_0|log(r0)|r0", + "plus group" ) # Create keywords database ---------------------------------------------------------------- working_path <- here::here("StockAssessment") -subfolder_path <- list.dirs(path = working_path, full.names = TRUE, recursive = FALSE) -subfolder_name <- list.dirs(path = working_path, full.names = FALSE, recursive = FALSE) - -# Create keyword database -col_name <- c("ID", "Science_Center", "File_Path", keyword) -frequency_database <- presence_database <- proportion_database <- - data.frame(matrix(NA, ncol = length(col_name))) -colnames(frequency_database) <- colnames(presence_database) <- colnames(proportion_database) <- - col_name - -for (subfolder_id in seq_along(subfolder_path)) { - file_path <- list.files(subfolder_path[subfolder_id], recursive = FALSE, full.names = TRUE) - - for (file_id in seq_along(file_path)) { - file <- file_path[file_id] - - # Create metadata of files - docs <- tm::Corpus(URISource(file), - readerControl = list(reader = readPDF) - ) - - # Convert symbols to space - toSpace <- tm::content_transformer( - function(x, pattern) gsub(pattern, " ", x) - ) - docs <- tm::tm_map(docs, toSpace, "/") - docs <- tm::tm_map(docs, toSpace, "@") - docs <- tm::tm_map(docs, toSpace, "\\|") - - # Convert text to lower case - docs <- tm::tm_map( - docs, - content_transformer(tolower) - ) - - # Remove punctuations - docs <- tm::tm_map(docs, removePunctuation) - - # Eliminate extra white spaces - docs <- tm::tm_map(docs, stripWhitespace) - - frequency <- presence <- proportion <- c() - for (keyword_id in seq_along(keyword)) { - # print(paste0("Folder: ", subfolder_id, "; File: ", file_id, "; Keyword: ", keyword_id)) - frequency[keyword_id] <- sum(stringr::str_count(docs[[1]]$content, paste("\\b", keyword[keyword_id], "\\b", sep = ""))) # Match if the current position is a word boundary - presence[keyword_id] <- ifelse(frequency[keyword_id] > 0, 1, 0) - proportion[keyword_id] <- round(frequency[keyword_id] / sum(stringr::str_count(docs[[1]]$content)) * 100, digits = 2) - } - - if (subfolder_id == 1 & file_id == 1) { - frequency_database[1, ] <- c(NA, subfolder_name[subfolder_id], file_path[file_id], frequency) - - presence_database[1, ] <- c(NA, subfolder_name[subfolder_id], file_path[file_id], presence) - - proportion_database[1, ] <- c(NA, subfolder_name[subfolder_id], file_path[file_id], proportion) - } else { - frequency_database <- rbind( - frequency_database, - c(NA, subfolder_name[subfolder_id], file_path[file_id], frequency) +subfolder_path_all <- list.dirs(path = working_path, full.names = TRUE, recursive = FALSE) +subfolder_name_all <- list.dirs(path = working_path, full.names = FALSE, recursive = FALSE) + +subfolder_info <- list(1, 2, 3:length(subfolder_path_all), 1:length(subfolder_path_all)) +names(subfolder_info) <- c("Australia", "ICES", "NOAA", "All") + +for (org in seq_along(subfolder_info)){ + subfolder_path <- subfolder_path_all[subfolder_info[[org]]] + subfolder_name <- subfolder_name_all[subfolder_info[[org]]] + + # Create keyword database + col_name <- c("ID", "Source", "File_Path", keyword) + frequency_database <- + presence_database <- + proportion_database <- + data.frame(matrix(NA, ncol = length(col_name))) + + colnames(frequency_database) <- + colnames(presence_database) <- + colnames(proportion_database) <- + col_name + + for (subfolder_id in seq_along(subfolder_path)) { + + file_path <- list.files(subfolder_path[subfolder_id], recursive = FALSE, full.names = TRUE) + + for (file_id in seq_along(file_path)) { + + # cat("file:", file_path[file_id], "\n") + file <- file_path[file_id] + + # Create metadata of files + docs <- tm::Corpus(URISource(file), + readerControl = list(reader = readPDF) ) - - presence_database <- rbind( - presence_database, - c(NA, subfolder_name[subfolder_id], file_path[file_id], presence) + + # Convert symbols to space + toSpace <- tm::content_transformer( + function(x, pattern) gsub(pattern, " ", x) ) - - proportion_database <- rbind( - proportion_database, - c(NA, subfolder_name[subfolder_id], file_path[file_id], proportion) + docs <- tm::tm_map(docs, toSpace, "/") + docs <- tm::tm_map(docs, toSpace, "@") + docs <- tm::tm_map(docs, toSpace, "\\|") + + # Convert text to lower case + docs <- tm::tm_map( + docs, + content_transformer(tolower) ) + + # Remove punctuations + docs <- tm::tm_map(docs, removePunctuation) + + # Eliminate extra white spaces + docs <- tm::tm_map(docs, stripWhitespace) + + frequency <- presence <- proportion <- c() + for (keyword_id in seq_along(keyword)) { + # print(paste0("Folder: ", subfolder_id, "; File: ", file_id, "; Keyword: ", keyword_id)) + frequency[keyword_id] <- sum(stringr::str_count(docs[[1]]$content, paste("\\b", keyword[keyword_id], "\\b", sep = ""))) # Match if the current position is a word boundary + presence[keyword_id] <- ifelse(frequency[keyword_id] > 0, 1, 0) + proportion[keyword_id] <- round(frequency[keyword_id] / sum(stringr::str_count(docs[[1]]$content)) * 100, digits = 2) + } + + if (subfolder_id == 1 & file_id == 1) { + frequency_database[1, ] <- c(NA, subfolder_name[subfolder_id], file_path[file_id], frequency) + + presence_database[1, ] <- c(NA, subfolder_name[subfolder_id], file_path[file_id], presence) + + proportion_database[1, ] <- c(NA, subfolder_name[subfolder_id], file_path[file_id], proportion) + } else { + frequency_database <- rbind( + frequency_database, + c(NA, subfolder_name[subfolder_id], file_path[file_id], frequency) + ) + + presence_database <- rbind( + presence_database, + c(NA, subfolder_name[subfolder_id], file_path[file_id], presence) + ) + + proportion_database <- rbind( + proportion_database, + c(NA, subfolder_name[subfolder_id], file_path[file_id], proportion) + ) + } } } + + frequency_database$ID <- 1:nrow(frequency_database) + presence_database$ID <- 1:nrow(presence_database) + proportion_database$ID <- 1:nrow(proportion_database) + + frequency_database[, 4:ncol(frequency_database)] <- sapply(frequency_database[, 4:ncol(frequency_database)], as.numeric) + + frequency_database <- rbind( + frequency_database, + c(NA, NA, NA, apply(frequency_database[, 4:ncol(frequency_database)], 2, sum)) + ) + frequency_database[nrow(frequency_database), "ID"] <- "Sum" + + presence_database[, 4:ncol(presence_database)] <- sapply(presence_database[, 4:ncol(presence_database)], as.numeric) + presence_database <- rbind( + presence_database, + c(NA, NA, NA, apply(presence_database[, 4:ncol(presence_database)], 2, sum)) + ) + presence_database[nrow(presence_database), "ID"] <- "Sum" + + proportion_database[, 4:ncol(proportion_database)] <- sapply(proportion_database[, 4:ncol(proportion_database)], as.numeric) + proportion_database <- rbind( + proportion_database, + c(NA, NA, NA, apply(proportion_database[, 4:ncol(proportion_database)], 2, sum)) + ) + proportion_database[nrow(proportion_database), "ID"] <- "Sum" + + write.csv(frequency_database, file=here::here("TextAnalysis", paste0("top20_frequency_", names(subfolder_info)[org], ".csv")), row.names=FALSE) + write.csv(presence_database, file=here::here("TextAnalysis", paste0("top20_presence_", names(subfolder_info)[org], ".csv")), row.names=FALSE) + write.csv(proportion_database, file=here::here("TextAnalysis", paste0("top20_proportion_", names(subfolder_info)[org], ".csv")), row.names=FALSE) + # Upload xlsx to Google Drive + if (authorize_GoogleDrive) { + # Google Drive folder id + id_googledrive <- "1BUsYYd11lE2TECqHru5tX6LwkMniVnKv" + googledrive::drive_upload(media = xlsx_path, path = as_id(id_googledrive), overwrite = TRUE, type = "spreadsheet") + } + + # Plot results ------------------------------------------------------------ + frequency_database <- read.csv(file=here::here("TextAnalysis", paste0("top20_frequency_", names(subfolder_info)[org], ".csv"))) + presence_database<-read.csv(file=here::here("TextAnalysis", paste0("top20_presence_", names(subfolder_info)[org], ".csv"))) + proportion_database<-read.csv(file=here::here("TextAnalysis", paste0("top20_proportion_", names(subfolder_info)[org], ".csv"))) + + word_frequency <- as.matrix(frequency_database[frequency_database$ID == "Sum", 4:ncol(frequency_database)]) + word_presence <- as.matrix(presence_database[presence_database$ID == "Sum", 4:ncol(presence_database)]) + word_proportion <- as.matrix(proportion_database[proportion_database$ID == "Sum", 4:ncol(proportion_database)]) + + xlabels <- c( + "biomass", + "spawning biomass", + "unfished", + "recruitment", + "recruit(s)", + "catch", + "catch per unit effort", + "landings", + "spawner per recruit", + "maximum sustainable yield", + "instantaneous total mortality rate", + "fishing mortality", + "FMSY", + "weight", + "length composition", + "age composition", + "projection", + "sex", + "natural log of unfished recruitment", + "plus group" + ) + + # barplot + jpeg(filename = here::here("TextAnalysis", paste0("top20_barplot_", names(subfolder_info)[org], ".jpg")), width = 200, height = 120, units = "mm", res = 1200) + par(mar = c(6, 4, 1, 1), mfrow = c(3, 1)) + frequency_barplot <- barplot(height = word_frequency, xaxt = "n", ylab = "Frequency") + text(frequency_barplot - 0.25, par("usr")[3] - 0.25, xlabels, xpd = TRUE, srt = 40, adj = 1, cex = 0.8) + + + presence_barplot <- barplot(height = word_presence, xaxt = "n", ylab = "Presence") + text(presence_barplot - 0.25, par("usr")[3] - 0.25, xlabels, xpd = TRUE, srt = 40, adj = 1, cex = 0.8) + + proportion_barplot <- barplot(height = word_proportion, xaxt = "n", ylab = "Proportion") + text(proportion_barplot - 0.25, par("usr")[3] - 0.25, xlabels, xpd = TRUE, srt = 40, adj = 1, cex = 0.8) + + dev.off() + + jpeg(filename = here::here("TextAnalysis", paste0("top20_presence_", names(subfolder_info)[org], ".jpg")), width = 200, height = 120, units = "mm", res = 1200) + par(mar = c(6, 4, 1, 1), mfrow = c(1, 1)) + presence_barplot <- barplot(height = word_presence, xaxt = "n", ylab = "Frequency") # range: 26-83, median:68 + text(presence_barplot - 0.25, par("usr")[3] - 0.25, xlabels, xpd = TRUE, srt = 40, adj = 1, cex = 0.7) + dev.off() + + # wordcloud figure + jpeg(filename = here::here("TextAnalysis", paste0("top20_wordcloud_", names(subfolder_info)[org], ".jpg")), width = 200, height = 200, units = "mm", res = 1200) + par(mar = c(1, 1, 1, 1), mfrow = c(1, 1)) + wordcloud( + words = xlabels, freq = word_presence, rot.per = 0.35, + colors = brewer.pal(8, "Dark2") + ) + dev.off() + } -frequency_database$ID <- 1:nrow(frequency_database) -presence_database$ID <- 1:nrow(presence_database) -proportion_database$ID <- 1:nrow(proportion_database) - -frequency_database[, 4:ncol(frequency_database)] <- sapply(frequency_database[, 4:ncol(frequency_database)], as.numeric) - -frequency_database <- rbind( - frequency_database, - c(NA, NA, NA, apply(frequency_database[, 4:ncol(frequency_database)], 2, sum)) -) -frequency_database[nrow(frequency_database), "ID"] <- "Sum" - -presence_database[, 4:ncol(presence_database)] <- sapply(presence_database[, 4:ncol(presence_database)], as.numeric) -presence_database <- rbind( - presence_database, - c(NA, NA, NA, apply(presence_database[, 4:ncol(presence_database)], 2, sum)) -) -presence_database[nrow(presence_database), "ID"] <- "Sum" - -proportion_database[, 4:ncol(proportion_database)] <- sapply(proportion_database[, 4:ncol(proportion_database)], as.numeric) -proportion_database <- rbind( - proportion_database, - c(NA, NA, NA, apply(proportion_database[, 4:ncol(proportion_database)], 2, sum)) -) -proportion_database[nrow(proportion_database), "ID"] <- "Sum" - -xlsx_path <- here::here("TextAnalysis", "top20_analysis.xlsx") -xlsx::write.xlsx(frequency_database, file = xlsx_path, sheetName = "frequency", row.names = FALSE) -xlsx::write.xlsx(presence_database, file = xlsx_path, sheetName = "presence", append = TRUE, row.names = FALSE) -xlsx::write.xlsx(proportion_database, file = xlsx_path, sheetName = "proportion", append = TRUE, row.names = FALSE) -# Upload xlsx to Google Drive -# Google Drive folder id -id_googledrive <- "1BUsYYd11lE2TECqHru5tX6LwkMniVnKv" -googledrive::drive_upload(media = xlsx_path, path = as_id(id_googledrive), overwrite = TRUE, type = "spreadsheet") - -# Plot results ------------------------------------------------------------ -xlsx_path <- here::here("TextAnalysis", "top20_analysis.xlsx") -frequency_database <- xlsx::read.xlsx(file = xlsx_path, sheetName = "frequency") -presence_database <- xlsx::read.xlsx(file = xlsx_path, sheetName = "presence") -proportion_database <- xlsx::read.xlsx(file = xlsx_path, sheetName = "proportion") - -word_frequency <- as.matrix(frequency_database[frequency_database$ID == "Sum", 4:ncol(frequency_database)]) -word_presence <- as.matrix(presence_database[presence_database$ID == "Sum", 4:ncol(presence_database)]) -word_proportion <- as.matrix(proportion_database[proportion_database$ID == "Sum", 4:ncol(proportion_database)]) - -xlabels <- c( - "biomass", - "spawning biomass", - "unfished", - "recruitment", - "catch", - "landings", - "catch per unit effort", - "MSY", - "Z", - "F", - "FMSY", - "spawner per recruit", - "weight", - "length composition", - "age composition", - "projection", - "sex", - "natural log of unfished recruitment", - "plus group", - "cohort" -) - -# barplot -jpeg(filename = here::here("TextAnalysis", "top20_barplot.jpg"), width = 200, height = 120, units = "mm", res = 1200) -par(mar = c(6, 4, 1, 1), mfrow = c(3, 1)) -frequency_barplot <- barplot(height = word_frequency, xaxt = "n", ylab = "Frequency") -text(frequency_barplot - 0.25, par("usr")[3] - 0.25, xlabels, xpd = TRUE, srt = 40, adj = 1, cex = 0.8) - - -presence_barplot <- barplot(height = word_presence, xaxt = "n", ylab = "Presence") -text(presence_barplot - 0.25, par("usr")[3] - 0.25, xlabels, xpd = TRUE, srt = 40, adj = 1, cex = 0.8) - -proportion_barplot <- barplot(height = word_proportion, xaxt = "n", ylab = "Proportion") -text(proportion_barplot - 0.25, par("usr")[3] - 0.25, xlabels, xpd = TRUE, srt = 40, adj = 1, cex = 0.8) - -dev.off() - -jpeg(filename = here::here("TextAnalysis", "top20_presence.jpg"), width = 200, height = 120, units = "mm", res = 1200) -par(mar = c(6, 4, 1, 1), mfrow = c(1, 1)) -presence_barplot <- barplot(height = word_presence, xaxt = "n", ylab = "Frequency") # range: 26-84, median:67.5 -text(presence_barplot - 0.25, par("usr")[3] - 0.25, xlabels, xpd = TRUE, srt = 40, adj = 1, cex = 0.7) -dev.off() - -# wordcloud figure -jpeg(filename = here::here("TextAnalysis", "top20_wordcloud.jpg"), width = 200, height = 200, units = "mm", res = 1200) -par(mar = c(1, 1, 1, 1), mfrow = c(1, 1)) -wordcloud( - words = xlabels, freq = word_presence, rot.per = 0.35, - colors = brewer.pal(8, "Dark2") -) -dev.off() diff --git a/TextAnalysis/top20_analysis.xlsx b/TextAnalysis/top20_analysis.xlsx deleted file mode 100644 index c7ec6c1..0000000 Binary files a/TextAnalysis/top20_analysis.xlsx and /dev/null differ diff --git a/TextAnalysis/top20_barplot.jpg b/TextAnalysis/top20_barplot.jpg deleted file mode 100644 index 5089d6a..0000000 Binary files a/TextAnalysis/top20_barplot.jpg and /dev/null differ diff --git a/TextAnalysis/top20_barplot_All.jpg b/TextAnalysis/top20_barplot_All.jpg new file mode 100644 index 0000000..f82ac0a Binary files /dev/null and b/TextAnalysis/top20_barplot_All.jpg differ diff --git a/TextAnalysis/top20_barplot_Australia.jpg b/TextAnalysis/top20_barplot_Australia.jpg new file mode 100644 index 0000000..3dc410a Binary files /dev/null and b/TextAnalysis/top20_barplot_Australia.jpg differ diff --git a/TextAnalysis/top20_barplot_ICES.jpg b/TextAnalysis/top20_barplot_ICES.jpg new file mode 100644 index 0000000..82766fd Binary files /dev/null and b/TextAnalysis/top20_barplot_ICES.jpg differ diff --git a/TextAnalysis/top20_barplot_NOAA.jpg b/TextAnalysis/top20_barplot_NOAA.jpg new file mode 100644 index 0000000..84b5d6d Binary files /dev/null and b/TextAnalysis/top20_barplot_NOAA.jpg differ diff --git a/TextAnalysis/top20_frequency_All.csv b/TextAnalysis/top20_frequency_All.csv new file mode 100644 index 0000000..2fbf09b --- /dev/null +++ b/TextAnalysis/top20_frequency_All.csv @@ -0,0 +1,105 @@ +"ID","Source","File_Path","biomass|b|abundance","spawning biomass|sb|spawning stock biomass|ssb|spawning stock output|sso|mature biomass|spawners","unfished|virgin|initial|equilibrium|unfished equilibrium","recruitment","recruits|recruit|age-0 fish|age-1 fish","catch|total mortality|harvest","catch per unit effort|cpue|catch rate|index of abundance|catch per effort|fishing success","landings|retained catch","spawning per recruit|spawning potential ratio|spr","maximum sustainable yield|msy","instantaneous total mortality rate|z","fishing mortality rate|f|instantaneous fishing mortality rate|harvest rate|exploitation rate|finite fishing mortality|apical f","fishing mortality at maximum sustainable yield|fmsy","weight|mass","length composition|length frequency|length observation","age composition|age frequency|age observation","projection|forecast|prediction","sex|gender","natural log of unfished recruitment|lnr0|logr0|logr_0|log(r0)|r0","plus group" +"1","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/blue-warehou-rebuilding-strategy-2022.pdf",711,10,5,4,6,129,31,2,2,3,0,1214,0,16,0,1,0,2,0,0 +"2","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/frr276.pdf",2720,37,15,95,143,542,65,0,100,0,62,4451,0,51,21,42,0,100,0,0 +"3","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/frr294.pdf",3139,30,63,37,57,569,135,14,0,21,185,6161,0,185,0,7,55,35,5,0 +"4","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/Gummy-assessment-report-Dec2020.pdf",1207,12,9,4,5,97,126,5,0,3,0,1780,0,50,16,20,10,12,0,7 +"5","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/King threadfin stock assessment 2020.pdf",1666,105,53,35,52,354,121,6,5,12,3,3765,0,127,25,9,5,9,17,1 +"6","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/Marine_Scalefish_Fishery_Assessment_Report_2020_-_FINAL_20200424.pdf",3471,53,4,67,74,1139,341,2,0,0,5,9234,0,72,1,2,0,11,0,0 +"7","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/puntae_x2006a.pdf",1279,87,11,40,52,266,21,4,2,6,3,2063,1,114,2,0,6,5,1,0 +"8","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/stock-status-summary-2021-22-gemfish.pdf",289,7,4,6,9,93,14,9,3,0,0,645,0,21,3,2,3,6,1,0 +"9","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/Stock assessment of black jewfish with data to December 2021.pdf",1332,74,55,10,21,231,45,16,0,20,0,2475,8,131,10,4,4,0,12,0 +"10","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/Stock assessment of Queensland east coast dusky flathead with data to December 2020.pdf",1071,85,46,23,27,245,57,19,0,18,1,2560,2,130,27,0,4,64,9,0 +"11","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/Stock assessment of Queensland red emperor 2022.pdf",1575,161,100,21,24,372,95,34,0,22,0,4852,0,175,16,5,2,25,4,0 +"12","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/Stock assessment of the Queensland ballots saucer scallop_2022ed..pdf",1101,52,36,30,35,249,109,1,0,5,3,1763,0,77,0,0,13,0,8,0 +"13","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/Stock assessments for SESSF- 2019 - Part 2.pdf",5919,21,35,0,0,1638,1536,4,0,0,1,12834,0,43,0,0,1,0,0,0 +"14","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/Stock Assessments for SESSF 2020–21 - Part 1.pdf",8327,512,235,768,846,992,378,48,17,6,3,15600,0,682,170,51,121,24,20,72 +"15","ICES","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/ICES/01_WGNSSK_Report_2019.pdf",18719,814,27,514,647,2179,153,1543,36,820,37,26921,428,919,54,54,593,57,1,21 +"16","ICES","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/ICES/ices2023_WKBCOD_report_2023.pdf",4945,277,10,176,221,453,13,402,0,136,14,7439,36,299,3,29,119,0,0,12 +"17","ICES","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/ICES/WKBALTCOD2_2019.pdf",6066,173,15,78,82,546,80,88,0,23,38,8095,15,212,52,14,42,18,11,1 +"18","ICES","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/ICES/WKBBALTPEL_2023_final_report.pdf",8102,298,55,120,169,529,16,126,58,409,45,10875,215,310,3,19,73,23,7,20 +"19","ICES","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/ICES/wkdem_2020.pdf",2111,85,9,37,44,310,6,80,0,48,10,3594,32,143,2,12,24,0,1,5 +"20","ICES","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/ICES/WKFlatNSCS_2020.pdf",12799,239,33,132,166,683,51,3373,1,388,6,19156,206,638,4,76,56,117,6,19 +"21","ICES","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/ICES/WKMSYSPiCT_2021.pdf",4958,34,77,13,14,580,266,254,0,311,37,7983,133,202,15,1,79,16,0,1 +"22","ICES","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/ICES/WKSPRAT_2018_Report.pdf",1127,29,0,43,47,143,7,5,1,3,8,1712,1,39,1,2,29,0,0,1 +"23","NOAA-AFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-AFSC/BSAIatf.pdf",249,5,0,0,0,40,1,0,0,0,1,414,0,18,0,2,11,0,0,0 +"24","NOAA-AFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-AFSC/BSAIatka.pdf",3107,98,11,58,77,294,46,8,1,7,27,4540,0,303,6,43,26,6,2,1 +"25","NOAA-AFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-AFSC/BSAIocto.pdf",1096,11,1,5,5,118,11,1,0,2,6,1615,0,47,0,0,1,3,0,0 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+"61","NOAA-NWFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-NWFSC/dover_sole_december_2021_final.pdf",2667,141,85,54,66,163,22,80,37,13,3,4979,0,242,43,19,25,109,6,2 +"62","NOAA-NWFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-NWFSC/g-5-attachment-3-draft-full-assessment-of-status-of-the-pacific-spiny-dogfish-shark-resource-off-the-continental-u-s-pacific-coast-in-2021-electronic-only.pdf",2119,67,63,38,80,302,9,113,46,22,2,4935,0,76,59,11,10,29,14,0 +"63","NOAA-NWFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-NWFSC/Gopher_BlackandYellow_Assessment_2019-1.pdf",2703,35,44,90,111,330,38,109,22,2,11,5330,0,78,76,14,20,9,17,1 +"64","NOAA-NWFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-NWFSC/hake-assessment-post-srg-final_20210303.pdf",4432,296,74,189,250,569,26,30,81,51,10,7230,3,532,2,45,90,10,30,0 +"65","NOAA-NWFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-NWFSC/Longnose skate 2019_FINAL.pdf",2660,154,64,43,75,318,26,176,56,26,3,4696,0,195,61,20,8,16,20,0 +"66","NOAA-NWFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-NWFSC/PacificOceanPerch2017_Assessment_Final.pdf",1948,25,46,64,85,154,42,62,21,9,1,4307,0,134,16,20,15,18,6,0 +"67","NOAA-NWFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-NWFSC/sablefish_20191022.pdf",5976,185,73,407,524,372,49,109,43,16,60,10656,2,298,23,24,56,26,23,11 +"68","NOAA-NWFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-NWFSC/WidowAssessment2015.pdf",2449,124,62,101,125,259,9,227,28,23,13,5768,4,211,58,41,46,29,19,0 +"69","NOAA-NWFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-NWFSC/Yelloweye rockfish 2017.pdf",2243,82,58,68,124,294,40,60,43,22,1,5459,0,94,76,40,11,19,18,0 +"70","NOAA-NWFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-NWFSC/Yellowtail rockfish 2017.pdf",2741,42,42,44,80,220,44,62,23,3,0,5953,0,147,22,13,29,19,12,0 +"71","NOAA-PIFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-PIFSC/NMFS-PIFSC-60.pdf",2013,27,26,7,11,411,0,2,173,2,16,3107,0,74,2,0,0,1,0,0 +"72","NOAA-PIFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-PIFSC/noaa_17252_DS1.pdf",3076,15,60,0,0,523,484,0,0,186,3,5303,7,221,1,0,33,3,0,0 +"73","NOAA-PIFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-PIFSC/noaa_20062_DS1.pdf",1568,31,8,11,17,243,0,4,139,2,14,2389,0,85,1,0,0,3,0,0 +"74","NOAA-PIFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-PIFSC/noaa_21164_DS1.pdf",3752,15,66,2,2,628,178,6,0,519,4,6004,0,326,1,0,39,0,0,0 +"75","NOAA-PIFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-PIFSC/SA-WP-06-[SP-alb-assessment] Rev 1.pdf",1221,93,30,63,70,88,50,0,0,45,6,2723,8,87,14,3,1,5,0,1 +"76","NOAA-PIFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-PIFSC/SC14-SA-WP-08 Silky shark stock assessment (1).pdf",2319,229,32,35,37,302,320,0,0,18,15,4382,6,41,34,0,0,25,2,0 +"77","NOAA-PIFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-PIFSC/SC15-SA-WP-05 SKJ-Assessment REV2 (1).pdf",1601,222,24,55,68,125,73,0,0,74,5,3976,28,113,53,0,18,5,0,1 +"78","NOAA-PIFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-PIFSC/SC15-SA-WP-06 Oceanic whitetip shark_assessment.pdf",2044,296,60,27,41,310,90,0,0,81,1,2742,27,78,3,0,15,11,4,0 +"79","NOAA-SEFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SEFSC/05.-Traditional-Interim-assessment-report-RS-002-1.pdf",213,0,0,0,0,33,6,1,0,0,2,402,0,16,0,0,2,0,0,0 +"80","NOAA-SEFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SEFSC/08b.-SEDAR61_2021IA_Final.pdf",212,0,0,1,1,38,11,8,0,0,0,430,0,15,0,0,13,0,0,0 +"81","NOAA-SEFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SEFSC/2019_WHM_SA_ENG.pdf",1118,22,17,14,14,105,60,10,0,96,15,1690,39,43,2,0,32,12,3,0 +"82","NOAA-SEFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SEFSC/2020_ALB_ENG.pdf",3153,19,13,4,5,159,219,1,0,149,52,3073,58,134,1,1,32,11,0,0 +"83","NOAA-SEFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SEFSC/2021_WBFT_SA_ENG.pdf",721,35,22,43,51,30,5,0,0,0,11,967,0,24,7,2,14,0,7,0 +"84","NOAA-SEFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SEFSC/Atl_Blacknose_SAR.pdf",9034,130,73,34,56,652,369,144,4,302,23,13655,185,250,4,15,114,25,18,1 +"85","NOAA-SEFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SEFSC/B-8a-Gray_triggerfish_interim_9102020.pdf",219,1,1,0,0,30,3,5,0,0,0,343,0,13,0,0,8,0,0,0 +"86","NOAA-SEFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SEFSC/Dusky_update_report_2016.pdf",891,13,45,21,33,51,8,12,2,59,2,1663,30,30,5,4,26,3,5,1 +"87","NOAA-SEFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SEFSC/KGM_GOM_SA_08282020_final-revision_3.pdf",791,101,35,35,45,36,17,95,0,5,0,1655,2,62,20,4,11,10,10,0 +"88","NOAA-SEFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SEFSC/S23_SAR_complete_and_final.pdf",4465,245,32,27,44,326,19,205,326,59,24,9226,29,136,1,10,73,20,0,0 +"89","NOAA-SEFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SEFSC/S28UpdateSAR_V2.pdf",1745,142,50,64,118,54,26,99,20,2,0,3494,1,110,53,29,48,8,11,2 +"90","NOAA-SEFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SEFSC/S34_ATSH_SAR.pdf",4005,41,76,28,38,333,101,38,3,316,19,7862,224,147,7,11,214,7,27,0 +"91","NOAA-SEFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SEFSC/S51_FINAL_SAR_0.pdf",4085,189,54,75,119,136,67,309,27,34,53,11298,14,165,56,7,61,25,18,0 +"92","NOAA-SEFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SEFSC/S52_Final_SAR_v2.pdf",3443,177,69,154,247,130,83,108,48,37,108,11099,8,123,34,142,111,2,2,2 +"93","NOAA-SEFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SEFSC/S57_Final_SAR.pdf",3514,97,163,40,75,102,28,194,18,45,58,4507,20,100,100,0,22,25,55,1 +"94","NOAA-SEFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SEFSC/S64_SAR_FINAL.pdf",5816,328,146,136,201,191,109,340,96,47,81,11390,23,273,138,23,45,38,26,3 +"95","NOAA-SEFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SEFSC/S67_Final_SAR.pdf",3248,223,75,114,186,171,107,145,47,65,29,6897,31,120,44,72,89,10,10,1 +"96","NOAA-SEFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SEFSC/S72_SAR_FINAL.pdf",3539,429,98,83,124,147,68,178,6,42,93,8354,20,311,194,59,42,21,15,4 +"97","NOAA-SEFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SEFSC/SA BSB 2018.pdf",3137,176,73,49,109,80,25,145,12,230,5,3782,103,148,31,38,95,6,7,1 +"98","NOAA-SEFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SEFSC/SEDAR_60_SA_Red_Porgy_SAR_4.9.2020.pdf",2825,259,67,57,147,94,26,193,19,257,13,4900,118,165,42,40,111,7,18,1 +"99","NOAA-SEFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SEFSC/SEDAR65_FullSAR_12.8.2020_V3.pdf",8869,91,163,154,243,500,107,125,4,318,53,11823,263,158,194,1,289,80,21,0 +"100","NOAA-SEFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SEFSC/SMA_ASS_ENG.pdf",1498,21,15,10,26,197,75,11,0,249,12,2043,49,80,21,0,19,16,4,0 +"101","NOAA-SWFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SWFSC/agenda-item-d-3.pdf",2168,100,45,76,108,153,16,54,12,11,32,3675,3,225,8,46,40,22,8,0 +"102","NOAA-SWFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SWFSC/SAC-11-07-MTG_Yellowfin tuna benchmark assessment 2019.pdf",1665,121,38,47,65,170,59,10,0,52,4,3325,18,88,26,1,3,6,10,0 +"103","NOAA-SWFSC","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/NOAA-SWFSC/SC14-SA-WP-11 ISC18 Shortfin Mako Stock Assessment.pdf",1461,16,118,79,110,241,123,3,33,99,15,3421,4,37,24,0,38,34,24,4 +"Sum",NA,NA,282167,10742,4153,6506,8895,27574,8006,10900,2011,6418,1664,490620,2519,15161,2606,1608,3842,2081,780,208 diff --git a/TextAnalysis/top20_frequency_Australia.csv b/TextAnalysis/top20_frequency_Australia.csv new file mode 100644 index 0000000..dda8087 --- /dev/null +++ b/TextAnalysis/top20_frequency_Australia.csv @@ -0,0 +1,16 @@ +"ID","Source","File_Path","biomass|b|abundance","spawning biomass|sb|spawning stock biomass|ssb|spawning stock output|sso|mature biomass|spawners","unfished|virgin|initial|equilibrium|unfished equilibrium","recruitment","recruits|recruit|age-0 fish|age-1 fish","catch|total mortality|harvest","catch per unit effort|cpue|catch rate|index of abundance|catch per effort|fishing success","landings|retained catch","spawning per recruit|spawning potential ratio|spr","maximum sustainable yield|msy","instantaneous total mortality rate|z","fishing mortality rate|f|instantaneous fishing mortality rate|harvest rate|exploitation rate|finite fishing mortality|apical f","fishing mortality at maximum sustainable yield|fmsy","weight|mass","length composition|length frequency|length observation","age composition|age frequency|age observation","projection|forecast|prediction","sex|gender","natural log of unfished recruitment|lnr0|logr0|logr_0|log(r0)|r0","plus group" +"1","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/blue-warehou-rebuilding-strategy-2022.pdf",711,10,5,4,6,129,31,2,2,3,0,1214,0,16,0,1,0,2,0,0 +"2","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/frr276.pdf",2720,37,15,95,143,542,65,0,100,0,62,4451,0,51,21,42,0,100,0,0 +"3","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/frr294.pdf",3139,30,63,37,57,569,135,14,0,21,185,6161,0,185,0,7,55,35,5,0 +"4","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/Gummy-assessment-report-Dec2020.pdf",1207,12,9,4,5,97,126,5,0,3,0,1780,0,50,16,20,10,12,0,7 +"5","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/King threadfin stock assessment 2020.pdf",1666,105,53,35,52,354,121,6,5,12,3,3765,0,127,25,9,5,9,17,1 +"6","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/Marine_Scalefish_Fishery_Assessment_Report_2020_-_FINAL_20200424.pdf",3471,53,4,67,74,1139,341,2,0,0,5,9234,0,72,1,2,0,11,0,0 +"7","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/puntae_x2006a.pdf",1279,87,11,40,52,266,21,4,2,6,3,2063,1,114,2,0,6,5,1,0 +"8","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/stock-status-summary-2021-22-gemfish.pdf",289,7,4,6,9,93,14,9,3,0,0,645,0,21,3,2,3,6,1,0 +"9","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/Stock assessment of black jewfish with data to December 2021.pdf",1332,74,55,10,21,231,45,16,0,20,0,2475,8,131,10,4,4,0,12,0 +"10","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/Stock assessment of Queensland east coast dusky flathead with data to December 2020.pdf",1071,85,46,23,27,245,57,19,0,18,1,2560,2,130,27,0,4,64,9,0 +"11","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/Stock assessment of Queensland red emperor 2022.pdf",1575,161,100,21,24,372,95,34,0,22,0,4852,0,175,16,5,2,25,4,0 +"12","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/Stock assessment of the Queensland ballots saucer scallop_2022ed..pdf",1101,52,36,30,35,249,109,1,0,5,3,1763,0,77,0,0,13,0,8,0 +"13","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/Stock assessments for SESSF- 2019 - Part 2.pdf",5919,21,35,0,0,1638,1536,4,0,0,1,12834,0,43,0,0,1,0,0,0 +"14","Australia","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/Australia/Stock Assessments for SESSF 2020–21 - Part 1.pdf",8327,512,235,768,846,992,378,48,17,6,3,15600,0,682,170,51,121,24,20,72 +"Sum",NA,NA,33807,1246,671,1140,1351,6916,3074,164,129,116,266,69397,11,1874,291,143,224,293,77,80 diff --git a/TextAnalysis/top20_frequency_ICES.csv b/TextAnalysis/top20_frequency_ICES.csv new file mode 100644 index 0000000..e355d27 --- /dev/null +++ b/TextAnalysis/top20_frequency_ICES.csv @@ -0,0 +1,10 @@ +"ID","Source","File_Path","biomass|b|abundance","spawning biomass|sb|spawning stock biomass|ssb|spawning stock output|sso|mature biomass|spawners","unfished|virgin|initial|equilibrium|unfished equilibrium","recruitment","recruits|recruit|age-0 fish|age-1 fish","catch|total mortality|harvest","catch per unit effort|cpue|catch rate|index of abundance|catch per effort|fishing success","landings|retained catch","spawning per recruit|spawning potential ratio|spr","maximum sustainable yield|msy","instantaneous total mortality rate|z","fishing mortality rate|f|instantaneous fishing mortality rate|harvest rate|exploitation rate|finite fishing mortality|apical f","fishing mortality at maximum sustainable yield|fmsy","weight|mass","length composition|length frequency|length observation","age composition|age frequency|age observation","projection|forecast|prediction","sex|gender","natural log of unfished recruitment|lnr0|logr0|logr_0|log(r0)|r0","plus group" +"1","ICES","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/ICES/01_WGNSSK_Report_2019.pdf",18719,814,27,514,647,2179,153,1543,36,820,37,26921,428,919,54,54,593,57,1,21 +"2","ICES","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/ICES/ices2023_WKBCOD_report_2023.pdf",4945,277,10,176,221,453,13,402,0,136,14,7439,36,299,3,29,119,0,0,12 +"3","ICES","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/ICES/WKBALTCOD2_2019.pdf",6066,173,15,78,82,546,80,88,0,23,38,8095,15,212,52,14,42,18,11,1 +"4","ICES","C:/Users/bai.li/Documents/GitHub/fishdictionary/StockAssessment/ICES/WKBBALTPEL_2023_final_report.pdf",8102,298,55,120,169,529,16,126,58,409,45,10875,215,310,3,19,73,23,7,20 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Assessment.pdf",0.94,0.01,0.08,0.05,0.07,0.16,0.08,0,0.02,0.06,0.01,2.2,0,0.02,0.02,0,0.02,0.02,0.02,0 +"Sum",NA,NA,113.05,5.21,1.55,2.63,3.66,13.04,2.86,2.91,0.68,2.73,0.55,199.35,0.92,8.08,0.92,0.51,2.16,0.72,0.24,0.02 diff --git a/TextAnalysis/top20_proportion_Australia.csv b/TextAnalysis/top20_proportion_Australia.csv new file mode 100644 index 0000000..4634532 --- /dev/null +++ b/TextAnalysis/top20_proportion_Australia.csv @@ -0,0 +1,16 @@ +"ID","Source","File_Path","biomass|b|abundance","spawning biomass|sb|spawning stock biomass|ssb|spawning stock output|sso|mature biomass|spawners","unfished|virgin|initial|equilibrium|unfished equilibrium","recruitment","recruits|recruit|age-0 fish|age-1 fish","catch|total mortality|harvest","catch per unit effort|cpue|catch rate|index of abundance|catch per effort|fishing success","landings|retained catch","spawning per recruit|spawning potential ratio|spr","maximum sustainable yield|msy","instantaneous total mortality rate|z","fishing 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