ab_syrphids = col_double(),ab_humbleflies = col_double(),
ab_other_flies = col_double(),ab_beetles = col_double(),
ab_lepidoptera = col_double(),ab_nonbee_hymenoptera = col_double(),
ab_others = col_double(),
total_sampled_area = col_character(),
total_sampled_time = col_double(),
visitation_rate_units = col_character(),
visitation_rate = col_double(),visit_honeybee = col_double(),
visit_bombus = col_double(),visit_wildbees = col_double(),
visit_syrphids = col_double(),visit_humbleflies = col_double(),
visit_other_flies = col_double(),visit_beetles = col_double(),
visit_lepidoptera = col_double(),visit_nonbee_hymenoptera = col_double(),
visit_others = col_double(),
Publication = col_character(),
Credit = col_character(),Email_contact = col_character()))
field_level_i
}
test_file("../testthat/test-format.R", reporter = "summary") #Visualize testing
options(testthat.output_file = "../testthat/test_out_Create_Dataset.txt")
report <- readLines("../testthat/test_out_Create_Dataset.txt")
file.failures <- str_match(report, "field_level_data_(.*?)csv")
file.failures <- file.failures[!is.na(file.failures[,1]),1]
file.failures <- file.failures[!duplicated(file.failures)]
list_files_field_level <- list_files_field_level[!list_files_field_level %in% file.failures]
for (i in seq(length(list_files_field_level))) {
file_field_level_i <- paste(folder_base, list_files_field_level[i], sep = "/")
field_level_i <- extract_template_i(file_field_level_i)
if (i == 1) {
FINAL_field_level_data <- field_level_i
}
else {
FINAL_field_level_data <- FINAL_field_level_data %>% bind_rows(field_level_i)
}
}
FINAL_field_level_data$crop[FINAL_field_level_data$crop=="Malus Domestica"] <- "Malus domestica"
FINAL_field_level_data$crop[FINAL_field_level_data$crop=="Fragaria × ananassa"] <- "Fragaria x ananassa"
# Fix country:
FINAL_field_level_data$country[FINAL_field_level_data$country=="United States"] <- "USA"
FINAL_field_level_data$country %>% unique() %>% sort()
# Fix variety:
FINAL_field_level_data$variety[FINAL_field_level_data$variety=="Koipesol Oleko"] <- "Koipesol OLEKO"
FINAL_field_level_data$variety %>% unique() %>% sort()
FINAL_field_level_data$richness_restriction[is.na(FINAL_field_level_data$richness_restriction)] <- "none"
FINAL_field_level_data$richness_restriction[is.na(FINAL_field_level_data$observed_pollinator_richness)&
is.na(FINAL_field_level_data$other_pollinator_richness)&
is.na(FINAL_field_level_data$other_richness_estimator_method)] <- NA
write_csv(FINAL_field_level_data, "../Final_Data/FINAL_field_level_data_V0p2.csv")
library(tidyverse)
library(testthat)
folder_base <- "../Datasets_storage"
files_base <- list.files(folder_base)
list_files_field_level <- files_base[grepl("field_level_data", files_base)]
extract_template_i <- function(file_name){
field_level_i <- read_csv(file_name,
col_types = cols(
study_id = col_character(),
site_id = col_character(),
crop = col_character(),
variety = col_character(),management = col_character(),
country = col_character(),latitude = col_double(),
longitude = col_double(),X_UTM = col_double(),
Y_UTM = col_double(),zone_UTM = col_character(),
sampling_start_month = col_double(),
sampling_end_month = col_double(),
field_size = col_double(),sampling_year = col_character(),
yield = col_double(),
yield_units = col_character(),
yield2 = col_double(),yield2_units = col_character(),
yield_treatments_no_pollinators = col_double(),
yield_treatments_pollen_supplement = col_double(),
yield_treatments_no_pollinators2 = col_double(),
yield_treatments_pollen_supplement2 = col_double(),
fruits_per_plant = col_double(),fruit_weight = col_double(),
plant_density = col_double(),seeds_per_fruit = col_double(),
seeds_per_plant = col_double(),seed_weight = col_double(),
observed_pollinator_richness = col_double(),
other_pollinator_richness = col_double(),
other_richness_estimator_method = col_character(),
richness_restriction = col_character(),
abundance = col_double(),ab_honeybee = col_double(),
ab_bombus = col_double(),ab_wildbees = col_double(),
ab_syrphids = col_double(),ab_humbleflies = col_double(),
ab_other_flies = col_double(),ab_beetles = col_double(),
ab_lepidoptera = col_double(),ab_nonbee_hymenoptera = col_double(),
ab_others = col_double(),
total_sampled_area = col_character(),
total_sampled_time = col_double(),
visitation_rate_units = col_character(),
visitation_rate = col_double(),visit_honeybee = col_double(),
visit_bombus = col_double(),visit_wildbees = col_double(),
visit_syrphids = col_double(),visit_humbleflies = col_double(),
visit_other_flies = col_double(),visit_beetles = col_double(),
visit_lepidoptera = col_double(),visit_nonbee_hymenoptera = col_double(),
visit_others = col_double(),
Publication = col_character(),
Credit = col_character(),Email_contact = col_character()))
field_level_i
}
test_file("../testthat/test-format.R", reporter = "summary") #Visualize testing
options(testthat.output_file = "../testthat/test_out_Create_Dataset.txt")
report <- readLines("../testthat/test_out_Create_Dataset.txt")
file.failures <- str_match(report, "field_level_data_(.*?)csv")
file.failures <- file.failures[!is.na(file.failures[,1]),1]
file.failures <- file.failures[!duplicated(file.failures)]
list_files_field_level <- list_files_field_level[!list_files_field_level %in% file.failures]
for (i in seq(length(list_files_field_level))) {
file_field_level_i <- paste(folder_base, list_files_field_level[i], sep = "/")
field_level_i <- extract_template_i(file_field_level_i)
if (i == 1) {
FINAL_field_level_data <- field_level_i
}
else {
FINAL_field_level_data <- FINAL_field_level_data %>% bind_rows(field_level_i)
}
}
FINAL_field_level_data$crop[FINAL_field_level_data$crop=="Malus Domestica"] <- "Malus domestica"
FINAL_field_level_data$crop[FINAL_field_level_data$crop=="Fragaria × ananassa"] <- "Fragaria x ananassa"
# Fix country:
FINAL_field_level_data$country[FINAL_field_level_data$country=="United States"] <- "USA"
FINAL_field_level_data$country %>% unique() %>% sort()
# Fix variety:
FINAL_field_level_data$variety[FINAL_field_level_data$variety=="Koipesol Oleko"] <- "Koipesol OLEKO"
FINAL_field_level_data$variety %>% unique() %>% sort()
FINAL_field_level_data$richness_restriction[is.na(FINAL_field_level_data$richness_restriction)] <- "none"
FINAL_field_level_data$richness_restriction[is.na(FINAL_field_level_data$observed_pollinator_richness)&
is.na(FINAL_field_level_data$other_pollinator_richness)&
is.na(FINAL_field_level_data$other_richness_estimator_method)] <- NA
write_csv(FINAL_field_level_data, "../Final_Data/FINAL_field_level_data_V0p2.csv")
list_files_insect_sampling <- files_base[grepl("insect_sampling", files_base)]
library(tidyverse)
library(testthat)
folder_base <- "../Datasets_storage"
files_base <- list.files(folder_base)
list_files_field_level <- files_base[grepl("field_level_data", files_base)]
extract_template_i <- function(file_name){
field_level_i <- read_csv(file_name,
col_types = cols(
study_id = col_character(),
site_id = col_character(),
crop = col_character(),
variety = col_character(),management = col_character(),
country = col_character(),latitude = col_double(),
longitude = col_double(),X_UTM = col_double(),
Y_UTM = col_double(),zone_UTM = col_character(),
sampling_start_month = col_double(),
sampling_end_month = col_double(),
field_size = col_double(),sampling_year = col_character(),
yield = col_double(),
yield_units = col_character(),
yield2 = col_double(),yield2_units = col_character(),
yield_treatments_no_pollinators = col_double(),
yield_treatments_pollen_supplement = col_double(),
yield_treatments_no_pollinators2 = col_double(),
yield_treatments_pollen_supplement2 = col_double(),
fruits_per_plant = col_double(),fruit_weight = col_double(),
plant_density = col_double(),seeds_per_fruit = col_double(),
seeds_per_plant = col_double(),seed_weight = col_double(),
observed_pollinator_richness = col_double(),
other_pollinator_richness = col_double(),
other_richness_estimator_method = col_character(),
richness_restriction = col_character(),
abundance = col_double(),ab_honeybee = col_double(),
ab_bombus = col_double(),ab_wildbees = col_double(),
ab_syrphids = col_double(),ab_humbleflies = col_double(),
ab_other_flies = col_double(),ab_beetles = col_double(),
ab_lepidoptera = col_double(),ab_nonbee_hymenoptera = col_double(),
ab_others = col_double(),
total_sampled_area = col_character(),
total_sampled_time = col_double(),
visitation_rate_units = col_character(),
visitation_rate = col_double(),visit_honeybee = col_double(),
visit_bombus = col_double(),visit_wildbees = col_double(),
visit_syrphids = col_double(),visit_humbleflies = col_double(),
visit_other_flies = col_double(),visit_beetles = col_double(),
visit_lepidoptera = col_double(),visit_nonbee_hymenoptera = col_double(),
visit_others = col_double(),
Publication = col_character(),
Credit = col_character(),Email_contact = col_character()))
field_level_i
}
test_file("../testthat/test-format.R", reporter = "summary") #Visualize testing
options(testthat.output_file = "../testthat/test_out_Create_Dataset.txt")
report <- readLines("../testthat/test_out_Create_Dataset.txt")
file.failures <- str_match(report, "field_level_data_(.*?)csv")
file.failures <- file.failures[!is.na(file.failures[,1]),1]
file.failures <- file.failures[!duplicated(file.failures)]
list_files_field_level <- list_files_field_level[!list_files_field_level %in% file.failures]
for (i in seq(length(list_files_field_level))) {
file_field_level_i <- paste(folder_base, list_files_field_level[i], sep = "/")
field_level_i <- extract_template_i(file_field_level_i)
if (i == 1) {
FINAL_field_level_data <- field_level_i
}
else {
FINAL_field_level_data <- FINAL_field_level_data %>% bind_rows(field_level_i)
}
}
FINAL_field_level_data$crop[FINAL_field_level_data$crop=="Malus Domestica"] <- "Malus domestica"
FINAL_field_level_data$crop[FINAL_field_level_data$crop=="Fragaria × ananassa"] <- "Fragaria x ananassa"
# Fix country:
FINAL_field_level_data$country[FINAL_field_level_data$country=="United States"] <- "USA"
FINAL_field_level_data$country %>% unique() %>% sort()
# Fix variety:
FINAL_field_level_data$variety[FINAL_field_level_data$variety=="Koipesol Oleko"] <- "Koipesol OLEKO"
FINAL_field_level_data$variety %>% unique() %>% sort()
FINAL_field_level_data$richness_restriction[is.na(FINAL_field_level_data$richness_restriction)] <- "none"
FINAL_field_level_data$richness_restriction[is.na(FINAL_field_level_data$observed_pollinator_richness)&
is.na(FINAL_field_level_data$other_pollinator_richness)&
is.na(FINAL_field_level_data$other_richness_estimator_method)] <- NA
write_csv(FINAL_field_level_data, "../Final_Data/FINAL_field_level_data_V0p2.csv")
list_files_insect_sampling <- files_base[grepl("insect_sampling", files_base)]
extract_sampling_i <- function(file_name){
sampling_i <- read_csv(file_name,
col_types = cols(
study_id = col_character(),
site_id = col_character(),
pollinator = col_character(),
guild = col_character(),
sampling_method = col_character(),
abundance = col_double(),
total_sampled_area = col_double(),
total_sampled_time = col_double(),
total_sampled_flowers = col_double(),
Description = col_character()
))
sampling_i
}
for (i in seq(length(list_files_insect_sampling))) {
sampling_i <- paste(folder_base, list_files_insect_sampling[i], sep = "/")
sampling_i <- extract_sampling_i(sampling_i)
if (i == 1) {
FINAL_sampling_data <- sampling_i
}
else {
FINAL_sampling_data <- FINAL_sampling_data %>% bind_rows(sampling_i)
}
}
FINAL_sampling_data <- FINAL_sampling_data %>% filter(abundance > 0)
FINAL_sampling_data %>% group_by(guild) %>% count()
FINAL_sampling_data$guild[FINAL_sampling_data$guild=="bombyliidae"] <- "humbleflies"
FINAL_sampling_data$guild[FINAL_sampling_data$guild=="other wild bees"] <- "other_wild_bees"
FINAL_sampling_data$guild[FINAL_sampling_data$guild=="wild_bees"] <- "other_wild_bees"
FINAL_sampling_data$guild[FINAL_sampling_data$guild=="others"] <- "other"
FINAL_sampling_data %>% group_by(guild) %>% count()
write_csv(FINAL_sampling_data, "../Final_Data/FINAL_sampling_data_V0p2.csv")
library(tidyverse)
library(testthat)
folder_base <- "../Datasets_storage"
files_base <- list.files(folder_base)
list_files_field_level <- files_base[grepl("field_level_data", files_base)]
extract_template_i <- function(file_name){
field_level_i <- read_csv(file_name,
col_types = cols(
study_id = col_character(),
site_id = col_character(),
crop = col_character(),
variety = col_character(),management = col_character(),
country = col_character(),latitude = col_double(),
longitude = col_double(),X_UTM = col_double(),
Y_UTM = col_double(),zone_UTM = col_character(),
sampling_start_month = col_double(),
sampling_end_month = col_double(),
field_size = col_double(),sampling_year = col_character(),
yield = col_double(),
yield_units = col_character(),
yield2 = col_double(),yield2_units = col_character(),
yield_treatments_no_pollinators = col_double(),
yield_treatments_pollen_supplement = col_double(),
yield_treatments_no_pollinators2 = col_double(),
yield_treatments_pollen_supplement2 = col_double(),
fruits_per_plant = col_double(),fruit_weight = col_double(),
plant_density = col_double(),seeds_per_fruit = col_double(),
seeds_per_plant = col_double(),seed_weight = col_double(),
observed_pollinator_richness = col_double(),
other_pollinator_richness = col_double(),
other_richness_estimator_method = col_character(),
richness_restriction = col_character(),
abundance = col_double(),ab_honeybee = col_double(),
ab_bombus = col_double(),ab_wildbees = col_double(),
ab_syrphids = col_double(),ab_humbleflies = col_double(),
ab_other_flies = col_double(),ab_beetles = col_double(),
ab_lepidoptera = col_double(),ab_nonbee_hymenoptera = col_double(),
ab_others = col_double(),
total_sampled_area = col_character(),
total_sampled_time = col_double(),
visitation_rate_units = col_character(),
visitation_rate = col_double(),visit_honeybee = col_double(),
visit_bombus = col_double(),visit_wildbees = col_double(),
visit_syrphids = col_double(),visit_humbleflies = col_double(),
visit_other_flies = col_double(),visit_beetles = col_double(),
visit_lepidoptera = col_double(),visit_nonbee_hymenoptera = col_double(),
visit_others = col_double(),
Publication = col_character(),
Credit = col_character(),Email_contact = col_character()))
field_level_i
}
test_file("../testthat/test-format.R", reporter = "summary") #Visualize testing
options(testthat.output_file = "../testthat/test_out_Create_Dataset.txt")
report <- readLines("../testthat/test_out_Create_Dataset.txt")
file.failures <- str_match(report, "field_level_data_(.*?)csv")
file.failures <- file.failures[!is.na(file.failures[,1]),1]
file.failures <- file.failures[!duplicated(file.failures)]
list_files_field_level <- list_files_field_level[!list_files_field_level %in% file.failures]
for (i in seq(length(list_files_field_level))) {
file_field_level_i <- paste(folder_base, list_files_field_level[i], sep = "/")
field_level_i <- extract_template_i(file_field_level_i)
if (i == 1) {
FINAL_field_level_data <- field_level_i
}
else {
FINAL_field_level_data <- FINAL_field_level_data %>% bind_rows(field_level_i)
}
}
FINAL_field_level_data$crop[FINAL_field_level_data$crop=="Malus Domestica"] <- "Malus domestica"
FINAL_field_level_data$crop[FINAL_field_level_data$crop=="Fragaria × ananassa"] <- "Fragaria x ananassa"
# Fix country:
FINAL_field_level_data$country[FINAL_field_level_data$country=="United States"] <- "USA"
FINAL_field_level_data$country %>% unique() %>% sort()
# Fix variety:
FINAL_field_level_data$variety[FINAL_field_level_data$variety=="Koipesol Oleko"] <- "Koipesol OLEKO"
FINAL_field_level_data$variety %>% unique() %>% sort()
FINAL_field_level_data$richness_restriction[is.na(FINAL_field_level_data$richness_restriction)] <- "none"
FINAL_field_level_data$richness_restriction[is.na(FINAL_field_level_data$observed_pollinator_richness)&
is.na(FINAL_field_level_data$other_pollinator_richness)&
is.na(FINAL_field_level_data$other_richness_estimator_method)] <- NA
# Fix chao 1
FINAL_field_level_data$other_richness_estimator_method[FINAL_field_level_data$other_richness_estimator_method=="Chao1"] <- "Chao 1"
FINAL_field_level_data$study_id[FINAL_field_level_data$other_richness_estimator_method=="Chao"]
FINAL_field_level_data$study_id[FINAL_field_level_data$other_richness_estimator_method=="chao"]
FINAL_field_level_data$study_id[FINAL_field_level_data$other_richness_estimator_method=="chao"] %>% unique()
write_csv(FINAL_field_level_data, "../Final_Data/FINAL_field_level_data_V0p2.csv")
FINAL_field_level_data %>% select(other_richness_estimator_method) %>% unique()
library(tidyverse)
library(testthat)
folder_base <- "../Datasets_storage"
files_base <- list.files(folder_base)
list_files_field_level <- files_base[grepl("field_level_data", files_base)]
extract_template_i <- function(file_name){
field_level_i <- read_csv(file_name,
col_types = cols(
study_id = col_character(),
site_id = col_character(),
crop = col_character(),
variety = col_character(),management = col_character(),
country = col_character(),latitude = col_double(),
longitude = col_double(),X_UTM = col_double(),
Y_UTM = col_double(),zone_UTM = col_character(),
sampling_start_month = col_double(),
sampling_end_month = col_double(),
field_size = col_double(),sampling_year = col_character(),
yield = col_double(),
yield_units = col_character(),
yield2 = col_double(),yield2_units = col_character(),
yield_treatments_no_pollinators = col_double(),
yield_treatments_pollen_supplement = col_double(),
yield_treatments_no_pollinators2 = col_double(),
yield_treatments_pollen_supplement2 = col_double(),
fruits_per_plant = col_double(),fruit_weight = col_double(),
plant_density = col_double(),seeds_per_fruit = col_double(),
seeds_per_plant = col_double(),seed_weight = col_double(),
observed_pollinator_richness = col_double(),
other_pollinator_richness = col_double(),
other_richness_estimator_method = col_character(),
richness_restriction = col_character(),
abundance = col_double(),ab_honeybee = col_double(),
ab_bombus = col_double(),ab_wildbees = col_double(),
ab_syrphids = col_double(),ab_humbleflies = col_double(),
ab_other_flies = col_double(),ab_beetles = col_double(),
ab_lepidoptera = col_double(),ab_nonbee_hymenoptera = col_double(),
ab_others = col_double(),
total_sampled_area = col_character(),
total_sampled_time = col_double(),
visitation_rate_units = col_character(),
visitation_rate = col_double(),visit_honeybee = col_double(),
visit_bombus = col_double(),visit_wildbees = col_double(),
visit_syrphids = col_double(),visit_humbleflies = col_double(),
visit_other_flies = col_double(),visit_beetles = col_double(),
visit_lepidoptera = col_double(),visit_nonbee_hymenoptera = col_double(),
visit_others = col_double(),
Publication = col_character(),
Credit = col_character(),Email_contact = col_character()))
field_level_i
}
test_file("../testthat/test-format-field_level.R", reporter = "summary") #Visualize testing
library(tidyverse)
library(testthat)
folder_base <- "../Datasets_storage"
files_base <- list.files(folder_base)
list_files_field_level <- files_base[grepl("field_level_data", files_base)]
extract_template_i <- function(file_name){
field_level_i <- read_csv(file_name,
col_types = cols(
study_id = col_character(),
site_id = col_character(),
crop = col_character(),
variety = col_character(),management = col_character(),
country = col_character(),latitude = col_double(),
longitude = col_double(),X_UTM = col_double(),
Y_UTM = col_double(),zone_UTM = col_character(),
sampling_start_month = col_double(),
sampling_end_month = col_double(),
field_size = col_double(),sampling_year = col_character(),
yield = col_double(),
yield_units = col_character(),
yield2 = col_double(),yield2_units = col_character(),
yield_treatments_no_pollinators = col_double(),
yield_treatments_pollen_supplement = col_double(),
yield_treatments_no_pollinators2 = col_double(),
yield_treatments_pollen_supplement2 = col_double(),
fruits_per_plant = col_double(),fruit_weight = col_double(),
plant_density = col_double(),seeds_per_fruit = col_double(),
seeds_per_plant = col_double(),seed_weight = col_double(),
observed_pollinator_richness = col_double(),
other_pollinator_richness = col_double(),
other_richness_estimator_method = col_character(),
richness_restriction = col_character(),
abundance = col_double(),ab_honeybee = col_double(),
ab_bombus = col_double(),ab_wildbees = col_double(),
ab_syrphids = col_double(),ab_humbleflies = col_double(),
ab_other_flies = col_double(),ab_beetles = col_double(),
ab_lepidoptera = col_double(),ab_nonbee_hymenoptera = col_double(),
ab_others = col_double(),
total_sampled_area = col_character(),
total_sampled_time = col_double(),
visitation_rate_units = col_character(),
visitation_rate = col_double(),visit_honeybee = col_double(),
visit_bombus = col_double(),visit_wildbees = col_double(),
visit_syrphids = col_double(),visit_humbleflies = col_double(),
visit_other_flies = col_double(),visit_beetles = col_double(),
visit_lepidoptera = col_double(),visit_nonbee_hymenoptera = col_double(),
visit_others = col_double(),
Publication = col_character(),
Credit = col_character(),Email_contact = col_character()))
field_level_i
}
test_file("../testthat/test-format-field_level.R", reporter = "summary") #Visualize testing
options(testthat.output_file = "../testthat/test_out_Create_Dataset.txt")
report <- readLines("../testthat/test_out_Create_Dataset.txt")
file.failures <- str_match(report, "field_level_data_(.*?)csv")
file.failures <- file.failures[!is.na(file.failures[,1]),1]
file.failures <- file.failures[!duplicated(file.failures)]
list_files_field_level <- list_files_field_level[!list_files_field_level %in% file.failures]
for (i in seq(length(list_files_field_level))) {
file_field_level_i <- paste(folder_base, list_files_field_level[i], sep = "/")
field_level_i <- extract_template_i(file_field_level_i)
if (i == 1) {
FINAL_field_level_data <- field_level_i
}
else {
FINAL_field_level_data <- FINAL_field_level_data %>% bind_rows(field_level_i)
}
}
FINAL_field_level_data$crop[FINAL_field_level_data$crop=="Malus Domestica"] <- "Malus domestica"
FINAL_field_level_data$crop[FINAL_field_level_data$crop=="Fragaria × ananassa"] <- "Fragaria x ananassa"
# Fix country:
FINAL_field_level_data$country[FINAL_field_level_data$country=="United States"] <- "USA"
FINAL_field_level_data$country %>% unique() %>% sort()
# Fix variety:
FINAL_field_level_data$variety[FINAL_field_level_data$variety=="Koipesol Oleko"] <- "Koipesol OLEKO"
FINAL_field_level_data$variety %>% unique() %>% sort()
FINAL_field_level_data$richness_restriction[is.na(FINAL_field_level_data$richness_restriction)] <- "none"
FINAL_field_level_data$richness_restriction[is.na(FINAL_field_level_data$observed_pollinator_richness)&
is.na(FINAL_field_level_data$other_pollinator_richness)&
is.na(FINAL_field_level_data$other_richness_estimator_method)] <- NA
FINAL_field_level_data$other_richness_estimator_method[FINAL_field_level_data$other_richness_estimator_method=="Chao1"] <- "Chao 1"
write_csv(FINAL_field_level_data, "../Final_Data/FINAL_field_level_data_V0p2.csv")
list_files_insect_sampling <- files_base[grepl("insect_sampling", files_base)]
extract_sampling_i <- function(file_name){
sampling_i <- read_csv(file_name,
col_types = cols(
study_id = col_character(),
site_id = col_character(),
pollinator = col_character(),
guild = col_character(),
sampling_method = col_character(),
abundance = col_double(),
total_sampled_area = col_double(),
total_sampled_time = col_double(),
total_sampled_flowers = col_double(),
Description = col_character()
))
sampling_i
}
test_file("../testthat/test-format-insect_sampling.R", reporter = "summary") #Visualize testing
options(testthat.output_file = "../testthat/test_out_Create_Dataset_I.txt")
report <- readLines("../testthat/test_out_Create_Dataset_I.txt")
test_file("../testthat/test-format-insect_sampling.R", reporter = "summary") #Visualize testing
options(testthat.output_file = "../testthat/test_out_Create_Dataset_I.txt")
report <- readLines("../testthat/test_out_Create_Dataset_I.txt")
file.failures <- str_match(report, "insect_sampling_(.*?)csv")
file.failures <- file.failures[!is.na(file.failures[,1]),1]
file.failures <- file.failures[!duplicated(file.failures)]
list_files_insect_sampling <- list_files_insect_sampling[!list_files_insect_sampling %in% file.failures]
for (i in seq(length(list_files_insect_sampling))) {
sampling_i <- paste(folder_base, list_files_insect_sampling[i], sep = "/")
sampling_i <- extract_sampling_i(sampling_i)
if (i == 1) {
FINAL_sampling_data <- sampling_i
}
else {
FINAL_sampling_data <- FINAL_sampling_data %>% bind_rows(sampling_i)
}
}
FINAL_sampling_data <- FINAL_sampling_data %>% filter(abundance > 0)
FINAL_sampling_data %>% group_by(guild) %>% count()
FINAL_sampling_data$guild[FINAL_sampling_data$guild=="bombyliidae"] <- "humbleflies"
FINAL_sampling_data$guild[FINAL_sampling_data$guild=="other wild bees"] <- "other_wild_bees"
FINAL_sampling_data$guild[FINAL_sampling_data$guild=="wild_bees"] <- "other_wild_bees"
FINAL_sampling_data$guild[FINAL_sampling_data$guild=="others"] <- "other"
FINAL_sampling_data %>% group_by(guild) %>% count()
FINAL_sampling_data %>% group_by(guild) %>% count()
write_csv(FINAL_sampling_data, "../Final_Data/FINAL_sampling_data_V0p2.csv")
