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readdata.R
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readdata.R
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library(gsheet)
library(tidyverse)
library(crosstalk)
library(DT)
library(ggthemes)
library(janitor)
library(cowplot)
library(plotly)
library(flexdashboard)
library(tidyverse)
library(crosstalk)
library(plotly)
library(viridis)
library(leaflet.providers)
library(leaflet)
Sys.setlocale("LC_ALL", "pt_BR.UTF-8")
#Ascari et al 202?
ascari = gsheet2tbl("https://docs.google.com/spreadsheets/d/1R6UXFcsbVgpPYyvfkPvZ81rqkyk4U_9aS7qV8TKPsxQ/edit#gid=532754791")
ascari_all <- ascari %>%
filter(labcode != 0) %>%
mutate(id = case_when(
is.na(py_binomial) ~ "No",
TRUE ~ "Yes"
)) %>%
mutate(wheat = case_when(
host_binomial == "Triticum aestivum" ~ "Wheat",
TRUE ~ "Non-wheat")) %>%
filter(host_binomial != "Oryza sativa")
ascari_all = ascari_all %>%
dplyr::select(labcode, year, lat, lon, country, state_province, county_municipality, source, host_binomial, py_binomial, py_lineage, wheat)
#BioTrigo
biotrigo = gsheet2tbl("https://docs.google.com/spreadsheets/d/1R6UXFcsbVgpPYyvfkPvZ81rqkyk4U_9aS7qV8TKPsxQ/edit#gid=1498154130")
biotrigo_all = biotrigo %>%
filter(labcode != 0) %>%
mutate(id = case_when(
is.na(py_binomial) ~ "No",
TRUE ~ "Yes"
)) %>%
mutate(wheat = case_when(
host_binomial == "Triticum aestivum" ~ "Wheat",
TRUE ~ "Non-wheat"
))%>%
filter(host_binomial != "Oryza sativa")
biotrigo_all <- biotrigo_all %>%
dplyr::select(labcode, year, lat, lon, country, state_province, county_municipality, source, host_binomial, py_binomial, py_lineage, wheat)
#Tembo et al 2021
tembo = gsheet2tbl("https://docs.google.com/spreadsheets/d/1R6UXFcsbVgpPYyvfkPvZ81rqkyk4U_9aS7qV8TKPsxQ/edit#gid=1727645447")
tembo_all = tembo %>%
filter(labcode != 0) %>%
mutate(id = case_when(
is.na(py_binomial) ~ "No",
TRUE ~ "Yes"
)) %>%
mutate(wheat = case_when(
host_binomial == "Triticum aestivum" ~ "Wheat",
TRUE ~ "Non-wheat"
))%>%
filter(host_binomial != "Oryza sativa")
tembo_all <- tembo_all %>%
dplyr::select(labcode, year, lat, lon, country, state_province, county_municipality, source, host_binomial, py_binomial, py_lineage, wheat)
# #Croll 2021
# croll = gsheet2tbl("https://docs.google.com/spreadsheets/d/1R6UXFcsbVgpPYyvfkPvZ81rqkyk4U_9aS7qV8TKPsxQ/edit#gid=106318963")
# croll_all = croll %>%
# filter(labcode != 0) %>%
# mutate(id = case_when(
# is.na(py_binomial) ~ "No",
# TRUE ~ "Yes"
# )) %>%
# mutate(wheat = case_when(
# host_binomial == "Triticum aestivum" ~ "Wheat",
# TRUE ~ "Non-wheat"
# ))
#
# croll_all <- croll_all %>%
# dplyr::select(labcode, year, lat, lon, country, state_province, county_municipality, source, host_binomial, py_binomial, py_lineage, wheat)
#
# #Rahnama et al 202?
# Rahnama = gsheet2tbl("https://docs.google.com/spreadsheets/d/1R6UXFcsbVgpPYyvfkPvZ81rqkyk4U_9aS7qV8TKPsxQ/edit#gid=2126271613")
# Rahnama_all = Rahnama %>%
# filter(labcode != 0) %>%
# mutate(id = case_when(
# is.na(py_binomial) ~ "No",
# TRUE ~ "Yes"
# )) %>%
# mutate(wheat = case_when(
# host_binomial == "Triticum aestivum" ~ "Wheat",
# TRUE ~ "Non-wheat"
# ))
#
# Rahnama_all <- Rahnama_all %>%
# dplyr::select(labcode, year, lat, lon, country, state_province, county_municipality, source, host_binomial, py_binomial, py_lineage, wheat)
# #Castroaugudin et al 2016
# Castroaugudin = gsheet2tbl("https://docs.google.com/spreadsheets/d/1R6UXFcsbVgpPYyvfkPvZ81rqkyk4U_9aS7qV8TKPsxQ/edit#gid=1870344414")
# Castroaugudin_all = Castroaugudin %>%
# filter(labcode != 0) %>%
# mutate(id = case_when(
# is.na(py_binomial) ~ "No",
# TRUE ~ "Yes"
# )) %>%
# mutate(wheat = case_when(
# host_binomial == "Triticum aestivum" ~ "Wheat",
# TRUE ~ "Non-wheat"
# ))
#
# Castroaugudin_all <- Castroaugudin_all %>%
# dplyr::select(labcode, year, lat, lon, country, state_province, county_municipality, source, host_binomial, py_binomial, py_lineage, wheat)
#Raw data
set.seed(1)
wb_all = bind_rows(ascari_all, biotrigo_all, tembo_all) %>%
unite("latlong", lat, lon, sep ="/", remove = F ) %>%
group_by(latlong) %>%
mutate(n = n(),
lat = case_when(n > 1 ~ rnorm(n, lat,0.01),
n == 1 ~ lat),
lon = case_when(n > 1 ~ rnorm(n, lon,0.01),
n == 1 ~ lon)
) %>%
ungroup() %>%
dplyr::select(-latlong)
sd <- SharedData$new(wb_all)
wb_all2 <- wb_all %>%
select(labcode, year, country, source, host_binomial, py_binomial, py_lineage, wheat)
sd2 <- SharedData$new(wb_all2)