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assess_data.Rmd
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---
title: "WHIP DATA QUALITY ASSESSMENT"
output: html_document
params:
spec: spec
obs: obs
country.of.interest: country.of.interest
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
```{r load packages , echo=FALSE, warning=FALSE, message=FALSE, eval=T}
library(knitr)
library(kableExtra)
library(stringi)
library(dplyr)
library(tibble)
library(rworldmap)
library(tidyverse)
library(plyr)
```
```{r load data, echo=FALSE, warning=FALSE, message=FALSE}
spec<-params$spec
obs<-params$obs
# modify column names to delete weird characters
colnames(spec)=sapply(names(spec), function(x) gsub(" ", "_", x, fixed = TRUE), USE.NAMES = F)
colnames(spec)=sapply(names(spec), function(x) gsub("/", "_", x, fixed = TRUE), USE.NAMES = F)
colnames(spec)=sapply(names(spec), function(x) gsub("_-", "", x, fixed = TRUE), USE.NAMES = F)
colnames(spec)=sapply(names(spec), function(x) gsub(" ", "", x, fixed = TRUE), USE.NAMES = F)
colnames(spec)=stri_trans_general(str = colnames(spec),
id = "Latin-ASCII")
colnames(obs)=sapply(names(obs), function(x) gsub(" ", "_", x, fixed = TRUE), USE.NAMES = F)
colnames(obs)=sapply(names(obs), function(x) gsub("/", "_", x, fixed = TRUE), USE.NAMES = F)
colnames(obs)=sapply(names(obs), function(x) gsub("_-", "", x, fixed = TRUE), USE.NAMES = F)
colnames(obs)=sapply(names(obs), function(x) gsub(" ", "", x, fixed = TRUE), USE.NAMES = F)
colnames(obs)=stri_trans_general(str = colnames(obs),
id = "Latin-ASCII")
# spec=spec[!(spec$Tags%in%c("Delete", "Delete,Test")),]
# spec=spec[!(spec$Tags%in%c("Test,Delete", "Test")),]
spec=spec[!(grepl("test", spec$Projects, ignore.case = T)),]
spec=spec[!(grepl("delete", spec$Projects, ignore.case = T)),]
spec=spec[!(grepl("test", spec$Tags, ignore.case = T)),]
spec=spec[!(grepl("delete", spec$Tags, ignore.case = T)),]
spec=spec[spec$Event_Code!="WCS.100294",] #
# obs=obs[!(obs$Tags%in%c("Delete", "Delete,Test")),]
# obs=obs[!(obs$Tags%in%c("Test,Delete", "Test")),]
obs=obs[!(grepl("test", obs$Projects, ignore.case = T)),]
obs=obs[!(grepl("delete", obs$Projects, ignore.case = T)),]
obs=obs[!(grepl("test", obs$Tags, ignore.case = T)),]
obs=obs[!(grepl("delete", obs$Tags, ignore.case = T)),]
# delete a WHIP test. the fact that it is a test is mentioned in an open text box
obs=obs[obs$Event_Code!="WCS.100035",]
# Set all Lao PDR as Laos in spec and obs
if(any(spec$Country=="Laos", na.rm = T)){spec[which(spec$Country=="Laos"), ]$Country="Lao PDR"}
if(any(obs$Country=="Laos", na.rm = T)){obs[which(obs$Country=="Laos"), ]$Country="Lao PDR"}
countries=sort(c("Cambodia", "Lao PDR", "Vietnam"))
spec=spec%>%filter(Country%in%c(countries, NA))
obs=obs%>%filter(Country%in%c(countries, NA))
# Divide data per country for specimens including rows with country as NA
data.per.country.spec=
# lapply(sort(unique(spec$Country)), function(x)
lapply(countries, function(x)
spec[which(spec$Country==x),])
data.per.country.spec.na= # specimens with NAs in the country
list(spec[is.na(spec$Country),])
#full set
data.per.country.spec=c(data.per.country.spec, data.per.country.spec.na)
#names(data.per.country.spec)= c(sort(unique(spec$Country)), "NA_Country")
names(data.per.country.spec)= c(countries, "NA_Country")
# add the country name to those specimens with unknown country based on the project tag
if(nrow(data.per.country.spec$NA_Country)>0){
if(nrow(data.per.country.spec$NA_Country)>1){
data.per.country.spec$NA_Country$Country=
apply(sapply(countries, function(x)
grepl(x, data.per.country.spec$NA_Country$Projects,
ignore.case = T)), MARGIN = 1, function(y)
ifelse(any(y), names(y[y==T]), "NA"))}
if(nrow(data.per.country.spec$NA_Country)==1){
temp=sapply(countries, function(x)
grepl(x, data.per.country.spec$NA_Country$Projects,
ignore.case = T))
data.per.country.spec$NA_Country$Country=
ifelse(any(temp), names(temp[temp==T]), "NA")}
}
# Divide data per country for observations including rows with country as NA
# number sick, dead, heaelthy, observed is numeric
cols.num <- c("observation_number_observed",
"observation_number_healthy",
"observation_number_sick",
"observation_number_dead")
obs[cols.num] <- sapply(obs[cols.num],as.numeric)
data.per.country.obs=
lapply(countries, function(x)
# lapply(sort(unique(obs$Country)), function(x)
obs[which(obs$Country==x),])
data.per.country.obs.na= # specimens with NAs in the country
list(obs[is.na(obs$Country),])
#full set
data.per.country.obs=c(data.per.country.obs, data.per.country.obs.na)
#names(data.per.country.obs)= c(sort(unique(obs$Country)), "NA_Country")
names(data.per.country.obs)= c(countries, "NA_Country")
#add the country name to those events with unknown country based on the project tag
if(nrow(data.per.country.obs$NA_Country)>0){
if(nrow(data.per.country.obs$NA_Country)>1){
data.per.country.obs$NA_Country$Country=
apply(sapply(countries, function(x)
grepl(x, data.per.country.obs$NA_Country$Projects,
ignore.case = T)), MARGIN = 1, function(y)
ifelse(any(y), names(y[y==T]), "NA"))}
if(nrow(data.per.country.obs$NA_Country)==1){
temp=sapply(countries, function(x)
grepl(x, data.per.country.obs$NA_Country$Projects,
ignore.case = T))
data.per.country.obs$NA_Country$Country=
ifelse(any(temp), names(temp[temp==T]), "NA")}
}
data.per.country.spec=data.per.country.spec[sapply(data.per.country.spec, nrow)>0]
```
<!-- ## EVENT CROSS REFERENCE NUMBER -->
```{r checking event cross reference number, echo=FALSE, eval=F}
spec$ev_cross_reference_number
```
## EVENTS
```{r checking events codes, echo=FALSE, eval=F}
# Are there any na's in the event codes
any.nas.event.code.specimen=any(is.na(spec$Event_Code)) # no NAs as it should.
any.nas.event.code.observation=any(is.na(obs$Event_Code)) # no NAs as it should.
if(any.nas.event.code.specimen==F & any.nas.event.code.observation==F){
message("All rows in the observation and specimen sheets have event codes")}else{
message("The observation or specimen sheets have empty event codes")}
# Do all events codes start with "WCS"
event.code.does.not.start.with.WCS.spec=any(!grepl("WCS", spec$Event_Code))
event.code.does.not.start.with.WCS.obs=any(!grepl("WCS", spec$Event_Code))
if(event.code.does.not.start.with.WCS.spec==F & event.code.does.not.start.with.WCS.obs==F){
message("All event codes in the specimen and observation sheets start with WCS")}else{
message("Not all event codes start with WCS.
This could be in the observation or the specimen sheet")}
```
### EVENT DATES
#
##### Are the start dates provided for all the events?
#
#
```{r checking start dates of events, echo=FALSE, warning=FALSE, cache=F, eval=T}
# ----------------------------- #
# ---- START AND END DATES ---- #
# ----------------------------- #
names.countries.obs.spec=sort(unique(c(names(data.per.country.obs),
names(data.per.country.spec))))
# specimens and observations per country
event.codes.per.country=vector(mode = "list",
length = length(names.countries.obs.spec))
names(event.codes.per.country)=names.countries.obs.spec
event.codes.per.country=lapply(names.countries.obs.spec, function(x)
rbind(data.per.country.obs[[x]], data.per.country.spec[[x]]))
names(event.codes.per.country)=names.countries.obs.spec
# events wo the start date
event.codes.start.dates.not.provided.per.country=
lapply(event.codes.per.country, function(x)
x%>%
filter(is.na(Start_date))%>%
dplyr::select(Country,Event_Code)%>%
distinct(Country, Event_Code))
# add the country name to those events with unknown country based on the project tag
if(nrow(event.codes.start.dates.not.provided.per.country$NA_Country)>0){
event.codes.start.dates.not.provided.per.country$NA_Country$Country=
unlist(apply(sapply(countries, function(x)
grepl(x, event.codes.start.dates.not.provided.per.country$NA_Country$Projects,
ignore.case = T)), MARGIN = 1, function(y)
ifelse(all(y==F), "NA_Country", names(y)[which(y)])),
use.names = F)}
# if there are rows with wrong latitude
if(nrow(do.call(rbind, event.codes.start.dates.not.provided.per.country))>0){
event.codes.start.dates.not.provided.per.country=do.call(
rbind, event.codes.start.dates.not.provided.per.country)
# spit the data by country again now including the data of country based on the project tag
# for those rows wo country
event.codes.start.dates.not.provided.per.country=
lapply(sort(unique(event.codes.start.dates.not.provided.per.country$Country)), function(x)
event.codes.start.dates.not.provided.per.country%>%filter(Country==x)%>%
dplyr::select(Country, Event_Code)%>%
distinct(Country, Event_Code))
# name the list
names(event.codes.start.dates.not.provided.per.country)=sapply(
event.codes.start.dates.not.provided.per.country, function(x) unique(x$Country))
# order by event code
event.codes.start.dates.not.provided.per.country=
lapply(event.codes.start.dates.not.provided.per.country, function(x)
x[order(x[,"Event_Code"]), ])
# move to da dataset with the event codes in a single row
event.codes.start.dates.not.provided.per.country.df=
lapply(event.codes.start.dates.not.provided.per.country, function(x)
data.frame(Event_Codes=paste(unique(x$Event_Code), collapse = " ")))
event.codes.start.dates.not.provided.per.country.df=data.frame(
Country=names(event.codes.start.dates.not.provided.per.country.df),
Event_Codes=unlist(event.codes.start.dates.not.provided.per.country.df, use.names = F))
event.codes.start.dates.not.provided.per.country.df=
event.codes.start.dates.not.provided.per.country.df[
event.codes.start.dates.not.provided.per.country.df$Event_Codes!="",]
#delete rownames
rownames(event.codes.start.dates.not.provided.per.country.df)=NULL
# subset to specific country
event.codes.start.dates.not.provided.per.country.df=event.codes.start.dates.not.provided.per.country.df%>%
filter(Country==params$country.of.interest)
if(nrow(event.codes.start.dates.not.provided.per.country.df)>0){
message("No. Not all the events have their start dates are provided. These are the events without start date per country.")
# table
kableExtra::kbl(event.codes.start.dates.not.provided.per.country.df,
caption = "Event codes without the start date per country") %>%
kableExtra::kable_paper(full_width = F) %>%
kableExtra::column_spec(1, bold = T, border_right = T) %>%
kableExtra::column_spec(2, width = "50em")}}
if(!exists("event.codes.start.dates.not.provided.per.country.df") |
exists("event.codes.start.dates.not.provided.per.country.df") && nrow(event.codes.start.dates.not.provided.per.country.df)==0){
event.codes.start.dates.not.provided.per.country=list(data.frame(Country="", Event_Code="" ))
message("Yes, start dates are provided for all events")}
```
#
##### Are the end dates provided for all the events?
#
#
```{r checking end dates of events, echo=FALSE, warning=FALSE, cache=F, eval=T}
# events wo the start date
event.codes.end.dates.not.provided.per.country=
lapply(event.codes.per.country, function(x)
x%>%
filter(is.na(End_date))%>%
dplyr::select(Country,Event_Code)%>%
distinct(Country, Event_Code))
# if there are rows with wrong latitude
if(nrow(do.call(rbind, event.codes.end.dates.not.provided.per.country))>0){
event.codes.end.dates.not.provided.per.country=do.call(
rbind, event.codes.end.dates.not.provided.per.country)
# spit the data by country again now including the data of country based on the project tag
# for those rows wo country
event.codes.end.dates.not.provided.per.country=
lapply(sort(unique(event.codes.end.dates.not.provided.per.country$Country)), function(x)
event.codes.end.dates.not.provided.per.country%>%filter(Country==x)%>%
dplyr::select(Country, Event_Code)%>%
distinct(Country, Event_Code))
# name the list
names(event.codes.end.dates.not.provided.per.country)=sapply(
event.codes.end.dates.not.provided.per.country, function(x) unique(x$Country))
# order by event code
event.codes.end.dates.not.provided.per.country=
lapply(event.codes.end.dates.not.provided.per.country, function(x)
x[order(x[,"Event_Code"]), ])
# move to da dataset with the event codes in a single row
event.codes.end.dates.not.provided.per.country.df=
lapply(event.codes.end.dates.not.provided.per.country, function(x)
data.frame(Event_Codes=paste(unique(x$Event_Code), collapse = " ")))
event.codes.end.dates.not.provided.per.country.df=data.frame(
Country=names(event.codes.end.dates.not.provided.per.country.df),
Event_Codes=unlist(event.codes.end.dates.not.provided.per.country.df, use.names = F))
event.codes.end.dates.not.provided.per.country.df=
event.codes.end.dates.not.provided.per.country.df[
event.codes.end.dates.not.provided.per.country.df$Event_Codes!="",]
#delete rownames
rownames(event.codes.end.dates.not.provided.per.country.df)=NULL
# subset to specific country
event.codes.end.dates.not.provided.per.country.df=event.codes.end.dates.not.provided.per.country.df%>%
filter(Country==params$country.of.interest)
if(nrow(event.codes.end.dates.not.provided.per.country.df)>0){
message("No. Not all the events have their end dates are provided. These are the events without end date per country.")
# table
kableExtra::kbl(event.codes.end.dates.not.provided.per.country.df,
caption = "Event codes without the end date per country") %>%
kableExtra::kable_paper(full_width = F) %>%
kableExtra::column_spec(1, bold = T, border_right = T) %>%
kableExtra::column_spec(2, width = "50em")}}
if(!exists("event.codes.end.dates.not.provided.per.country.df") |
exists("event.codes.end.dates.not.provided.per.country.df") && nrow(event.codes.end.dates.not.provided.per.country.df)==0){
event.codes.end.dates.not.provided.per.country=list(data.frame(Country="", Event_Code="" ))
message("Yes, end dates are provided for all the events")}
```
#
##### Does the interpretation occurs since the event started?
#
#
```{r interpretation dates, echo=FALSE, warning=FALSE, eval=T, cache=F}
event.codes.date.interpretation.earlier.start.date.per.country=
lapply(event.codes.per.country, function(x)
x%>%
filter(!is.na(Interpretation_date))%>%
filter(!(as.Date(Start_date)<=as.Date(Interpretation_date)))%>%
dplyr::select(Country,Event_Code)%>%
distinct(Country, Event_Code))
# if there are rows with wrong latitude
if(nrow(do.call(rbind, event.codes.date.interpretation.earlier.start.date.per.country))>0){
date.interpretation.earlier.start.date.per.country=do.call(
rbind, event.codes.date.interpretation.earlier.start.date.per.country)
# spit the data by country again now including the data of country based on the project tag
# for those rows wo country
date.interpretation.earlier.start.date.per.country=
lapply(sort(unique(date.interpretation.earlier.start.date.per.country$Country)), function(x)
date.interpretation.earlier.start.date.per.country%>%filter(Country==x)%>%
dplyr::select(Country, Event_Code)%>%
distinct(Country, Event_Code))
# name the list
names(date.interpretation.earlier.start.date.per.country)=sapply(
date.interpretation.earlier.start.date.per.country, function(x) unique(x$Country))
# order by event code
date.interpretation.earlier.start.date.per.country=
lapply(date.interpretation.earlier.start.date.per.country, function(x)
x[order(x[,"Event_Code"]), ])
# move to da dataset with the event codes in a single row
event.codes.date.interpretation.earlier.start.date.per.country.df=
lapply(date.interpretation.earlier.start.date.per.country, function(x)
data.frame(Event_Codes=paste(unique(x$Event_Code), collapse = " ")))
event.codes.date.interpretation.earlier.start.date.per.country.df=data.frame(
Country=names(event.codes.date.interpretation.earlier.start.date.per.country.df),
Event_Codes=unlist(event.codes.date.interpretation.earlier.start.date.per.country.df, use.names = F))
event.codes.date.interpretation.earlier.start.date.per.country.df=
event.codes.date.interpretation.earlier.start.date.per.country.df[
event.codes.date.interpretation.earlier.start.date.per.country.df$Event_Codes!="",]
#delete rownames
rownames(event.codes.date.interpretation.earlier.start.date.per.country.df)=NULL
# subset to specific country
event.codes.date.interpretation.earlier.start.date.per.country.df=event.codes.date.interpretation.earlier.start.date.per.country.df%>%filter(Country==params$country.of.interest)
if(nrow(event.codes.date.interpretation.earlier.start.date.per.country.df)>0){
# Show the results
message("No. Not all the interpretations occur since the start date. These are the events with inconsistency between
the interpretation date and the start date")
kableExtra::kbl(event.codes.date.interpretation.earlier.start.date.per.country.df,
caption = "Event codes with inconsistent start date and date of interpretation") %>%
kableExtra::kable_paper(full_width = F) %>%
kableExtra::column_spec(1, bold = T, border_right = T) %>%
kableExtra::column_spec(2, border_right = T, width = "30em")
}}
if(!exists("event.codes.date.interpretation.earlier.start.date.per.country.df") |
exists("event.codes.date.interpretation.earlier.start.date.per.country.df") && nrow(event.codes.date.interpretation.earlier.start.date.per.country.df)==0){
date.interpretation.earlier.start.date.per.country=list(
data.frame(Country="", Event_Code="" ))
rownames(date.interpretation.earlier.start.date.per.country[[1]])<-NULL
message("Yes, all interpretations occur since the corresponding start date")}
```
#
##### Does the interpretation occur since the event ended?
#
#
```{r interpretation dates 2, echo=FALSE, warning=FALSE, eval=T, cache=F}
event.codes.date.interpretation.earlier.end.date.per.country=
lapply(event.codes.per.country, function(x)
x%>%
filter(!is.na(Interpretation_date))%>%
filter(!(as.Date(End_date)<=as.Date(Interpretation_date)))%>%
dplyr::select(Country,Event_Code)%>%
distinct(Country, Event_Code))
# if there are rows with wrong latitude
if(nrow(do.call(rbind, event.codes.date.interpretation.earlier.end.date.per.country))>0){
date.interpretation.earlier.end.date.per.country=do.call(
rbind, event.codes.date.interpretation.earlier.end.date.per.country)
# spit the data by country again now including the data of country based on the project tag
# for those rows wo country
date.interpretation.earlier.end.date.per.country=
lapply(sort(unique(date.interpretation.earlier.end.date.per.country$Country)), function(x)
date.interpretation.earlier.end.date.per.country%>%filter(Country==x)%>%
dplyr::select(Country, Event_Code)%>%
distinct(Country, Event_Code))
# name the list
names(date.interpretation.earlier.end.date.per.country)=sapply(
date.interpretation.earlier.end.date.per.country, function(x) unique(x$Country))
# order by event code
date.interpretation.earlier.end.date.per.country=
lapply(date.interpretation.earlier.end.date.per.country, function(x)
x[order(x[,"Event_Code"]), ])
# move to da dataset with the event codes in a single row
event.codes.date.interpretation.earlier.end.date.per.country.df=
lapply(date.interpretation.earlier.end.date.per.country, function(x)
data.frame(Event_Codes=paste(unique(x$Event_Code), collapse = " ")))
event.codes.date.interpretation.earlier.end.date.per.country.df=data.frame(
Country=names(event.codes.date.interpretation.earlier.end.date.per.country.df),
Event_Codes=unlist(event.codes.date.interpretation.earlier.end.date.per.country.df, use.names = F))
event.codes.date.interpretation.earlier.end.date.per.country.df=
event.codes.date.interpretation.earlier.end.date.per.country.df[
event.codes.date.interpretation.earlier.end.date.per.country.df$Event_Codes!="",]
#delete rownames
rownames(event.codes.date.interpretation.earlier.end.date.per.country.df)=NULL
# subset to specific country
event.codes.date.interpretation.earlier.end.date.per.country.df=
event.codes.date.interpretation.earlier.end.date.per.country.df%>%filter(Country==params$country.of.interest)
if(nrow(event.codes.date.interpretation.earlier.start.date.per.country.df)>0){
message("No. Not all the interpretation dates occur after the end date. These are the events with inconsistency between
the interpretation date and the end date")
kableExtra::kbl(event.codes.date.interpretation.earlier.end.date.per.country.df,
caption = "Event codes with inconsistent end date and date of interpretation") %>%
kableExtra::kable_paper(full_width = F) %>%
kableExtra::column_spec(1, bold = T, border_right = T) %>%
kableExtra::column_spec(2, border_right = T, width = "30em")
}}
if(!exists("event.codes.date.interpretation.earlier.end.date.per.country.df") |
exists("event.codes.date.interpretation.earlier.end.date.per.country.df") && nrow(event.codes.date.interpretation.earlier.end.date.per.country.df)==0){
date.interpretation.earlier.end.date.per.country=list(
data.frame(Country="", Event_Code="" ))
rownames(date.interpretation.earlier.end.date.per.country[[1]])<-NULL
message("Yes, all interpretation dates occur after the corresponding end date")}
```
### COUNTRY OF THE EVENTS
#
##### Is the country provided for all the events?
#
#
```{r country of the events, echo=FALSE, warning=FALSE, eval=T, cache=F}
# this apply for event.codes.per.country$NA_Country$Projects
if(nrow(event.codes.per.country$NA_Country)>0){
# list per county when the country can be extracted from the project tags
event.codes.wo.country.per.country=
lapply(
sort(unique(event.codes.per.country$NA_Country$Country)), function(x)
event.codes.per.country$NA_Country%>%filter(Country==x)%>%
dplyr::select(Country,Event_Code)%>%
distinct(Country, Event_Code))
# name the list
names(event.codes.wo.country.per.country)=sapply(
event.codes.wo.country.per.country, function(x) unique(x$Country))
# order by event code
event.codes.wo.country.per.country=
lapply(event.codes.wo.country.per.country, function(x)
x[order(x[,"Event_Code"]), ])
# move to da dataset with the event codes in a single row
event.codes.wo.country.per.country.df=
lapply(event.codes.wo.country.per.country, function(x)
data.frame(Event_Codes=paste(unique(x$Event_Code), collapse = " ")))
event.codes.wo.country.per.country.df=data.frame(
Country=names(event.codes.wo.country.per.country.df),
Event_Codes=unlist(event.codes.wo.country.per.country.df, use.names = F))
event.codes.wo.country.per.country.df=
event.codes.wo.country.per.country.df[
event.codes.wo.country.per.country.df$Event_Codes!="",]
#delete rownames
rownames(event.codes.wo.country.per.country.df)=NULL
# subset to specific country
event.codes.wo.country.per.country.df=
event.codes.wo.country.per.country.df%>%filter(Country==params$country.of.interest)
if(nrow(event.codes.wo.country.per.country.df)>0){
# Show the results
message("No. Not all events have the country provided.
These are the Events without country per country.
The country is provided based on the project tag")
kableExtra::kbl(event.codes.wo.country.per.country.df,
caption = "Event codes without country per country. Country based on project tag") %>%
kableExtra::kable_paper(full_width = F) %>%
kableExtra::column_spec(1, bold = T, border_right = T) %>%
kableExtra::column_spec(2, width = "30em")
}}
if(!exists("event.codes.wo.country.per.country.df") |
exists("event.codes.wo.country.per.country.df") && nrow(event.codes.wo.country.per.country.df)==0){
message("Yes, all the events have the country assigned")
event.codes.wo.country.per.country=list(data.frame(
Country="",
Event_Code=""))
rownames(event.codes.wo.country.per.country[[1]])<-NULL
}
```
#
##### Does the country, when provided, exist? Or is it a bogus random word?
#
#
```{r check countries, echo=FALSE, warning=FALSE, eval=T, cache=F}
# events.countries.provided=
event.codes.per.country.temp=event.codes.per.country
event.codes.per.country.temp[["NA_Country"]] <- NULL # remove observations wo country
event.codes.countries.provided=
do.call(rbind, event.codes.per.country.temp)
# dplyr::select those rows with bogus countries
events.countries.provided.bogus=
event.codes.countries.provided[
!(event.codes.countries.provided$Country%in%countries),]
# create a list with the codes of he events that do have country but is bogus.
# The country is based on the project tag field
# add the country name to those events with unknown country based on the project tag
if(nrow(events.countries.provided.bogus)>0){
# split the data by country
events.countries.provided.bogus.per.country=
lapply(sort(unique(events.countries.provided.bogus$Country)), function(x)
events.countries.provided.bogus%>%filter(Country==x)%>%
dplyr::select(Country, Event_Code)%>%
distinct(Country, Event_Code))
# name the list
names(events.countries.provided.bogus.per.country)=sapply(
events.countries.provided.bogus.per.country, function(x) unique(x$Country))
# order by event code
events.countries.provided.bogus.per.country=
lapply(events.countries.provided.bogus.per.country, function(x)
x[order(x[,"Event_Code"]), ])
# move to da dataset with the event codes in a single row
events.countries.provided.bogus.per.country.df=
lapply(events.countries.provided.bogus.per.country, function(x)
data.frame(Event_Codes=paste(unique(x$Event_Code), collapse = " ")))
events.countries.provided.bogus.per.country.df=data.frame(
Country=names(events.countries.provided.bogus.per.country.df),
Event_Codes=unlist(events.countries.provided.bogus.per.country.df, use.names = F))
events.countries.provided.bogus.per.country.df=
events.countries.provided.bogus.per.country.df[
events.countries.provided.bogus.per.country.df$Event_Codes!="",]
#delete rownames
rownames(events.countries.provided.bogus.per.country.df)=NULL
# subset to specific country
events.countries.provided.bogus.per.country.df=
events.countries.provided.bogus.per.country.df%>%filter(Country==params$country.of.interest)
if(nrow(events.countries.provided.bogus.per.country.df)>0){
# Show the results
message("No. Not all the countries provided are acceptable. These are the events without a proper country per country. The country provided is based on the project tag")
kableExtra::kbl(events.countries.provided.bogus.per.country.df,
caption = "Event codes with incorrect country per country. The country is based on the project tag") %>%
kableExtra::kable_paper(full_width = F) %>%
kableExtra::column_spec(1, bold = T, border_right = T) %>%
kableExtra::column_spec(2, width = "30em")
}}
if(!exists("events.countries.provided.bogus.per.country.df") |
exists("events.countries.provided.bogus.per.country.df") && nrow(events.countries.provided.bogus.per.country.df)==0){
event.codes.bogus.country.per.country=list(data.frame(Country="", Event_Code=""))
rownames(event.codes.bogus.country.per.country[[1]])<-NULL
message("Yes, all the countries provided are appropriate")}
```
### LATITUDE AND LONGITUDE OF THE EVENTS
##### Are the latitude and longitude coordinates of the events feasible using decimal degress?
#
##### Latitude
#
#
```{r check latitude, echo=FALSE, warning=FALSE, eval=T, cache=F}
# based on the project tag, find the country of those events wo country
for(i in 1:length(event.codes.per.country)){
event.codes.per.country[[i]]$Latitude=
as.numeric(event.codes.per.country[[i]]$Latitude)}
event.codes.wrong.lat.per.country=
lapply(event.codes.per.country, function(x)
x%>%filter(Latitude>90 | Latitude<(-90))%>%
dplyr::select(Country,Event_Code, Projects)%>%
distinct(Country,Event_Code, Projects))
# if there are rows with wrong latitude
if(nrow(do.call(rbind, event.codes.wrong.lat.per.country))>0){
event.codes.wrong.lat.per.country=do.call(rbind, event.codes.wrong.lat.per.country)
# spit the data by country again now including the data of country based on the project tag
# for those rows wo country
event.codes.wrong.lat.per.country=
lapply(sort(unique(event.codes.wrong.lat.per.country$Country)), function(x)
event.codes.wrong.lat.per.country%>%filter(Country==x)%>%
dplyr::select(Country, Event_Code)%>%
distinct(Country, Event_Code))
# name the list
names(event.codes.wrong.lat.per.country)=sapply(
event.codes.wrong.lat.per.country, function(x) unique(x$Country))
# order by event code
event.codes.wrong.lat.per.country=
lapply(event.codes.wrong.lat.per.country, function(x)
x[order(x[,"Event_Code"]), ])
# move to da dataset with the event codes in a single row
event.codes.wrong.lat.per.country.df=
lapply(event.codes.wrong.lat.per.country, function(x)
data.frame(Event_Codes=paste(unique(x$Event_Code), collapse = " ")))
event.codes.wrong.lat.per.country.df=data.frame(
Country=names(event.codes.wrong.lat.per.country.df),
Event_Codes=unlist(event.codes.wrong.lat.per.country.df, use.names = F))
event.codes.wrong.lat.per.country.df=
event.codes.wrong.lat.per.country.df[event.codes.wrong.lat.per.country.df$Event_Codes!="",]
#delete rownames
rownames(event.codes.wrong.lat.per.country.df)=NULL
# subset to specific country
event.codes.wrong.lat.per.country.df=
event.codes.wrong.lat.per.country.df%>%filter(Country==params$country.of.interest)
if(nrow(event.codes.wrong.lat.per.country.df)>0){
# Show the results
message("No. Not all the latitudes values reported are feasible These are the events with impossible latitude values
(in decimal degrees) per country.")
kableExtra::kbl(event.codes.wrong.lat.per.country.df,
caption = "Event codes with implausible latitude values (in decimal degrees) per country") %>%
kableExtra::kable_paper(full_width = F) %>%
kableExtra::column_spec(1, bold = T, border_right = T) %>%
kableExtra::column_spec(2, width = "30em")
}}
if(!exists("event.codes.wrong.lat.per.country.df") |
exists("event.codes.wrong.lat.per.country.df") && nrow(event.codes.wrong.lat.per.country.df)==0){
event.codes.wrong.lat.per.country=list(data.frame(Country="", Event_Code=""))
rownames(event.codes.wrong.lat.per.country[[1]])<-NULL
message("Yes, all the latitude values reported are feasible (in decimal degrees)")}
```
#
##### Longitude
#
#
```{r check Longitude, echo=FALSE, warning=FALSE, eval=T, cache=F}
for(i in 1:length(event.codes.per.country)){
event.codes.per.country[[i]]$Longitude=
as.numeric(event.codes.per.country[[i]]$Longitude)}
event.codes.wrong.lon.per.country=
lapply(event.codes.per.country, function(x)
x%>%filter(Longitude>180 | Longitude<(-180))%>%
dplyr::select(Country,Event_Code, Projects)%>%
distinct(Country,Event_Code, Projects))
# if there are rows with wrong latitude
if(nrow(do.call(rbind, event.codes.wrong.lon.per.country))>0){
event.codes.wrong.lon.per.country=
do.call(rbind, event.codes.wrong.lon.per.country)
# spit the data by country again now including the data of country based on the project tag
# for those rows wo country
event.codes.wrong.lon.per.country=
lapply(sort(unique(event.codes.wrong.lon.per.country$Country)), function(x)
event.codes.wrong.lon.per.country%>%filter(Country==x)%>%
dplyr::select(Country, Event_Code)%>%
distinct(Country, Event_Code))
# name the list
names(event.codes.wrong.lon.per.country)=sapply(
event.codes.wrong.lon.per.country, function(x) unique(x$Country))
# order by event code
event.codes.wrong.lon.per.country=
lapply(event.codes.wrong.lon.per.country, function(x)
x[order(x[,"Event_Code"]), ])
# move to da dataset with the event codes in a single row
event.codes.wrong.lon.per.country.df=
lapply(event.codes.wrong.lon.per.country, function(x)
data.frame(Event_Codes=paste(unique(x$Event_Code), collapse = " ")))
event.codes.wrong.lon.per.country.df=data.frame(
Country=names(event.codes.wrong.lon.per.country.df),
Event_Codes=unlist(event.codes.wrong.lon.per.country.df, use.names = F))
event.codes.wrong.lon.per.country.df=
event.codes.wrong.lon.per.country.df[event.codes.wrong.lon.per.country.df$Event_Codes!="",]
#delete rownames
rownames(event.codes.wrong.lon.per.country.df)=NULL
# subset to specific country
event.codes.wrong.lon.per.country.df=
event.codes.wrong.lon.per.country.df%>%filter(Country==params$country.of.interest)
if(nrow(event.codes.wrong.lon.per.country.df)>0){
# Show the results
message("No. Not all the longitude values reported are feasible These are the events with impossible longitude values
(in decimal degrees) per country.")
kableExtra::kbl(event.codes.wrong.lon.per.country.df,
caption = "Event codes with implausible longitude values (in decimal degrees) per country") %>% kableExtra::kable_paper(full_width = F) %>%
kableExtra::column_spec(1, bold = T, border_right = T) %>%
kableExtra::column_spec(2, width = "30em")
}}
if(!exists("event.codes.wrong.lon.per.country.df") |
exists("event.codes.wrong.lon.per.country.df") && nrow(event.codes.wrong.lon.per.country.df)==0){
event.codes.wrong.lon.per.country=list(data.frame(Country="", Event_Code=""))
rownames(event.codes.wrong.lon.per.country[[1]])<-NULL
message("Yes, all the longitude values reported are feasible (in decimal degrees)")}
```
#
### HISTORY
#
##### Is the history of the events reported in WHIP?
#
```{r history, echo=FALSE, warning=FALSE, eval=T, cache=FALSE}
event.history.not.reported.per.country.spec=
lapply(data.per.country.spec, function(x)
x%>%filter(is.na(History))%>%dplyr::select(Country, Event_Code, History)%>%distinct())
event.history.not.reported.per.country.obs=
lapply(data.per.country.obs, function(x)
x%>%filter(is.na(History))%>%dplyr::select(Country, Event_Code, History)%>%distinct())
event.history.not.reported.per.country=
lapply(sort(unique(unlist(c(unique(do.call(rbind, event.history.not.reported.per.country.spec)[,"Country"]),
unique(do.call(rbind, event.history.not.reported.per.country.obs)[,"Country"]))))), #getting the unique countries in obs and spec
function(x)
rbind(do.call(rbind, event.history.not.reported.per.country.spec),
do.call(rbind, event.history.not.reported.per.country.obs))%>%filter(Country==x))
event.history.not.reported.per.country=do.call(rbind,event.history.not.reported.per.country)
if(!is.null(event.history.not.reported.per.country)){
# if there are rows with wrong latitude
if(nrow(do.call(rbind,event.history.not.reported.per.country))>0){
event.history.not.reported.per.country=do.call(
rbind, event.history.not.reported.per.country)%>%
dplyr::select(Country, Event_Code)
# spit the data by country again now including the data of country based on the project tag
# for those rows wo country
event.history.not.reported.per.country=
lapply(sort(unique(event.history.not.reported.per.country$Country)), function(x)
event.history.not.reported.per.country%>%filter(Country==x)%>%
dplyr::select(Country, Event_Code)%>%
distinct(Country, Event_Code))
# name the list
names(event.history.not.reported.per.country)=sapply(
event.history.not.reported.per.country, function(x) unique(x$Country))
# order by specimen code
event.history.not.reported.per.country=
lapply(event.history.not.reported.per.country, function(x)
x[order(x[,"Event_Code"]), ])
# move to da dataset with the event codes in a single row