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process_wqx_downloads.Rmd
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process_wqx_downloads.Rmd
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---
title: "Datacleaningcode"
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
```{r setup}
library(tidyverse)
non_numerics <- function(data=data_temp) {
return(data %>% filter(is.na(as.numeric(ResultMeasureValue))) %>%
select(ResultMeasureValue,
DetectionQuantitationLimitMeasure.MeasureValue,
ResultMeasure.MeasureUnitCode,
DetectionQuantitationLimitMeasure.MeasureUnitCode,
ResultDetectionConditionText,
ActivityBottomDepthHeightMeasure.MeasureValue,
ActivityBottomDepthHeightMeasure.MeasureUnitCode,Obs_Id) %>%
drop_na(ResultMeasureValue))
}
`%notin%` <- Negate(`%in%`)
#here are functions
#for temperature
# resultconvert_celsius<-function(dat, variable, unit, out_unit) {
# dat$ResultMeasureValue[which(dat$CharacteristicName == variable & dat$ResultMeasure.MeasureUnitCode == unit)] <- (dat$ResultMeasureValue[which(dat$CharacteristicName == variable & dat$ResultMeasure.MeasureUnitCode == unit)] -32)* 5/9
#
# dat$ResultMeasure.MeasureUnitCode[which(dat$CharacteristicName == variable & dat$ResultMeasure.MeasureUnitCode == unit)] <- out_unit
#
# return(dat)
#
# }
#
#
# detectconvert_celsius<-function(dat, variable, unit, out_unit) {
# dat$DetectionQuantitationLimitMeasure.MeasureValue[which(dat$CharacteristicName == variable & dat$DetectionQuantitationLimitMeasure.MeasureUnitCode == unit)] <- (dat$DetectionQuantitationLimitMeasure.MeasureValue[which(dat$CharacteristicName == variable & dat$DetectionQuantitationLimitMeasure.MeasureUnitCode == unit)] * -32)*5/9
#
# dat$DetectionQuantitationLimitMeasure.MeasureUnitCode[which(dat$CharacteristicName == variable & dat$DetectionQuantitationLimitMeasure.MeasureUnitCode == unit)] <- out_unit
#
# return(dat)
#
# }
#
# #for all other conversions
#
# resultconvert<-function(dat, variable, unit, out_unit, conv_factor) {
# dat$ResultMeasureValue[which(dat$CharacteristicName == variable & dat$ResultMeasure.MeasureUnitCode == unit)] <- dat$ResultMeasureValue[which(dat$CharacteristicName == variable & dat$ResultMeasure.MeasureUnitCode == unit)] * conv_factor
#
# dat$ResultMeasure.MeasureUnitCode[which(dat$CharacteristicName == variable & dat$ResultMeasure.MeasureUnitCode == unit)] <- out_unit
#
# return(dat)
#
# }
#
#
# detectconvert<-function(dat, variable, unit, out_unit, conv_factor) {
# dat$DetectionQuantitationLimitMeasure.MeasureValue[which(dat$CharacteristicName == variable & dat$DetectionQuantitationLimitMeasure.MeasureUnitCode == unit)] <- dat$DetectionQuantitationLimitMeasure.MeasureValue[which(dat$CharacteristicName == variable & dat$DetectionQuantitationLimitMeasure.MeasureUnitCode == unit)] * conv_factor
#
# dat$DetectionQuantitationLimitMeasure.MeasureUnitCode[which(dat$CharacteristicName == variable & dat$DetectionQuantitationLimitMeasure.MeasureUnitCode == unit)] <- out_unit
#
# return(dat)
#
# }
```
```{r noah-read}
file.path <- "~/Lottig Dropbox/Noah Lottig/CL_LAGOSUS_exports/LAGOSUS_LIMNO/US_NEW/raw_data/" #Noah
```
```{r kait-read}
file.path <-"" #kait
```
```{r arnab-read}
file.path <-"~/Lagos Limno/" #arnab
```
```{r read-files}
read.csv("list of unique parameters to remove.csv") -> remove_params #update this
#NE STATES PULL
CTdatPull<-read.csv(paste0(file.path,"CT_cleaned.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
CTdatPull$State<-c("CT")
CTdatPull$Id_num<-c(seq(1:nrow(CTdatPull)))
CTdatPull <- CTdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(CTdatPull)
summary(CTdatPull)
IAdatPull<-read.csv(paste0(file.path,"IA_cleaned.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
IAdatPull$State<-c("IA")
IAdatPull$Id_num<-c(seq(1:nrow(IAdatPull)))
IAdatPull <- IAdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(IAdatPull)
summary(IAdatPull)
ILdatPull<-read.csv(paste0(file.path,"IL_cleaned.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
ILdatPull$State<-c("IL")
ILdatPull$Id_num<-c(seq(1:nrow(ILdatPull)))
ILdatPull <- ILdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(ILdatPull)
summary(ILdatPull)
INdatPull<-read.csv(paste0(file.path,"IN_cleaned.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
INdatPull$State<-c("IN")
INdatPull$Id_num<-c(seq(1:nrow(INdatPull)))
INdatPull <- INdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(INdatPull)
summary(INdatPull)
MAdatPull<-read.csv(paste0(file.path,"MA_cleaned.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
MAdatPull$State<-c("MA")
MAdatPull$Id_num<-c(seq(1:nrow(MAdatPull)))
MAdatPull <- MAdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(MAdatPull)
summary(MAdatPull)
MEdatPull<-read.csv(paste0(file.path,"ME_cleaned.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
MEdatPull$State<-c("ME")
MEdatPull$Id_num<-c(seq(1:nrow(MEdatPull)))
MEdatPull <- MEdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(MEdatPull)
summary(MEdatPull)
MIdatPull<-read.csv(paste0(file.path,"MI_cleaned.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
MIdatPull$State<-c("MI")
MIdatPull$Id_num<-c(seq(1:nrow(MIdatPull)))
MIdatPull <- MIdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(MIdatPull)
summary(MIdatPull)
MNdatPull<-read.csv(paste0(file.path,"MN_cleaned.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
MNdatPull$State<-c("MN")
MNdatPull$Id_num<-c(seq(1:nrow(MNdatPull)))
MNdatPull <- MNdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(MNdatPull)
summary(MNdatPull)
MOdatPull<-read.csv(paste0(file.path,"MO_cleaned.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
MOdatPull$State<-c("MO")
MOdatPull$Id_num<-c(seq(1:nrow(MOdatPull)))
MOdatPull <- MOdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(MOdatPull)
summary(MOdatPull)
NHdatPull<-read.csv(paste0(file.path,"NH_cleaned.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
NHdatPull$State<-c("NH")
NHdatPull$Id_num<-c(seq(1:nrow(NHdatPull)))
NHdatPull <- NHdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(NHdatPull)
summary(NHdatPull)
NJdatPull<-read.csv(paste0(file.path,"NJ_cleaned.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
NJdatPull$State<-c("NJ")
NJdatPull$Id_num<-c(seq(1:nrow(NJdatPull)))
NJdatPull <- NJdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(NJdatPull)
summary(NJdatPull)
NYdatPull<-read.csv(paste0(file.path,"NY_cleaned.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
NYdatPull$State<-c("NY")
NYdatPull$Id_num<-c(seq(1:nrow(NYdatPull)))
NYdatPull <- NYdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(NYdatPull)
summary(NYdatPull)
OHdatPull<-read.csv(paste0(file.path,"OH_cleaned.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
OHdatPull$State<-c("OH")
OHdatPull$Id_num<-c(seq(1:nrow(OHdatPull)))
OHdatPull <- OHdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(OHdatPull)
summary(OHdatPull)
PAdatPull<-read.csv(paste0(file.path,"PA_cleaned.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
PAdatPull$State<-c("PA")
PAdatPull$Id_num<-c(seq(1:nrow(PAdatPull)))
PAdatPull <- PAdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(PAdatPull)
summary(PAdatPull)
RIdatPull<-read.csv(paste0(file.path,"RI_cleaned.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
RIdatPull$State<-c("RI")
RIdatPull$Id_num<-c(seq(1:nrow(RIdatPull)))
RIdatPull <- RIdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(RIdatPull)
summary(RIdatPull)
VTdatPull<-read.csv(paste0(file.path,"VT_cleaned.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
VTdatPull$State<-c("VT")
VTdatPull$Id_num<-c(seq(1:nrow(VTdatPull)))
VTdatPull <- VTdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(VTdatPull)
summary(VTdatPull)
WIdatPull<-read.csv(paste0(file.path,"WI_cleaned.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
WIdatPull$State<-c("WI")
WIdatPull$Id_num<-c(seq(1:nrow(WIdatPull)))
WIdatPull <- WIdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(WIdatPull)
summary(WIdatPull)
#LAGOSUS STATES PULL
IDdatPull<-read.csv(paste0(file.path,"ID_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
IDdatPull$State<-c("ID")
IDdatPull$Id_num<-c(seq(1:nrow(IDdatPull)))
IDdatPull <- IDdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(IDdatPull)
summary(IDdatPull)
DEdatPull<-read.csv(paste0(file.path,"DE_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
DEdatPull$State<-c("DE")
DEdatPull$Id_num<-c(seq(1:nrow(DEdatPull)))
DEdatPull <- DEdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(DEdatPull)
summary(DEdatPull)
MDdatPull<-read.csv(paste0(file.path,"MD_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
MDdatPull$State<-c("MD")
MDdatPull$Id_num<-c(seq(1:nrow(MDdatPull)))
MDdatPull <- MDdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(MDdatPull)
summary(MDdatPull)
VAdatPull<-read.csv(paste0(file.path,"VA_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
VAdatPull$State<-c("VA")
VAdatPull$Id_num<-c(seq(1:nrow(VAdatPull)))
VAdatPull <- VAdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(VAdatPull)
summary(VAdatPull)
COdatPull<-read.csv(paste0(file.path,"CO_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
COdatPull$State<-c("CO")
COdatPull$Id_num<-c(seq(1:nrow(COdatPull)))
COdatPull <- COdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(COdatPull)
summary(COdatPull)
AZdatPull<-read.csv(paste0(file.path,"AZ_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
AZdatPull$State<-c("AZ")
AZdatPull$Id_num<-c(seq(1:nrow(AZdatPull)))
AZdatPull <- AZdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(AZdatPull)
summary(AZdatPull)
ARdatPull<-read.csv(paste0(file.path,"AR_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
ARdatPull$State<-c("AR")
ARdatPull$Id_num<-c(seq(1:nrow(ARdatPull)))
ARdatPull <- ARdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(ARdatPull)
summary(ARdatPull)
ALdatPull<-read.csv(paste0(file.path,"AL_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
ALdatPull$State<-c("AL")
ALdatPull$Id_num<-c(seq(1:nrow(ALdatPull)))
ALdatPull <- ALdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(ALdatPull)
summary(ALdatPull)
WYdatPull<-read.csv(paste0(file.path,"WY_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
WYdatPull$State<-c("WY")
WYdatPull$Id_num<-c(seq(1:nrow(WYdatPull)))
WYdatPull <- WYdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(WYdatPull)
summary(WYdatPull)
KYdatPull<-read.csv(paste0(file.path,"KY_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
KYdatPull$State<-c("KY")
KYdatPull$Id_num<-c(seq(1:nrow(KYdatPull)))
KYdatPull <- KYdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(KYdatPull)
summary(KYdatPull)
NVdatPull<-read.csv(paste0(file.path,"NV_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
NVdatPull$State<-c("NV")
NVdatPull$Id_num<-c(seq(1:nrow(NVdatPull)))
NVdatPull <- NVdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(NVdatPull)
summary(NVdatPull)
OKdatPull<-read.csv(paste0(file.path,"OK_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
OKdatPull$State<-c("OK")
OKdatPull$Id_num<-c(seq(1:nrow(OKdatPull)))
OKdatPull <- OKdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(OKdatPull)
summary(OKdatPull)
WAdatPull<-read.csv(paste0(file.path,"WA_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
WAdatPull$State<-c("WA")
WAdatPull$Id_num<-c(seq(1:nrow(WAdatPull)))
WAdatPull <- WAdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(WAdatPull)
summary(WAdatPull)
KSdatPull<-read.csv(paste0(file.path,"KS_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
KSdatPull$State<-c("KS")
KSdatPull$Id_num<-c(seq(1:nrow(KSdatPull)))
KSdatPull <- KSdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(KSdatPull)
summary(KSdatPull)
TNdatPull<-read.csv(paste0(file.path,"TN_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
TNdatPull$State<-c("TN")
TNdatPull$Id_num<-c(seq(1:nrow(TNdatPull)))
TNdatPull <- TNdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(TNdatPull)
summary(TNdatPull)
CAdatPull<-read.csv(paste0(file.path,"CA_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
CAdatPull$State<-c("CA")
CAdatPull$Id_num<-c(seq(1:nrow(CAdatPull)))
CAdatPull <- CAdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(CAdatPull)
summary(CAdatPull)
FLdatPull<-read.csv(paste0(file.path,"FL_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
FLdatPull$State<-c("FL")
FLdatPull$Id_num<-c(seq(1:nrow(FLdatPull)))
FLdatPull <- FLdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(FLdatPull)
summary(FLdatPull)
GAdatPull<-read.csv(paste0(file.path,"GA_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
GAdatPull$State<-c("GA")
GAdatPull$Id_num<-c(seq(1:nrow(GAdatPull)))
GAdatPull <- GAdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(GAdatPull)
summary(GAdatPull)
LAdatPull<-read.csv(paste0(file.path,"LA_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
LAdatPull$State<-c("LA")
LAdatPull$Id_num<-c(seq(1:nrow(LAdatPull)))
LAdatPull <- LAdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(LAdatPull)
summary(LAdatPull)
MSdatPull<-read.csv(paste0(file.path,"MS_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
MSdatPull$State<-c("MS")
MSdatPull$Id_num<-c(seq(1:nrow(MSdatPull)))
MSdatPull <- MSdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(MSdatPull)
summary(MSdatPull)
MTdatPull<-read.csv(paste0(file.path,"MT_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
MTdatPull$State<-c("MT")
MTdatPull$Id_num<-c(seq(1:nrow(MTdatPull)))
MTdatPull <- MTdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(MTdatPull)
summary(MTdatPull)
NEdatPull<-read.csv(paste0(file.path,"NE_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
NEdatPull$State<-c("NE")
NEdatPull$Id_num<-c(seq(1:nrow(NEdatPull)))
NEdatPull <- NEdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(NEdatPull)
summary(NEdatPull)
NMdatPull<-read.csv(paste0(file.path,"NM_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
NMdatPull$State<-c("NM")
NMdatPull$Id_num<-c(seq(1:nrow(NMdatPull)))
NMdatPull <- NMdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(NMdatPull)
summary(NMdatPull)
NCdatPull<-read.csv(paste0(file.path,"NC_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
NCdatPull$State<-c("NC")
NCdatPull$Id_num<-c(seq(1:nrow(NCdatPull)))
NCdatPull <- NCdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(NCdatPull)
summary(NCdatPull)
NDdatPull<-read.csv(paste0(file.path,"ND_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
NDdatPull$State<-c("ND")
NDdatPull$Id_num<-c(seq(1:nrow(NDdatPull)))
NDdatPull <- NDdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(NDdatPull)
summary(NDdatPull)
ORdatPull<-read.csv(paste0(file.path,"OR_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
ORdatPull$State<-c("OR")
ORdatPull$Id_num<-c(seq(1:nrow(ORdatPull)))
ORdatPull <- ORdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(ORdatPull)
summary(ORdatPull)
SCdatPull<-read.csv(paste0(file.path,"SC_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
SCdatPull$State<-c("SC")
SCdatPull$Id_num<-c(seq(1:nrow(SCdatPull)))
SCdatPull <- SCdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(SCdatPull)
summary(SCdatPull)
SDdatPull<-read.csv(paste0(file.path,"SD_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
SDdatPull$State<-c("SD")
SDdatPull$Id_num<-c(seq(1:nrow(SDdatPull)))
SDdatPull <- SDdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(SDdatPull)
summary(SDdatPull)
TXdatPull<-read.csv(paste0(file.path,"TX_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
TXdatPull$State<-c("TX")
TXdatPull$Id_num<-c(seq(1:nrow(TXdatPull)))
TXdatPull <- TXdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(TXdatPull)
summary(TXdatPull)
UTdatPull<-read.csv(paste0(file.path,"UT_alldata_1975_to_2020.csv")) %>% filter(!CharacteristicName %in% remove_params$Unique.parameters)
UTdatPull$State<-c("UT")
UTdatPull$Id_num<-c(seq(1:nrow(UTdatPull)))
UTdatPull <- UTdatPull %>%
unite('Obs_Id', c(State, Id_num), sep = "-", remove = FALSE)
names(UTdatPull)
summary(UTdatPull)
```
```{r}
allstates <- do.call("rbind", lapply(ls(pattern='datPull'),get))
allstates<-allstates %>% select(-ActivityStartTime.TimeZoneCode, -ActivityEndTime.Time, -ActivityEndTime.TimeZoneCode, -HydrologicCondition, -HydrologicEvent, -LaboratoryName, -AnalysisStartDate, -PreparationStartDate)
allstates<-allstates %>% select(-ActivityEndDate, -ResultTimeBasisText, -ResultParticleSizeBasisText, -ActivityStartDateTime, -ActivityEndDateTime)
#figure out how to autodelete files that contain datpull
merge1 <- allstates %>% group_by(State) %>% summarize(n=n())
rm(list=ls(pattern="datPull"))
```
```{r}
#removing data that have Y's instead of keeping data that have N's
read.csv("list of unique parameters to remove.csv") -> remove_params #update this
data<- allstates[allstates$CharacteristicName %notin% remove_params$Unique.parameters,]
rm(allstates)
gc()
merge2 <- data %>% group_by(State) %>% summarize(n=n())
data$ActivityStartDate<-lubridate:::ymd(data$ActivityStartDate)
data<-data %>% filter(ActivityStartDate >= lubridate:::ymd ("1975-01-01")) %>% filter(ActivityStartDate <= lubridate:::ymd("2020-11-20"))
write.csv(unique(data$CharacteristicName), file = "unique_characteristicnames.csv")
```
```{r}
data <- data %>%
unite('Method_Id', c(ResultAnalyticalMethod.MethodIdentifierContext, ResultAnalyticalMethod.MethodIdentifier), sep = " ", remove = FALSE)
data<-data %>% select(-ResultAnalyticalMethod.MethodIdentifierContext, -ResultAnalyticalMethod.MethodIdentifier)
#get only locations that have a lagoslakeid
lagos_link <- read_csv("lagos_wqp_20210920.csv") %>%
rename(MonitoringLocationIdentifier = wqp_monitoringlocationidentifier)
data <- data %>% left_join(lagos_link) %>% drop_na(lagoslakeid)
merge2 = data %>% group_by(State) %>% summarize(n=n())
rm(allstates)
rm(lagos_link)
gc()
str(data$ResultMeasureValue)
sum(is.na(data$ResultMeasureValue))
data1<-data %>% filter(!is.na(ResultMeasureValue))
data2<-data %>% filter(!is.na(DetectionQuantitationLimitMeasure.MeasureValue)) %>% filter(is.na(ResultMeasureValue))
data<-rbind(data1, data2)
rm(data1, data2)
gc()
```
```{r Check-for-Activity-type}
#looking at activity type codes #getting rid of quality control vars
unique(data$ActivityTypeCode)
remove_activity <- unique(data$ActivityTypeCode)
activitytype_keep<-c(
"Quality Control Sample-Field Replicate",
"Quality Control Sample-Field Blank",
"Quality Control Field Replicate Msr/Obs",
"Quality Control Field Replicate Portable Data Logger",
"Quality Control Sample-Reference Sample",
"Quality Control Sample-Field Spike",
"Quality Control Sample-Lab Matrix Spike",
"Quality Control Field Sample Equipment Rinsate Blank",
"Quality Control Sample-Spike Solution",
"Quality Control Sample-Measurement Precision Sample",
"Quality Control Sample-Other",
"Quality Control Sample-Equipment Blank",
"Quality Control Sample-Inter-lab Split",
"Quality Control Sample-Lab Spike",
"Quality Control Sample-Lab Matrix Spike Duplicate",
"Quality Control Sample-Lab Duplicate",
"Quality Control Sample-Blind Duplicate",
"Quality Control Sample-Trip Blank",
"Quality Control Alternative Measurement Sensitivity Plus",
"Quality Control Sample-Lab Blank",
"Quality Control Alternative Measurement Sensitivity Plus",
"Quality Control Sample-Lab Blank",
"Quality Control Sample-Blind",
"Quality Control Sample-Reagent Blank"
)
remove_activity <- remove_activity[!remove_activity %in% activitytype_keep]
remove_activity
data<-data[which(data$ActivityTypeCode %notin% activitytype_keep),]
unique(data$ActivityTypeCode)
gc()
```
```{r }
#manually checking these columns to see if these is data we keep or can drop
unique(data$SubjectTaxonomicName) #expected it to be na - to make sure nothing we need is in there
data<-data %>% filter(is.na(SubjectTaxonomicName))
unique(data$SampleTissueAnatomyName) #also NA's - expected
unique(data$ActivityMediaSubdivisionName)
subdivision_remove<-c("Groundwater",
"Elutriation",
"Wastewater Treatment Plant Effluent",
"Interstitial",
"Interstitial Water",
"Surface Soil/Sediment",
"Soil moisture",
"Landfill effluent",
"Bulk deposition",
"Surface Water Sediment",
"Wet Fall Material",
"Stormwater"
)
data<-data %>% filter(!ActivityMediaSubdivisionName %in% subdivision_remove)
unique(data$ActivityMediaSubdivisionName)
rm(subdivision_remove)
#only keeping subdivision name with surface water and NA's - dropping everything else
#want to filter things out that are non-ambigouous - keep unknowns - eg. filter out tissue but keep uncertain data
#data<-data %>% filter(ActivityMediaSubdivisionName == "Surface Water" | is.na(ActivityMediaSubdivisionName))
#unique(data$ActivityMediaSubdivisionName)
unique(data$ResultStatusIdentifier)
data <- data %>% filter(ResultStatusIdentifier != "Rejected")
unique(data$ResultValueTypeName)
value_typename_remove<-c("Estimated",
"Calculated")
data<-data %>% filter(!ResultValueTypeName %in% value_typename_remove)
unique(data$ResultValueTypeName)
rm(value_typename_remove)
unique(data$ResultAnalyticalMethod.MethodName)
data <- data %>% filter(ResultAnalyticalMethod.MethodName !="Computation by NWIS algorithm" | is.na(ResultAnalyticalMethod.MethodName))
unique(data$ResultDetectionConditionText)
#filtered out vars we don't need in resultsdetection condition text - did it in multistep because R doesn't handle multiple OR statements well
data<-data %>% filter(ResultDetectionConditionText != "Systematic Contamination" | is.na(ResultDetectionConditionText))
unique(data$ResultDetectionConditionText)
unique(data$ResultSampleFractionText)
types_to_exclude<-c("Bed Sediment",
"Recoverable",
"Acid Soluble",
"Total Recoverable",
"Volatile",
"Non-volatile",
"Supernate",
"Total Recovrble",
"Total Residual",
"Extractable")
data<-data %>% filter(!ResultSampleFractionText %in% types_to_exclude)
unique(data$ResultSampleFractionText)
rm(types_to_exclude)
unique(data$SampleAquifer)
data<-data %>% filter(is.na(SampleAquifer))
unique(data$SampleAquifer)
data<-data %>% select(-ActivityMediaName, -ActivityMediaSubdivisionName, -SampleAquifer, -SubjectTaxonomicName, -SampleTissueAnatomyName)
gc()
merge2<-data %>% group_by(State) %>% summarise(n=n())
saveRDS(data, "USlimno.rds")
#data<-readRDS("USlimno.rds")
#depthheight conversions
#ActivityDepthHeightMeasure.MeasureUnitCode
#ActivityDepthHeightMeasure.MeasureValue
unique(data$ActivityDepthHeightMeasure.MeasureUnitCode)
data$ActivityDepthHeightMeasure.MeasureValue<-ifelse(data$ActivityDepthHeightMeasure.MeasureUnitCode == "ft", data$ActivityDepthHeightMeasure.MeasureValue*0.3048, data$ActivityDepthHeightMeasure.MeasureValue)
data$ActivityDepthHeightMeasure.MeasureValue<-ifelse(data$ActivityDepthHeightMeasure.MeasureUnitCode == "feet", data$ActivityDepthHeightMeasure.MeasureValue*0.3048, data$ActivityDepthHeightMeasure.MeasureValue)
data$ActivityDepthHeightMeasure.MeasureValue<-ifelse(data$ActivityDepthHeightMeasure.MeasureUnitCode == "cm", data$ActivityDepthHeightMeasure.MeasureValue*0.01, data$ActivityDepthHeightMeasure.MeasureValue)
data$ActivityDepthHeightMeasure.MeasureValue<-ifelse(data$ActivityDepthHeightMeasure.MeasureUnitCode == "mm", data$ActivityDepthHeightMeasure.MeasureValue*0.001, data$ActivityDepthHeightMeasure.MeasureValue)
data$ActivityDepthHeightMeasure.MeasureValue<-ifelse(data$ActivityDepthHeightMeasure.MeasureUnitCode == "in", data$ActivityDepthHeightMeasure.MeasureValue*0.0254, data$ActivityDepthHeightMeasure.MeasureValue)
unitstodrop<-c("FTU", "None")
data<-data %>% filter(!ActivityDepthHeightMeasure.MeasureUnitCode %in% unitstodrop)
unique(data$ActivityDepthHeightMeasure.MeasureUnitCode)
data$ActivityDepthHeightMeasure.MeasureUnitCode[!is.na(data$ActivityDepthHeightMeasure.MeasureUnitCode)]<-"m"
#ResultDepthHeightMeasure.MeasureValue
#ResultDepthHeightMeasure.MeasureUnitCOde
unique(data$ResultDepthHeightMeasure.MeasureValue[is.na(as.numeric(data$ResultDepthHeightMeasure.MeasureValue))])
data$ResultDepthHeightMeasure.MeasureValue<-as.numeric(as.character(data$ResultDepthHeightMeasure.MeasureValue))
unique(data$ResultDepthHeightMeasure.MeasureValue)
data$ResultDepthHeightMeasure.MeasureValue<-ifelse(data$ResultDepthHeightMeasure.MeasureUnitCode == "ft", data$ResultDepthHeightMeasure.MeasureValue*0.3048, data$ResultDepthHeightMeasure.MeasureValue)
data$ResultDepthHeightMeasure.MeasureValue<-ifelse(data$ResultDepthHeightMeasure.MeasureUnitCode == "cm", data$ResultDepthHeightMeasure.MeasureValue*0.01, data$ResultDepthHeightMeasure.MeasureValue)
data$ResultDepthHeightMeasure.MeasureValue<-ifelse(data$ResultDepthHeightMeasure.MeasureUnitCode == "in", data$ResultDepthHeightMeasure.MeasureValue*0.0254, data$ResultDepthHeightMeasure.MeasureValue)
data$ResultDepthHeightMeasure.MeasureUnitCode[!is.na(data$ResultDepthHeightMeasure.MeasureUnitCode)]<-"m"
#ActivityTopDepthHeightMeasure.MeasureValue
#ActivityTopDepthHeightMeasure.MeasureUnitCode
unique(data$ActivityTopDepthHeightMeasure.MeasureValue[is.na(as.numeric(data$ActivityTopDepthHeightMeasure.MeasureValue))])
data <- data %>% mutate(ActivityTopDepthHeightMeasure.MeasureValue = case_when(ActivityTopDepthHeightMeasure.MeasureValue=="0-2" ~ "0",TRUE ~ as.character(ActivityTopDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityTopDepthHeightMeasure.MeasureValue = case_when(ActivityTopDepthHeightMeasure.MeasureValue=="'0.85" ~ "0.85",TRUE ~ as.character(ActivityTopDepthHeightMeasure.MeasureValue)))
data$ActivityTopDepthHeightMeasure.MeasureValue<-as.numeric(as.character(data$ActivityTopDepthHeightMeasure.MeasureValue))
unique(data$ActivityTopDepthHeightMeasure.MeasureUnitCode)
data$ActivityTopDepthHeightMeasure.MeasureValue<-ifelse(data$ActivityTopDepthHeightMeasure.MeasureUnitCode == "ft", data$ActivityTopDepthHeightMeasure.MeasureValue*0.3048, data$ActivityTopDepthHeightMeasure.MeasureValue)
data$ActivityTopDepthHeightMeasure.MeasureValue<-ifelse(data$ActivityTopDepthHeightMeasure.MeasureUnitCode == "feet", data$ActivityTopDepthHeightMeasure.MeasureValue*0.3048, data$ActivityTopDepthHeightMeasure.MeasureValue)
data$ActivityTopDepthHeightMeasure.MeasureUnitCode[!is.na(data$ActivityTopDepthHeightMeasure.MeasureUnitCode)]<-"m"
#ActivityBottomDepthHeightMeasure.MeasureUnitCode
#ActivityBottomDepthHeightMeasure.MeasureValue
unique(data$ActivityBottomDepthHeightMeasure.MeasureUnitCode)
unique(data$ActivityBottomDepthHeightMeasure.MeasureValue[is.na(as.numeric(data$ActivityBottomDepthHeightMeasure.MeasureValue))])
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="6.4-7.3" ~ "7.3",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="2-2.4" ~ "2.4",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="3-3.7" ~ "3.7",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="7.9-8.5" ~ "8.5",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="4.6-5.2" ~ "5.2",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="4.3-4.6" ~ "4.6",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="10.7-11" ~ "11",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="10.1-10.7" ~ "10.7",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="6.4-6.7" ~ "6.7",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="5.8-7" ~ "7",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="11.6-12.2" ~ "12.2",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="14-15.8" ~ "15.8",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="10.1-11" ~ "11",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="10.5-11" ~ "11",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="13.7-14.3" ~ "14.3",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="7.5-8.5" ~ "8.5",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="5.5-5.8" ~ "5.8",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="16.8-18" ~ "18",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="12.2-13.9" ~ "13.9",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="18-19" ~ "19",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="14.3-15.2" ~ "15.2",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="14-14.6" ~ "14.6",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="14-15.2" ~ "15.2",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="8.8-9.1" ~ "9.1",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="18-18.6" ~ "18.6",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="4.3-5.6" ~ "5.6",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="5.5-6.1" ~ "6.1",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="6.1-7.3" ~ "7.3",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="7.6-8.2" ~ "8.2",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="5.2-6.7" ~ "6.7",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="2.1-4.6" ~ "4.6",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="6.7-8.8" ~ "8.8",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="18.3-19.8" ~ "19.8",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="6.7-7.3" ~ "7.3",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="4.3-5.2" ~ "5.2",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="13.1-14.6" ~ "14.6",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="17.7-18.6" ~ "18.6",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="5.9-6.7" ~ "6.7",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="4.9-6.1" ~ "6.1",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="1.8-2.1" ~ "2.1",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="10.4-11.6" ~ "11.6",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="10.2-11.9" ~ "11.9",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="9.1-10.1" ~ "10.1",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="6.4-7" ~ "7",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="9.1-9.8" ~ "9.8",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="7.6-9.1" ~ "9.1",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="6.4-7.6" ~ "7.6",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="5.8-6.7" ~ "6.7",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="5.8-7.3" ~ "7.3",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="2.7-3.0" ~ "3.0",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="2.5-3" ~ "3",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
data <- data %>% mutate(ActivityBottomDepthHeightMeasure.MeasureValue = case_when(ActivityBottomDepthHeightMeasure.MeasureValue=="7.9-8.2" ~ "8.2",TRUE ~ as.character(ActivityBottomDepthHeightMeasure.MeasureValue)))
unique(data$ActivityBottomDepthHeightMeasure.MeasureValue[is.na(as.numeric(data$ActivityBottomDepthHeightMeasure.MeasureValue))])
data$ActivityBottomDepthHeightMeasure.MeasureValue<-as.numeric(as.character(data$ActivityBottomDepthHeightMeasure.MeasureValue))
unique(data$ActivityBottomDepthHeightMeasure.MeasureUnitCode)
data$ActivityBottomDepthHeightMeasure.MeasureValue<-ifelse(data$ActivityBottomDepthHeightMeasure.MeasureUnitCode == "ft", data$ActivityBottomDepthHeightMeasure.MeasureValue*0.3048, data$ActivityBottomDepthHeightMeasure.MeasureValue)
data$ActivityBottomDepthHeightMeasure.MeasureValue<-ifelse(data$ActivityBottomDepthHeightMeasure.MeasureUnitCode == "feet", data$ActivityBottomDepthHeightMeasure.MeasureValue*0.3048, data$ActivityBottomDepthHeightMeasure.MeasureValue)
data$ActivityBottomDepthHeightMeasure.MeasureUnitCode[!is.na(data$ActivityBottomDepthHeightMeasure.MeasureUnitCode)]<-"m"
#check
unique(data$ActivityDepthHeightMeasure.MeasureUnitCode)
unique(data$ResultDepthHeightMeasure.MeasureUnitCode)
unique(data$ActivityTopDepthHeightMeasure.MeasureUnitCode)
unique(data$ActivityBottomDepthHeightMeasure.MeasureUnitCode)
```
```{r backupvalues}
###creating new columns to preserve original pulled data
data$source_parameter<- data$CharacteristicName
data$source_value<- data$ResultMeasureValue
data$source_unit <- data$ResultMeasure.MeasureUnitCode
data$detectionlimit_legacy<- data$DetectionQuantitationLimitMeasure.MeasureValue
data$detectionlimit_unit_legacy<- data$DetectionQuantitationLimitMeasure.MeasureUnitCode
vars2process <- unique(data$CharacteristicName)#only once for first occurrence
write.csv(unique(data$CharacteristicName), file = "unique_characteristicnames.csv")
```
```{r depth}
#Depth
abbrev <- "depth"
lagos_name <- "Depth"
lagos_unit <- "m"
dataset_name <-"depth"
params<-c("Depth", "Depth, bottom", "Depth of water column", "Depth, data-logger (non-ported)", "Depth, data-logger (ported)")
vars2process<-vars2process[! vars2process %in% params] #remove grab samples from list
vars2process #check if any new varables to inlcude
data_temp<-data[data$CharacteristicName%in%params,] #want to match all records to the vector we created above
###create dataset to check for non numeric objects in dataset
temp <- non_numerics()
source("unit_conversions.R")
#done
```
```{r secchi}
abbrev <- "secchi"
lagos_name <- "Secchi"
lagos_unit <- "m"
dataset_name <-"secchi"
params<-c("Depth, Secchi disk depth","Depth, Secchi disk depth (choice list)","Water transparency, Secchi disc", "Transparency, Secchi tube with disk", "Horizontal Secchi Disk") #values for secchi
vars2process<-vars2process[! vars2process %in% params] #remove grab samples from list
vars2process #che
data_temp<-data[data$CharacteristicName%in%params,] #want to match all records to the vector we created above
###create dataset to check for non numeric objects in dataset
temp <- non_numerics()
{
#notes for processing non-numerics
#have to be able to assign a value and units to either result measure value and/or detection limit value to process
temp2 <- temp %>%
filter(grepl(">",ResultMeasureValue,fixed=TRUE)) %>%
filter(is.na(DetectionQuantitationLimitMeasure.MeasureValue))
#extract Values
vals <- gsub("[^0-9.-]", "", temp2$ResultMeasureValue)
data_temp$DetectionQuantitationLimitMeasure.MeasureValue[which(data_temp$Obs_Id %in% temp2$Obs_Id)] <- vals
data_temp$ResultDetectionConditionText[which(data_temp$Obs_Id %in% temp2$Obs_Id)] <- "Greater Than"
data_temp$ResultMeasureValue[which(data_temp$Obs_Id %in% temp2$Obs_Id)] <- NA
temp2 <- temp %>%
filter(ResultMeasureValue=="On Bottom") %>%
filter(is.na(DetectionQuantitationLimitMeasure.MeasureValue)) %>%
filter(!is.na(ActivityBottomDepthHeightMeasure.MeasureValue))
vals <- temp2$ActivityBottomDepthHeightMeasure.MeasureValue
data_temp$DetectionQuantitationLimitMeasure.MeasureValue[which(data_temp$Obs_Id %in% temp2$Obs_Id)] <- vals
data_temp$ResultDetectionConditionText[which(data_temp$Obs_Id %in% temp2$Obs_Id)] <- "Greater Than"
data_temp$ResultMeasureValue[which(data_temp$Obs_Id %in% temp2$Obs_Id)] <- NA
#check temp again to make sure everything is fixed that can be fixed
}
source("unit_conversions.R")
```
```{r calcium}
abbrev <- "Calcium"
lagos_name <- "Calcium, dissolved"
lagos_unit <- "mg/l"
dataset_name <-"Calcium_dissolved"
vars2process
params<-c("Calcium")
vars2process<-vars2process[! vars2process %in% params] #remove grab samples from list
vars2process #check if any new varables to inlcude
data_temp<-data[data$CharacteristicName%in%params,] #want to match all records to the vector we created above
unique(data_temp$ResultSampleFractionText)
data_temp <- data_temp %>% filter(ResultSampleFractionText=="Dissolved")
unique(data_temp$ResultSampleFractionText)
###create dataset to check for non numeric objects in dataset
temp <- non_numerics()
temp <- non_numerics()
temp2 <- temp %>% filter(grepl("<",temp$ResultMeasureValue,fixed=TRUE)==TRUE) %>%
filter(is.na(DetectionQuantitationLimitMeasure.MeasureValue)) #grab values with "<" from result measure value and NA in detection limit
vals <- gsub("[^0-9.-]", "", temp2$ResultMeasureValue) #extract only values from result measure value
data_temp$DetectionQuantitationLimitMeasure.MeasureValue[which(data_temp$Obs_Id %in% temp2$Obs_Id)] <- vals #place values in the detectionlim col
data_temp$ResultDetectionConditionText[which(data_temp$Obs_Id %in% temp2$Obs_Id)] <- "Less Than"
data_temp$ResultMeasureValue[which(data_temp$Obs_Id %in% temp2$Obs_Id)] <- NA
temp <- non_numerics()
source("unit_conversions.R")
```
```{r aluminum-total}
abbrev <- "tAl"
lagos_name <- "Aluminum, total"
lagos_unit <- "ug/l"
dataset_name <-"Aluminum_total"
vars2process
params<-c("Aluminum", "Aluminum, Organic + Inorganic Monomeric (reactive aluminum)")
vars2process<-vars2process[! vars2process %in% params] #remove grab samples from list
vars2process #check if any new varables to inlcude
data_temp<-data[data$CharacteristicName%in%params,] #want to match all records to the vector we created above
unique(data_temp$ResultSampleFractionText)
data_temp <- data_temp %>% filter(ResultSampleFractionText=="Total")
unique(data_temp$ResultSampleFractionText)
###create dataset to check for non numeric objects in dataset
temp <- non_numerics()
temp2 <- temp %>% filter(grepl("<",temp$ResultMeasureValue,fixed=TRUE)==TRUE) %>%
filter(is.na(DetectionQuantitationLimitMeasure.MeasureValue)) #grab values with "<" from result measure value and NA in detection limit
vals <- gsub("[^0-9.-]", "", temp2$ResultMeasureValue) #extract only values from result measure value
data_temp$DetectionQuantitationLimitMeasure.MeasureValue[which(data_temp$Obs_Id %in% temp2$Obs_Id)] <- vals #place values in the detectionlim col
data_temp$ResultDetectionConditionText[which(data_temp$Obs_Id %in% temp2$Obs_Id)] <- "Less Than"
data_temp$ResultMeasureValue[which(data_temp$Obs_Id %in% temp2$Obs_Id)] <- NA
temp <- non_numerics()
source("unit_conversions.R")
```
```{r aluminum-dissolved}