Packages

library(tidyverse)
library(readxl)
library(forcats)

Set working directory

setwd("I:/ENVA/WORK/Nick's Folder/R/Ulao")
getwd()
[1] "I:/ENVA/WORK/Nick's Folder/R/Ulao"

Pull in data

ulaodf<-read_excel("I:/ENVA/WORK/Nick's Folder/R/Ulao/ULAO_Master_2.xlsx")
view(ulaodf)

Map

DF_ULAO <- read_excel("I:/ENVA/WORK/Nick's Folder/R/Maps/DF_statusmap11_1.xlsx")%>%
  filter(County=="Ozaukee")
  dale_map <- slice(DF_ULAO,1,3,4,5)

pal <- colorFactor(palette = c( "orange", "green","blue","dark red"), 
                   levels = c( "Ulao Creek Downstream", "Ulao Creek Upstream","Helms Creek","Gateway Tributary"))


Dmap<-leaflet(data = dale_map) %>% 
  setView(lng =-87.91813 ,lat =43.30184 ,zoom =10 )%>%
  addProviderTiles("Esri.NatGeoWorldMap") %>%
  addCircleMarkers(~long, ~lat, popup = ~as.character(Nickname),
                   radius = 3,fillOpacity=6,color = ~pal(Nickname))
Dmap%>%
  addLegend(pal=pal,values=c("Ulao Creek Downstream", "Ulao Creek Upstream","Helms Creek","Gateway Tributary"))
NA
NA

Graphs

scatter<-ggplot(data = ulaodf,aes(x=Date,y=Chloride,color=Site_Name))+
  geom_point()+labs(title = "Ulao Chloride Lab Samples(mg/l)")
scatter

scatter_event<-ggplot(data = ulaodf,aes(x=Date,y=Chloride,color=Sampling_Type))+
  geom_point()+labs(title = "Ulao Chloride Lab Samples By Sample Type(mg/l)")
scatter_event

ulao_monthly<-ulaodf%>%
filter(Sampling_Type=="monthly")
view(ulao_monthly)
 scatterCL_monthly<-ggplot(data = ulao_monthly ,aes(x=Date,y=Chloride,color=Site_Name))+
  geom_line()+labs(title = "Regular Monthly Ulao Chloride Lab Samples(mg/l)")
scatterCL_monthly 

ulao_monthly<-ulaodf%>%
filter(Sampling_Type=="monthly")
 scatterCON_monthly<-ggplot(data = ulao_monthly ,aes(x=Date,y=spcon,color=Site_Name))+
  geom_line()+labs(title = "Regular Monthly Ulao Conductivity(us/cm)")
scatterCON_monthly 

Ulao Event

ulao_event<-ulaodf%>%
filter(Sampling_Type=="event")
view(ulao_event)
 scatter_event<-ggplot(data = ulao_event ,aes(x=Date,y=Chloride,color=Site_Name))+
  geom_point()+labs(title = " Ulao Chloride Lab Event Samples(mg/l)")
scatter_event 

ulao_monthly<-ulaodf%>%
filter(Sampling_Type=="monthly")
 scatter_monthly<-ggplot(data = ulao_monthly ,aes(x=Date,y=Chloride,color=Site_Name))+
  geom_boxplot()+geom_jitter(width=0.1,alpha=0.2)+labs(title = "Regular Monthly Ulao Chloride Lab Samples(mg/l)")
scatter_monthly 

Sodium

 ulao_monthly<-ulaodf%>%
filter(Sampling_Type=="monthly")
 scatter_monthly<-ggplot(data = ulao_monthly ,aes(x=Date,y=Sodium,color=Site_Name))+
  geom_boxplot()+geom_jitter(width=0.1,alpha=0.2)+labs(title = "Regular Monthly Ulao Sodium Lab Samples(mg/l)")
scatter_monthly 

NA
NA
ulao_monthly<-ulaodf%>%
filter(Sampling_Type=="monthly")
 scatter_monthly<-ggplot(data = ulao_monthly ,aes(x=Date,y=Hardness,color=Site_Name))+
  geom_boxplot()+geom_jitter(width=0.1,alpha=0.2)+labs(title = "Regular Monthly Ulao Hardness Lab Samples(mg/l)")
scatter_monthly 

ulao_monthly<-ulaodf%>%
filter(Sampling_Type=="monthly")
 scatter_monthly<-ggplot(data = ulao_monthly ,aes(x=Date,y=Magnesium,color=Site_Name))+
  geom_boxplot()+geom_jitter(width=0.1,alpha=0.2)+labs(title = "Regular Monthly Ulao Magnesium Lab Samples(mg/l)")
scatter_monthly 

ulao_monthly<-ulaodf%>%
filter(Sampling_Type=="monthly")
 scatter_monthly<-ggplot(data = ulao_monthly ,aes(x=Date,y=Potassium,color=Site_Name))+
  geom_boxplot()+geom_jitter(width=0.1,alpha=0.2)+labs(title = "Regular Monthly Ulao Potassium Lab Samples(mg/l)")
scatter_monthly 

ulao_monthly<-ulaodf%>%
filter(Sampling_Type=="monthly")
 scatter_monthly<-ggplot(data = ulao_monthly ,aes(x=Date,y=Sulfate,color=Site_Name))+
  geom_boxplot()+geom_jitter(width=0.1,alpha=0.2)+labs(title = "Regular Monthly Ulao Sulfate Lab Samples(mg/l)")
scatter_monthly 

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