teresa_test_plots.Rmd

---
title: "teresa_test_plot"
author: "Teresa Gonzalez"
date: "1/26/2022"
output: html_document
---

###Set up 

####Load Libraries
```{r}
#read in data 
library(readr)
#plotting 
library(ggplot2)
library(tidyverse)
#arranging plots in panel
library(ggpubr)
#creating interactive maps in R 
library(leaflet)
#splitting and averaging by unique values
library(data.table)
```

####Read in Files 
```{r}
#cast and bottle preprocessed data 
cast_bottle <- read_csv("data/preprocessed/bottle_and_cast.csv")

#descriptions of the variables in the cast and bottle preprocessed data 
descrip <- read_csv("data/Bottle Field Descriptions (1).csv")
```

```{r}

#creating a new dataframe from the cast_bottle preprocessed data 
sal_tem_o2 <- cast_bottle %>% 
#selecting only temp, salinity, oxygen, depth, bottle id, cast id, year for new dataframe
  select(T_degC, Salnty, O2ml_L, Depthm, Btl_Cnt, Cast_ID, Year) %>% 
#making a longer dataframe and putting temp, salinity, oxygen into a column called variable 
#and the values into a column called values 
  pivot_longer(1:3, names_to = "Variable", values_to = "Value")
```


###Creating Graphs 

####Graph of Salinity, Temperature, and Oxygen vs Depth 
```{r}
#creating a plot from the new dataframe with the salinity, temp, oxygen -> variable column 
sal_tem_o2_vs_depth <- ggplot(data = sal_tem_o2, aes(x = Value, y = Depthm)) + 
#putting everything into one graph and color coding by what type of variable 
  geom_point(aes(color = Variable)) + 
  scale_color_manual(values = c("darkred", "steelblue", "darkgreen")) + 
#reversing the y-axis so it resembles a thermocline graph 
  scale_y_reverse()
  

sal_tem_o2_vs_depth

# panel of graphs instead of all on same/ diff scales? 
#time and space? 



```
Temperature and O2 both decrease with depth. 

####Graph of salinity, temp, oxygen panels 
```{r}
#salinity plot 
salinity_plot <- ggplot() + 
#putting everything into one graph and color coding by what type of variable 
  geom_line(data = cast_bottle, aes(x = Salnty, y = Depthm)) + 
  scale_y_reverse()

salinity_plot


#temperature plot 
temp_plot <- ggplot() + 
#putting everything into one graph and color coding by what type of variable 
  geom_line(data = cast_bottle, aes(x = T_degC, y = Depthm)) + 
  scale_y_reverse()

temp_plot

#oxygen plot 
o2_plot <- ggplot() + 
#putting everything into one graph and color coding by what type of variable 
  geom_line(data = cast_bottle, aes(x = O2ml_L, y = Depthm)) + 
  scale_y_reverse()

o2_plot

#panel of graphs

sal_temp_o2_grid <- ggarrange(salinity_plot, temp_plot, o2_plot, 
          ncol = 3)

```



####Graph of Year vs Oxygen 
```{r}

#multiple sampling in a year, first make an ave, (use day, month, hour), use just one depth, or location 

year_o2_plot <- ggplot(data = cast_bottle, aes(x = Year, y = O2ml_L, group = )) + 
  geom_line() + 
  scale_color_manual(values = c("darkred", "steelblue", "darkgreen"))
  

year_o2_plot
```
Oxygen not decreasing with time? 


####Graph of pH vs Depth 
```{r}

#all Na's for depth with this current data, not much to do with pH right now 
ph1_vs_depth <- ggplot(data = cast_bottle, aes(x = pH1, y = Depthm)) + 
  geom_line()
  
ph1_vs_depth
```
####Looking into map making in R 
```{r}
#take the averages of the lat/long for each station 
station_avg <- setDT(cast_bottle)[, .(mean_lat = mean(Lat_Dec), mean_long = mean(Lon_Dec)), by = Sta_ID]

#create a base map using leaflet 
basemap <- leaflet() %>% 
#set the latitude and longitude for California, zoom into desired area 
  setView(lng = -119.4179, lat = 36.7783, zoom = 5.3) %>%
#add markers for each of the stations average lat and long 
  addTiles() %>%
  addCircleMarkers(
    lat = station_avg$mean_lat, 
    lng = station_avg$mean_long, 
    label = station_avg$Sta_ID, 
    color = "red", 
    radius = 0.6)
  
basemap



```