Data_Analysis_Cost.Rmd

---
title: "Microplastics Intercalibration Study Data Analysis: Cost"
author: "Southern California Coastal Water Research Project, University of Toronto & State Water Resources Control Board of California"
date: "`r format(Sys.time(), '%d %B, %Y')`"
output:
  html_document: 
    toc: true
    toc_depth: 4
    number_sections: true
    toc_float: true
---
![](www/logobanner.png)

```{r Install Packages, echo = FALSE, results = 'hide', error = FALSE, warning = FALSE, message = FALSE}

#### Packages ####
library(tidyverse)#A ton of useful functions
library(ggbeeswarm) #Beeswarm plots
library(knitr) #Needed to display table
library(kableExtra) #Needed for table features (i.e., scroll_box)

```

```{r Import Data, echo = FALSE, results = 'hide', error = FALSE, warning = FALSE, message = FALSE}

Cost <- read_csv("https://mpchecker.sccwrp.org/checker/intercal-data?table=tbl_costresults", guess_max = 100000) #Raw data file for other matrices

```

```{r Data Cleaning and Filtering, echo = FALSE, results = 'hide', error = FALSE, warning = FALSE, message = FALSE}

Cost_Clean <- Cost %>%
  #Removed lab D - incomparable with other data - deviation from methods
  filter(!(labid == "D"&matrix == "CW")) %>%
  #Removed pygcms data data
  filter(!(labid == "T"&matrix == "CW")) %>%
  filter(!(labid == "F"&matrix == "CW")) %>%
  #Removed labs that submitted clean water data late (want to match with original clean water data analysis)
  filter(!(labid == "WW"&matrix == "CW")) %>%
  filter(!(labid == "NN"&matrix == "CW")) %>%
  #Exclude augmentation data
  filter(!(labid %in% c("R","D", "L") & matrix %in% c("SD"))) %>% 
  filter(!(labid %in% c("L") & matrix %in% c("FT"))) %>% 
  filter(!grepl("Other", instrumenttype))%>%  # Remove instrument named 'other' so we are just comparing the 5 main instruments
  filter(!grepl("99", objectid))%>% # Remove lab that has -88 for both instrument and consumables cost
  filter(!grepl("123", objectid))%>% # Remove lab that has -88 for both instrument and consumables cost
  mutate(instrumentcost = na_if(instrumentcost, "-88")) %>% # Change all non-results to NA
  mutate(instrumentcost = na_if(instrumentcost, "0")) %>%
  mutate(consumables = na_if(consumables, "-88")) %>%
  mutate(consumables = na_if(consumables, "0")) %>%
  mutate(instrumenttype = case_when( # Re-name instruments
    instrumenttype == "FTIR" ~ "FTIR",
    instrumenttype == "ATR-FTIR" ~ "FTIR",
    instrumenttype == "FPA-FTIR" ~ "FTIR",
    instrumenttype == "PyroGCMS" ~ "Py-GCMS",
    instrumenttype == "Raman" ~ "Raman",
    instrumenttype == "Stereoscope" ~ "Stereoscope",
    instrumenttype == "StereoscopewithFluorescenceStaining" ~ "Fluorescent Stereoscope")) %>% 
  #Rename and create factor for sample type
  mutate(matrix = case_when(
    matrix == "CW" ~ "Clean Water",
    matrix == "FT" ~ "Fish Tissue",
    matrix == "SD" ~ "Sediment",
    matrix == "DW" ~ "Dirty Water")) %>% 
  mutate(matrix_f = as.factor(matrix)) 
```

# Instrument

```{r Instrument Cost, echo = FALSE, error = FALSE, warning = FALSE, message = FALSE}

Cost_Clean_1 <- Cost_Clean %>% drop_na(instrumentcost)

Cost_Instrument <- Cost_Clean_1 %>% 
  ggplot(aes(x=instrumenttype, y=instrumentcost)) +
  theme_test() +
  geom_beeswarm(aes(color = instrumenttype, fill = instrumenttype), alpha = 0.7, size = 2, groupOnX = TRUE) +
  geom_boxplot(alpha = 0.5, aes(color = instrumenttype, fill = instrumenttype))+
  ylab("Instrument Cost (USD)")+ xlab("Instrument Type")+
  scale_x_discrete(limits = c("Stereoscope", "FTIR", "Raman"))+
  scale_y_continuous( limits=c(0, 400000), labels = scales::number_format(accuracy = 1))+
  scale_fill_brewer(palette = "Set1") +
  scale_color_brewer(palette = "Set1") +
  facet_wrap(~matrix_f)+
  theme(text = element_text(size = 12), 
        plot.title = element_text(hjust = 0.5), 
        legend.position = "none",
        axis.text.x = element_text(angle = 45 , hjust = 1, vjust = 1),
        axis.title.y = element_text(margin = margin(t = 0, r = 20, b = 0, l = 0)))

Cost_Instrument

Table1 <- Cost_Clean_1 %>% 
  #Calculate SD 
  group_by(instrumenttype, matrix_f) %>% 
  mutate(SD = sd (instrumentcost)) %>% 
  mutate(Mean = mean(instrumentcost)) %>%
  ungroup() %>%
  group_by(matrix_f, instrumenttype, Mean, SD) %>%
  summarise() %>%
  rename("Matrix" = matrix_f) %>% 
  rename("Instrument" = instrumenttype) 

 kable(Table1, digits = 0, caption = "Instrument Cost (USD). Summary statistics.") %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
  scroll_box(width = "700px", height = "400px")

```

# Consumables

```{r Consumables Cost, echo = FALSE, error = FALSE, warning = FALSE, message = FALSE}

Cost_Consumables <- Cost_Clean %>% 
  ggplot(aes(x=instrumenttype, y=consumables)) +
  theme_test() +
  geom_beeswarm(aes(color = instrumenttype, fill = instrumenttype), alpha = 0.7, size = 2, groupOnX = TRUE) +
  geom_boxplot(alpha = 0.5,aes(color = instrumenttype, fill = instrumenttype))+
  ylab("Consumables Cost (USD)")+ xlab("Instrument Type")+
  scale_x_discrete(limits = c("Stereoscope", "FTIR", "Raman"))+
  scale_y_continuous(limits =c(0,12000))+
  scale_fill_brewer(palette = "Set1") +
  scale_color_brewer(palette = "Set1") +
  facet_wrap(~matrix_f)+
  theme(text = element_text(size = 12), 
        plot.title = element_text(hjust = 0.5), 
        legend.position = "none",
        axis.text.x = element_text(angle = 45 , hjust = 1, vjust = 1),
        axis.title.y = element_text(margin = margin(t = 0, r = 20, b = 0, l = 0)))

Cost_Consumables

Cost_Clean_2 <- Cost_Clean %>% drop_na(consumables)


Table2 <- Cost_Clean_2 %>% 
  #Calculate SD 
  group_by(instrumenttype, matrix_f) %>% 
  mutate(SD = sd (consumables)) %>% 
  mutate(Mean = mean(consumables)) %>%
  ungroup() %>%
  group_by(matrix_f, instrumenttype, Mean, SD) %>%
  summarise() %>%
  rename("Matrix" = matrix_f) %>%
  rename("Instrument" = instrumenttype) 

 kable(Table2, digits = 0, caption = "Consumables Cost (USD). Summary statistics.") %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
  scroll_box(width = "700px", height = "400px")
```

# Stereoscope

```{r Stereoscope Cost, echo = FALSE, error = FALSE, warning = FALSE, message = FALSE}
#Instrument
Stereoscope <- Cost_Clean %>%
  filter(instrumenttype == "Stereoscope") %>%
  drop_na(instrumentcost)

Summary_S <- Stereoscope %>%
  ungroup() %>% 
  group_by(matrix_f) %>% 
  mutate(Mean = mean(instrumentcost)) %>%
  mutate(SD = sd (instrumentcost)) %>% 
  ungroup() %>%
  group_by(matrix_f, instrumenttype, Mean, SD) %>%
  summarise() %>% 
  rename("Matrix" = matrix_f) %>%
  rename("Instrument" = instrumenttype)

 kable(Summary_S, digits = 0, caption = "Instrument Cost (USD). Summary statistics.") %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
  scroll_box(width = "700px", height = "400px")

#Consumables 
 Stereoscope_C <- Cost_Clean %>%
  filter(instrumenttype == "Stereoscope") %>%
  drop_na(consumables)
 
 Summary_SC <- Stereoscope_C %>% 
  ungroup() %>% 
  group_by(matrix_f) %>% 
  mutate(Mean = mean(consumables)) %>%
  mutate(SD = sd (consumables)) %>% 
  ungroup() %>%
  group_by(matrix_f, instrumenttype, Mean, SD) %>%
  summarise() %>% 
  rename("Matrix" = matrix_f) %>%
  rename("Instrument" = instrumenttype) 

 kable(Summary_SC, digits = 0, caption = "Consumables Cost (USD). Summary statistics.") %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
  scroll_box(width = "700px", height = "400px")
 
```

# FTIR

```{r FTIR Cost, echo = FALSE, error = FALSE, warning = FALSE, message = FALSE}
#Instrument
FTIR <- Cost_Clean %>%
  filter(instrumenttype == "FTIR") %>%
  filter(labid != "A")%>%
  drop_na(instrumentcost)

Summary_F <- FTIR %>% 
  ungroup() %>% 
  group_by(matrix_f) %>%
  mutate(Mean = mean(instrumentcost)) %>%
  mutate(SD = sd (instrumentcost)) %>% 
  ungroup() %>%
  group_by(matrix_f, instrumenttype, Mean, SD) %>%
  summarise() %>% 
  rename("Matrix" = matrix_f) %>%
  rename("Instrument" = instrumenttype) 

 kable(Summary_F, digits = 0, caption = "Instrument Cost (USD). Summary statistics.") %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
  scroll_box(width = "700px", height = "400px")

#Consumables
 FTIR_C <- Cost_Clean %>%
  filter(instrumenttype == "FTIR") %>%
  filter(labid != "A")%>%
  drop_na(consumables)
 
 Summary_FC <- FTIR_C %>%
  ungroup() %>% 
  group_by(matrix_f) %>%
  mutate(Mean = mean(consumables)) %>%
  mutate(SD = sd (consumables)) %>% 
  ungroup() %>%
  group_by(matrix_f, instrumenttype, Mean, SD) %>%
  summarise() %>% 
  rename("Matrix" = matrix_f) %>%
  rename("Instrument" = instrumenttype)  

 kable(Summary_FC, digits = 0, caption = "Consumables Cost (USD). Summary statistics.") %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
  scroll_box(width = "700px", height = "400px")
 
```

# Raman

```{r Raman Cost, echo = FALSE, error = FALSE, warning = FALSE, message = FALSE}
#Instrument
Raman <- Cost_Clean %>%
  filter(instrumenttype == "Raman") %>%
  drop_na(instrumentcost)

Summary_R <- Raman %>% 
  ungroup() %>% 
  group_by(matrix_f) %>%
  mutate(Mean = mean(instrumentcost)) %>%
  mutate(SD = sd (instrumentcost)) %>% 
  ungroup() %>%
  group_by(matrix_f, instrumenttype, Mean, SD) %>%
  summarise() %>% 
  rename("Matrix" = matrix_f) %>%
  rename("Instrument" = instrumenttype) 

 kable(Summary_R, digits = 0, caption = "Instrument Cost (USD). Summary statistics.") %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
  scroll_box(width = "700px", height = "400px")

#Consumables
 Raman_C <- Cost_Clean %>%
  filter(instrumenttype == "Raman") %>%
  drop_na(consumables)
 
 Summary_RC <- Raman_C %>% 
  ungroup() %>% 
  group_by(matrix_f) %>%
  mutate(Mean = mean(consumables)) %>%
  mutate(SD = sd (consumables)) %>% 
  ungroup() %>%
  group_by(matrix_f, instrumenttype, Mean, SD) %>%
  summarise() %>% 
  rename("Matrix" = matrix_f) %>%
  rename("Instrument" = instrumenttype)

 kable(Summary_RC, digits = 0, caption = "Consumables Cost (USD). Summary statistics.") %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
  scroll_box(width = "700px", height = "400px")
 
```

End of Analysis.