Ammonium (N)

Ammonium (N) Report

Code

if (!requireNamespace("librarian", quietly = TRUE)) {
  # If not installed, install the package
  install.packages("librarian")
}

librarian::shelf(
  glue,
  here,
  skimr,
  ggplot2
)

data <- read.csv(here("data/df_cleaned_01.csv"))
parameter_name <- params$parameter_name

apply param bounds

bounds <- read.csv(here("parameter_bounds.csv"), stringsAsFactors = FALSE, strip.white = T)
lower_bound <- bounds$min[bounds$param == parameter_name]
upper_bound <- bounds$max[bounds$param == parameter_name]

filter_condition <- (data$Parameter == parameter_name & (data$Value < lower_bound | data$Value > upper_bound))

tryCatch({  # this tryCatch is for when filter_condition is logical(0) i.e. no matches
  data <- dplyr::filter(
    data, 
    !filter_condition
  )
  print(glue("{sum(filter_condition)} rows dropped as < {lower_bound} or > {upper_bound}"))
}, error = function(e){
  print(glue("no rows removed"))
})

6 rows dropped as < 0 or > 6

apply param bounds

print(glue("{sum(filter_condition)} rows dropped as < {lower_bound} or > {upper_bound}"))

6 rows dropped as < 0 or > 6

write cleaned DataFrame to a file

write.csv(data, here("data/df_cleaned_02.csv"), row.names = FALSE)

load data & skim

subset_data <- subset(data, Parameter == parameter_name)
print(skimr::skim(subset_data))

── Data Summary ────────────────────────
                           Values     
Name                       subset_data
Number of rows             23550      
Number of columns          16         
_______________________               
Column type frequency:                
  character                4          
  numeric                  12         
________________________              
Group variables            None       

── Variable type: character ────────────────────────────────────────────────────
  skim_variable n_missing complete_rate min max empty n_unique whitespace
1 Source                0             1   3  21     0        9          0
2 Site                  0             1   1  28     0      515          0
3 Parameter             0             1  12  12     0        1          0
4 Units                 0             1   4   6     0        2          0

── Variable type: numeric ──────────────────────────────────────────────────────
   skim_variable     n_missing complete_rate        mean         sd      p0
 1 ...1                      0        1      131266.     160487.    66448  
 2 Latitude                  0        1          26.1         0.605    24.2
 3 Longitude                 0        1         -80.3         0.561   -83.6
 4 Month                     0        1           6.65        3.42      1  
 5 Day                      30        0.999      11.5         7.28      1  
 6 Year                      0        1        2020.          3.10   1998  
 7 Value                     0        1           0.0845      0.243     0  
 8 Sample.Depth            552        0.977       3.49       23.9       0  
 9 Total.Depth           22248        0.0553      5.37        7.93      0.5
10 verbatimValue             0        1           0.0845      0.243     0  
11 VerbatimLatitude          0        1          26.1         0.605    24.2
12 verbatimLongitude         0        1         -80.3         0.561   -83.6
         p25       p50       p75     p100 hist 
 1 78823.    84712.    90599.    696626   ▇▁▁▁▁
 2    25.8      26.0      26.4       28.0 ▁▂▇▃▁
 3   -80.3     -80.1     -80.1      -80.0 ▁▁▁▁▇
 4     4         7        10         12   ▇▅▅▆▇
 5     6        10        16         31   ▇▆▅▂▁
 6  2019      2020      2021       2023   ▁▁▁▂▇
 7     0.006     0.014     0.065      5.5 ▇▁▁▁▁
 8     0.5       0.5       2.5     2494   ▇▁▁▁▁
 9     0.708     3.4       6.7       62.2 ▇▁▁▁▁
10     0.006     0.014     0.065      5.5 ▇▁▁▁▁
11    25.8      26.0      26.4       28.0 ▁▂▇▃▁
12   -80.3     -80.1     -80.1      -80.0 ▁▁▁▁▇

create params$parameter_name histogram

ggplot2::ggplot(subset_data, aes(x=Value)) +
    geom_histogram(bins=30, fill="blue", color="black") +
    scale_y_log10() +  # Transform the y-axis to a logarithmic scale
    labs(title=paste("Histogram of Values for", params$parameter_name),
         x="Value",
         y="Log Frequency") +
    theme_minimal()