Cleaning up plot in ggplot2

General
3
  1. I don't see how to reduce the number of dates on the x axis because the dates are not evenly spaced and they cover a large range. If they are left as characters, there will be no way to interpolate between labeled dates to determine an unlabeled date. If they are converted to numeric dates, the large date range makes the columns too small to see. I suggest you rotate the text of the x axis tick labels, as I did in the code below in the theme() function.
  2. How to change the colors is shown in my other answer:
    Reformatting x and y-axis in ggplot2
  3. I suggest you filter out the 0 values that are causing the negative infinity values when you take log(0). I did this with the filter() function from dplyr.
  4. I used the theme() function to remove the grid lines.
mydata = structure(list(Date = c("2022-08-05", "2022-08-18", "2022-02-23", 
                                 "2022-09-09", "2022-09-25", "2022-10-12", "2022-11-06", "2023-04-29", 
                                 "2023-05-19", "2023-06-24", "2023-06-29", "2023-07-09", "2023-07-26"), 
                        C1In1 = c(0, 8.794, 0, 9.38, 8.86, 4.866, 5.124, 250, 484.63, 
                                  1107.53, 821.92, 367.5, 1265.6), 
                        C1In2 = c(NA, 8.794, NA, NA, 8.66, NA, NA, 70.59, 
                                  NA, NA, NA, NA, NA), 
                        C1Out = c(NA, 8.898, NA, 8.9, 7.98, 4.28, 4.88, 
                                  91.95, 197.91, 196.26, 367.92, 317.3, 433.3), 
                        C2In = c(NA, NA, NA, 8.64, NA, 4.38, NA, 313.87, NA, 
                                 233.01, NA, NA, 788.6), 
                        C2Out = c(NA, NA, NA, 8.5, NA, 4.21, NA, 237.7, NA, 
                                  162.16, NA, NA, 117.2), 
                        C3In = c(NA, 8.52, 9.1, 8.5, 4.21, 4.46, NA, 98.16, 
                                 4494.04, NA, NA, NA, 606.6), 
                        C3Out = c(NA, 8.96, 8.85, 4.23, 4.48, 4.54, NA, 
                                  57.43, 2487.91, NA, NA, NA, 447.6)), 
                   row.names = c(NA, 13L), 
                   class = "data.frame")

library(tidyr)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(ggplot2)

df = mydata |>
  pivot_longer(cols = -'Date') |> 
  filter(!is.na(value), value > 0) #|> 
  #mutate(Date = ymd(Date))

ggplot() + scale_y_continuous(trans = "log10") + 
  labs(x = "Date", y = "Total Dissolved Solids Concentration (mg/L)", 
       fill = "Sample Location") +
  geom_bar(data = df, aes(x = Date, y = value, fill = name), 
           stat = 'identity', 
           position = 'dodge') +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5), 
        panel.grid = element_blank())

Created on 2023-09-20 with reprex v2.0.2