Box Plot creation

General
1

Hello,
I´m very new in Rstudio programing language but I realize I really need it. I have a table with multiple columns and i would like to create a box plot "trend line".
Basically the first column contains the values that should be in the x axes, and the other columns contains the sample I want to plot with the trend. For each x values i have 3 replicas

In the end I´d like to have a boxplot figure like the following:
image

Can you help me?
I just managed to define the dataframe, but after then i´m lost...

Thank you in advance

3

Let's clarify the goal a bit.
You say you want to make box plots but your example seems to have data points with error bars, not box plots. Which of those two to you want?
If you want points with error bars, are the limits of the error bars already present in the data, maybe as repeated measurements, or do those limits have to be calculated?
It is not clear from the image of the data frame how the three replicas of the data are arranged. Are some of the columns replicas of others or are the replicas within individual columns?

It will be much easier to help you if you provide some data in a form others can easily copy. Posting an image means those who want to help you need to construct the data. You can make a simple data frame with a minimum number of data points and post it in copy-friendly format. Here is a tutorial about that:

4

Hey,
thank you for your answer.
I would like to have a box plot as final graph. The picture I posted is only to show how i´d like to visualize it at the end. I´m sorry if it created confusion.
By the way, the limits for the error bars are not present already.

Concerning the replicas:
the first column contains the values I should put in the x-axis,
the other columns contain the samples I have and the replicas are represented in the raw. For example: sample "dark" for the 0,28 µE (which is 1st red light fluence rate value) has
first replica value=1,1427
2nd " " =1,039...ecc
3rd " " =1,1010...ecc

...

is ok if i copy like this
red light fluence ra~ dark col-0` MUT3 MUT7 MUT8 MUT11 MUTB

1 0.28999999999999998 1.1427 1.07935 0.921499999999~ 0.954550000000~ 1.00930000000~ NA NA
2 NA 1.039480000000~ 0.9716000000000~ 1.051359999999~ 0.722159999999~ 0.64827999999~ 0.89825000000~ 1.11400000000~
3 NA 1.101080000000~ 1.1401199999999~ 1.179319999999~ 0.973760000000~ 1.08220000000~ 1.18639999999~ 1.12827999999~
4 0.8 NA NA NA NA NA NA NA
5 NA NA NA NA NA NA NA NA
6 NA NA NA NA NA NA NA NA
7 NA NA NA NA NA NA NA NA
8 2 1.393149999999~ 1.0741000000000~ NA 1.235049999999~ NA 1.00275 1.29444999999~
9 NA 1.053800000000~ 0.6585000000000~ 0.956849999999~ 0.881600000000~ 0.75710000000~ 0.77700000000~ 1.0848
10 NA 1.071439999999~ 0.7472000000000~ 0.864239999999~ 0.923959999999~ 0.94127999999~ 0.75144000000~ 1.04908
11 3.8 0.867639999999~ 0.5850800000000~ NA 0.694879999999~ 0.74407999999~ 0.72272000000~ 1.16696000000~
12 NA 1.282319999999~ 0.9388399999999~ 0.982360000000~ 0.862720000000~ 1.02315999999~ 0.85915999999~ 1.13587999999~
13 NA 0.887119999999~ 0.5697200000000~ NA 0.999879999999~ 0.77439999999~ 0.72199999999~ 1.17872
14 10 0.788999999999~ 0.4948799999999~ 0.650320000000~ 0.651479999999~ 0.78180000000~ 0.53323999999~ 0.87880000000~
15 NA 1.196160000000~ 0.8010399999999~ 1.119559999999~ 0.830839999999~ 1.05012000000~ 0.80299999999~ 1.18224
16 NA 1.03348 0.6445200000000~ 0.737479999999~ 0.903439999999~ 0.96139999999~ 0.60148000000~ 1.11059999999~

5

The way you posted your data makes to hard to use. I put it in a csv file and after a little editing ended up with this:

      ra    dark   col.0    MUT3    MUT7    MUT8   MUT11    MUTB
1   0.29 1.14270 1.07935 0.92150 0.95455 1.00930      NA      NA
2     NA 1.03948 0.97160 1.05136 0.72216 0.64828 0.89825 1.11400
3     NA 1.10108 1.14012 1.17932 0.97376 1.08220 1.18640 1.12828
4   0.80      NA      NA      NA      NA      NA      NA      NA
5     NA      NA      NA      NA      NA      NA      NA      NA
6     NA      NA      NA      NA      NA      NA      NA      NA
7     NA      NA      NA      NA      NA      NA      NA      NA
8   2.00 1.39315 1.07410      NA 1.23505      NA 1.00275 1.29445
9     NA 1.05380 0.65850 0.95685 0.88160 0.75710 0.77700 1.08480
10    NA 1.07144 0.74720 0.86424 0.92396 0.94128 0.75144 1.04908
11  3.80 0.86764 0.58508      NA 0.69488 0.74408 0.72272 1.16696
12    NA 1.28232 0.93884 0.98236 0.86272 1.02316 0.85916 1.13588
13    NA 0.88712 0.56972      NA 0.99988 0.77440 0.72200 1.17872
14 10.00 0.78900 0.49488 0.65032 0.65148 0.78180 0.53324 0.87880
15    NA 1.19616 0.80104 1.11956 0.83084 1.05012 0.80300 1.18224
16    NA 1.03348 0.64452 0.73748 0.90344 0.96140 0.60148 1.11060

It seems that your repeated measurements are designated by having NA in the first column. I used the fill() function to put the actual values in the first column then pivoted the data to a long format and made a box plot. I think a box plot is not a good choice for this plot. With only three values per condition, the box plot gives the impression of having more data than are actually available. The first and third quartiles are not very well determined from such a small sample. Also, the x axis is categorical in a box plot but your x values are continuous values.

DF <- read.csv("~/R/Play/Dummy.csv", sep = " ")
library(tidyr)
DF <- fill(DF, ra, .direction = "down")
DFlong <- DF %>% pivot_longer(cols = -"ra", names_to = "samples", values_to = "Value")
DFlong
#> # A tibble: 112 × 3
#>       ra samples  Value
#>    <dbl> <chr>    <dbl>
#>  1  0.29 dark     1.14 
#>  2  0.29 col.0    1.08 
#>  3  0.29 MUT3     0.921
#>  4  0.29 MUT7     0.955
#>  5  0.29 MUT8     1.01 
#>  6  0.29 MUT11   NA    
#>  7  0.29 MUTB    NA    
#>  8  0.29 dark     1.04 
#>  9  0.29 col.0    0.972
#> 10  0.29 MUT3     1.05 
#> # … with 102 more rows
library(ggplot2)
ggplot(DFlong, aes(x = factor(ra), y = Value, fill = samples)) + geom_boxplot()
#> Warning: Removed 34 rows containing non-finite values (stat_boxplot).

Created on 2022-04-19 by the reprex package (v0.2.1)

A better way to post data is with the dput() function The output of dput(DF) is

structure(list(ra = c(0.29, NA, NA, 0.8, NA, NA, NA, 2, NA, NA, 
3.8, NA, NA, 10, NA, NA), dark = c(1.1427, 1.03948, 1.10108, 
NA, NA, NA, NA, 1.393149999999, 1.0538, 1.071439999999, 0.867639999999, 
1.282319999999, 0.887119999999, 0.788999999999, 1.19616, 1.03348
), col.0 = c(1.07935, 0.9716, 1.1401199999999, NA, NA, NA, NA, 
1.0741, 0.6585, 0.7472, 0.58508, 0.9388399999999, 0.56972, 0.4948799999999, 
0.8010399999999, 0.64452), MUT3 = c(0.921499999999, 1.051359999999, 
1.179319999999, NA, NA, NA, NA, NA, 0.956849999999, 0.864239999999, 
NA, 0.98236, NA, 0.65032, 1.119559999999, 0.737479999999), MUT7 = c(0.95455, 
0.722159999999, 0.97376, NA, NA, NA, NA, 1.235049999999, 0.8816, 
0.923959999999, 0.694879999999, 0.86272, 0.999879999999, 0.651479999999, 
0.830839999999, 0.903439999999), MUT8 = c(1.0093, 0.64827999999, 
1.0822, NA, NA, NA, NA, NA, 0.7571, 0.94127999999, 0.74407999999, 
1.02315999999, 0.77439999999, 0.7818, 1.05012, 0.96139999999), 
    MUT11 = c(NA, 0.89825, 1.18639999999, NA, NA, NA, NA, 1.00275, 
    0.777, 0.75144, 0.72272, 0.85915999999, 0.72199999999, 0.53323999999, 
    0.80299999999, 0.60148), MUTB = c(NA, 1.114, 1.12827999999, 
    NA, NA, NA, NA, 1.29444999999, 1.0848, 1.04908, 1.16696, 
    1.13587999999, 1.17872, 0.8788, 1.18224, 1.11059999999)), class = "data.frame", row.names = c(NA, -16L))

That can be easily used to recreate the data in my csv file by just copying the structure() call and assigning its value to DF.

6

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