boxplot is not ok

[anzbsrh]

Hi, can anybody help me with my boxplot. Why the SPI 9 is divided it should be only SPI3 SPI6 SPI 9 and SPI12, not SPI 9 SPI 9

[FJCC]

I suspect you have leading and/or trailing spaces in some instances of SPI 9. You can use the unique() function to list the different values in a column.

[ANiraula]

Would you ming posting you R code?
That would simplify investigation.

[anzbsrh]

Hi, the problem is solved but can you help me, how can i rearrange the position of plot, i mean it should be SPI3, SPI6, SPI9 and SPI12 but the SPI12 comes out first.

df.m <- melt(testtukui, id.var = "MONTH")
ggplot(data = df.m, aes(x=variable, y=value)) + geom_boxplot(aes(fill=MONTH)) + ylab("SPI") + xlab(NULL)

this is my script.

and my data is like:

|MONTH|MODERATE|
|SPI3|-1.32|
|SPI3|-1.25|
|SPI3|-1.09|
|SPI3|-1.02|
|SPI3|-1.15|
|SPI3|-1.40|
|SPI6|-1.11|
|SPI6|-1.43|
|SPI9|-1.21|
|SPI9|-1.18|
|SPI12|-1.16|
|SPI12|-1.24|

[FJCC]

You can force the order of the x axis categories by using the factor() function.

df.m$MONTH <- factor(df.m$MONTH, levels = c("SPI3", "SPI6", "SPI9", "SPI12"))

[ANiraula]

Another alternative to @FJCC's suggestion may be to use "%>% select()" before "melt".
Example:
testtukui <- testtukui %>% select(MONTH, SPI3, SPI6, SPI9, SPI12)

[anzbsrh]

Hi. I need help. Why I get

Error in $<-.data.frame(*tmp*, MONTH, value = integer(0)) :
replacement has 0 rows, data has 6027

[anzbsrh]

hi. it says

could not find function "%>%"

why is that?

[FJCC]

@anzbsrh

could not find function "%>%"

The pipe %>% is part of the magrittr package. You have to load either that package or the dplyr package that will import magrittr. Use

library(magrittr)
#or
library(dplyr)

For your other error, please show your code or, better, a reproducible example.

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…