Starting the Months on the X-axis from May instead of January (Custom start for months)

[sarthak]

I am trying to plot a graph with Months on the X-axis and some value on the Y-axis. The months on the X-axis start from January and end in December. I want them to start on May and end at April. How do I do this?

 plot_ly(data = fdata, type = "scatter", mode = "markers+lines",
            x = ~months, y = ~Total, color = ~Years.Since.Initiation,height = "100%") %>%
      layout(xaxis = xx, yaxis = yy)})

This is a small part of the dataset. The months column is a factor

[andresrcs]

You have to specify the order of the levels for the factor, otherwise, it gets ordered alphabetically. See this example:

months <- c("January", "February", "March", "April")
as.factor(months)
#> [1] January  February March    April   
#> Levels: April February January March
factor(months, levels = c("January", "February", "March", "April"))
#> [1] January  February March    April   
#> Levels: January February March April

^{Created on 2020-03-24 by the reprex package (v0.3.0.9001)}

[sarthak]

Hey! I actually did specify the order of levels. I just didn't attach that code. My months arrange like your second example (January, February.... December) the question remains how can I make them start from May when I make the plot instead of January?

[andresrcs]

To help us help you, could you please prepare a reproducible example (reprex) illustrating your issue? Please have a look at this guide, to see how to create one:

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 0.2…