Convert a dataframe whose row name is month and column name is year to a time series object using R-CodePudding

Say I have an excel file with format like this (to download from

Note the first column is year and the first row is month.

I try to convert it to time series object then draw a seasonal plot using ggseasonplot or ggplot2.

df <- openxlsx::read.xlsx('dataset1.xlsx', sheet='Sheet1', colNames=TRUE, rowNames = TRUE)
# df <- t(df)
df <- ts(df, start = c(2008, 1), end=c(2021, 12), frequency = 12)
forecast::ggseasonplot(df, col=rainbow(12), year.labels=TRUE)

Output:

Error in data.frame(y = as.numeric(x), year = trunc(round(time(x), 8)),  : 
  arguments imply differing number of rows: 2352, 168

How could I do that correctly using R? Thanks in advance.

References:

Data

df <- structure(list(month = 1:12, `2008` = c(4466.7095, 3654.5805, 
10195.65, 10093.13, 11854.13, 18171.78, 13724.1, 12759.61, 14951.02, 
13318.36, 14425.07, 20553.11), `2009` = c(4597.063947, 5678.726053, 
13286.21, 13520.3, 16438.02, 24578.03, 17833.66, 17052.78, 20191.81, 
17533.16, 17924.44, 25504.42), `2010` = c(7034.610811, 5979.419189, 
16778.65, 16950.07, 20615.55, 30689.08, 21818.87, 21131.49, 24871.84, 
21686.52, 23141.76, 30717.07)), class = "data.frame", row.names = c(NA, 
-12L))