r plotly chart based on multiple columns [duplicate] - r

Question

This question already has answers here:
Format axis tick labels to percentage in plotly
(2 answers)
Closed 2 years ago.
I have a df which can have 2 or more columns with the first one month always fixed.I am trying to plot them using plotly r. As of now it has three columns: month,apple,orange. Based on analysis it can have another column banana. Below is the code I am using right now but it even takes the column month for y-axis. How do I fix this:
> sample_test
month apple orange
2 Aug-17 2 1
3 Dec-17 2 1
4 Feb-18 2 1
5 Jan-18 2 1
6 Jul-17 2 1
7 Jun-17 2 1
8 May-17 2 1
9 Nov-17 2 1
10 Oct-17 2 1
11 Sep-17 2 1
p<- plot_ly(sample_test, x = sample_test$month, name = 'alpha', type = 'scatter', mode = 'lines',
line = list(color = 'rgb(24, 205, 12)', width = 4)) %>%
layout(#title = "abbb",
xaxis = list(title = "Time"),
yaxis = list (title = "Percentage"))
for(trace in colnames(sample_test)){
p <- p %>% plotly::add_trace(y = as.formula(paste0("~`", trace, "`")), name = trace)
}
p
The output looks like this :

Answer 1

Does this help?
sample_test <- read.table(
text = ' month apple orange
2 Aug-17 2 1
3 Dec-17 2 1
4 Feb-18 2 1
5 Jan-18 2 1
6 Jul-17 2 1
7 Jun-17 2 1
8 May-17 2 1
9 Nov-17 2 1
10 Oct-17 2 1
11 Sep-17 2 1'
)
sample_test$month <- as.Date(paste('01', sample_test$month, sep = '-'), format = '%d-%b-%y')
library(plotly)
p <- plot_ly(sample_test, type = 'scatter', mode = 'lines',
line = list(color = 'rgb(24, 205, 12)', width = 4)) %>%
layout(#title = "abbb",
xaxis = list(title = "Time"),
yaxis = list (title = "Percentage", tickformat = '%'))
for(trace in colnames(sample_test)[2:ncol(sample_test)]){
p <- p %>% plotly::add_trace(x = sample_test[['month']], y = sample_test[[trace]], name = trace)
}
p
There are couple of things to note here -
While dealing with dates, it's best to format them as dates. This can save a lot of headache later on. It is also useful as most if not all functions that require dealing with dates have methods built to handle them.
While adding traces in a for loop, always reference the vector to be plotted explicitly like data$vector or data[['vector']] and not like y = ~vector, because plotly for some reason ends up plotting just one trace over and over again.

Answer 2

You can specify a trace for the first y element, which will give you your raw counts. Next you can add a format for your y-axis using tickformat, which will convert to percentages.
sample_test <- data.frame(month = c("Aug-17", "Dec-17", "Feb-18"), apple = c(2,2,2), orange = c(1,1,1))
p <- plot_ly(sample_test, x = sample_test$month, y = ~apple, name = 'alpha', type = 'scatter', mode = 'lines',
line = list(color = 'rgb(24, 205, 12)', width = 4)) %>%
layout(xaxis = list(title = "Time")) %>%
layout(yaxis = list(tickformat = "%", title = "Percentage"))
Although for some reason this appears to just multiply by 100 and add a % label for some reason, rather than actually calculate a percentage. From this SO answer, looks like that's all it does. I don't really use plotly, but in ggplot you can do this if you reshape your data to long and map your categorical variable (in this case fruit) as a percent.
Edit: per OP's comment, removed month from being traced.
p <- plot_ly(type = 'scatter', mode = 'lines') %>%
layout(yaxis = list(tickformat = "%", title = "Percentage"))
colNames <- names(sample_test)
colNames <- colNames[-which(colNames == 'month')]
for(trace in colNames){
p <- p %>% plotly::add_trace(data = sample_test, x = ~ month, y = as.formula(paste0("~`", trace, "`")), name = trace)
print(paste0("~`", trace, "`"))
}
p