I have a dataset that contains over 100 categories. If I am going to plot it, I have to write over 100 lines code for it. Here is the example from plotly official website:
library(plotly)
Animals <- c("giraffes", "orangutans", "monkeys")
SF_Zoo <- c(20, 14, 23)
LA_Zoo <- c(12, 18, 29)
data <- data.frame(Animals, SF_Zoo, LA_Zoo)
p <- plot_ly(data, x = ~Animals, y = ~SF_Zoo, type = 'bar', name = 'SF Zoo') %>%
add_trace(y = ~LA_Zoo, name = 'LA Zoo') %>%
layout(yaxis = list(title = 'Count'), barmode = 'stack')
As you can see, if I have over 100 zoos that are going to be plotted, I need to write add_trace for over 100 times, which is inefficient. Does anyone know of ways to simplify it? I tried using for loop but I failed.
Or if anyone know how to use ggplotly to transfer a ggplot to an interactive format, it will also solve my problem. The plot produced by ggplot is a stacked grouped bar chart which x-axis have 10 facet_grid and about 100 categories in each grid. I tried using ggplotly directly and save it as an .html, however the plot's scale is very weird. It should looks like a rectangular with width about 40 and height about 8, but in html, it just shows like a square which is unreadable.
You can melt the data and then plot them like below:
library(data.table)
library(plotly)
data.table::melt(data, id.vars='Animals') %>%
plot_ly(x = ~Animals, y = ~value, type = 'bar',
name = ~variable, color = ~variable) %>%
layout(yaxis = list(title = 'Count'), barmode = 'stack')
This will plot:
来源：https://stackoverflow.com/questions/44929859/r-plotly-stacked-bar-chart-with-over-100-categories