Plotly: How to convert ggplot object into plotly? - r

Question

I have one data set with two columns.First column is with name Centile.threshold and second is Effective.tax.rates. So next steep is to make plot with this code below.
# Data and code
library("rJava")
library("xlsxjars")
library("xlsx")
require(tidyr)
require(plyr)
library("ggplot2")
library("plotly")
g4_data_ext<-data.frame(structure(list(Centile.threshold = c(1, 2, 3, 4, 5, 6, 7, 8,
9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24,
25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40,
41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56,
57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72,
73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88,
89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100), Effective.tax.rates = c(11.4875111183361,
8.07673874931679, 7.8639563682086, 6.84656368538612, 6.8383437884744,
5.83532681932012, 5.11955857753708, 4.68757220539562, 4.66492423437793,
4.63051650494602, 4.71570390296145, 4.4419481131279, 4.16374366969064,
4.4424750798236, 4.2633646392858, 4.10185821346884, 2.29819561722,
2.01895390855722, 0, 0, 2.80530318111453, 2.83367683951859, 3.03173307975026,
3.58758933227946, 3.05869003045607, 3.59225918463074, 3.01588015121759,
3.55943967998446, 3.6220565232692, 3.40885422585891, 3.51447401518606,
3.68902868712004, 3.77018314638409, 3.72783452684771, 3.80791342516448,
3.99449874248864, 4.08421307782513, 4.07517557211112, 4.19659018929637,
4.22887420998102, 4.25529382081159, 4.36205679154288, 4.40690982734329,
4.33909305037396, 4.45990415426276, 4.59436808108174, 4.6831546716255,
4.73811656768519, 4.75412915916737, 4.84778797281815, 4.94690785473091,
5.06784298188807, 5.1769208879221, 5.2520552039406, 5.33650672817794,
5.43499638671921, 5.52400199193912, 5.58169115527766, 5.70509046165446,
5.76549758450655, 5.86333222670147, 5.87097687497217, 5.98729128544292,
6.07397530734785, 6.15030076581313, 6.21615540600908, 6.28135059352123,
6.38292345287997, 6.43416757218245, 6.5863284138631, 6.63365437304645,
6.70316768627345, 6.7816891944299, 6.85128738244695, 6.94261253911407,
7.01673024329712, 7.11081973369591, 7.18077796481166, 7.26197149513331,
7.32607460317916, 7.39638728837014, 7.47062968448649, 7.55194205005014,
7.64318101794584, 7.73728594723894, 7.79092205170689, 7.88152530983832,
7.97428540786095, 8.09278589483141, 8.20373396784042, 8.27757060469128,
8.40889176349213, 8.50851684368756, 8.64124701008068, 8.72559960562268,
8.85276486059087, 9.06564270204267, 9.26861906650096, 9.43047799204161,
10.2298639144453), grp_id = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6,
6, 6, 6, 7, 8), grp_label = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 2L, 3L), .Label = c("<=50%",
"=99%", ">99%", "51%-60%", "61%-70%", "71%-80%", "81%-90%", "91%-98%"
), class = "factor")), row.names = c(NA, -100L), class = "data.frame"))
This is code for plotting a plot with ggplot. This code works well.
g4_data_ext<-data.frame(g4_data, grp_id=NA, grp_label=NA)
for (i in 1:length((g4_data$Centile.threshold)))
{
if (g4_data$Centile.threshold[i]<=50)
{
g4_data_ext$grp_label[i] <- "<=50%"
g4_data_ext$grp_id[i] <- 1
}
else if (51<=g4_data$Centile.threshold[i] & g4_data$Centile.threshold[i]<=60)
{
g4_data_ext$grp_label[i] <- "51%-60%"
g4_data_ext$grp_id[i] <- 2
}
else if (61<=g4_data$Centile.threshold[i] & g4_data$Centile.threshold[i]<=70)
{
g4_data_ext$grp_label[i] <- "61%-70%"
g4_data_ext$grp_id[i] <- 3
}
else if (71<=g4_data$Centile.threshold[i] & g4_data$Centile.threshold[i]<=80)
{
g4_data_ext$grp_label[i] <- "71%-80%"
g4_data_ext$grp_id[i] <- 4
}
else if (81<=g4_data$Centile.threshold[i] & g4_data$Centile.threshold[i]<=90)
{
g4_data_ext$grp_label[i] <- "81%-90%"
g4_data_ext$grp_id[i] <- 5
}
else if (90<=g4_data$Centile.threshold[i] & g4_data$Centile.threshold[i]<=98)
{
g4_data_ext$grp_label[i] <- "91%-98%"
g4_data_ext$grp_id[i] <- 6
}
else if (g4_data$Centile.threshold[i]==99)
{
g4_data_ext$grp_label[i] <- "=99%"
g4_data_ext$grp_id[i] <- 7
}
else
{
g4_data_ext$grp_label[i] <- ">99%"
g4_data_ext$grp_id[i] <- 8
}
}
g4_data_ext$grp_label<-factor(g4_data_ext$grp_label)
color_code<-factor(c(rep("dark turquoise", 6), "tomato", "orange red"))
means_g4<-data.frame(ddply(g4_data_ext,~grp_id+grp_label,summarise,mean=mean(Effective.tax.rates),sd=sd(Effective.tax.rates)), color_code)
ggplot(data = means_g4, aes(x=factor(grp_id),y=mean, label =mean ))+
scale_x_discrete("Group",breaks=c(1:8), labels=means_g4$grp_label)+
coord_cartesian(ylim = c(-3, 12)) +
geom_bar(stat="identity", fill=color_code)+
geom_text(aes(y = mean*1.1, label = round(mean,2)), position=position_dodge(0.9))+
theme(axis.text.x = element_text(angle = 0))
But my intention is to convert this plot with ggplotly().I tryed to convert but is work well, so can anybody help me how to convert this plot into plotly object ?

Answer 1

When I try
ggplotly(ggplot(data = means_g4, aes(x=factor(grp_id),y=mean, label =mean ))+
scale_x_discrete("Group",breaks=c(1:8), labels=means_g4$grp_label)+
coord_cartesian(ylim = c(-3, 12)) +
geom_bar(stat="identity", fill=color_code)+
geom_text(aes(y = mean*1.1, label = round(mean,2)), position=position_dodge(0.9))+
theme(axis.text.x = element_text(angle = 0)))
I get the error
Error in nchar(axisObj$ticktext) : 'nchar()' requires a character vector
This error goes away if I leave out the scale_x_discrete term. The only thing there that looks like it should be a character vector is labels=means_g4$grp_label, and indeed means_g4$grp_label is a factor. So convert it, and the ggplotly() works:
ggplotly(ggplot(data = means_g4, aes(x=factor(grp_id),y=mean, label =mean ))+
scale_x_discrete("Group",breaks=c(1:8), labels=as.character(means_g4$grp_label))+
coord_cartesian(ylim = c(-3, 12)) +
geom_bar(stat="identity", fill=color_code)+
geom_text(aes(y = mean*1.1, label = round(mean,2)), position=position_dodge(0.9))+
theme(axis.text.x = element_text(angle = 0)))
This looks like a bug in ggplotly(), which should be doing that conversion automatically.

Answer 2

user2554330 figured out the hard part of your question. The rest is easy, and since I don't see your actual attempt at converting ggplot to plotly, here's how you can do that:
From a "standard" ggplot approach, just include ggplotly:
p <- ggplot(...)
p <- p + geom_point(...) # just an example...
fig <- ggplotly(p)
fig
Here's an example:
library(plotly)
library(tidyverse)
library(ggplot2)
# ggplot
p <- ggplot(data=iris, aes(x = Sepal.Length, y = Sepal.Width))
p <- p + geom_point(aes(color=Species, shape=Species)) +
xlab("Sepal Length") + ylab("Sepal Width") +
ggtitle("Sepal Length-Width")
# plotly
fig <- ggplotly(p)
fig
Plot: