Here is my data:
data <- data.table(year = rep(1980:1985,each = 5),
Relationship = rep(c(" Acquaintance","Unknown","Wife","Stranger","Girlfriend","Friend"), 5),
N = sample(1:100, 30)
)
I can use plotly::plot_ly function to plot a Dynamic map of the years like this:
plot_ly(data
,x=~Relationship
,y=~N
,frame=~year
,type = 'bar'
)
but when I using ggplot with parameter frame ,I get a error
Error in -data$group : invalid argument to unary operator
here is my ggplot code :
p <- ggplot(data = data,aes(x =Relationship,y = N ))+
geom_bar(stat = "identity",aes(frame = year))
ggplotly(p)
Can you modify my ggplot code to produce the same graph ？
This example runs successfully using frame parameter:
data(gapminder, package = "gapminder")
gg <- ggplot(gapminder, aes(gdpPercap, lifeExp, color = continent)) +
geom_point(aes(size = pop, frame = year)) +
scale_x_log10()
ggplotly(gg)
In case others are still looking, this does appear to be a bug related to geom_bar. Per Stéphane Laurent's GitHub report (https://github.com/ropensci/plotly/issues/1544) a workaround is to use geom_col(position = "dodge2") or geom_col(position = "identity") instead of geom_bar(stat='identity')
Related
Having a dataframe like this one:
From a dataframe like this one:
data <- data.frame(year = c(2010,2011,2012,2010,2011,2012),
name = c("stock1","stock1","stock1","stock2","stock2","stock2"),
value = c(0,3,1,4,1,3))
I would like to create a plot and I use this:
library(ggplot2)
ggplot(data=data, xName="year", groupName="name", brewerPalette="Blues")
but I can't receive the plot. Anything wrong in the call?
I think you need something like this:
library(ggplot2)
library(dplyr)
library(RColorBrewer)
df %>%
group_by(name) %>%
ggplot(aes(year,value,fill=name))+
geom_col()+
scale_fill_brewer(palette = "Blues")
If you want a grouped bar plot (as I guessed from your code), this code may be helpful:
ggplot(data = data, aes(x = as.factor(year), y = value, fill = name)) +
geom_bar(stat = "identity", position = position_dodge(0.8), width = 0.7) +
scale_fill_brewer(palette = "Blues")
I am trying to write a function to plot graphs in a grid. I am using ggplot and facet grid. I am unable to pass the argument for facet grid. I wonder if anybody can point me in the right direction.
The data example:
Year = as.factor(rep(c("01", "02"), each = 4, times = 1))
Group = as.factor(rep(c("G1", "G2"), each = 2, times = 2))
Gender = as.factor(rep(c("Male", "Female"), times = 4))
Percentage = as.integer(c("80","20","50","50","45","55","15","85"))
df1 = data.frame (Year, Group, Gender, Percentage)
The code for the grid plot without function is:
p = ggplot(data=df1, aes(x=Year, y=Percentage, fill = Gender)) + geom_bar(stat = "identity")
p = p + facet_grid(~ Group, scales = 'free')
p
This produces a plot like the ones I want to do. However, when I put it into a function:
MyGridPlot <- function (df, x_axis, y_axis, bar_fill, fgrid){
p = ggplot(data=df1, aes(x=x_axis, y=y_axis, fill = bar_fill)) + geom_bar(stat = "identity")
p = p + facet_grid(~ fgrid, scales = 'free')
return(p)
}
And then run:
MyGridPlot(df1, df1Year, df1$Percentage, df1$Gender, df1$Group)
It comes up with the error:
Error: At least one layer must contain all faceting variables: `fgrid`.
* Plot is missing `fgrid`
* Layer 1 is missing `fgrid
I have tried using aes_string, which works for the x, y and fill but not for the grid.
MyGridPlot <- function (df, x_axis, y_axis, bar_fill, fgrid){
p = ggplot(data=df1, aes_string(x=x_axis, y=y_axis, fill = bar_fill)) + geom_bar(stat = "identity")
p = p + facet_grid(~ fgrid, scales = 'free')
return(p)
}
and then run:
MyGridPlot(df1, Year, Percentage, Gender, Group)
This produces the same error. If I delete the facet grid, both function code runs well, though no grid :-(
Thanks a lot for helping this beginner.
Gustavo
Your problem is that in your function, ggplot is looking for variable names (x_axis, y_axis, etc), but you're giving it objects (df1$year...).
There are a couple ways you could deal with this. Maybe the simplest would be to rewrite the function so that it expects objects. For example:
MyGridPlot <- function(x_axis, y_axis, bar_fill, fgrid){ # Note no df parameter here
df1 <- data.frame(x_axis = x_axis, y_axis = y_axis, bar_fill = bar_fill, fgrid = fgrid) # Create a data frame from inputs
p = ggplot(data=df1, aes(x=x_axis, y=y_axis, fill = bar_fill)) + geom_bar(stat = "identity")
p = p + facet_grid(~ fgrid, scales = 'free')
return(p)
}
MyGridPlot(Year, Percentage, Gender, Group)
Alternatively, you could set up the function with a data frame and variable names. There isn't really much reason to do this if you're working with individual objects the way you are here, but if you're working with a data frame, it might make your life easier:
MyGridPlot <- function(df, x_var, y_var, fill_var, grid_var){
# Need to "tell" R to treat parameters as variable names.
df <- df %>% mutate(x_var = UQ(enquo(x_var)), y_var = UQ(enquo(y_var)), fill_var = UQ(enquo(fill_var)), grid_var = UQ(enquo(grid_var)))
p = ggplot(data = df, aes(x = x_var, y = y_var, fill = fill_var)) + geom_bar(stat = "identity")
p = p + facet_grid(~grid_var, scales = 'free')
return(p)
}
MyGridPlot(df1, Year, Percentage, Gender, Group)
I have the following dataset:
year <- as.factor(c(1999,2000,2001))
era <- c(0.4,0.6,0.7)
player_id <- as.factor(c(2,2,2))
df <- data.frame(year, era, player_id)
Using this data I created the following graph:
ggplot(data = df, aes(x = year, y=era, colour = player_id))+
geom_line() +
geom_text(aes(label = player_id), hjust=0.7)
Thing is however that I do now get a label at every datapoint. I only want to have a label at the end of each datapoint.
Any thoughts on what I should change to I get only one label?
If I understand correctly, you want label at end of data point. You could do this using directlabels library, as below:
library(ggplot2)
library(directlabels)
ggplot(data = df, aes(x = year, y=era, group = player_id, colour = player_id))+
geom_line() +
scale_colour_discrete(guide = 'none') +
scale_x_discrete(expand=c(0, 1)) +
geom_dl(aes(label = player_id), method = list(dl.combine("last.points"), cex = 0.8))
Output:
If I am understanding correctly what you want, then you can replace the geom_text(...) with geom_point()
How do I show the specific values of variables on a graph?
For example:
ggplot(data=df)+
geom_bar(mapping=aes(x=var))
How do I get it to have the actual count on the bar chart?
I believe this question has asked before but I couldn' find a duplicate quickly.
Here is an example how to annotate the columns of a bar chart with the counts:
n_row <- 100L
set.seed(123L)
df <- data.frame(var = sample(LETTERS[1:5], n_row, TRUE, 5:1))
library(ggplot2)
ggplot(data = df) + aes(x = var) +
geom_bar() +
stat_count(geom = "text", aes(label = ..count..), vjust = "bottom")
Alternatively, we can write
ggplot(data = df) + aes(x = var, label = ..count..) +
geom_bar() +
geom_text(stat = "count", vjust = "bottom")
Some geoms and stats do compute variables which can be accessed using special names like ..count... To plot labels, the x and y positions and the text need to be specified. The x position is taken from the date as specified in aes(). The y position seems to be taken automatically from the statistical transformation but the text needs to be specified explicitely.
Suggested reading:
Statistical transformations in R for Data Science
ggplot2 homepage
New to R.
I created a new variable with dplyr::mutate() and I see the values in the df output when I run the code, but when I try to plot it with ggplot, I receive object not found error. What am I doing wrong? Thx.
Works as expected:
mutate(avg_inv = (inv_total / sr_count))
Error here:
# Plot avg invoice
p <- ggplot(df1, aes(x = Date_Group, y = avg_inv) ) +
geom_bar(stat = "identity", position="dodge")
p
Error message:
Error in eval(expr, envir, enclos) : object 'avg_inv' not found
I think you might not be saving the result of mutate, so even though the results print to your console, it's not available for ggplot2.
Try:
df1 <- df %>% mutate(avg_inv = (inv_total / sr_count))
p <- ggplot(df1, aes(x = Date_Group, y = avg_inv) ) +
geom_bar(stat = "identity", position="dodge")
p
How about this; Here I'm computing the additional variable within the function call to ggplot. This saves me the hassle of a temporary variable to hold the temporary result and is error free too.
data("airquality")
library(ggplot2)
library(dplyr)
p<- ggplot(airquality %>%
mutate(somevar=(Month/Day)), aes(x = somevar) ) +
geom_histogram(position = "stack", stat = "bin", binwidth = 5)
print(p)