New to R coding, new to coding in general

[Dan_Almeida]

Hello all, thank so much for your attention.

I'm very new to coding and I'm trying to learn how to do some nice plots with ggplot2.

I have this dataset, I want to represent the Employee Job Satisfaction per country. I made a bar chart as follows:

##############
data08_n <- data08%>%mutate(like_job = ifelse(job_satisfaction=="Satisfied", 1, 0),
love_job = ifelse(job_satisfaction=="Very satisfied", 1, 0),
dislike_job = ifelse(job_satisfaction=="Not very satisfied", 1, 0),
hate_job = ifelse(job_satisfaction=="Not at all satisfied", 1, 0))

data08_n <- data08_n[complete.cases(data08_n), ]

ggplot(data08_n, aes(country, fill=job_satisfaction))+
geom_bar(position = "fill")+
labs(title="Employee satisfaction", x=element_blank(), y=element_blank(), fill="Satisfaction")+
scale_fill_brewer()+
theme_minimal()+
coord_flip()

##############

MY QUESTION:
How can I add a percentual to each color to get something like:

Sorry for the trivial question. I'm very new to all of this.
Thank you for taking some time to help a newbie.

Daniel Almeida.

[rene_at_coco]

It is going to require use of geom_text(). Maybe something like:

ggplot(
    data = data08_n
    )+
geom_col(
    mapping = aes(
        x = country, 
        y = percentage # a new variable you need to calculate before calling ggplot
        fill = job_satisfaction
        ),
        position = "fill"
    )+
geom_text(
    position = position_fill(vjust = 0.5),
    mapping = aes(label = percent(percentage)) # not sure about this, exactly
  ) +
  scale_y_continuous(scales::labels = percent)

If you want more specific advice, then prepare a reproducible example.

[M_AcostaCH]

Hi @Dan_Almeida , welcome.

Is better if you put a reproducible example of data, see this link for that.

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.2…

You need something like that, and the data is this order for make more easy:

df <- data.frame(brands=c('Merc','Fiat','Hornet','Merc','Fiat','Hornet'),
                 cnt=c(20,15,12,10,13,7),
                 type=c('A','B','C','C','A','B'),
                 percentage=c(25.974026,19.480519,15.584416,12.987013,16.883117,9.090909))

tibble(df) %>% 
  ggplot(aes(
    x = brands,
    y = percentage,
    fill = type,
    label = percentage)) +
  geom_bar(stat = 'identity') +
  scale_fill_manual(values=c('#CA0067','#F6BB00','#00C20D'))+
  geom_text(position = position_stack(vjust = .5), 
    aes(x = brands,
        y = percentage,
        label = paste0(round(percentage,2),"%"))) +
  labs(title='put title',
       caption = 'caption',
       y=' ')+
  coord_flip()+ # for rotate the plot
  theme_classic()

In a before opportunity Im make the same quenstions and other user help me.
Im make better the code for you.

Add values in each stackerd bar whit extensive data

I think your issue is that your bars are actually loads of little bars stacked up. If you summarise your data ahead of the plot you get the result you're looking for: library(tidyverse) tibble(data) %>% group_by(MES, ANO) %>% summarise(CANTIDAD = sum(CANTIDAD)) %>% ggplot(aes( x = MES, y = CANTIDAD, fill = ANO, label = CANTIDAD )) + geom_bar(stat = 'identity') + geom_text( position = position_stack(vjust = .5), aes( x = MES, y = CANTIDAD, label = CANTIDAD, )) [image]