How to get both positive and negative number for x-axis in ggplot2 and rescale the y-axis in R?

Question

I am drawing a graph using ggplot2 in R for two objects called A and B. My code is

  ggplot(test_error_bar_14_10_21, aes(x=levels, y=len, colour=index, group=index)) + 
  geom_errorbar(aes(ymin=len-ci, ymax=len+ci), width=.03) +
  geom_line() +
  geom_point(size=3, shape=21, fill="white") + # 21 is filled circle
  xlab("Percentage(%population)") +
  ylab("Treatment on new cases") +
  scale_colour_hue(name="Type of indices",    # Legend label, use darker colors
                   breaks=c("doses/population", "death/population"),
                   labels=c("A", "B"),
                   l=40) +                    # Use darker colors, lightness=40
  ggtitle("The Effect of different vaccines rates on \nA and B") +
  coord_flip() +                              #rotate the graph (https://ggplot2.tidyverse.org/reference/coord_flip.html)
  expand_limits(y=0) +                        # Expand y range
  scale_y_continuous(breaks=0:20*4) +         # Set tick every 4
  theme_bw() +
  theme(legend.justification=c(1,0),
        legend.position=c(1,0))               # Position legend in bottom right 

The result is

As can be seen, I have the negative results on x-axis, so what I should do to also mark the negative interval on x-axis ? I saw a post here but it is only for negative value, not for both negative and positive values on the same axis.

Apart from that, how to rescale the y-axis based on 10%-20%-...100% rather than 0-25%-75%-100% as in the current graph.

As suggested by @Park, I add the whole sample of test_error_bar_14_10_21 here

index            levels   len        ci

doses/population 0.1      7.232200   7.511183

doses/population 0.2      2.542600   8.51828

doses/population 0.3      -0.615100  10.090960

doses/population 0.4      -1.219400  9.363690

doses/population 0.5      -2.942717  11.359863

doses/population 0.6      -2.063000  9.12014

doses/population 0.7      0.721000   8.69263

doses/population 0.8      3.288216   10.747079

doses/population 0.9      6.778900   8.944848

doses/population 1.0      7.652900   8.24641

death/population 0.1      4.645150   11.179297

death/population 0.2     -5.860138   14.206702

death/population 0.3     -3.841500   15.451860

death/population 0.4      2.966200   16.215530

death/population 0.5      2.168000   18.536120

(sorry I got an error when using dput that it only reads 2 over 4 columns of mine so I type here the data directly). I followed this post to use dput but I failed so far unfortunately.

I add the code suggested by @Dave2e and it works so far, the result is as below

Update: I add the code of @Park to improve the display in the left column to percentage display

enter image description here

After the help from @Park, I got the desired results. Thanks a heaps

enter image description here

Answer 1

I named your data dummy. In x axis, @Dave2e 's comment is very helpful, so I made nothing change, just some addition. Change labels = scales::percent to lables = label_percent(accuracy = 5L) will get rid of rounds. And make another vector dummy2 that indicates the size of errorbar.

dummy2 <- dummy %>%
  mutate(width = ifelse(index == "doses/population", 1, 0.03)) %>% pull(width)

dummy %>%
  ggplot( aes(x=levels, y=len, colour=index, group=index)) + 
  geom_errorbar(aes(ymin=len-ci, ymax=len+ci), width= 0.03, size = dummy2) +
  geom_line() +
  geom_point(size=3, shape=21, fill="white") + # 21 is filled circle
  xlab("Percentage(%population)") +
  ylab("Treatment on new cases") +
  scale_colour_hue(name="Type of indices",    # Legend label, use darker colors
                   breaks=c("doses/population", "death/population"),
                   labels=c("A", "B"),
                   l=40) +                    # Use darker colors, lightness=40
  ggtitle("The Effect of different vaccines rates on \nA and B") +
  coord_flip() +                              #rotate the graph (https://ggplot2.tidyverse.org/reference/coord_flip.html)
  expand_limits(y=0) +                        # Expand y range
  theme_bw() +
  theme(legend.justification=c(1,0), legend.position=c(1,0)) + 
  scale_y_continuous(breaks=seq(-20,20,4)) + 
  scale_x_continuous(n.breaks=10, labels = label_percent(accuracy = 5L))