combine dataframes in a same plot Bar and point plot in R-CodePudding

I have a long-format data frame and I want to produce a bar plot using only a subset of the factors and in the same chart to also add points using the information/data of the other factors.

I came up with the following solution, but I am wondering whether there is a better way.

Here is an example:

rbind(df_fund_contributions,benmark_comp_returns) %>%
ggplot2::ggplot(aes(x = Date, y = Ra_contributions*100, fill =Fund))      #plot 
               geom_col()  
               geom_point(data = benmark_comp_returns, aes(color=Fund))   
               scale_color_manual(labels = c("Benchmark_Returns", 'portfolio_isa'), values = c("black", 'red'))   
               ylab('Returns Contributions (%)') 
               scale_fill_brewer(palette = "Paired")  
               scale_x_date(breaks = scales::breaks_pretty(10))  
               theme_minimal() theme(legend.position="bottom", text = element_text(size=20), 
                                     legend.title = element_blank())

The graph that I am producing looks like this:

[![enter image description here][1]][1]

I don't understand why all legends have a bullet point in their respective legends. How I can get rid of this?

Then, the two legends in the far right ( Benchmark_returns and portfolio_isa) do not align well. I would like to see the legend for portoflio_isa below the Benchmar_Returns

Is there any better way to have one dataframe that then can use a subset of the factors to do the bars and the other subset to do the geom_point and at the same time have better control and more aligned legends?

data

benmark_comp_returns <-  structure(list(Date = structure(c(18687, 18718, 18748, 18779, 
    18809, 18840, 18871, 18901, 18932, 18687, 18718, 18748, 18779, 
    18809, 18840, 18871, 18901, 18932), class = "Date"), Fund = structure(c(1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L), .Label = c("Benchmark_returns", "portfolio_isa"), class = "factor"), 
        Ra_contributions = c(0.0478973275493924, 0.0429625498691601, 
        -0.00987146529562977, 0.0410011423823866, 0.00941758614497523, 
        0.0349864600422998, -0.0223448750023872, 0.0381121681545589, 
        0.0351134695720898, 0.0166496661166204, 0.0531586687108598, 
        -0.0111559412001453, 0.0445469287928051, 0.00281101024533914, 
        0.0406282718668045, -0.0247869783939432, 0.0182891154197813, 
        0.0306387718131751)), row.names = c(NA, -18L), class = "data.frame")

df_fund_contributions <- structure(list(Date = structure(c(18687, 18718, 18748, 18779, 
    18809, 18840, 18871, 18901, 18932, 18687, 18718, 18748, 18779, 
    18809, 18840, 18871, 18901, 18932, 18687, 18718, 18748, 18779, 
    18809, 18840, 18871, 18901, 18932, 18687, 18718, 18748, 18779, 
    18809, 18840, 18871, 18901, 18932, 18687, 18718, 18748, 18779, 
    18809, 18840, 18871, 18901, 18932, 18687, 18718, 18748, 18779, 
    18809, 18840, 18871, 18901, 18932, 18687, 18718, 18748, 18779, 
    18809, 18840, 18871, 18901, 18932, 18687, 18718, 18748, 18779, 
    18809, 18840, 18871, 18901, 18932, 18687, 18718, 18748, 18779, 
    18809, 18840, 18871, 18901, 18932, 18687, 18718, 18748, 18779, 
    18809, 18840, 18871, 18901, 18932), class = "Date"), Fund = structure(c(1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 
    6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 
    8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 
    10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L), .Label = c("Artemis.UK", 
    "BG.American", "BG.European", "BG.Income", "BG.Pacific", "BG.Positive.Change", 
    "BNY.Investment", "Fidelity.Global.Tech", "MI.UK.Growth", "World.ex.UK"
    ), class = "factor"), Ra_contributions = c(0.00427165860999756, 
    0.00239847079026867, 0.00117754431202788, -0.00182894880661211, 
    0.0015714866119696, 0.00201985515304526, -0.000716111837747446, 
    0.00010844025664758, 0.000296559872361435, -0.00508106647547668, 
    0.00539584888044975, -0.00383796593852037, 0.00855760451422838, 
    -0.00105783414147886, 0.000502473932103786, -0.00329749205964847, 
    0.00209960811690113, 0.00183961510114417, 6.71423347435862e-05, 
    0.00403497203293068, -0.000284608500461858, 0.00233153961039023, 
    0.00146119835882152, 0.00315505857164022, -0.00417470041499501, 
    0.00138159592845111, 0.00343378138815176, 0.00245278797963633, 
    0.00441384714166171, -0.00064894253810821, 0.00358075762309507, 
    0.000857235410842261, 0.00280005532175731, -0.00250885316984295, 
    0.000953426797174473, 0.00363500835515063, -0.00685496500594374, 
    0.00588805087459376, -0.00243735627253794, 0.00752211168889483, 
    -0.00664016151247449, 0.00452144840571567, -0.00231800643829383, 
    0.00349181572848734, 0.00287501425724956, -0.00352018405882992, 
    0.0049448322743415, -0.00271660296964804, 0.0062422319547486, 
    0.00220134456831755, 0.00537823632154089, -0.00325469442031678, 
    0.000355838099185712, 0.00314657419344022, 0.00360353406021052, 
    0.00258097460780138, 0.000249327400845045, 0.00100446224081341, 
    0.00127957955088753, 0.00369878329082507, -0.00180152113372478, 
    0.00157127690034642, 0.00202363989457321, 0.00454903485057523, 
    0.00393549763466505, -0.00261753482244564, 0.00595399549768572, 
    -0.000685767558080919, 0.00461089490695632, -0.00194258549446136, 
    0.00202935948974536, 0.0050601619875501, 0.00692337793283104, 
    0.008156643520149, 0.00273205877224991, -0.000360455871006415, 
    0.00227382442135737, 0.00534524356313515, 0.000194645051589504, 
    -0.003185806335541, -8.25666847555917e-05, 0.0107961198005677, 
    0.00969975634580234, -0.00215785565985938, 0.0091873637594504, 
    0.00218940885990282, 0.00788171585200015, -0.00507956513557561, 
    0.00868991655727291, 0.00809432118772446)), row.names = c(NA, 
    -90L), class = "data.frame")


  [1]: https://i.stack.imgur.com/mUqsF.png

CodePudding user response：

Your first problem is easily solved - pass aesthetics to each geom separately.

For your second problem, you can specify the number of rows within guides for your color aesthetic.

library(tidyverse)

ggplot()     
  geom_col(data = df_fund_contributions, aes(x = Date, y = Ra_contributions*100, fill =Fund))  
  geom_point(data = benmark_comp_returns, aes(x = Date, y = Ra_contributions*100, color=Fund))   
  scale_color_manual(labels = c("Benchmark_Returns", 'portfolio_isa'), values = c("black", 'red'))   
  scale_fill_brewer(palette = "Paired")  
  theme(legend.position="bottom",  
                        legend.title = element_blank())  
  guides(color = guide_legend(nrow = 2))

CodePudding user response：

You asked how to possibly use facets to make your visualisation more compelling. Here a very quick idea.

library(tidyverse)

df_new <- 
  df_fund_contributions %>%
  mutate(contrib = 100*Ra_contributions,
         month = lubridate::month(Date, label = TRUE, abbr = TRUE))

ggplot(df_new)    
  geom_col(aes(x = Fund, y = contrib, fill = contrib >0))  
  scale_fill_brewer(palette = "Set1")  
  geom_hline(yintercept = 0)  
  facet_grid(~month)  
  coord_flip()