Plot Multiple Columns on the Same Graph in R

Plot multiple columns on the same graph in R

The easiest is to convert your data to a "tall" format.

s <- 
"A       B        C       G       Xax
0.451   0.333   0.034   0.173   0.22        
0.491   0.270   0.033   0.207   0.34    
0.389   0.249   0.084   0.271   0.54    
0.425   0.819   0.077   0.281   0.34
0.457   0.429   0.053   0.386   0.53    
0.436   0.524   0.049   0.249   0.12    
0.423   0.270   0.093   0.279   0.61    
0.463   0.315   0.019   0.204   0.23
"
d <- read.delim(textConnection(s), sep="")

library(ggplot2)
library(reshape2)
d <- melt(d, id.vars="Xax")

# Everything on the same plot
ggplot(d, aes(Xax,value, col=variable)) + 
  geom_point() + 
  stat_smooth() 

# Separate plots
ggplot(d, aes(Xax,value)) + 
  geom_point() + 
  stat_smooth() +
  facet_wrap(~variable)

Plot multiple columns on same plot

We can reshape to 'long' format with pivot_longer and plot at once

library(dplyr)
library(tidyr)
library(ggplot2)
mydf %>%
     mutate(rn = row_number()) %>% 
     pivot_longer(cols = -rn) %>%
     ggplot(aes(x = rn, y = value, color = name)) + 
          geom_point()

It may be also better to have geom_line as it will show the trend more easily

mydf %>%
  mutate(rn = row_number()) %>% 
  pivot_longer(cols = -rn) %>%
  ggplot(aes(x = rn, y = value, color = name)) + 
       geom_line()

---

Or using base R with matplot

matplot(as.matrix(mydf), type = 'l', col = c('red', 'green', 'blue'))
legend("topright", legend = names(mydf), fill = c('red', "green", "blue"))

R: Plot multiple columns in one graph

I get a little bit scared when you say you have 100 lines, might hurt your eyes doing this, so be careful!

The simplest I can come up with without manipulating the data is

matplot(df$Date, df, type="l"

With ggplot2, dplyr (for readability) and zoo packages you can do

df %>% select(matches("^V")) %>% zoo %>% autoplot

but you don't get the x-scale right there and I haven't spent time trying to get it right :).

With tidyr package you can also reshape the data before plotting.

df2 <- df %>% gather("variable","value", -Date)
ggplot(df2, aes(x=Date, y=value, color=variable)) + geom_line()

There are probably variations of this, or better ways :).

Plotting multiple columns against one column in ggplot2

Yes, you can use pivot_longer (or gather) and facets to achieve this.

One issue is that by default the labels will not be in the order X1 - X12, so you will need to specify the factor levels.

Try this:

data %>% 
  pivot_longer(cols = 1:12) %>% 
  mutate(name = factor(name, levels = paste0("X", 1:12))) %>% 
  ggplot(aes(x, value)) + 
  geom_line() + 
  facet_wrap(~name) +
  theme_bw()

Result:

Plotting multiple columns in same graph with R

Here I extract the granular data and put it along with the date of measurement in a dataframe. You will get a long data format that is easy to plot with ggplot:

library(dplyr)
library(ggplot2)

tb <- mData[['types']][['buckets']]  
dt <- mData[['key']]

pdf <- do.call(rbind,lapply(seq_len(length(tb)), 
                            function(x) tb[[x]] %>% mutate(date = dt[x])))

ggplot(pdf, aes(x = date, y=doc_count, col=key)) + geom_line()

How to plot multiple columns in R for the same X-Axis Value

I created my own dataset to demonstrate how to do it:

Data:

x <- runif(12,1,1.5)
y <- runif(12,1,1.5)
z <- runif(12,1,1.5)
m <- letters[1:12]
df <- data.frame(x,y,z,m)

Solution:

#first of all you need to melt your data.frame
library(reshape2)
#when you melt essentially you create only one column with the value
#and one column with the variable i.e. your x,y,z 
df <- melt(df, id.vars='m')

#ggplot it. x axis will be m, y will be the value and fill will be
#essentially your x,y,z
library(ggplot2)
ggplot(df, aes(x=m, y=value, fill=variable)) + geom_bar(stat='identity')

Output:

If you want the bars one next to the other you need to specify the dodge position at geom_bar i.e.:

ggplot(df, aes(x=m, y=value, fill=variable)) + 
       geom_bar(stat='identity', position='dodge')

How to plot multiple columns in r?

Is this what you're looking for?

library(tidyverse)

df <- data.frame(structure(list(Gene1 = c("RP11-983P164", "SLC25A20", "GLS", "IKZF4",
                                      "NRIP3", "SENP1", "SLC27A6", "SRFBP1", "OBFC1", "STEAP2"), 
                            label4 = c(0.267807692, 0.264456809, 0.256017476, 0.24682942, 0.244638979, 0.237201422, 
                                       0.232182056, 0.229398578, 0.227901191, 0.223994106), 
                            label3 = c(0.211951256, 0.258681595, 0.263101041, 0.218958497, 0.217096806, 0.272486806, 
                                       0.221822709, 0.268824399, 0.218744099, 0.20014748)), 
                       row.names = c(NA, -10L), class = c("data.table", "data.frame")))

df %>%
  pivot_longer(cols=c(-Gene1)) %>%
  ggplot(., aes(Gene1, value, group=name, fill=name)) +
  geom_col(position = 'dodge')

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