How to Plot Multiple Lines in R

Plot multiple line graphs on the same window with auto-assigned different colors

The function to use is matplot, not plot. There is also matlines but if the data to be plotted is in a matrix, matplot can plot all columns in one call.

1. Create a vector of y coordinates, yy, from the x values. This is done in a sapply loop. In the code below I have called the x coordinates values xx since there is no dat[,2] to work with.
2. Plot the resulting matrix in one matplot function call, which takes care of the colors automatically.

The lines labels problem is not addressed, only the lines plotting problem. With so many lines their labels would make the plot more difficult to read.

icc <- function(year, x) {
  z = exp(year - x)
  inf = z / (1 + z)
  return (inf)
}

# Example data
year <- seq(-4, 4, 0.1)

xx <- seq(-1, 1, by = 0.2)
yy <- sapply(xx, \(x) icc(year, x))
matplot(year, yy, type = "l", lty = "solid")

^{Created on 2022-07-26 by the reprex package (v2.0.1)}

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Note

Function icc is the logistic distribution CDF with location x and scale 1. The base R plogis function can substitute for it, the results are equal within floating-point precision.

icc2 <- function(year, x) plogis(year, location = x, scale = 1)

yy2 <- sapply(xx, \(x) icc2(year, x))
identical(yy, yy2)
#> [1] FALSE
all.equal(yy, yy2)
#> [1] TRUE

How to plot multiple line chart in ggplot2?

The quick way is adding two geom_lines, one for each column - as @Basti and @Yacine Hajji have suggested. However, this is suboptimal (for example, it won't create a legend).

The better way is reshaping your dataset to long format, as @mfalco is suggesting. This can be done programmatically, for example with tidyr's pivot_longer.

# Create dataset
dat <- data.table::fread("Date       Total Count_1   %_one    Count_2  %_two
07-11-2022   368     43     11.7%    132    35.9%
07-12-2022   510     56     11.0%    177    34.7%
07-13-2022   544     62     11.4%    187    34.4%
07-14-2022   496     77     15.5%    196    39.5%
07-15-2022   320     39     12.2%    118    36.9%
07-16-2022   295     33     11.2%    99     33.6%")

library(tidyr)
library(dplyr)
library(ggplot2)

dat_long <- dat |> 
    # Make names follow the same pattern
    rename(percent_1 = `%_one`, percent_2 = `%_two`) |> 
    # Reshape multiple columns at once
    pivot_longer(-c(Date, Total),
                 names_to = c(".value", "measurement"),
                 names_pattern = "(.*)_(.*)"
                 ) |> 
    # Coerce data type for the percent column from chr to numeric
    mutate(percent = gsub("%", "", percent) |> as.numeric())

# Plot
dat_long |>
    ggplot(aes(Date, percent, colour = measurement, group = measurement)) +
    geom_line() +
    coord_cartesian(ylim = c(0, 50))

^{Created on 2022-08-12 by the reprex package (v2.0.1)}

How to plot a multiple line graph in R

It's very difficult to help without a reproducible example, but one way would be to use ggplot2. You can use either the group or the color aesthetic in your plot:

library(coronavirus)
library(dplyr)
library(ggplot2)
data(coronavirus)

coronavirus %>%
    filter(type == "confirmed") %>%
    filter(Country.Region != "Mainland China") %>% 
    group_by(Country.Region, date) %>%
    summarise(total = sum(cases)) %>% 
    ggplot(aes(x = date, y = total, color = Country.Region)) + 
    geom_line()

Plot two graphs in same plot in R

lines() or points() will add to the existing graph, but will not create a new window. So you'd need to do

plot(x,y1,type="l",col="red")
lines(x,y2,col="green")

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