I have a dataframe that shows the number of car sales in each country for years 2000 to 2020. I wish to plot a line graph to show how the number of car sales have changed over time for only a specific country/row, with year on the x axis and sales on the y axis. How would I do this using ggplot?
1
-
1Does this answer your question? Plotting each value of columns for a specific rowTim– Tim2021-06-07 12:56:49 +00:00Commented Jun 7, 2021 at 12:56
Add a comment
|
2 Answers
You perhaps want this
#toy_data
sales
#> Country 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
#> 2 A 1002 976 746 147 1207 627 157 1481 1885 1908 392
#> 3 B 846 723 1935 176 1083 636 1540 1692 899 607 1446
#> 4 C 1858 139 1250 121 1520 199 864 238 1109 1029 937
#> 5 D 534 1203 1759 553 1765 1784 1410 420 606 467 1391
library(tidyverse)
#for all countries
sales %>% pivot_longer(!Country, names_to = 'year', values_to = 'sales') %>%
mutate(year = as.numeric(year)) %>%
ggplot(aes(x = year, y = sales, color = Country)) +
geom_line()
#for one country
sales %>% pivot_longer(!Country, names_to = 'year', values_to = 'sales') %>%
mutate(year = as.numeric(year)) %>%
filter(Country == 'A') %>%
ggplot(aes(x = year, y = sales)) +
geom_line()
Created on 2021-06-07 by the reprex package (v2.0.0)
Comments
Suppose you have a data frame that looks like this:
#make dummy df
df <- matrix(sample(1:100, 63), ncol=21, nrow=3)
rownames(df) <- c("UK", "US", "UAE")
colnames(df) <- 2000:2020
Here I generated some random data for 21 years between 2000 and 2020, and for three countries. To get a line plot with ggplot for UK, I did:
data_uk <- data.frame(year=colnames(df), sales=df["UK",], row.names=NULL)
ggplot(data=data_uk, aes(x=year, y=sales, group=1)) + geom_point() + geom_line()
1 Comment
NicolasH2
For more flexibility, instead of creating data_uk you could also just do
new_df = as.data.frame(t(df)). Then in ggplot, you can say x=UK or x=UAE. Just faster to change and less code to write.