How can I add values on my line plot with the dataframe named freight

My data looks like this:

 freight_rate
         date LR2_115000dwt LR1_74000dwt MR_50000dwt
1  2020-04-03         21125        17000       16875
2  2021-04-02         21125        16125       15625
3  2022-04-01         21625        16125       16500
4  2019-08-02         19125        15375       16750
5  2020-08-07         24750        16500       16875
6  2021-08-06         21625        16125       16375
7  2022-08-05         23500        16625       20500
8  2019-12-06         21500        17250       17375
9  2020-12-04         21750        16125       16250
10 2021-12-03         21625        16125       16375
11 2020-02-07         21125        17250       16875
12 2021-02-05         21125        16125       15375
13 2022-02-04         21625        16125       16375
14 2020-01-03         21500        17250       17375
15 2021-01-01         21500        16125       15625
16 2022-01-07         21625        16125       16375
17 2019-07-05         19125        15375       16750
18 2020-07-03         24750        16500       16875

My code:

freight_rate %>%   
ggplot(aes(x = freight_rate$date))    
geom_line(aes(y = freight_rate$LR2_115000dwt), color = "darkred")    
geom_line(aes(y = freight_rate$LR1_74000dwt), color = "steelblue")   
geom_line(aes(y = freight_rate$MR_50000dwt), color = "green")

I want to have values on all of my line plots like this (the values on the line):

How can I do this with the given code? I am sorry for bad way of posting because I am new.

CodePudding user response：

Rather than doing one layer for each series you wish to plot, it would be far easier to pivot your data into long format and plot your layers altogether.

Whatever way to do it, you are going to end up with a very messy plot, since you have three series on a single panel, each with several points, and each point with a long number attached to it. This can be mitigated a bit by using geom_text_repel

library(tidyverse)
library(ggrepel)

freight_rate %>%
  pivot_longer(-date) %>%
  ggplot(aes(date, value, color = name))  
  geom_line(alpha = 0.5)  
  geom_point()  
  geom_text_repel(aes(label = scales::comma(value)), size = 3)  
  scale_color_manual(values = c('steelblue', 'red4', 'green4'), name = NULL)  
  scale_y_continuous(labels = scales::dollar, name = '$/day')  
  labs(x = 'Date')

You can make this a bit clearer by using facets to separate the series:

freight_rate %>%
  pivot_longer(-date) %>%
  ggplot(aes(date, value, color = name))  
  geom_line(alpha = 0.5)  
  geom_point()  
  geom_text_repel(aes(label = scales::comma(value)), size = 3)  
  scale_color_manual(values = c('steelblue', 'red4', 'green4'), name = NULL)  
  scale_y_continuous(labels = scales::dollar, name = '$/day')  
  labs(x = 'Date')  
  theme_minimal()  
  facet_grid(name ~ ., scales = 'free_y')  
  theme(panel.border = element_rect(fill = NA),
        strip.text = element_blank(),
        panel.spacing.y = unit(5, 'mm'))

Personally, I think the labels are just distracting here and the plot looks better without; I would trust my viewers to be able to read the data from the axes. Otherwise, why not just show a table?

freight_rate %>%
  pivot_longer(-date) %>%
  ggplot(aes(date, value, color = name))  
  geom_line(alpha = 0.7, size = 1)  
  geom_point(size = 3)  
  scale_color_manual(values = c('steelblue', 'red4', 'green4'), name = NULL)  
  scale_y_continuous(labels = scales::dollar, name = '$/day')  
  labs(x = 'Date')  
  theme_minimal(base_size = 16)