My dataset looks like this :
Here's a table with a sample of the data: | City | AverageClientUsage | AverageClientEst | EstimatedTraffic | |---------|--------------------|------------------|------------------| |Atlanta |2695.68 |3555.62 |2812.89 | |Boston |559.48 |1080.49 |583.81 | |Chicago |3314.44 |5728 |3458.56 |
I'd like ggplot to use City as the X axis and have three bars for each point on the x axis, one for AverageClientUsage, one for AverageClientEst, one for EstimatedTraffic. How do I go about doing this? At the end I'd like the ggplot to look like this:
CodePudding user response:
First, you need to pivot_longer()
your dataframe:
library(dplyr)
df_long <- df %>% pivot_longer(!City, names_to = "Type", values_to = "Count")
Afterwards, you can create bars filled by Type, and using position = "dodge"
within geom_col()
library(ggplot)
ggplot(df_long, aes(x = City, y = Count, fill = Type)) # specify x and y axis, specify fill
geom_col(position = position_dodge(0.7), width = 0.6, color = "black") # position.dodge sets the bars side by side
theme_minimal() # add a ggplot theme
theme(legend.position = "bottom", # move legend to bottom
legend.title = element_blank(), # remove legend title
axis.text.x = element_text(angle = 45, vjust = 0.5, color = "gray33"), # rotate x axis text by 45 degrees, center again, change color
axis.text.y = element_text(color = "gray33"), # change y axis text coor
axis.title = element_blank(), # remove axis titles
panel.grid.major.x = element_blank()) # remove vertical grid lines
scale_fill_manual(values = c("blue", "darkorange2", "gray")) # adjust the bar colors
Data
df <- structure(list(City = c("Atlanta", "Boston", "Chicago"), AverageClientUsage = c(2695.68,
559.48, 3314.44), AverageClientEst = c(3555.62, 1080.49, 5728
), EstimatedTraffic = c(2812.89, 583.81, 3458.56)), class = c("tbl_df",
"tbl", "data.frame"), row.names = c(NA, -3L))