plotcli: ggplot2 in Your Terminal

plotcli renders ggplot2 plots directly in the terminal using Unicode Braille characters and ANSI colors. Write your ggplot code as usual, then call ggplotcli() to see it in the console -- no graphics device needed.

Inspired by the excellent UnicodePlots.jl.

Installation

# From CRAN
install.packages("plotcli")

# Development version from GitHub
# remotes::install_github("cheuerde/plotcli")
install.packages("plotcli", repos = c('https://cheuerde.r-universe.dev', 'https://cloud.r-project.org'))

Quick Start

Any ggplot2 plot works. Build your plot as usual, then pass it to ggplotcli():

library(plotcli)
library(ggplot2)

p <- ggplot(mtcars, aes(x = wt, y = mpg, color = factor(cyl))) +
  geom_point() +
  labs(title = "MPG vs Weight by Cylinders",
       x = "Weight (1000 lbs)", y = "Miles per Gallon",
       color = "Cylinders") +
  theme_bw()

ggplotcli(p)

Gallery

Boxplots

p <- ggplot(df, aes(x = group, y = value, fill = group)) +
  geom_boxplot() +
  labs(title = "Distribution Comparison by Group")
ggplotcli(p)

Line Charts

p <- ggplot(economics, aes(x = date, y = unemploy)) +
  geom_line(color = "steelblue") +
  geom_smooth(color = "red", se = FALSE) +
  labs(title = "US Unemployment Over Time")
ggplotcli(p)

Bar Charts

Histograms

Density Plots

Heatmaps

cor_mat <- cor(mtcars[, c("mpg", "cyl", "disp", "hp", "wt", "qsec")])
df <- as.data.frame(as.table(cor_mat))
names(df) <- c("Var1", "Var2", "value")
p <- ggplot(df, aes(Var1, Var2, fill = value)) +
  geom_tile() +
  labs(title = "Correlation Heatmap", fill = "correlation")
ggplotcli(p)

Faceted Plots

p <- ggplot(mpg, aes(x = displ, y = hwy)) +
  geom_point(color = "steelblue") +
  geom_smooth(method = "lm", color = "red", se = FALSE) +
  facet_wrap(~drv) +
  theme_bw()
ggplotcli(p, width = 80, height = 18)

Canvas Types

Block canvas -- medium resolution using block characters:

ASCII canvas -- basic ASCII for maximum compatibility:

Supported Geoms (27)

Geom	Status
geom_point	:white_check_mark:
geom_line, geom_path	:white_check_mark:
geom_step	:white_check_mark:
geom_bar, geom_col, geom_histogram	:white_check_mark:
geom_boxplot	:white_check_mark:
geom_violin	:white_check_mark:
geom_density	:white_check_mark:
geom_smooth	:white_check_mark:
geom_area	:white_check_mark:
geom_ribbon	:white_check_mark:
geom_segment, geom_hline, geom_vline, geom_abline	:white_check_mark:
geom_errorbar, geom_linerange, geom_pointrange, geom_crossbar	:white_check_mark:
geom_rect, geom_tile, geom_raster (heatmaps)	:white_check_mark:
geom_text, geom_label	:white_check_mark:
geom_rug	:white_check_mark:
facet_wrap, facet_grid	:white_check_mark:

Options

# Control size
ggplotcli(p, width = 80, height = 24)

# Canvas types
ggplotcli(p, canvas_type = "braille")  # High resolution (default)
ggplotcli(p, canvas_type = "block")    # Block characters
ggplotcli(p, canvas_type = "ascii")    # ASCII only

Direct R6 Class Usage

For lower-level control, use the plotcli R6 class directly:

pc <- plotcli$new(plot_width = 60, plot_height = 20, x_label = "wt", y_label = "mpg",
                  title = "MPG vs Weight")
pc$add_data(list(x = mtcars$wt, y = mtcars$mpg, type = "scatter", name = "mtcars"))
pc$print_plot()

Similar Projects

• txtplot: The OG in R
• r-plot: Collection of excellent terminal plotting functions
• UnicodePlots.jl: The gold standard for terminal graphics
• plotext: Powerful terminal graphics in Python

License

plotcli is released under the LGPL-3 License.