Welcome

The save package is an experimental tool designed to simplify file-saving tasks for data analysis and visualization. It offers methods like csv, text, and plot to save data, text, and plot outputs with ease. As an experimental package, it aims to provide a user-friendly experience while exploring file-saving options. Please note that this package is still under development and may undergo changes in future releases.

You can install the development version of save like so:

devtools::install_github("tpq/save")

Example

The save package is an experimental tool designed to streamline file-saving tasks for data analysis and visualization in R. With its intuitive interface, the package supports piping using the %>% operator, providing a seamless workflow for saving data and plot outputs.

Let’s see a minimal example of how to use the save package with piping:

library(dplyr)
library(ggplot2)
library(save)

# Set directory to use for all saved files
save <- Save$new(wd = getwd())

# Save data as CSV
data <-
  data.frame(A = 1:5, B = 6:10) %>%
  save$csv(file = "csv-1") %>%
  mutate(C = A + B) %>%
  save$csv(file = "csv-2")

# Save data as text
model <-
  lm(C ~ A + B, data) %>%
  save$text(file = "model")

# Save data as plot (base R plot)
# (note: pipe with %>%)
null <-
  plot(data$A, data$B) %>%
  save$plot(file = "plot-1")

# Save data as plot (ggplot2)
# (note: pipe with +)
gg <-
  data %>%
  ggplot(aes(x = A, y = B)) +
  geom_point() +
  save$gg(file = "plot-2") +
  theme_bw() +
  save$gg(file = "plot-3")

In these examples, the save package allows you to directly pipe data frames and plot objects into the respective saving methods, providing a concise and efficient workflow for file-saving operations. Please note that the package is still under development, and your feedback is valuable for further improvements and enhancements.

#> [1] TRUE
#> [1] TRUE
#> [1] TRUE
#> [1] TRUE
#> [1] TRUE
#> [1] TRUE