Diff, patch and merge for data.frames, see http://paulfitz.github.io/daff/
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README.md

Daff: diff, patch and merge for data.frames

daff is an R package that can find difference in values between data.frames, store this difference, render it and apply this difference to patch a data.frame. It can also merge two versions of a data.frame having a common parent. It wraps the daff.js library using the V8 package.

The diff format is described in http://dataprotocols.org/tabular-diff-format.

version downloads Build Status AppVeyor Build Status

Working:

  • diff: diff_data
  • patch: patch_data
  • write/read diff: read_diff and write_diff
  • render to html: render_diff
  • merge two tables based on a same version: merge_data

TODO:

  • add htmlwidgets
  • implement extra parameters for diff_data: ids, ignore etc.
  • make column type changes explicit (is now internally available)
  • see if daff can be implemented in C++, using the Haxe C++ target of daff: this would remove the V8/jsonlite dependency

Install

Install from CRAN

install.packages('daff')

The latest version of daff can be installed with devtools

devtools::install_github("edwindj/daff")

Usage

diff_data

Calculate the difference between a reference and a changed data.frame

library(daff)
y <- iris[1:3,]
x <- y

x <- head(x,2) # remove a row
x[1,1] <- 10 # change a value
x$hello <- "world"  # add a column
x$Species <- NULL # remove a column

patch <- diff_data(y, x)

# write a patch to disk
write_diff(patch, "patch.csv")

render_diff(patch) will generate the following HTML page:

render_diff

patch_data

Patch a data.frame using a diff generated with diff_data.

# read a diff from disk
patch <- read_diff("patch.csv")

# apply patch
y_patched <- patch_data(y, patch)

merge_data

Merge two data.frames that have diverged from a common parent data.frame.

parent <- a <- b <- iris[1:3,]
a[1,1] <- 10
b[2,1] <- 11
# succesful merge
merge_data(parent, a, b)

parent <- a <- b <- iris[1:3,]
a[1,1] <- 10
b[1,1] <- 11
# conflicting merge (both a and b change same cell)
merged <- merge_data(parent, a, b)
merged #note the conflict

#find out which rows contain a conflict
which_conflicts(merged)