| Title: | Compute the Difference Between Data Frames |
|---|---|
| Description: | Shows you which rows have changed between two data frames with the same column structure. Useful for diffing slowly mutating data. |
| Authors: | Riaz Arbi [aut, cre] |
| Maintainer: | Riaz Arbi <[email protected]> |
| License: | MIT + file LICENSE |
| Version: | 0.9 |
| Built: | 2025-03-07 03:33:28 UTC |
| Source: | https://github.com/riazarbi/diffdfs |
Checks that a provided vector of column names constitue a unique key (that is, no rows are duplicated) for a dataframe.
checkkey(df, key_cols, verbose = FALSE)checkkey(df, key_cols, verbose = FALSE)
df |
a dataframe |
key_cols |
vector of column names |
verbose |
TRUE/FALSE should we print a message? |
TRUE if key cols have unique rows; FALSE if not
irisint = iris irisint$rownum = 1:nrow(irisint) key_cols = c("rownum") checkkey(irisint, key_cols, TRUE) checkkey(irisint, "Species", TRUE)irisint = iris irisint$rownum = 1:nrow(irisint) key_cols = c("rownum") checkkey(irisint, key_cols, TRUE) checkkey(irisint, "Species", TRUE)
Returns a dataframe describing the modifications required to transform old_df into new_df. The dataframes needBugReports: https://github.com/tidyverse/dplyr/issues to have identical columns and column types and share unique index columns.
diffdfs(new_df, old_df = NA, key_cols = NA, verbose = FALSE)diffdfs(new_df, old_df = NA, key_cols = NA, verbose = FALSE)
new_df |
A dataframe of new data. |
old_df |
A dataframe of old data. new_df and old_df can (and usually do) have overlapping data. |
key_cols |
optional vector of column names that constitute a unique table key. If NA, colnames(old_df) will be used. |
verbose |
logical, default FALSE. Should the processing be chatty? |
a dataframe.
iris$key <- 1:nrow(iris) old_df <- iris[1:100,] old_df[75,1] <- 100 new_df <- iris[50:150,] diffdfs(new_df, old_df, key_cols = "key")iris$key <- 1:nrow(iris) old_df <- iris[1:100,] old_df[75,1] <- 100 new_df <- iris[50:150,] diffdfs(new_df, old_df, key_cols = "key")