| Title: | Compute the Difference Between Data Frames |
| Version: | 0.9.0 |
| Description: | Shows you which rows have changed between two data frames with the same column structure. Useful for diffing slowly mutating data. |
| License: | MIT + file LICENSE |
| Imports: | arrow, dplyr, janitor, rlang |
| BugReports: | https://github.com/riazarbi/diffdfs |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.2.1 |
| Suggests: | testthat (≥ 3.0.0) |
| Config/testthat/edition: | 3 |
| NeedsCompilation: | no |
| Packaged: | 2022-08-05 10:38:53 UTC; jovyan |
| Author: | Riaz Arbi [aut, cre] |
| Maintainer: | Riaz Arbi <diffdfs@arbidata.com> |
| Repository: | CRAN |
| Date/Publication: | 2022-08-09 13:50:06 UTC |
Check That A Dataframe Key Col Set Is Unique
Description
Checks that a provided vector of column names constitue a unique key (that is, no rows are duplicated) for a dataframe.
Usage
checkkey(df, key_cols, verbose = FALSE)
Arguments
df |
a dataframe |
key_cols |
vector of column names |
verbose |
TRUE/FALSE should we print a message? |
Value
TRUE if key cols have unique rows; FALSE if not
Examples
irisint = iris
irisint$rownum = 1:nrow(irisint)
key_cols = c("rownum")
checkkey(irisint, key_cols, TRUE)
checkkey(irisint, "Species", TRUE)
Compute the Difference Between Dataframes
Description
Returns a dataframe describing the modifications required to transform old_df into new_df. The dataframes needBugReports: https://github.com/tidyverse/dplyr/issues to have identical columns and column types and share unique index columns.
Usage
diffdfs(new_df, old_df = NA, key_cols = NA, verbose = FALSE)
Arguments
new_df |
A dataframe of new data. |
old_df |
A dataframe of old data. new_df and old_df can (and usually do) have overlapping data. |
key_cols |
optional vector of column names that constitute a unique table key. If NA, colnames(old_df) will be used. |
verbose |
logical, default FALSE. Should the processing be chatty? |
Value
a dataframe.
Examples
iris$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")