Compares 2 dataframes and outputs any differences.
Usage
diffdf(
base,
compare,
keys = NULL,
suppress_warnings = FALSE,
strict_numeric = TRUE,
strict_factor = TRUE,
file = NULL,
tolerance = sqrt(.Machine$double.eps),
scale = NULL
)Arguments
- base
input dataframe
- compare
comparison dataframe
- keys
vector of variables (as strings) that defines a unique row in the base and compare dataframes
- suppress_warnings
Do you want to suppress warnings? (logical)
- strict_numeric
Flag for strict numeric to numeric comparisons (default = TRUE). If False diffdf will cast integer to double where required for comparisons. Note that variables specified in the keys will never be casted.
- strict_factor
Flag for strict factor to character comparisons (default = TRUE). If False diffdf will cast factors to characters where required for comparisons. Note that variables specified in the keys will never be casted.
- file
Location and name of a text file to output the results to. Setting to NULL will cause no file to be produced.
- tolerance
Set tolerance for numeric comparisons. Note that comparisons fail if (x-y)/scale > tolerance.
- scale
Set scale for numeric comparisons. Note that comparisons fail if (x-y)/scale > tolerance. Setting as NULL is a slightly more efficient version of scale = 1.
Examples
x <- subset( iris, -Species)
#> Warning: ‘-’ not meaningful for factors
x[1,2] <- 5
COMPARE <- diffdf( iris, x)
#> Warning:
#> There are rows in BASE that are not in COMPARE !!
#> Not all Values Compared Equal
print( COMPARE )
#> Differences found between the objects!
#>
#> A summary is given below.
#>
#> There are rows in BASE that are not in COMPARE !!
#> First 10 of 149 rows are shown in table below
#>
#> ===============
#> ..ROWNUMBER..
#> ---------------
#> 2
#> 3
#> 4
#> 5
#> 6
#> 7
#> 8
#> 9
#> 10
#> 11
#> ---------------
#>
#> Not all Values Compared Equal
#> All rows are shown in table below
#>
#> =================================
#> Variable No of Differences
#> ---------------------------------
#> Sepal.Length 1
#> Sepal.Width 1
#> Petal.Length 1
#> Petal.Width 1
#> Species 1
#> ---------------------------------
#>
#>
#> All rows are shown in table below
#>
#> ============================================
#> VARIABLE ..ROWNUMBER.. BASE COMPARE
#> --------------------------------------------
#> Sepal.Length 1 5.1 <NA>
#> --------------------------------------------
#>
#>
#> All rows are shown in table below
#>
#> ===========================================
#> VARIABLE ..ROWNUMBER.. BASE COMPARE
#> -------------------------------------------
#> Sepal.Width 1 3.5 5
#> -------------------------------------------
#>
#>
#> All rows are shown in table below
#>
#> ============================================
#> VARIABLE ..ROWNUMBER.. BASE COMPARE
#> --------------------------------------------
#> Petal.Length 1 1.4 <NA>
#> --------------------------------------------
#>
#>
#> All rows are shown in table below
#>
#> ===========================================
#> VARIABLE ..ROWNUMBER.. BASE COMPARE
#> -------------------------------------------
#> Petal.Width 1 0.2 <NA>
#> -------------------------------------------
#>
#>
#> All rows are shown in table below
#>
#> ==========================================
#> VARIABLE ..ROWNUMBER.. BASE COMPARE
#> ------------------------------------------
#> Species 1 setosa <NA>
#> ------------------------------------------
#>
print( COMPARE , "Sepal.Length" )
#> Differences found between the objects!
#>
#> A summary is given below.
#>
#> There are rows in BASE that are not in COMPARE !!
#> First 10 of 149 rows are shown in table below
#>
#> ===============
#> ..ROWNUMBER..
#> ---------------
#> 2
#> 3
#> 4
#> 5
#> 6
#> 7
#> 8
#> 9
#> 10
#> 11
#> ---------------
#>
#> Not all Values Compared Equal
#> All rows are shown in table below
#>
#> =================================
#> Variable No of Differences
#> ---------------------------------
#> Sepal.Length 1
#> Sepal.Width 1
#> Petal.Length 1
#> Petal.Width 1
#> Species 1
#> ---------------------------------
#>
#>
#> All rows are shown in table below
#>
#> ============================================
#> VARIABLE ..ROWNUMBER.. BASE COMPARE
#> --------------------------------------------
#> Sepal.Length 1 5.1 <NA>
#> --------------------------------------------
#>
#>
#> All rows are shown in table below
#>
#> ===========================================
#> VARIABLE ..ROWNUMBER.. BASE COMPARE
#> -------------------------------------------
#> Sepal.Width 1 3.5 5
#> -------------------------------------------
#>
#>
#> All rows are shown in table below
#>
#> ============================================
#> VARIABLE ..ROWNUMBER.. BASE COMPARE
#> --------------------------------------------
#> Petal.Length 1 1.4 <NA>
#> --------------------------------------------
#>
#>
#> All rows are shown in table below
#>
#> ===========================================
#> VARIABLE ..ROWNUMBER.. BASE COMPARE
#> -------------------------------------------
#> Petal.Width 1 0.2 <NA>
#> -------------------------------------------
#>
#>
#> All rows are shown in table below
#>
#> ==========================================
#> VARIABLE ..ROWNUMBER.. BASE COMPARE
#> ------------------------------------------
#> Species 1 setosa <NA>
#> ------------------------------------------
#>
#### Sample data frames
DF1 <- data.frame(
id = c(1,2,3,4,5,6),
v1 = letters[1:6],
v2 = c(NA , NA , 1 , 2 , 3 , NA)
)
DF2 <- data.frame(
id = c(1,2,3,4,5,7),
v1 = letters[1:6],
v2 = c(NA , NA , 1 , 2 , NA , NA),
v3 = c(NA , NA , 1 , 2 , NA , 4)
)
diffdf(DF1 , DF1 , keys = "id")
#> No issues were found!
# We can control matching with scale/location for example:
DF1 <- data.frame(
id = c(1,2,3,4,5,6),
v1 = letters[1:6],
v2 = c(1,2,3,4,5,6)
)
DF2 <- data.frame(
id = c(1,2,3,4,5,6),
v1 = letters[1:6],
v2 = c(1.1,2,3,4,5,6)
)
diffdf(DF1 , DF2 , keys = "id")
#> Warning:
#> Not all Values Compared Equal
#> Differences found between the objects!
#>
#> A summary is given below.
#>
#> Not all Values Compared Equal
#> All rows are shown in table below
#>
#> =============================
#> Variable No of Differences
#> -----------------------------
#> v2 1
#> -----------------------------
#>
#>
#> All rows are shown in table below
#>
#> =============================
#> VARIABLE id BASE COMPARE
#> -----------------------------
#> v2 1 1 1.1
#> -----------------------------
#>
diffdf(DF1 , DF2 , keys = "id", tolerance = 0.2)
#> No issues were found!
diffdf(DF1 , DF2 , keys = "id", scale = 10, tolerance = 0.2)
#> No issues were found!
# We can use strict_factor to compare factors with characters for example:
DF1 <- data.frame(
id = c(1,2,3,4,5,6),
v1 = letters[1:6],
v2 = c(NA , NA , 1 , 2 , 3 , NA),
stringsAsFactors = FALSE
)
DF2 <- data.frame(
id = c(1,2,3,4,5,6),
v1 = letters[1:6],
v2 = c(NA , NA , 1 , 2 , 3 , NA)
)
diffdf(DF1 , DF2 , keys = "id", strict_factor = TRUE)
#> No issues were found!
diffdf(DF1 , DF2 , keys = "id", strict_factor = FALSE)
#> No issues were found!