# The comparedf function

#### Ethan Heinzen, Ryan Lennon, Andrew Hanson

# Introduction

The `comparedf()` function can be used to determine and report differences between two data.frames. It was written in the spirit of replacing `PROC COMPARE` from SAS.

    library(arsenal)

Why “comparedf”? We originally called this function `compare.data.frame()`, using `testthat::compare()` as our S3 generic, but that ended up getting us in trouble because of conflicting object structures. Why this didn’t occur to us at the time remains a mystery. To replace it, we brainstormed several ideas (`comparedf()`, `dfcompare()`, `collate()`, `comparison()`) but settled on the former for three reasons:

1. There were no other objects with that generic or class (see `testthat::compare()` and `compare::compare()`).

2. It is mnemonically easy to remember (we “compare data.frames”, not “data.frames compare”).

3. It tab auto-completes from the original “compare”.

# Basic examples

We first build two similar data.frames to compare.

    df1 <- data.frame(id = paste0("person", 1:3),
                      a = c("a", "b", "c"),
                      b = c(1, 3, 4),
                      c = c("f", "e", "d"),
                      row.names = paste0("rn", 1:3),
                      stringsAsFactors = FALSE)
    df2 <- data.frame(id = paste0("person", 3:1),
                      a = c("c", "b", "a"),
                      b = c(1, 3, 4),
                      d = paste0("rn", 1:3),
                      row.names = paste0("rn", c(1,3,2)),
                      stringsAsFactors = FALSE)

To compare these datasets, simply pass them to the `comparedf()` function:

    comparedf(df1, df2)

    Compare Object

    Function Call:
    comparedf(x = df1, y = df2)

    Shared: 3 non-by variables and 3 observations.
    Not shared: 2 variables and 0 observations.

    Differences found in 2/3 variables compared.
    0 variables compared have non-identical attributes.

Use `summary()` to get a more detailed summary

    summary(comparedf(df1, df2))

Summary of data.frames
version | arg | ncol | nrow
--- | --- | --- | ---
x | df1 | 4 | 3
y | df2 | 4 | 3

Summary of overall comparison
statistic | value
--- | ---
Number of by-variables | 0
Number of non-by variables in common | 3
Number of variables compared | 3
Number of variables in x but not y | 1
Number of variables in y but not x | 1
Number of variables compared with some values unequal | 2
Number of variables compared with all values equal | 1
Number of observations in common | 3
Number of observations in x but not y | 0
Number of observations in y but not x | 0
Number of observations with some compared variables unequal | 2
Number of observations with all compared variables equal | 1
Number of values unequal | 4

Variables not shared
version | variable | position | class
--- | --- | --- | ---
x | c | 4 | character
y | d | 4 | character

Other variables not compared
No other variables not compared

Observations not shared
No observations not shared

Differences detected by variable
var.x | var.y | n | NAs
--- | --- | --- | ---
id | id | 2 | 0
a | a | 2 | 0
b | b | 0 | 0

Differences detected
var.x | var.y | ..row.names.. | values.x | values.y | row.x | row.y
--- | --- | --- | --- | --- | --- | ---
id | id | 1 | person1 | person3 | 1 | 1
id | id | 3 | person3 | person1 | 3 | 3
a | a | 1 | a | c | 1 | 1
a | a | 3 | c | a | 3 | 3

Non-identical attributes
No non-identical attributes

By default, the datasets are compared row-by-row. To change this, use the `by=` or `by.x=` and `by.y=` arguments:

    summary(comparedf(df1, df2, by = "id"))

Summary of data.frames
version | arg | ncol | nrow
--- | --- | --- | ---
x | df1 | 4 | 3
y | df2 | 4 | 3

Summary of overall comparison
statistic | value
--- | ---
Number of by-variables | 1
Number of non-by variables in common | 2
Number of variables compared | 2
Number of variables in x but not y | 1
Number of variables in y but not x | 1
Number of variables compared with some values unequal | 1
Number of variables compared with all values equal | 1
Number of observations in common | 3
Number of observations in x but not y | 0
Number of observations in y but not x | 0
Number of observations with some compared variables unequal | 2
Number of observations with all compared variables equal | 1
Number of values unequal | 2

Variables not shared
version | variable | position | class
--- | --- | --- | ---
x | c | 4 | character
y | d | 4 | character

Other variables not compared
No other variables not compared

Observations not shared
No observations not shared

Differences detected by variable
var.x | var.y | n | NAs
--- | --- | --- | ---
a | a | 0 | 0
b | b | 2 | 0

Differences detected
var.x | var.y | id | values.x | values.y | row.x | row.y
--- | --- | --- | --- | --- | --- | ---
b | b | person1 | 1 | 4 | 1 | 3
b | b | person3 | 4 | 1 | 3 | 1

Non-identical attributes
No non-identical attributes

# A larger example

Let’s muck up the `mockstudy` data.

    data(mockstudy)
    mockstudy2 <- muck_up_mockstudy()

We’ve changed row order, so let’s compare by the case ID:

    summary(comparedf(mockstudy, mockstudy2, by = "case"))

Summary of data.frames
version | arg | ncol | nrow
--- | --- | --- | ---
x | mockstudy | 14 | 1499
y | mockstudy2 | 13 | 1495

Summary of overall comparison
statistic | value
--- | ---
Number of by-variables | 1
Number of non-by variables in common | 9
Number of variables compared | 7
Number of variables in x but not y | 4
Number of variables in y but not x | 3
Number of variables compared with some values unequal | 3
Number of variables compared with all values equal | 4
Number of observations in common | 1495
Number of observations in x but not y | 4
Number of observations in y but not x | 0
Number of observations with some compared variables unequal | 1495
Number of observations with all compared variables equal | 0
Number of values unequal | 1762

Variables not shared
version | variable | position | class
--- | --- | --- | ---
x | age | 2 | integer
x | arm | 3 | character
x | fu.time | 6 | integer
x | fu.stat | 7 | integer
y | fu_time | 11 | integer
y | fu stat | 12 | integer
y | Arm | 13 | character

Other variables not compared
var.x | pos.x | class.x | var.y | pos.y | class.y
--- | --- | --- | --- | --- | ---
race | 5 | character | race | 3 | factor
ast | 12 | integer | ast | 8 | numeric

Observations not shared
version | case | observation
--- | --- | ---
x | 88989 | 9
x | 90158 | 8
x | 99508 | 7
x | 112263 | 5

Differences detected by variable
var.x | var.y | n | NAs
--- | --- | --- | ---
sex | sex | 1495 | 0
ps | ps | 1 | 1
hgb | hgb | 266 | 266
bmi | bmi | 0 | 0
alk.phos | alk.phos | 0 | 0
mdquality.s | mdquality.s | 0 | 0
age.ord | age.ord | 0 | 0

Differences detected (1741 not shown)
var.x | var.y | case | values.x | values.y | row.x | row.y
--- | --- | --- | --- | --- | --- | ---
sex | sex | 76170 | Male | Male | 26 | 20
sex | sex | 76240 | Male | Male | 27 | 21
sex | sex | 76431 | Female | Female | 28 | 22
sex | sex | 76712 | Male | Male | 29 | 23
sex | sex | 76780 | Female | Female | 30 | 24
sex | sex | 77066 | Female | Female | 31 | 25
sex | sex | 77316 | Male | Male | 32 | 26
sex | sex | 77355 | Male | Male | 33 | 27
sex | sex | 77591 | Male | Male | 34 | 28
sex | sex | 77851 | Male | Male | 35 | 29
ps | ps | 86205 | 0 | NA | 6 | 3
hgb | hgb | 88714 | NA | -9 | 192 | 186
hgb | hgb | 88955 | NA | -9 | 204 | 198
hgb | hgb | 89549 | NA | -9 | 229 | 223
hgb | hgb | 89563 | NA | -9 | 231 | 225
hgb | hgb | 89584 | NA | -9 | 237 | 231
hgb | hgb | 89591 | NA | -9 | 238 | 232
hgb | hgb | 89595 | NA | -9 | 239 | 233
hgb | hgb | 89647 | NA | -9 | 243 | 237
hgb | hgb | 89665 | NA | -9 | 244 | 238
hgb | hgb | 89827 | NA | -9 | 255 | 249

Non-identical attributes
var.x | var.y | name
--- | --- | ---
sex | sex | label
sex | sex | levels
race | race | class
race | race | label
race | race | levels
bmi | bmi | label

# Column name comparison options

It is possible to change which column names are considered “the same variable”.

## Ignoring case

For example, to ignore case in variable names (so that `Arm` and `arm` are considered the same), pass `tol.vars = "case"`.

You can do this using `comparedf.control()`

    summary(comparedf(mockstudy, mockstudy2, by = "case", control = comparedf.control(tol.vars = "case")))

or pass it through the `...` arguments.

    summary(comparedf(mockstudy, mockstudy2, by = "case", tol.vars = "case"))

Summary of data.frames
version | arg | ncol | nrow
--- | --- | --- | ---
x | mockstudy | 14 | 1499
y | mockstudy2 | 13 | 1495

Summary of overall comparison
statistic | value
--- | ---
Number of by-variables | 1
Number of non-by variables in common | 10
Number of variables compared | 8
Number of variables in x but not y | 3
Number of variables in y but not x | 2
Number of variables compared with some values unequal | 3
Number of variables compared with all values equal | 5
Number of observations in common | 1495
Number of observations in x but not y | 4
Number of observations in y but not x | 0
Number of observations with some compared variables unequal | 1495
Number of observations with all compared variables equal | 0
Number of values unequal | 1762

Variables not shared
version | variable | position | class
--- | --- | --- | ---
x | age | 2 | integer
x | fu.time | 6 | integer
x | fu.stat | 7 | integer
y | fu_time | 11 | integer
y | fu stat | 12 | integer

Other variables not compared
var.x | pos.x | class.x | var.y | pos.y | class.y
--- | --- | --- | --- | --- | ---
race | 5 | character | race | 3 | factor
ast | 12 | integer | ast | 8 | numeric

Observations not shared
version | case | observation
--- | --- | ---
x | 88989 | 9
x | 90158 | 8
x | 99508 | 7
x | 112263 | 5

Differences detected by variable
var.x | var.y | n | NAs
--- | --- | --- | ---
arm | Arm | 0 | 0
sex | sex | 1495 | 0
ps | ps | 1 | 1
hgb | hgb | 266 | 266
bmi | bmi | 0 | 0
alk.phos | alk.phos | 0 | 0
mdquality.s | mdquality.s | 0 | 0
age.ord | age.ord | 0 | 0

Differences detected (1741 not shown)
var.x | var.y | case | values.x | values.y | row.x | row.y
--- | --- | --- | --- | --- | --- | ---
sex | sex | 76170 | Male | Male | 26 | 20
sex | sex | 76240 | Male | Male | 27 | 21
sex | sex | 76431 | Female | Female | 28 | 22
sex | sex | 76712 | Male | Male | 29 | 23
sex | sex | 76780 | Female | Female | 30 | 24
sex | sex | 77066 | Female | Female | 31 | 25
sex | sex | 77316 | Male | Male | 32 | 26
sex | sex | 77355 | Male | Male | 33 | 27
sex | sex | 77591 | Male | Male | 34 | 28
sex | sex | 77851 | Male | Male | 35 | 29
ps | ps | 86205 | 0 | NA | 6 | 3
hgb | hgb | 88714 | NA | -9 | 192 | 186
hgb | hgb | 88955 | NA | -9 | 204 | 198
hgb | hgb | 89549 | NA | -9 | 229 | 223
hgb | hgb | 89563 | NA | -9 | 231 | 225
hgb | hgb | 89584 | NA | -9 | 237 | 231
hgb | hgb | 89591 | NA | -9 | 238 | 232
hgb | hgb | 89595 | NA | -9 | 239 | 233
hgb | hgb | 89647 | NA | -9 | 243 | 237
hgb | hgb | 89665 | NA | -9 | 244 | 238
hgb | hgb | 89827 | NA | -9 | 255 | 249

Non-identical attributes
var.x | var.y | name
--- | --- | ---
arm | Arm | label
sex | sex | label
sex | sex | levels
race | race | class
race | race | label
race | race | levels
bmi | bmi | label

## Treating dots and underscores the same (equivalence classes)

It is possible to treat certain characters or sets of characters as the same by passing a character vector of equivalence classes to the `tol.vars=` argument.

In short, each string in the vector is split into single characters, and the resulting set of characters is replaced by the first character in the string. For example, passing `c("._")` would replace all underscores with dots in the column names of both datasets. Similarly, passing `c("aA", "BbCc")` would replace all instances of `"A"` with `"a"` and all instances of `"b"`, `"C"`, or `"c"` with `"B"`. This is one way to ignore case for certain letters. Otherwise, it’s possible to combine the equivalence classes with ignoring case, by passing (e.g.) `c("._", "case")`.

Passing a single character as an element this vector will replace that character with the empty string. For example, passing c(” “,”.”) would remove all spaces and dots from the column names.

For mockstudy, let’s treat dots, underscores, and spaces as the same, and ignore case:

    summary(comparedf(mockstudy, mockstudy2, by = "case",
                    tol.vars = c("._ ", "case") # dots=underscores=spaces, ignore case
    ))

Summary of data.frames
version | arg | ncol | nrow
--- | --- | --- | ---
x | mockstudy | 14 | 1499
y | mockstudy2 | 13 | 1495

Summary of overall comparison
statistic | value
--- | ---
Number of by-variables | 1
Number of non-by variables in common | 12
Number of variables compared | 10
Number of variables in x but not y | 1
Number of variables in y but not x | 0
Number of variables compared with some values unequal | 3
Number of variables compared with all values equal | 7
Number of observations in common | 1495
Number of observations in x but not y | 4
Number of observations in y but not x | 0
Number of observations with some compared variables unequal | 1495
Number of observations with all compared variables equal | 0
Number of values unequal | 1762

Variables not shared
version | variable | position | class
--- | --- | --- | ---
x | age | 2 | integer

Other variables not compared
var.x | pos.x | class.x | var.y | pos.y | class.y
--- | --- | --- | --- | --- | ---
race | 5 | character | race | 3 | factor
ast | 12 | integer | ast | 8 | numeric

Observations not shared
version | case | observation
--- | --- | ---
x | 88989 | 9
x | 90158 | 8
x | 99508 | 7
x | 112263 | 5

Differences detected by variable
var.x | var.y | n | NAs
--- | --- | --- | ---
arm | Arm | 0 | 0
sex | sex | 1495 | 0
fu.time | fu_time | 0 | 0
fu.stat | fu stat | 0 | 0
ps | ps | 1 | 1
hgb | hgb | 266 | 266
bmi | bmi | 0 | 0
alk.phos | alk.phos | 0 | 0
mdquality.s | mdquality.s | 0 | 0
age.ord | age.ord | 0 | 0

Differences detected (1741 not shown)
var.x | var.y | case | values.x | values.y | row.x | row.y
--- | --- | --- | --- | --- | --- | ---
sex | sex | 76170 | Male | Male | 26 | 20
sex | sex | 76240 | Male | Male | 27 | 21
sex | sex | 76431 | Female | Female | 28 | 22
sex | sex | 76712 | Male | Male | 29 | 23
sex | sex | 76780 | Female | Female | 30 | 24
sex | sex | 77066 | Female | Female | 31 | 25
sex | sex | 77316 | Male | Male | 32 | 26
sex | sex | 77355 | Male | Male | 33 | 27
sex | sex | 77591 | Male | Male | 34 | 28
sex | sex | 77851 | Male | Male | 35 | 29
ps | ps | 86205 | 0 | NA | 6 | 3
hgb | hgb | 88714 | NA | -9 | 192 | 186
hgb | hgb | 88955 | NA | -9 | 204 | 198
hgb | hgb | 89549 | NA | -9 | 229 | 223
hgb | hgb | 89563 | NA | -9 | 231 | 225
hgb | hgb | 89584 | NA | -9 | 237 | 231
hgb | hgb | 89591 | NA | -9 | 238 | 232
hgb | hgb | 89595 | NA | -9 | 239 | 233
hgb | hgb | 89647 | NA | -9 | 243 | 237
hgb | hgb | 89665 | NA | -9 | 244 | 238
hgb | hgb | 89827 | NA | -9 | 255 | 249

Non-identical attributes
var.x | var.y | name
--- | --- | ---
arm | Arm | label
sex | sex | label
sex | sex | levels
race | race | class
race | race | label
race | race | levels
bmi | bmi | label

## Manually specifying columns to match together

If you pass a named vector to the `tol.vars=` argument, `comparedf()` will line up the names of that vector to the column names of `x` and the values of that vector to the column names of `y`. In this way, you can manually specify which non-identically-named columns to compare.

For mockstudy, let’s specify our variables manually in this way:

    summary(comparedf(mockstudy, mockstudy2, by = "case",
                    tol.vars = c(arm = "Arm", fu.stat = "fu stat", fu.time = "fu_time")
    ))

Summary of data.frames
version | arg | ncol | nrow
--- | --- | --- | ---
x | mockstudy | 14 | 1499
y | mockstudy2 | 13 | 1495

Summary of overall comparison
statistic | value
--- | ---
Number of by-variables | 1
Number of non-by variables in common | 12
Number of variables compared | 10
Number of variables in x but not y | 1
Number of variables in y but not x | 0
Number of variables compared with some values unequal | 3
Number of variables compared with all values equal | 7
Number of observations in common | 1495
Number of observations in x but not y | 4
Number of observations in y but not x | 0
Number of observations with some compared variables unequal | 1495
Number of observations with all compared variables equal | 0
Number of values unequal | 1762

Variables not shared
version | variable | position | class
--- | --- | --- | ---
x | age | 2 | integer

Other variables not compared
var.x | pos.x | class.x | var.y | pos.y | class.y
--- | --- | --- | --- | --- | ---
race | 5 | character | race | 3 | factor
ast | 12 | integer | ast | 8 | numeric

Observations not shared
version | case | observation
--- | --- | ---
x | 88989 | 9
x | 90158 | 8
x | 99508 | 7
x | 112263 | 5

Differences detected by variable
var.x | var.y | n | NAs
--- | --- | --- | ---
arm | Arm | 0 | 0
sex | sex | 1495 | 0
fu.time | fu_time | 0 | 0
fu.stat | fu stat | 0 | 0
ps | ps | 1 | 1
hgb | hgb | 266 | 266
bmi | bmi | 0 | 0
alk.phos | alk.phos | 0 | 0
mdquality.s | mdquality.s | 0 | 0
age.ord | age.ord | 0 | 0

Differences detected (1741 not shown)
var.x | var.y | case | values.x | values.y | row.x | row.y
--- | --- | --- | --- | --- | --- | ---
sex | sex | 76170 | Male | Male | 26 | 20
sex | sex | 76240 | Male | Male | 27 | 21
sex | sex | 76431 | Female | Female | 28 | 22
sex | sex | 76712 | Male | Male | 29 | 23
sex | sex | 76780 | Female | Female | 30 | 24
sex | sex | 77066 | Female | Female | 31 | 25
sex | sex | 77316 | Male | Male | 32 | 26
sex | sex | 77355 | Male | Male | 33 | 27
sex | sex | 77591 | Male | Male | 34 | 28
sex | sex | 77851 | Male | Male | 35 | 29
ps | ps | 86205 | 0 | NA | 6 | 3
hgb | hgb | 88714 | NA | -9 | 192 | 186
hgb | hgb | 88955 | NA | -9 | 204 | 198
hgb | hgb | 89549 | NA | -9 | 229 | 223
hgb | hgb | 89563 | NA | -9 | 231 | 225
hgb | hgb | 89584 | NA | -9 | 237 | 231
hgb | hgb | 89591 | NA | -9 | 238 | 232
hgb | hgb | 89595 | NA | -9 | 239 | 233
hgb | hgb | 89647 | NA | -9 | 243 | 237
hgb | hgb | 89665 | NA | -9 | 244 | 238
hgb | hgb | 89827 | NA | -9 | 255 | 249

Non-identical attributes
var.x | var.y | name
--- | --- | ---
arm | Arm | label
sex | sex | label
sex | sex | levels
race | race | class
race | race | label
race | race | levels
bmi | bmi | label

# Column comparison options

## Logical tolerance

Use the `tol.logical=` argument to change how logicals are compared. By default, they’re expected to be equal to each other.

## Numeric tolerance

To allow numeric differences of a certain tolerance, use the `tol.num=` and `tol.num.val=` options. `tol.num.val=` determines the maximum (unsigned) difference tolerated if `tol.num="absolute"` (default), and determines the maximum (unsigned) percent difference tolerated if `tol.num="percent"`.

Also note the option `int.as.num=`, which determines whether integers and numerics should be compared despite their class difference. If `TRUE`, the integers are coerced to numeric. Note that `mockstudy$ast` is integer, while `mockstudy2$ast` is numeric:

    summary(comparedf(mockstudy, mockstudy2, by = "case",
                    tol.vars = c("._ ", "case"), # dots=underscores=spaces, ignore case
                    int.as.num = TRUE            # compare integers and numerics
    ))

Summary of data.frames
version | arg | ncol | nrow
--- | --- | --- | ---
x | mockstudy | 14 | 1499
y | mockstudy2 | 13 | 1495

Summary of overall comparison
statistic | value
--- | ---
Number of by-variables | 1
Number of non-by variables in common | 12
Number of variables compared | 11
Number of variables in x but not y | 1
Number of variables in y but not x | 0
Number of variables compared with some values unequal | 4
Number of variables compared with all values equal | 7
Number of observations in common | 1495
Number of observations in x but not y | 4
Number of observations in y but not x | 0
Number of observations with some compared variables unequal | 1495
Number of observations with all compared variables equal | 0
Number of values unequal | 1765

Variables not shared
version | variable | position | class
--- | --- | --- | ---
x | age | 2 | integer

Other variables not compared
var.x | pos.x | class.x | var.y | pos.y | class.y
--- | --- | --- | --- | --- | ---
race | 5 | character | race | 3 | factor

Observations not shared
version | case | observation
--- | --- | ---
x | 88989 | 9
x | 90158 | 8
x | 99508 | 7
x | 112263 | 5

Differences detected by variable
var.x | var.y | n | NAs
--- | --- | --- | ---
arm | Arm | 0 | 0
sex | sex | 1495 | 0
fu.time | fu_time | 0 | 0
fu.stat | fu stat | 0 | 0
ps | ps | 1 | 1
hgb | hgb | 266 | 266
bmi | bmi | 0 | 0
alk.phos | alk.phos | 0 | 0
ast | ast | 3 | 0
mdquality.s | mdquality.s | 0 | 0
age.ord | age.ord | 0 | 0

Differences detected (1741 not shown)
var.x | var.y | case | values.x | values.y | row.x | row.y
--- | --- | --- | --- | --- | --- | ---
sex | sex | 76170 | Male | Male | 26 | 20
sex | sex | 76240 | Male | Male | 27 | 21
sex | sex | 76431 | Female | Female | 28 | 22
sex | sex | 76712 | Male | Male | 29 | 23
sex | sex | 76780 | Female | Female | 30 | 24
sex | sex | 77066 | Female | Female | 31 | 25
sex | sex | 77316 | Male | Male | 32 | 26
sex | sex | 77355 | Male | Male | 33 | 27
sex | sex | 77591 | Male | Male | 34 | 28
sex | sex | 77851 | Male | Male | 35 | 29
ps | ps | 86205 | 0 | NA | 6 | 3
hgb | hgb | 88714 | NA | -9 | 192 | 186
hgb | hgb | 88955 | NA | -9 | 204 | 198
hgb | hgb | 89549 | NA | -9 | 229 | 223
hgb | hgb | 89563 | NA | -9 | 231 | 225
hgb | hgb | 89584 | NA | -9 | 237 | 231
hgb | hgb | 89591 | NA | -9 | 238 | 232
hgb | hgb | 89595 | NA | -9 | 239 | 233
hgb | hgb | 89647 | NA | -9 | 243 | 237
hgb | hgb | 89665 | NA | -9 | 244 | 238
hgb | hgb | 89827 | NA | -9 | 255 | 249
ast | ast | 86205 | 27 | 36 | 6 | 3
ast | ast | 105271 | 100 | 36 | 3 | 2
ast | ast | 110754 | 35 | 36 | 1 | 1

Non-identical attributes
var.x | var.y | name
--- | --- | ---
arm | Arm | label
sex | sex | label
sex | sex | levels
race | race | class
race | race | label
race | race | levels
bmi | bmi | label

Suppose a tolerance of up to 10 is allowed for `ast`:

    summary(comparedf(mockstudy, mockstudy2, by = "case",
                    tol.vars = c("._ ", "case"), # dots=underscores=spaces, ignore case
                    int.as.num = TRUE,           # compare integers and numerics
                    tol.num.val = 10             # allow absolute differences <= 10
    ))

Summary of data.frames
version | arg | ncol | nrow
--- | --- | --- | ---
x | mockstudy | 14 | 1499
y | mockstudy2 | 13 | 1495

Summary of overall comparison
statistic | value
--- | ---
Number of by-variables | 1
Number of non-by variables in common | 12
Number of variables compared | 11
Number of variables in x but not y | 1
Number of variables in y but not x | 0
Number of variables compared with some values unequal | 4
Number of variables compared with all values equal | 7
Number of observations in common | 1495
Number of observations in x but not y | 4
Number of observations in y but not x | 0
Number of observations with some compared variables unequal | 1495
Number of observations with all compared variables equal | 0
Number of values unequal | 1763

Variables not shared
version | variable | position | class
--- | --- | --- | ---
x | age | 2 | integer

Other variables not compared
var.x | pos.x | class.x | var.y | pos.y | class.y
--- | --- | --- | --- | --- | ---
race | 5 | character | race | 3 | factor

Observations not shared
version | case | observation
--- | --- | ---
x | 88989 | 9
x | 90158 | 8
x | 99508 | 7
x | 112263 | 5

Differences detected by variable
var.x | var.y | n | NAs
--- | --- | --- | ---
arm | Arm | 0 | 0
sex | sex | 1495 | 0
fu.time | fu_time | 0 | 0
fu.stat | fu stat | 0 | 0
ps | ps | 1 | 1
hgb | hgb | 266 | 266
bmi | bmi | 0 | 0
alk.phos | alk.phos | 0 | 0
ast | ast | 1 | 0
mdquality.s | mdquality.s | 0 | 0
age.ord | age.ord | 0 | 0

Differences detected (1741 not shown)
var.x | var.y | case | values.x | values.y | row.x | row.y
--- | --- | --- | --- | --- | --- | ---
sex | sex | 76170 | Male | Male | 26 | 20
sex | sex | 76240 | Male | Male | 27 | 21
sex | sex | 76431 | Female | Female | 28 | 22
sex | sex | 76712 | Male | Male | 29 | 23
sex | sex | 76780 | Female | Female | 30 | 24
sex | sex | 77066 | Female | Female | 31 | 25
sex | sex | 77316 | Male | Male | 32 | 26
sex | sex | 77355 | Male | Male | 33 | 27
sex | sex | 77591 | Male | Male | 34 | 28
sex | sex | 77851 | Male | Male | 35 | 29
ps | ps | 86205 | 0 | NA | 6 | 3
hgb | hgb | 88714 | NA | -9 | 192 | 186
hgb | hgb | 88955 | NA | -9 | 204 | 198
hgb | hgb | 89549 | NA | -9 | 229 | 223
hgb | hgb | 89563 | NA | -9 | 231 | 225
hgb | hgb | 89584 | NA | -9 | 237 | 231
hgb | hgb | 89591 | NA | -9 | 238 | 232
hgb | hgb | 89595 | NA | -9 | 239 | 233
hgb | hgb | 89647 | NA | -9 | 243 | 237
hgb | hgb | 89665 | NA | -9 | 244 | 238
hgb | hgb | 89827 | NA | -9 | 255 | 249
ast | ast | 105271 | 100 | 36 | 3 | 2

Non-identical attributes
var.x | var.y | name
--- | --- | ---
arm | Arm | label
sex | sex | label
sex | sex | levels
race | race | class
race | race | label
race | race | levels
bmi | bmi | label

## Factor tolerance

By default, factors are compared to each other based on both the labels and the underlying numeric levels. Set `tol.factor="levels"` to match only the numeric levels, or set `tol.factor="labels"` to match only the labels.

    summary(comparedf(mockstudy, mockstudy2, by = "case",
                    tol.vars = c("._ ", "case"), # dots=underscores=spaces, ignore case
                    int.as.num = TRUE,           # compare integers and numerics
                    tol.num.val = 10,            # allow absolute differences <= 10
                    tol.factor = "labels"        # match only factor labels
    ))

Summary of data.frames
version | arg | ncol | nrow
--- | --- | --- | ---
x | mockstudy | 14 | 1499
y | mockstudy2 | 13 | 1495

Summary of overall comparison
statistic | value
--- | ---
Number of by-variables | 1
Number of non-by variables in common | 12
Number of variables compared | 11
Number of variables in x but not y | 1
Number of variables in y but not x | 0
Number of variables compared with some values unequal | 3
Number of variables compared with all values equal | 8
Number of observations in common | 1495
Number of observations in x but not y | 4
Number of observations in y but not x | 0
Number of observations with some compared variables unequal | 268
Number of observations with all compared variables equal | 1227
Number of values unequal | 268

Variables not shared
version | variable | position | class
--- | --- | --- | ---
x | age | 2 | integer

Other variables not compared
var.x | pos.x | class.x | var.y | pos.y | class.y
--- | --- | --- | --- | --- | ---
race | 5 | character | race | 3 | factor

Observations not shared
version | case | observation
--- | --- | ---
x | 88989 | 9
x | 90158 | 8
x | 99508 | 7
x | 112263 | 5

Differences detected by variable
var.x | var.y | n | NAs
--- | --- | --- | ---
arm | Arm | 0 | 0
sex | sex | 0 | 0
fu.time | fu_time | 0 | 0
fu.stat | fu stat | 0 | 0
ps | ps | 1 | 1
hgb | hgb | 266 | 266
bmi | bmi | 0 | 0
alk.phos | alk.phos | 0 | 0
ast | ast | 1 | 0
mdquality.s | mdquality.s | 0 | 0
age.ord | age.ord | 0 | 0

Differences detected (256 not shown)
var.x | var.y | case | values.x | values.y | row.x | row.y
--- | --- | --- | --- | --- | --- | ---
ps | ps | 86205 | 0 | NA | 6 | 3
hgb | hgb | 88714 | NA | -9 | 192 | 186
hgb | hgb | 88955 | NA | -9 | 204 | 198
hgb | hgb | 89549 | NA | -9 | 229 | 223
hgb | hgb | 89563 | NA | -9 | 231 | 225
hgb | hgb | 89584 | NA | -9 | 237 | 231
hgb | hgb | 89591 | NA | -9 | 238 | 232
hgb | hgb | 89595 | NA | -9 | 239 | 233
hgb | hgb | 89647 | NA | -9 | 243 | 237
hgb | hgb | 89665 | NA | -9 | 244 | 238
hgb | hgb | 89827 | NA | -9 | 255 | 249
ast | ast | 105271 | 100 | 36 | 3 | 2

Non-identical attributes
var.x | var.y | name
--- | --- | ---
arm | Arm | label
sex | sex | label
sex | sex | levels
race | race | class
race | race | label
race | race | levels
bmi | bmi | label

Also note the option `factor.as.char=`, which determines whether factors and characters should be compared despite their class difference. If `TRUE`, the factors are coerced to characters. Note that `mockstudy$race` is a character, while `mockstudy2$race` is a factor:

    summary(comparedf(mockstudy, mockstudy2, by = "case",
                    tol.vars = c("._ ", "case"), # dots=underscores=spaces, ignore case
                    int.as.num = TRUE,           # compare integers and numerics
                    tol.num.val = 10,            # allow absolute differences <= 10
                    tol.factor = "labels",       # match only factor labels
                    factor.as.char = TRUE        # compare factors and characters
    ))

Summary of data.frames
version | arg | ncol | nrow
--- | --- | --- | ---
x | mockstudy | 14 | 1499
y | mockstudy2 | 13 | 1495

Summary of overall comparison
statistic | value
--- | ---
Number of by-variables | 1
Number of non-by variables in common | 12
Number of variables compared | 12
Number of variables in x but not y | 1
Number of variables in y but not x | 0
Number of variables compared with some values unequal | 4
Number of variables compared with all values equal | 8
Number of observations in common | 1495
Number of observations in x but not y | 4
Number of observations in y but not x | 0
Number of observations with some compared variables unequal | 1339
Number of observations with all compared variables equal | 156
Number of values unequal | 1553

Variables not shared
version | variable | position | class
--- | --- | --- | ---
x | age | 2 | integer

Other variables not compared
No other variables not compared

Observations not shared
version | case | observation
--- | --- | ---
x | 88989 | 9
x | 90158 | 8
x | 99508 | 7
x | 112263 | 5

Differences detected by variable
var.x | var.y | n | NAs
--- | --- | --- | ---
arm | Arm | 0 | 0
sex | sex | 0 | 0
race | race | 1285 | 0
fu.time | fu_time | 0 | 0
fu.stat | fu stat | 0 | 0
ps | ps | 1 | 1
hgb | hgb | 266 | 266
bmi | bmi | 0 | 0
alk.phos | alk.phos | 0 | 0
ast | ast | 1 | 0
mdquality.s | mdquality.s | 0 | 0
age.ord | age.ord | 0 | 0

Differences detected (1531 not shown)
var.x | var.y | case | values.x | values.y | row.x | row.y
--- | --- | --- | --- | --- | --- | ---
race | race | 76170 | Caucasian | caucasian | 26 | 20
race | race | 76240 | Caucasian | caucasian | 27 | 21
race | race | 76431 | Caucasian | caucasian | 28 | 22
race | race | 76712 | Caucasian | caucasian | 29 | 23
race | race | 76780 | Caucasian | caucasian | 30 | 24
race | race | 77066 | Caucasian | caucasian | 31 | 25
race | race | 77316 | Caucasian | caucasian | 32 | 26
race | race | 77591 | Caucasian | caucasian | 34 | 28
race | race | 77851 | Caucasian | caucasian | 35 | 29
race | race | 77956 | Caucasian | caucasian | 36 | 30
ps | ps | 86205 | 0 | NA | 6 | 3
hgb | hgb | 88714 | NA | -9 | 192 | 186
hgb | hgb | 88955 | NA | -9 | 204 | 198
hgb | hgb | 89549 | NA | -9 | 229 | 223
hgb | hgb | 89563 | NA | -9 | 231 | 225
hgb | hgb | 89584 | NA | -9 | 237 | 231
hgb | hgb | 89591 | NA | -9 | 238 | 232
hgb | hgb | 89595 | NA | -9 | 239 | 233
hgb | hgb | 89647 | NA | -9 | 243 | 237
hgb | hgb | 89665 | NA | -9 | 244 | 238
hgb | hgb | 89827 | NA | -9 | 255 | 249
ast | ast | 105271 | 100 | 36 | 3 | 2

Non-identical attributes
var.x | var.y | name
--- | --- | ---
arm | Arm | label
sex | sex | label
sex | sex | levels
race | race | class
race | race | label
race | race | levels
bmi | bmi | label

## Character tolerance

Use the `tol.char=` argument to change how character variables are compared. By default, they are compared as-is, but they can be compared after ignoring case or trimming whitespace or both.

    summary(comparedf(mockstudy, mockstudy2, by = "case",
                    tol.vars = c("._ ", "case"), # dots=underscores=spaces, ignore case
                    int.as.num = TRUE,           # compare integers and numerics
                    tol.num.val = 10,            # allow absolute differences <= 10
                    tol.factor = "labels",       # match only factor labels
                    factor.as.char = TRUE,       # compare factors and characters
                    tol.char = "case"            # ignore case in character vectors
    ))

Summary of data.frames
version | arg | ncol | nrow
--- | --- | --- | ---
x | mockstudy | 14 | 1499
y | mockstudy2 | 13 | 1495

Summary of overall comparison
statistic | value
--- | ---
Number of by-variables | 1
Number of non-by variables in common | 12
Number of variables compared | 12
Number of variables in x but not y | 1
Number of variables in y but not x | 0
Number of variables compared with some values unequal | 3
Number of variables compared with all values equal | 9
Number of observations in common | 1495
Number of observations in x but not y | 4
Number of observations in y but not x | 0
Number of observations with some compared variables unequal | 268
Number of observations with all compared variables equal | 1227
Number of values unequal | 268

Variables not shared
version | variable | position | class
--- | --- | --- | ---
x | age | 2 | integer

Other variables not compared
No other variables not compared

Observations not shared
version | case | observation
--- | --- | ---
x | 88989 | 9
x | 90158 | 8
x | 99508 | 7
x | 112263 | 5

Differences detected by variable
var.x | var.y | n | NAs
--- | --- | --- | ---
arm | Arm | 0 | 0
sex | sex | 0 | 0
race | race | 0 | 0
fu.time | fu_time | 0 | 0
fu.stat | fu stat | 0 | 0
ps | ps | 1 | 1
hgb | hgb | 266 | 266
bmi | bmi | 0 | 0
alk.phos | alk.phos | 0 | 0
ast | ast | 1 | 0
mdquality.s | mdquality.s | 0 | 0
age.ord | age.ord | 0 | 0

Differences detected (256 not shown)
var.x | var.y | case | values.x | values.y | row.x | row.y
--- | --- | --- | --- | --- | --- | ---
ps | ps | 86205 | 0 | NA | 6 | 3
hgb | hgb | 88714 | NA | -9 | 192 | 186
hgb | hgb | 88955 | NA | -9 | 204 | 198
hgb | hgb | 89549 | NA | -9 | 229 | 223
hgb | hgb | 89563 | NA | -9 | 231 | 225
hgb | hgb | 89584 | NA | -9 | 237 | 231
hgb | hgb | 89591 | NA | -9 | 238 | 232
hgb | hgb | 89595 | NA | -9 | 239 | 233
hgb | hgb | 89647 | NA | -9 | 243 | 237
hgb | hgb | 89665 | NA | -9 | 244 | 238
hgb | hgb | 89827 | NA | -9 | 255 | 249
ast | ast | 105271 | 100 | 36 | 3 | 2

Non-identical attributes
var.x | var.y | name
--- | --- | ---
arm | Arm | label
sex | sex | label
sex | sex | levels
race | race | class
race | race | label
race | race | levels
bmi | bmi | label

## Date tolerance

Use the `tol.date=` argument to change how dates are compared. By default, they’re expected to be equal to each other.

## Other data type tolerances

Use the `tol.other=` argument to change how other objects are compared. By default, they’re expected to be `identical()`.

## Specifying tolerances for each variable

You can also provide a list of tolerance functions to `comparedf()`:

    comparedf.control(tol.char = list(
      "none",      # the default
      x1 = "case", # be case-insensitive for the variable "x1"
      x2 = function(x, y) tol.NA(x, y, x != y | y == "NA") # a custom-defined tolerance
    ))

## User-defined tolerance functions

### Details

The `comparedf.control()` function accepts functions for any of the tolerance arguments in addition to the short-hand character strings. This allows the user to create custom tolerance functions to suit his/her needs.

Any custom tolerance function must accept two vectors as arguments and return a logical vector of the same length. The `TRUE`s in the results should correspond to elements which are deemed “different”. Note that the numeric and date tolerance functions should also include a third argument for tolerance size (even if it’s not used).

CAUTION: the results should not include NAs, since the logical vector is used to subset the input data.frames. The `tol.NA()` function is useful for considering any NAs in the two vectors (but not both) as differences, in addition to other criteria.

The `tol.NA()` function is used in all default tolerance functions to help handle NAs.

### Example 1

Suppose we want to ignore any dates which are later in the second dataset than the first. We define a custom tolerance function.

    my.tol <- function(x, y, tol)
    {
      tol.NA(x, y, x > y)
    }

    date.df1 <- data.frame(dt = as.Date(c("2017-09-07", "2017-08-08", "2017-07-09", NA)))
    date.df2 <- data.frame(dt = as.Date(c("2017-10-01", "2017-08-08", "2017-07-10", "2017-01-01")))
    n.diffs(comparedf(date.df1, date.df2)) # default finds any differences

    [1] 3

    n.diffs(comparedf(date.df1, date.df2, tol.date = my.tol)) # our function identifies only the NA as different...

    [1] 1

    n.diffs(comparedf(date.df2, date.df1, tol.date = my.tol)) # ... until we change the argument order

    [1] 3

### Example 2

(Continuing our mockstudy example)

Suppose we’re okay with NAs getting replaced by -9.

    tol.minus9 <- function(x, y, tol)
    {
      idx1 <- is.na(x) & !is.na(y) & y == -9
      idx2 <- tol.num.absolute(x, y, tol) # find other absolute differences
      return(!idx1 & idx2)
    }

    summary(comparedf(mockstudy, mockstudy2, by = "case",
                    tol.vars = c("._ ", "case"), # dots=underscores=spaces, ignore case
                    int.as.num = TRUE,           # compare integers and numerics
                    tol.num.val = 10,            # allow absolute differences <= 10
                    tol.factor = "labels",       # match only factor labels
                    factor.as.char = TRUE,       # compare factors and characters
                    tol.char = "case",           # ignore case in character vectors
                    tol.num = tol.minus9         # ignore NA -> -9 changes
    ))

Summary of data.frames
version | arg | ncol | nrow
--- | --- | --- | ---
x | mockstudy | 14 | 1499
y | mockstudy2 | 13 | 1495

Summary of overall comparison
statistic | value
--- | ---
Number of by-variables | 1
Number of non-by variables in common | 12
Number of variables compared | 12
Number of variables in x but not y | 1
Number of variables in y but not x | 0
Number of variables compared with some values unequal | 2
Number of variables compared with all values equal | 10
Number of observations in common | 1495
Number of observations in x but not y | 4
Number of observations in y but not x | 0
Number of observations with some compared variables unequal | 2
Number of observations with all compared variables equal | 1493
Number of values unequal | 2

Variables not shared
version | variable | position | class
--- | --- | --- | ---
x | age | 2 | integer

Other variables not compared
No other variables not compared

Observations not shared
version | case | observation
--- | --- | ---
x | 88989 | 9
x | 90158 | 8
x | 99508 | 7
x | 112263 | 5

Differences detected by variable
var.x | var.y | n | NAs
--- | --- | --- | ---
arm | Arm | 0 | 0
sex | sex | 0 | 0
race | race | 0 | 0
fu.time | fu_time | 0 | 0
fu.stat | fu stat | 0 | 0
ps | ps | 1 | 1
hgb | hgb | 0 | 0
bmi | bmi | 0 | 0
alk.phos | alk.phos | 0 | 0
ast | ast | 1 | 0
mdquality.s | mdquality.s | 0 | 0
age.ord | age.ord | 0 | 0

Differences detected
var.x | var.y | case | values.x | values.y | row.x | row.y
--- | --- | --- | --- | --- | --- | ---
ps | ps | 86205 | 0 | NA | 6 | 3
ast | ast | 105271 | 100 | 36 | 3 | 2

Non-identical attributes
var.x | var.y | name
--- | --- | ---
arm | Arm | label
sex | sex | label
sex | sex | levels
race | race | class
race | race | label
race | race | levels
bmi | bmi | label

# Extract Differences

Differences can be easily extracted using the `diffs()` function. If you only want to determine how many differences were found, use the `n.diffs()` function.

    cmp <- comparedf(mockstudy, mockstudy2, by = "case", tol.vars = c("._ ", "case"), int.as.num = TRUE)
    n.diffs(cmp)

    [1] 1765

    head(diffs(cmp))

      var.x var.y  case values.x values.y row.x row.y
    1   sex   sex 76170     Male     Male    26    20
    2   sex   sex 76240     Male     Male    27    21
    3   sex   sex 76431   Female   Female    28    22
    4   sex   sex 76712     Male     Male    29    23
    5   sex   sex 76780   Female   Female    30    24
    6   sex   sex 77066   Female   Female    31    25

Differences can also be summarized by variable.

    diffs(cmp, by.var = TRUE)

             var.x       var.y    n NAs
    1          arm         Arm    0   0
    2          sex         sex 1495   0
    3      fu.time     fu_time    0   0
    4      fu.stat     fu stat    0   0
    5           ps          ps    1   1
    6          hgb         hgb  266 266
    7          bmi         bmi    0   0
    8     alk.phos    alk.phos    0   0
    9          ast         ast    3   0
    10 mdquality.s mdquality.s    0   0
    11     age.ord     age.ord    0   0

To report differences from only a few variables, one can pass a list of variable names to `diffs()`.

    diffs(cmp, vars = c("ps", "ast"), by.var = TRUE)

      var.x var.y n NAs
    5    ps    ps 1   1
    9   ast   ast 3   0

    diffs(cmp, vars = c("ps", "ast"))

         var.x var.y   case values.x values.y row.x row.y
    1496    ps    ps  86205        0       NA     6     3
    1763   ast   ast  86205       27       36     6     3
    1764   ast   ast 105271      100       36     3     2
    1765   ast   ast 110754       35       36     1     1

# Appendix

## Stucture of the Object

(This section is just as much for my use as for yours!)

    obj <- comparedf(mockstudy, mockstudy2, by = "case")

There are two main objects in the `"comparedf"` object, each with its own print method.

The `frame.summary` contains:

- the substituted-deparsed arguments

- information about the number of columns and rows in each dataset

- the by-variables for each dataset (which may not be the same)

- the attributes for each dataset (which get counted in the print method)

- a data.frame of by-variables and row numbers of observations not shared between datasets

- the number of shared observations

    print(obj$frame.summary)

      version        arg ncol nrow   by        attrs       unique n.shared
    1       x  mockstudy   14 1499 case 3 attributes 4 unique obs     1495
    2       y mockstudy2   13 1495 case 3 attributes 0 unique obs     1495

The `vars.summary` contains:

- variable name, column number, and class vector (with possibly more than one element) for each x and y. These are all `NA` if there isn’t a match in both datasets.

- values, a list-column of the text string `"by-variable"` for the by-variables, `NULL` for columns that aren’t compared, or a data.frame containing:

  - The by-variables for differences found

  - The values which are different for x and y

  - The row numbers for differences found

- attrs, a list-column of `NULL` if there are no attributes, or a data.frame containing:

  - The name of the attributes

  - The attributes for x and y, set to `NA` if non-existant

  - The actual attributes (if `show.attr=TRUE`).

    print(obj$vars.summary)

             var.x pos.x         class.x       var.y pos.y         class.y           values        attrs
    1         case     1         integer        case     1         integer      by-variable 0 attributes
    2          sex     4          factor         sex     2          factor 1495 differences 2 attributes
    3         race     5       character        race     3          factor     Not compared 3 attributes
    4           ps     8         integer          ps     4         integer    1 differences 0 attributes
    5          hgb     9         numeric         hgb     5         numeric  266 differences 0 attributes
    6          bmi    10         numeric         bmi     6         numeric    0 differences 1 attributes
    7     alk.phos    11         integer    alk.phos     7         integer    0 differences 0 attributes
    8          ast    12         integer         ast     8         numeric     Not compared 0 attributes
    9  mdquality.s    13         integer mdquality.s     9         integer    0 differences 0 attributes
    10     age.ord    14 ordered, factor     age.ord    10 ordered, factor    0 differences 0 attributes
    11         age     2         integer        <NA>    NA              NA     Not compared 0 attributes
    12         arm     3       character        <NA>    NA              NA     Not compared 0 attributes
    13     fu.time     6         integer        <NA>    NA              NA     Not compared 0 attributes
    14     fu.stat     7         integer        <NA>    NA              NA     Not compared 0 attributes
    15        <NA>    NA              NA     fu_time    11         integer     Not compared 0 attributes
    16        <NA>    NA              NA     fu stat    12         integer     Not compared 0 attributes
    17        <NA>    NA              NA         Arm    13       character     Not compared 0 attributes