Package 'dataCompareR'

Title: Compare Two Data Frames and Summarise the Difference
Description: Easy comparison of two tabular data objects in R. Specifically designed to show differences between two sets of data in a useful way that should make it easier to understand the differences, and if necessary, help you work out how to remedy them. Aims to offer a more useful output than all.equal() when your two data sets do not match, but isn't intended to replace all.equal() as a way to test for equality.
Authors: Sarah Johnston [aut, cre], Rob Noble-Eddy [aut], Merlijn van Horssen [aut], Krishan Bhasin [aut], Sarah Pollicott [aut], Lukas Drapal [ctb], Nikolaos Perrakis [ctb], Nikhil Thomas Joy [ctb], Shahriar Asta [ctb], Karandeep Lidher [ctb], Dan Kellett [ctb], Kevin Chisholm [ctb], Laura Joy [ctb], Fergus Wadsley [ctb], Heather Hackett [ctb], David Robinson [ctb], Cheryl Renton [ctb], Matt Triggs [ctb], Carola Deppe [ctb], Ruijing Li [ctb], John Swift [ctb], Capital One Services, LLC [cph]
Maintainer: Sarah Johnston <[email protected]>
License: Apache License 2.0 | file LICENSE
Version: 0.1.4
Built: 2025-03-12 04:59:46 UTC
Source: https://github.com/capitalone/datacomparer

Help Index

allVarMatchMessage

Description

Returns data about matching

Usage

allVarMatchMessage(x)

Arguments

x

An dataCompareR object

Value

A string containing the required message

checkEmpty

Description

Checks if a df is actually a single NA, or has no columns

Usage

checkEmpty(df)

Arguments

df

a data frame

Value

None. Stops if empty.

Examples

## Not run: checkEmpty(iris)

checkForRcompareCol

Description

checkForRcompareCol

Usage

checkForRCompareCol(df1)

Arguments

df1

a data frame

Value

None. Stops if error.

Examples

## Not run: checkForRcompareCol(iris)

checkKeysExist

Description

checkKeysExist

Usage

checkKeysExist(df, keys)

Arguments

df

a data frame
keys

a list of expected columns

Value

None. Stops if keys are not present as column names in df.

Examples

## Not run: checkKeysExist(iris, 'columnName')

CheckNA

Description

Checks a data frame is NA - if so, stops

Usage

checkNA(df)

Arguments

df

A (probable) dataframe

Value

Nothing. Errors is df is NA

Checks that a list of indexes areunique

Description

Checks that a list of indexes areunique

Usage

checkUniqueness(df_indices)

Arguments

df_indices

A vector of values

Value

Boolean - true if all values in vector are unique, false if not

Examples

## Not run: checkUniqueness(c('car','van','van'))
## Not run: checkUniqueness(c('car','van','bus'))

cleanColNames : get colnames, remove leading and trailing whitespace and push to upper case

Description

cleanColNames : get colnames, remove leading and trailing whitespace and push to upper case

Usage

cleanColNames(DF)

Arguments

DF

Input dataframe

Value

colInfo dataframe containing original and treated column names of DF

coerceData

Description

coerceData

Usage

coerceData(doa, dob)

Arguments

doa

Data object A (any object that can be coerced to a data frame)
dob

Data object B (any object that can be coerced to a data frame)

Value

A list of 2 data frames, which is DOA and DOB coerced as data.frames

Examples

## Not run: irisMatrix <- as.matrix(iris)
## Not run: coerceData(irisMatrix,iris)

coerceFactorsToChar: convert all factor type fields to characters

Description

coerceFactorsToChar: convert all factor type fields to characters

Usage

coerceFactorsToChar(DF)

Arguments

DF

Input dataframe

Value

DF with factor fields converted to character type

Examples

## Not run: coerceFactorsToChar(iris)

collapseClasses. Collapse the classes of an object to a single string

Description

collapseClasses. Collapse the classes of an object to a single string

Usage

collapseClasses(x)

Arguments

x

any object

Value

a string listing the classes of x, separated by commas

Examples

## Not run: collapseClasses(iris)
## Not run: collapseClasses("hello")

colsWithUnequalValues: a dataframe summarising a column with unequal values

Description

colsWithUnequalValues: a dataframe summarising a column with unequal values

Usage

colsWithUnequalValues(x, mismatches)

Arguments

x

the column to be considered
mismatches

- a mismatches object from an dataCompareR object

Value

data frame with a summary of the mismatching column

Compare data. Wrapper for comparison functionality.

Description

Compare data. Wrapper for comparison functionality.

Usage

compareData(DFA, DFB, keys = NULL, maxMismatches)

Arguments

DFA

dataframe as returned from prepareData
DFB

dataframe as returned from prepareData
keys

vector of chars - names of index variables
maxMismatches

Integer. The max number of mismatches to assess, after which dataCompareR will stop (without producing a dataCompareR object). Designed to improve performance for large datasets.

Value

mismatchObject containing mismatch data for each of the variables in the dataframes

Examples

## Not run: compareData(iris, iris)

## Not run: iris2 <- iris
## Not run: iris2[1,1] <- 5.2
## Not run: iris2[2,1] <- 5.2
## Not run: compareData(iris, iris2)

## Not run: compareData(pressure, pressure, keys = 'temperature')

compareNames : compare the intersect of colInfoA and colInfoB and return boolean of matched columns for each data frame

Description

compareNames : compare the intersect of colInfoA and colInfoB and return boolean of matched columns for each data frame

Usage

compareNames(colInfoA, colInfoB)

Arguments

colInfoA

input data frames with original and treated column names
colInfoB

input data frames with original and treated column names

Create a dataframe of the rows that don't match

Description

Create a dataframe of the rows that don't match

Usage

createAntiSubset(index_antisubset, original_keys, index_key, df)

Arguments

index_antisubset

Vector of mismatching indices
original_keys

A character array
index_key

A character array
df

A data frame

Value

A dataframe containing the dropped rows

Converts cleaning info into a format consumable by updateCompareObject.

Description

Converts cleaning info into a format consumable by updateCompareObject.

Usage

createCleaningInfo(compObj, cleaningInfo)

Arguments

compObj

dataCompareRobject to be updated
cleaningInfo

list of cleaning information

Value

compObj updated dataCompareRobject

Converts the output of the column matching logic to something consumable by updateCompareObject.

Description

Converts the output of the column matching logic to something consumable by updateCompareObject.

Usage

createColMatching(compObj, colMatchInfo)

Arguments

compObj

dataCompareRobject instance to be updated
colMatchInfo

List output from the column matching logic

Value

compObj updated with colMatching block

Generates an empty list of the correct class to store results

Description

Generates an empty list of the correct class to store results

Usage

createCompareObject()

Value

A list of class dataCompareRObject

Takes the raw info for the meta block of the output and puts it in a format usable by the updateCompareObject function

Description

Takes the raw info for the meta block of the output and puts it in a format usable by the updateCompareObject function

Usage

createMeta(dataCompareRobject, DFA, DFB, arguments, timestamp, roundDigits)

Arguments

dataCompareRobject

Object of class dataCompareRobject
DFA

First data set passed in to the dataCompareR function
DFB

Second data set passed in to the dataCompareR function
arguments

Collection of arguments passed to compare object with labels that match the dataCompareR arg definitions
timestamp

Timestamp
roundDigits

The number of digits to round to, using round

Value

dataCompareRobject

Create mismatch object

Description

Create mismatch object

Usage

createMismatches(compObj, misObj, keys)

Arguments

compObj

RCompareObject, output from processFlow
misObj

MismatchObject, output from compareData (processFlow)
keys

Character vector, the keys matched on, to allow removal of any extra columns introduced by the compare process

Value

The mismatch object

Create mismatch object

Description

Create mismatch object

Usage

createMismatchObject(dat_a, dat_b, dat_eq, str_index)

Arguments

dat_a

dataframe, output from prepareData
dat_b

dataframe, output from prepareDate
dat_eq

dataframe, output from locateMismatches
str_index

vector of index variables (could have length 1)

Value

An dataCompareR mismatch object

Examples

## Not run: createMismatchObject(dataA, dataB, mism, idx)

createReportText: prepares text which is used in the summary report Saves R markdown and HTML reports in the area specified by the user. Reports are called RcompareReport.Rmd (.html) Uses knitr package to create tables in the markdown (createReportText function) and HTML report.

Description

createReportText: prepares text which is used in the summary report Saves R markdown and HTML reports in the area specified by the user. Reports are called RcompareReport.Rmd (.html) Uses knitr package to create tables in the markdown (createReportText function) and HTML report.

Usage

createReportText(x)

Arguments

x

input object which summary comparison information

Value

text in R markdown format

Examples

## Not run: createReportText(x=MysummaryCompareObject)

function for updating a compare object with information passed to it from the match rows function

Description

function for updating a compare object with information passed to it from the match rows function

Usage

createRowMatching(compObj, x, matchKey)

Arguments

compObj

dataCompareRobject to be updated
x

Object of information with classes related to the relevant section of the dataCompareRobject
matchKey

the list of keys based on which the row matching was performed

Value

compObj Updated dataCompareRobject

createTextSummary: create a text based summary of an dataCompareR object

Description

createTextSummary: create a text based summary of an dataCompareR object

Usage

createTextSummary(x, ...)

Arguments

x

an dataCompareR object
...

Arguments passed on to other functions

Value

cat's lines to the screen (or to be captured) cat(newLine)

Place to store and access the current object version.

Description

Place to store and access the current object version.

Usage

currentObjVersion()

Value

currentVersion int of the version number

executeCoercions:

Description

executeCoercions:

Usage

executeCoercions(DFA, DFB, WhitespaceTrim = TRUE)

Arguments

DFA

Input dataframe A
DFB

Input dataframe B
WhitespaceTrim

User defined boolean for whether leading/trailing white space is trimmed in strings (TRUE / FALSE)

Value

out list containing 3 data frames DFA, DFB and DataTypes

DFA Dataframe with factor fields converted to character type and white space trimming (if option is selected by the user)

DFB Dataframe with factor fields converted to character type and white space trimming (if option is selected by the user)

DataTypes Dataframe with field types before and after cleaning for both DFA and DFB

Examples

## Not run: executeCoercions(DFA=iris,DFB=iris,WhitespaceTrim= TRUE)

Extract data from a dataCompareR comparison

Description

Produces a list of two data frames, containing the mismatched rows from the two input tables

Note that this function requires the user to pass in the two data frames used in the initial comparison. If this data does not match that used for the generation of the dataCompareR object the results produced will not be accurate.

Usage

generateMismatchData(x, dfA, dfB, ...)

Arguments

x

A dataCompareRobject.
dfA

Data frame (or object coercable to a data frame). One of the two data frames used in the initial rCompare call.
dfB

Data frame (or object coercable to a data frame). One of the two data frames used in the initial rCompare call.
...

Unused currently, may be used in future

Value

mismatchData A list containing two objects: mismatched rows in first data object and mismatched rows in second data object

See Also

Other dataCompareR.functions: print.dataCompareRobject(), rCompare(), saveReport(), summary.dataCompareRobject()

Subsets on the variables that have a coercion.

Description

Subsets on the variables that have a coercion.

Usage

getCoercions(typesDf)

Arguments

typesDf

Dataframe of type information from the executeCoercion function

Value

coercedT Subset version of typesDf where a coercion occurred

Extracts the column names only in one data frame from a table of match information

Description

Extracts the column names only in one data frame from a table of match information

Usage

getMismatchColNames(colMatchInfo, colNameCol, matchFlagCol)

Arguments

colMatchInfo

Dataframe with column names, match flag
colNameCol

Name of the column with the column names
matchFlagCol

Name of the column with the match flag

Value

Vector of column names that do not match

Check object is of class dataCompareRobject

Description

Check object is of class dataCompareRobject

Usage

is.dataCompareRobject(x)

Arguments

x

An object

Value

A boolean: TRUE if object is class dataCompareRobject and FALSE if not

isNotNull: is object not null

Description

isNotNull: is object not null

Usage

isNotNull(x)

Arguments

x

an object

Value

boolean is object null T/F

Examples

## Not run: isNotNull(NULL)
## Not run: isNotNull(5)

isSingleNA

Description

Boolean function - T if x is a single NA. False otherwise.

Usage

isSingleNA(x)

Arguments

x

literally anything

Value

boolean

listObsNotVerbose

Description

Return a summary of mismatching data

Usage

listObsNotVerbose(i, x, uniquevarlist, nObs)

Arguments

i

The position of the element we want to compare
x

An dataCompareR object
uniquevarlist

A list of the variables in the compare
nObs

How many observations to return

Value

A list of mismatching observations from start/end of mismatches

listObsVerbose

Description

Return all mismatching data

Usage

listObsVerbose(i, x)

Arguments

i

The position of the element we want to compare
x

An dataCompareR object

Value

A list of mismatching observations

Checks whether elements in two input data frames are equal.

Description

Checks whether elements in two input data frames are equal.

Usage

locateMismatches(DFA, DFB, keys = NULL, maxMismatches = NA)

Arguments

DFA

input data frame
DFB

input data frame
keys

character vector of index variables
maxMismatches

Integer. The max number of mismatches to assess, after which dataCompareR will stop (without producing a dataCompareR object). Designed to improve performance for large datasets.

Value

data frame containing keys and boolean logic of match/no match for each element If data types are not equal returns FALSE. Treats NA and NaN as unequal.

makeValidKeys

Description

Correct syntactically invalid Keys

Usage

makeValidKeys(keys)

Arguments

keys

A character vector

Value

A character vector with syntactically valid names

Examples

## Not run: makeValidKeys(c(" hello", "__BAD NAME___")

makeValidNames

Description

Correct syntactically invalid names in a data frame

Usage

makeValidNames(df)

Arguments

df

A data frame

Value

A data frame with syntactically valid names

Examples

## Not run: makeValidNames(iris)

matchColumns : create subset of DFA and DFB to contain matching column names for both data frames

Description

matchColumns : create subset of DFA and DFB to contain matching column names for both data frames

Usage

matchColumns(DFA, DFB)

Arguments

DFA

input data frame
DFB

input data frame

Value

matchColOut named list of data frames. subsetA,subsetB contain only columns common to both data frames. colInfoA,colInfoB contain mapping of column names from original to treated and boolean indicator of common columns.

Generate two dataframes that contain the same rows based on a two-column index

Description

Generate two dataframes that contain the same rows based on a two-column index

Usage

matchMultiIndex(df_a, df_b, indices)

Arguments

df_a

A dataframe
df_b

A dataframe
indices

A char vector

Value

A list containing the two dataframes, subsetted by shared indices, and a list which itself contains the vectors for the dropped rows

Generate two dataframes that contain the same rows based on a two-column index

Description

Generate two dataframes that contain the same rows based on a two-column index

Usage

matchNoIndex(df_a, df_b)

Arguments

df_a

A dataframe
df_b

A dataframe

Value

A list containing the two dataframes, subsetted to the size of the smaller one, and a list containing vectors of the rows dropped.

Generate two dataframes and returns subsets of these dataframes that have shared rows.

Description

Generate two dataframes and returns subsets of these dataframes that have shared rows.

Usage

matchRows(df_a, df_b, indices = NA)

Arguments

df_a

A dataframe
df_b

A dataframe
indices

The indices to match rows between df_a and df_b. Can be NA, single character, or a vector of characters

Value

A list containing the two dataframes, subsetted by shared indices, and a list which itself contains dataframes for the dropped rows

Generate two dataframes that contain the same rows based on a single index

Description

Generate two dataframes that contain the same rows based on a single index

Usage

matchSingleIndex(df_a, df_b, index_key, original_keys)

Arguments

df_a

A dataframe
df_b

A dataframe
index_key

A character vector
original_keys

A character vector

Value

A list containing the two dataframes, subsetted by shared indices, and a list which itself contains the vectors for the dropped rows

Creates a list of info about the dataframe.

Description

Creates a list of info about the dataframe.

Usage

metaDataInfo(name, df)

Arguments

name

The variable name of the df from the dataCompareR function call
df

A data frame

Value

dfInfo A list of info about the data frame

mismatchHighStop Checks if we've exceeded threshold of mismatches

Description

mismatchHighStop Checks if we've exceeded threshold of mismatches

Usage

mismatchHighStop(trueFalseMatrix, maxMismatches)

Arguments

trueFalseMatrix

a matrix of true/false
maxMismatches

number of mismatches at which the routine stops

Value

Nothing. Stops if threshold exceeded

orderColumns: order columns by treated column names

Description

orderColumns: order columns by treated column names

Usage

orderColumns(colInfo)

Arguments

colInfo

dataframe containing original and treated column names of DF

Value

ordered colInfo dataframe containing original and treated column names of DF

outputSectionHeader: creates an outputSectionHeader

Description

outputSectionHeader: creates an outputSectionHeader

Usage

outputSectionHeader(headerName)

Arguments

headerName

a header name

Value

character a character based section headers

prepareData Prepares data for comparison in 3 stages. 1. Match columns - filter dataframes to those columns that match and summarise differences 2. Match rows - filter dataframes to those rows that match and summarise differences 3. Coerce data

Description

prepareData Prepares data for comparison in 3 stages. 1. Match columns - filter dataframes to those columns that match and summarise differences 2. Match rows - filter dataframes to those rows that match and summarise differences 3. Coerce data

Usage

prepareData(dfA, dfB, keys = NA, trimChars = TRUE)

Arguments

dfA

data frame. The first data object. dataCompareR will attempt to coerce all data objects to data frames.
dfB

data frame. The second data object. dataCompareR will attempt to coerce all data objects to data frames.
keys

String. Name of identifier column(s) used to compare dfA and dfB. NA if no identifier (row order will be used instead), a character for a single column name, or a vector of column names to match of multiple columns
trimChars

Boolean. If true, strings and factors have whitespace trimmed before comparison.

Value

dataCompareRObject containing details of the comparison

Examples

## Not run: dfA <- iris
## Not run: dfB <- iris
## Not run: keys <- NA
## Not run: prepareData(dfA,dfB,keys, trimChars = TRUE)

Printing RCompare Output

Description

Prints a brief report of an dataCompareR object to the screen.

Usage

## S3 method for class 'dataCompareRobject'
print(x, nVars = 5, nObs = 5, verbose = FALSE, ...)

Arguments

x

an object of class "dataCompareR", usually a result of a call to rCompare.
nVars

the number of mismatched columns to print and extract rows for
nObs

the number of rows to print from the top and bottom of the mismatched list for each selected column
verbose

logical; if TRUE will print out the full list of columns and rows that do not match
...

Passes additional arguments to print

See Also

Other dataCompareR.functions: generateMismatchData(), rCompare(), saveReport(), summary.dataCompareRobject()

Examples

rc1 <- rCompare(iris,iris)
print(rc1)

Printing summaryRCompare Output

Description

Printing summaryRCompare Output

Usage

## S3 method for class 'summary.dataCompareRobject'
print(x, ...)

Arguments

x

an object of class "summary.dataCompareRobject", usually a result of a call to summary.dataCompareRobject.
...

Additional arguments passed on to createTextSummary

Examples

rc1 <- rCompare(iris,iris)
summary(rc1)

processFlow Handles the process flow for the whole package

Description

processFlow Handles the process flow for the whole package

Usage

processFlow(dfa, dfb, roundDigits, keys, mismatches, trimChars, argsIn)

Arguments

dfa

Dataframe. One of the two data frames to be compared
dfb

Dataframe. One of the two data frames to be compared
roundDigits

Integer. If NA, numerics are not rounded before comparison. If /coderoundDigits is specified, numerics are rounded to /coderoundDigits decimal places using round.
keys

The keys used to match rows between dfa and dfb
mismatches

Integer. The max number of mismatches to assess, after which dataCompareR will stop (without producing a dataCompareR object). Designed to improve performance for large datasets.
trimChars

Boolean. Do we trim characters before comparing?
argsIn

The arguments that were passed to the main dataCompareR function

Value

dataCompareRObject containing details of the comparison

Compare two data frames

Description

Compare two data frames (or objects coercible to data frames) and produce a dataCompareR object containing details of the matching and mismatching elements of the data. See vignette("dataCompareR") for more details.

Usage

rCompare(
  dfA,
  dfB,
  keys = NA,
  roundDigits = NA,
  mismatches = NA,
  trimChars = FALSE
)

Arguments

dfA

data frame. The first data object. dataCompareR will attempt to coerce all data objects to data frames.
dfB

data frame. The second data object. dataCompareR will attempt to coerce all data objects to data frames.
keys

String. Name of identifier column(s) used to compare dfA and dfB. NA if no identifier (row order will be used instead), a character for a single column name, or a vector of column names to match of multiple columns
roundDigits

Integer. If NA, numerics are not rounded before comparison. If specified, numerics are rounded to the specified number of decimal places using round.
mismatches

Integer. The max number of mismatches to assess, after which dataCompareR will stop (without producing an dataCompareR object). Designed to improve performance for large data sets.
trimChars

Boolean. If true, strings and factors have whitespace trimmed before comparison.

Value

An dataCompareR object. An S3 object containing details of the comparison between the two data objects. Can be used with summary, print, saveReport and generateMismatchData

See Also

Other dataCompareR.functions: generateMismatchData(), print.dataCompareRobject(), saveReport(), summary.dataCompareRobject()

Examples

iris2 <- iris
iris2 <- iris2[1:130,]
iris2[1,1] <- 5.2
iris2[2,1] <- 5.2
rCompare(iris,iris2,key=NA)
compDetails <- rCompare(iris,iris2,key=NA, trimChars = TRUE)
print(compDetails)
summary(compDetails)

pressure2 <- pressure
pressure2[2,2] <- pressure2[2,2] + 0.01
rCompare(pressure2,pressure2,key='temperature')
rCompare(pressure2,pressure2,key='temperature', mismatches = 10)

rcompObjItemLength: return length of an item, returning 0 if null, and handling the fact that we might have a data frames or a vector

Description

rcompObjItemLength: return length of an item, returning 0 if null, and handling the fact that we might have a data frames or a vector

Usage

rcompObjItemLength(x)

Arguments

x

an object

Value

length, numeric

Round all numeric fields in a data frame

Description

Round all numeric fields in a data frame

Usage

rounddf(df, roundDigits)

Arguments

df

A data frame to round
roundDigits

Number of digits to round to

Value

A rounded data frame

Save a report based on a dataCompareR object

Description

Saves R markdown and HTML reports in the area specified by the user.

Uses knitr and markdown to create reports. Reports have the extensions .Rmd or .html. By default the table.css style sheet is used for format the html output.

Usage

saveReport(
  compareObject,
  reportName,
  reportLocation = ".",
  HTMLReport = TRUE,
  showInViewer = TRUE,
  stylesheet = NA,
  printAll = FALSE,
  ...
)

Arguments

compareObject

a dataCompareR object.
reportName

String. The name of the report. Reports will be saved as reportName.Rmd and (optionally) reportName.html in reportLocation
reportLocation

String. Location to save reports specified by the user. The R markdown and (optionally) HTML reports will be saved in this area
HTMLReport

Boolean. Option to output html report.
showInViewer

Boolean. Does the html report open automatically in the viewer?
stylesheet

String. Optional link to customised css stylesheet
printAll

Boolean. If TRUE, all mis-matches in the data are printed to the file. This acts as a shortcut to get all mismatches in the report, compared to passing the number in mismatchCount. When TRUE, overrides the mismatchCount field passed via ellipses
...

Optional arguments which will be passed to summary, for example mismatchCount

See Also

Other dataCompareR.functions: generateMismatchData(), print.dataCompareRobject(), rCompare(), summary.dataCompareRobject()

Examples

## Not run: saveReport(rcObj, reportName = 'testReport')

subsetDataColumns : create subset of DFA and DFB to contain matching column names for both data frames

Description

subsetDataColumns : create subset of DFA and DFB to contain matching column names for both data frames

Usage

subsetDataColumns(DFA, DFB, colInfoList)

Arguments

DFA

input data frame
DFB

input data frame
colInfoList

named list containing the column mapping data frames and the list of common column names

Value

matchColOut named list of data frames. subsetA,subsetB contain only columns common to both data frames. colInfoA,colInfoB contain mapping of column names from original to treated and boolean indicator of common columns.

Summarizing RCompare Output

Description

Summarizing RCompare Output

Usage

## S3 method for class 'dataCompareRobject'
summary(object, mismatchCount = 5, ...)

Arguments

object

an dataCompareR object, usually a result of a call to rCompare.
mismatchCount

Integer. How many mismatches to include in tables
...

Passes any additional arguments (not used in current version)

Value

The function summary.dataCompareR computes and returns a list of summary details from the dataCompareR output given in object containing

datanameA

name of the first dataframe in the compare call
datanameB

name of the second dataframe in the compare call
nrowA

the number of rows in datanameA
nrowB

the number of rows in datanameB
version

the version of rCompare used to generate the dataCompareR object object
runtime

the date and time the dataCompareR object object was created
rversion

the version of R used
datasetSummary

a data frame containing the meta data information on datanameA and datanameB
ncolCommon

the number of columns of the same name contained in both datanameA and datanameB
ncolInAOnly

the number of columns only in datanameA
ncolInBOnly

the number of columns only in datanameB
ncolID

the number of columns used to match rows in datanameA and datanameB

typeMismatch

a data frame detailing which columns in both datanameA and datanameB have different class types
typeMismatchN

the number of columns with different variable types
nrowCommon

the number of rows with matching ID columns in both datanameA and datanameB
nrowInAOnly

the number of rows with non matching ID columns in datanameA
nrowInBOnly

the number of rows with non matching ID columns in datanameB
nrowSomeUnequal

the number of matched rows where at least one value is unequal
nrowAllEqual

the number of matched rows where all values are equal
ncolsAllEqual

the number of matched columns where all values are equal
ncolsSomeUnequal

the number of matched columns where at least one value is unequal
colsWithUnequalValues

a data frame detailing the mismatches for each matched column
nrowNAmisMatch

the number of matched numeric rows that contain a NA
maxDifference

the maximum difference between numeric columns from all matched columns

See Also

Other dataCompareR.functions: generateMismatchData(), print.dataCompareRobject(), rCompare(), saveReport()

Examples

rc1 <- rCompare(iris,iris) 
summary(rc1)

trimCharVars: trim white spaces in character variables from an input dataframe

Description

trimCharVars: trim white spaces in character variables from an input dataframe

Usage

trimCharVars(DF)

Arguments

DF

Input dataframe

Value

DF with preceding and trailing white spaces removed from character fields

Examples

## Not run: trimCharVars(iris)

Generic function for updating a compare object with information passed to it, that has methods based on the class of the info argument.

Description

Generic function for updating a compare object with information passed to it, that has methods based on the class of the info argument.

Usage

updateCompareObject(x, compObj)

Arguments

x

Object of information with classes related to the relevant section of the dataCompareRobject
compObj

dataCompareRobject to be updated

Value

compObj Updated dataCompareRobject

Updates cleaning info in the compare object

Description

Updates cleaning info in the compare object

Usage

## S3 method for class 'cleaninginfo'
updateCompareObject(x, compObj)

Arguments

x

list of type cleaninginfo with data types
compObj

dataCompareRobject to be updated

Value

compObj updated dataCompareRobject

Adds a colMatching block to the output

Description

Adds a colMatching block to the output

Usage

## S3 method for class 'colmatching'
updateCompareObject(x, compObj)

Arguments

x

List of class colmatching with column matching info
compObj

dataCompareRobject instance to be updated

Value

compObj Updated dataCompareRobject

Adds a colMatching block to the output

Description

Adds a colMatching block to the output

Usage

## S3 method for class 'matches'
updateCompareObject(x, compObj)

Arguments

x

List of class 'matches' with column matching info
compObj

dataCompareRobject instance to be updated

Value

compObj Updated dataCompareRobject

Takes raw info for meta and adds it to the compare object

Description

Takes raw info for meta and adds it to the compare object

Usage

## S3 method for class 'meta'
updateCompareObject(x, compObj)

Arguments

x

List of class 'meta' with data related to meta
compObj

dataCompareRobject to be appended

Value

compObj dataCompareRobject updated with meta block

Adds a colMatching block to the output

Description

Adds a colMatching block to the output

Usage

## S3 method for class 'mismatches'
updateCompareObject(x, compObj)

Arguments

x

List of class 'mismatches' with column matching info
compObj

dataCompareRobject instance to be updated

Value

compObj Updated dataCompareRobject

Adds a rowMatching block to the output

Description

Adds a rowMatching block to the output

Usage

## S3 method for class 'rowmatching'
updateCompareObject(x, compObj)

Arguments

x

List of class rowMatching with row matching info
compObj

dataCompareRobject instance to be updated

Value

compObj Updated dataCompareRobject

validateArguments

Description

validateArguments

Usage

validateArguments(
  matchKey = NA,
  roundDigits = NA,
  coerceCols = TRUE,
  maxMismatch = NA
)

Arguments

matchKey

A character or character vector of column names to match on
roundDigits

Integer. If NA, numerics are not rounded before comparison. If specified, numerics are rounded to the specified number of decimal places using round.
coerceCols

Boolean - do we coerce columns names?
maxMismatch

Cap for number of mismatches

Value

Nothing. Errors if any parameters are invalid.

Examples

## Not run: validateArguments('plantName',1E-8,T,1000)
## Not run: validateArguments('colorName',1E-9,F,10)

validateData : routine to validate the input data

Description

validateData : routine to validate the input data

Usage

validateData(df1, df2, keys = NA)

Arguments

df1

a data frame
df2

a data frame
keys

Keys used

Value

None. Stops if error.

Examples

## Not run: validateData(iris,iris)

Create variable mismatch details

Description

Create variable mismatch details

Usage

variableDetails(dat)

Arguments

dat

The mismatch data

Value

mismatch details

Create variable mismatch table

Description

Create variable mismatch table

Usage

variableMismatches(varname, vals_a, vals_b, vector_eq)

Arguments

varname

variable to create mismatch table for
vals_a

variables from dfA
vals_b

variables from dfB
vector_eq

a list of columns which are equal

Value

Mismatch table

Warn users if the calculation is likely to be slow

Description

Checks if there are more than 20E6 elements for comparison. If there are, spits out a warning message that the calculation may run slowly

Usage

warnLargeData(nrow_dfa, ncol_dfa, nrow_dfb, ncol_dfb)

Arguments

nrow_dfa

number of rows in first data frame
ncol_dfa

number of columns in first data frame
nrow_dfb

number of rows in second data frame
ncol_dfb

number of columns in second data frame

Value

Nothing