In ekstroem/dataMaid: A Suite of Checks for Identification of Potential Errors in a Data Frame as Part of the Data Screening Process
library(ggplot2)
library(pander)
ggAggHist <- getFromNamespace("ggAggHist", "dataMaid")
ggAggBarplot <- getFromNamespace("ggAggBarplot", "dataMaid")
Data report overview
The dataset examined has the following dimensions:
Feature Result
Number of observations 46
Number of variables 11
Checks performed
The following variable checks were performed, depending on the data type of each variable:
character factor labelled numeric integer logical Date
Identify miscoded missing values $\times$ $\times$ $\times$ $\times$ $\times$ $\times$
Identify prefixed and suffixed whitespace $\times$ $\times$ $\times$
Identify case issues $\times$ $\times$ $\times$
Identify misclassified numeric or integer variables $\times$ $\times$ $\times$
Identify levels with < 6 obs. $\times$ $\times$
Identify outliers $\times$ $\times$ $\times$
Non-supported variable types were set to be handled in the following way:
- Name is treated as character
Please note that all numerical values in the following have been rounded to 2 decimals.
Summary table
Variable class # unique values Missing observations Any problems?
[lastName] Name 40 0.00 % $\times$
[firstName] Name 31 0.00 % $\times$
[orderOfPresidency] factor 46 0.00 % $\times$
[birthday] Date 45 0.00 % $\times$
[stateOfBirth] character 23 0.00 % $\times$
[assassinationAttempt] numeric 2 0.00 %
[sex] factor 1 0.00 % $\times$
[ethnicity] factor 2 0.00 % $\times$
[presidencyYears] numeric 11 4.35 % $\times$
[ageAtInauguration] character 23 0.00 % $\times$
[favoriteNumber] complex 11 0.00 % $\times$
Variable list
lastName
\bminione
Feature Result
Variable type Name
Number of missing obs. 0 (0 %)
Number of unique values 40
Mode "Adams"
\emini
\bminitwo
ggAggBarplot(data = structure(list(x = structure(1:40, .Label = c(" Truman",
"Adams", "Arathornson", "Arthur", "Buchanan", "Bush", "Carter",
"Cleveland", "Clinton", "Coolidge", "Eisenhower", "Fillmore",
"Ford", "Garfield", "Grant", "Harding", "Harrison", "Hayes",
"Hoover", "Jackson", "Jefferson", "Johnson", "Kennedy", "Lincoln",
"Madison", "McKinley", "Monroe", "Nixon", "Obama", "Pierce",
"Polk", "Reagan", "Roosevelt", "Taft", "Taylor", "Trump", "Tyler",
"Van Buren", "Washington", "Wilson"), class = "factor"), y = c(1L,
2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
1L, 1L, 1L, 1L, 1L, 1L, 1L)), .Names = c("x", "y"), row.names = c(NA,
-40L), class = "data.frame"), vnam = "lastName")
\emini
- The following values appear with prefixed or suffixed white space: \" Truman\".
\fullline
firstName
\bminione
Feature Result
Variable type Name
Number of missing obs. 0 (0 %)
Number of unique values 31
Mode "James"
\emini
\bminitwo
ggAggBarplot(data = structure(list(x = structure(1:31, .Label = c(".",
"Abraham", "Andrew", "Aragorn", "Barack", "Benjamin", "Calvin",
"Chester", "Dwight", "Franklin", "George", "Gerald", "Grover",
"Harry", "Herbert", "James", "Jimmy", "John", "Lyndon", "Martin",
"Millard", "Richard", "Ronald", "Rutherford", "Theodore", "Thomas",
"Ulysses", "Warren", "William", "Woodrow", "Zachary"), class = "factor"),
y = c(1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 3L, 1L, 2L,
1L, 1L, 5L, 1L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
4L, 1L, 1L)), .Names = c("x", "y"), row.names = c(NA, -31L
), class = "data.frame"), vnam = "firstName")
\emini
- The following suspected missing value codes enter as regular values: \".\".
\fullline
orderOfPresidency
- The variable is a key (distinct values for each observation).
\fullline
birthday
\bminione
Feature Result
Variable type Date
Number of missing obs. 0 (0 %)
Number of unique values 45
Mode "1837-03-18"
Min. and max. 1300-03-01; 1961-08-04
1st and 3rd quartiles 1790-03-29; 1890-10-14
\emini
\bminitwo
ggAggHist(data = structure(list(factorV = structure(1:20, .Label = c("1300-03-01",
"1333-03-27", "1366-04-22", "1399-05-18", "1432-06-13", "1465-07-09",
"1498-08-04", "1531-08-31", "1564-09-25", "1597-10-21", "1630-11-16",
"1663-12-13", "1697-01-07", "1730-02-03", "1763-03-01", "1796-03-26",
"1829-04-22", "1862-05-18", "1895-06-13", "1928-07-09"), class = "factor"),
Freq = c(1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 5L, 8L, 6L, 9L, 6L, 7L, 4L), xmin = structure(c(-244653,
-232574, -220495, -208416, -196337, -184258, -172179, -160100,
-148021, -135942, -123863, -111783, -99704, -87625, -75546,
-63467, -51388, -39309, -27230, -15151), class = "Date"),
xmax = structure(c(-232574, -220495, -208416, -196337, -184258,
-172179, -160100, -148021, -135942, -123863, -111783, -99704,
-87625, -75546, -63467, -51388, -39309, -27230, -15151, -3072
), class = "Date"), ymin = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0), ymax = c(1L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 5L, 8L, 6L, 9L, 6L, 7L, 4L
)), .Names = c("factorV", "Freq", "xmin", "xmax", "ymin",
"ymax"), row.names = c(NA, -20L), class = "data.frame"), vnam = "birthday")
\emini
- Note that the following possible outlier values were detected: \"1300-03-01\".
\fullline
stateOfBirth
\bminione
Feature Result
Variable type character
Number of missing obs. 0 (0 %)
Number of unique values 23
Mode "Ohio"
\emini
\bminitwo
ggAggBarplot(data = structure(list(x = structure(1:23, .Label = c("Arkansas",
"California", "Connecticut", "Georgia", "Gondor", "Hawaii", "Illinois",
"Iowa", "Kentucky", "Massachusetts", "Missouri", "Nebraska",
"New Hampshire", "New Jersey", "New York", "New york", "North Carolina",
"Ohio", "Pennsylvania", "Tennessee", "Texas", "Vermont", "Virginia"
), class = "factor"), y = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
4L, 1L, 1L, 1L, 2L, 4L, 1L, 2L, 8L, 1L, 1L, 2L, 2L, 7L)), .Names = c("x",
"y"), row.names = c(NA, -23L), class = "data.frame"), vnam = "stateOfBirth")
\emini
- Note that there might be case problems with the following levels: \"New York\", \"New york\".
\fullline
assassinationAttempt
- Note that this variable is treated as a factor variable below, as it only takes a few unique values.
\bminione
Feature Result
Variable type numeric
Number of missing obs. 0 (0 %)
Number of unique values 2
Mode "0"
\emini
\bminitwo
ggAggBarplot(data = structure(list(x = structure(1:2, .Label = c("0",
"1"), class = "factor"), y = c(35L, 11L)), .Names = c("x", "y"
), row.names = c(NA, -2L), class = "data.frame"), vnam = "assassinationAttempt")
\emini
\fullline
sex
- The variable only takes one (non-missing) value: \"Male\". The variable contains 0 \% missing observations.
\fullline
ethnicity
\bminione
Feature Result
Variable type factor
Number of missing obs. 0 (0 %)
Number of unique values 2
Mode "Caucasian"
\emini
\bminitwo
ggAggBarplot(data = structure(list(x = structure(1:2, .Label = c("African American",
"Caucasian"), class = "factor"), y = c(1L, 45L)), .Names = c("x",
"y"), row.names = c(NA, -2L), class = "data.frame"), vnam = "ethnicity")
\emini
- Note that the following levels have at most five observations: \"African American\".
\fullline
presidencyYears
\bminione
Feature Result
Variable type numeric
Number of missing obs. 2 (4.35 %)
Number of unique values 10
Median 4
1st and 3rd quartiles 3.75; 8
Min. and max. 0; Inf
\emini
\bminitwo
ggAggHist(data = structure(list(factorV = structure(1:20, .Label = c("[0,0.6]",
"(0.6,1.2]", "(1.2,1.8]", "(1.8,2.4]", "(2.4,3]", "(3,3.6]",
"(3.6,4.2]", "(4.2,4.8]", "(4.8,5.4]", "(5.4,6]", "(6,6.6]",
"(6.6,7.2]", "(7.2,7.8]", "(7.8,8.4]", "(8.4,9]", "(9,9.6]",
"(9.6,10.2]", "(10.2,10.8]", "(10.8,11.4]", "(11.4,12]"), class = "factor"),
Freq = c(2L, 1L, 0L, 4L, 4L, 0L, 15L, 0L, 3L, 0L, 0L, 3L,
0L, 10L, 0L, 0L, 0L, 0L, 0L, 1L), xmin = c(0, 0.6, 1.2, 1.8,
2.4, 3, 3.6, 4.2, 4.8, 5.4, 6, 6.6, 7.2, 7.8, 8.4, 9, 9.6,
10.2, 10.8, 11.4), xmax = c(0.6, 1.2, 1.8, 2.4, 3, 3.6, 4.2,
4.8, 5.4, 6, 6.6, 7.2, 7.8, 8.4, 9, 9.6, 10.2, 10.8, 11.4,
12), ymin = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0), ymax = c(2L, 1L, 0L, 4L, 4L, 0L, 15L, 0L,
3L, 0L, 0L, 3L, 0L, 10L, 0L, 0L, 0L, 0L, 0L, 1L)), .Names = c("factorV",
"Freq", "xmin", "xmax", "ymin", "ymax"), row.names = c(NA, -20L
), class = "data.frame"), vnam = "presidencyYears")
\emini
-
The following suspected missing value codes enter as regular values: \"Inf\".
-
Note that the following possible outlier values were detected: \"0\", \"1\", \"Inf\".
\fullline
ageAtInauguration
\bminione
Feature Result
Variable type character
Number of missing obs. 0 (0 %)
Number of unique values 23
Mode "54"
\emini
\bminitwo
ggAggBarplot(data = structure(list(x = structure(1:23, .Label = c("42",
"43", "46", "47", "48", "49", "50", "51", "52", "54", "55", "56",
"57", "58", "60", "61", "62", "64", "65", "68", "69", "70", "87"
), class = "factor"), y = c(1L, 1L, 2L, 2L, 1L, 2L, 2L, 4L, 2L,
5L, 4L, 3L, 4L, 1L, 1L, 3L, 1L, 2L, 1L, 1L, 1L, 1L, 1L)), .Names = c("x",
"y"), row.names = c(NA, -23L), class = "data.frame"), vnam = "ageAtInauguration")
\emini
- Note: The variable consists exclusively of numbers and takes a lot of different values. Is it perhaps a misclassified numeric variable?
\fullline
favoriteNumber
- The variable has class complex which is not supported by dataMaid.
\fullline
Report generation information:
-
Created by Claus Thorn Ekstrøm (username: cld189).
-
Report creation time: Wed Apr 11 2018 01:02:26
-
Report Was run from directory: /Users/cld189/ku/R/cleanR/latex
-
dataMaid v1.1.0 [Pkg: 2018-03-02 from local (ekstroem/dataMaid@NA)]
-
R version 3.4.4 (2018-03-15).
-
Platform: x86_64-apple-darwin15.6.0 (64-bit)(macOS High Sierra 10.13.3).
-
Function call: makeDataReport(data = presidentData, replace = TRUE, checks = setChecks(character = defaultCharacterChecks(remove = "identifyLoners")),
reportTitle = "Dirty president data", treatXasY = list(Name = "character"))
ekstroem/dataMaid documentation built on Jan. 31, 2022, 9:10 a.m.
R Package Documentation
Browse R Packages
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
library(ggplot2) library(pander)
ggAggHist <- getFromNamespace("ggAggHist", "dataMaid") ggAggBarplot <- getFromNamespace("ggAggBarplot", "dataMaid")
Data report overview
The dataset examined has the following dimensions:
Feature Result
Number of observations 46
Number of variables 11
Checks performed
The following variable checks were performed, depending on the data type of each variable:
character factor labelled numeric integer logical Date
Identify miscoded missing values $\times$ $\times$ $\times$ $\times$ $\times$ $\times$
Identify prefixed and suffixed whitespace $\times$ $\times$ $\times$
Identify case issues $\times$ $\times$ $\times$
Identify misclassified numeric or integer variables $\times$ $\times$ $\times$
Identify levels with < 6 obs. $\times$ $\times$
Identify outliers $\times$ $\times$ $\times$
Non-supported variable types were set to be handled in the following way:
- Name is treated as character
Please note that all numerical values in the following have been rounded to 2 decimals.
Summary table
Variable class # unique values Missing observations Any problems?
[lastName] Name 40 0.00 % $\times$
[firstName] Name 31 0.00 % $\times$
[orderOfPresidency] factor 46 0.00 % $\times$
[birthday] Date 45 0.00 % $\times$
[stateOfBirth] character 23 0.00 % $\times$
[assassinationAttempt] numeric 2 0.00 %
[sex] factor 1 0.00 % $\times$
[ethnicity] factor 2 0.00 % $\times$
[presidencyYears] numeric 11 4.35 % $\times$
[ageAtInauguration] character 23 0.00 % $\times$
[favoriteNumber] complex 11 0.00 % $\times$
Variable list
lastName
\bminione
Feature Result
Variable type Name
Number of missing obs. 0 (0 %)
Number of unique values 40
Mode "Adams"
\emini \bminitwo
ggAggBarplot(data = structure(list(x = structure(1:40, .Label = c(" Truman", "Adams", "Arathornson", "Arthur", "Buchanan", "Bush", "Carter", "Cleveland", "Clinton", "Coolidge", "Eisenhower", "Fillmore", "Ford", "Garfield", "Grant", "Harding", "Harrison", "Hayes", "Hoover", "Jackson", "Jefferson", "Johnson", "Kennedy", "Lincoln", "Madison", "McKinley", "Monroe", "Nixon", "Obama", "Pierce", "Polk", "Reagan", "Roosevelt", "Taft", "Taylor", "Trump", "Tyler", "Van Buren", "Washington", "Wilson"), class = "factor"), y = c(1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L)), .Names = c("x", "y"), row.names = c(NA, -40L), class = "data.frame"), vnam = "lastName")
\emini
- The following values appear with prefixed or suffixed white space: \" Truman\".
\fullline
firstName
\bminione
Feature Result
Variable type Name
Number of missing obs. 0 (0 %)
Number of unique values 31
Mode "James"
\emini \bminitwo
ggAggBarplot(data = structure(list(x = structure(1:31, .Label = c(".", "Abraham", "Andrew", "Aragorn", "Barack", "Benjamin", "Calvin", "Chester", "Dwight", "Franklin", "George", "Gerald", "Grover", "Harry", "Herbert", "James", "Jimmy", "John", "Lyndon", "Martin", "Millard", "Richard", "Ronald", "Rutherford", "Theodore", "Thomas", "Ulysses", "Warren", "William", "Woodrow", "Zachary"), class = "factor"), y = c(1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 3L, 1L, 2L, 1L, 1L, 5L, 1L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 4L, 1L, 1L)), .Names = c("x", "y"), row.names = c(NA, -31L ), class = "data.frame"), vnam = "firstName")
\emini
- The following suspected missing value codes enter as regular values: \".\".
\fullline
orderOfPresidency
- The variable is a key (distinct values for each observation).
\fullline
birthday
\bminione
Feature Result
Variable type Date
Number of missing obs. 0 (0 %)
Number of unique values 45
Mode "1837-03-18"
Min. and max. 1300-03-01; 1961-08-04
1st and 3rd quartiles 1790-03-29; 1890-10-14
\emini \bminitwo
ggAggHist(data = structure(list(factorV = structure(1:20, .Label = c("1300-03-01", "1333-03-27", "1366-04-22", "1399-05-18", "1432-06-13", "1465-07-09", "1498-08-04", "1531-08-31", "1564-09-25", "1597-10-21", "1630-11-16", "1663-12-13", "1697-01-07", "1730-02-03", "1763-03-01", "1796-03-26", "1829-04-22", "1862-05-18", "1895-06-13", "1928-07-09"), class = "factor"), Freq = c(1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 5L, 8L, 6L, 9L, 6L, 7L, 4L), xmin = structure(c(-244653, -232574, -220495, -208416, -196337, -184258, -172179, -160100, -148021, -135942, -123863, -111783, -99704, -87625, -75546, -63467, -51388, -39309, -27230, -15151), class = "Date"), xmax = structure(c(-232574, -220495, -208416, -196337, -184258, -172179, -160100, -148021, -135942, -123863, -111783, -99704, -87625, -75546, -63467, -51388, -39309, -27230, -15151, -3072 ), class = "Date"), ymin = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), ymax = c(1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 5L, 8L, 6L, 9L, 6L, 7L, 4L )), .Names = c("factorV", "Freq", "xmin", "xmax", "ymin", "ymax"), row.names = c(NA, -20L), class = "data.frame"), vnam = "birthday")
\emini
- Note that the following possible outlier values were detected: \"1300-03-01\".
\fullline
stateOfBirth
\bminione
Feature Result
Variable type character
Number of missing obs. 0 (0 %)
Number of unique values 23
Mode "Ohio"
\emini \bminitwo
ggAggBarplot(data = structure(list(x = structure(1:23, .Label = c("Arkansas", "California", "Connecticut", "Georgia", "Gondor", "Hawaii", "Illinois", "Iowa", "Kentucky", "Massachusetts", "Missouri", "Nebraska", "New Hampshire", "New Jersey", "New York", "New york", "North Carolina", "Ohio", "Pennsylvania", "Tennessee", "Texas", "Vermont", "Virginia" ), class = "factor"), y = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 4L, 1L, 1L, 1L, 2L, 4L, 1L, 2L, 8L, 1L, 1L, 2L, 2L, 7L)), .Names = c("x", "y"), row.names = c(NA, -23L), class = "data.frame"), vnam = "stateOfBirth")
\emini
- Note that there might be case problems with the following levels: \"New York\", \"New york\".
\fullline
assassinationAttempt
- Note that this variable is treated as a factor variable below, as it only takes a few unique values.
\bminione
Feature Result
Variable type numeric
Number of missing obs. 0 (0 %)
Number of unique values 2
Mode "0"
\emini \bminitwo
ggAggBarplot(data = structure(list(x = structure(1:2, .Label = c("0", "1"), class = "factor"), y = c(35L, 11L)), .Names = c("x", "y" ), row.names = c(NA, -2L), class = "data.frame"), vnam = "assassinationAttempt")
\emini
\fullline
sex
- The variable only takes one (non-missing) value: \"Male\". The variable contains 0 \% missing observations.
\fullline
ethnicity
\bminione
Feature Result
Variable type factor
Number of missing obs. 0 (0 %)
Number of unique values 2
Mode "Caucasian"
\emini \bminitwo
ggAggBarplot(data = structure(list(x = structure(1:2, .Label = c("African American", "Caucasian"), class = "factor"), y = c(1L, 45L)), .Names = c("x", "y"), row.names = c(NA, -2L), class = "data.frame"), vnam = "ethnicity")
\emini
- Note that the following levels have at most five observations: \"African American\".
\fullline
presidencyYears
\bminione
Feature Result
Variable type numeric
Number of missing obs. 2 (4.35 %)
Number of unique values 10
Median 4
1st and 3rd quartiles 3.75; 8
Min. and max. 0; Inf
\emini \bminitwo
ggAggHist(data = structure(list(factorV = structure(1:20, .Label = c("[0,0.6]", "(0.6,1.2]", "(1.2,1.8]", "(1.8,2.4]", "(2.4,3]", "(3,3.6]", "(3.6,4.2]", "(4.2,4.8]", "(4.8,5.4]", "(5.4,6]", "(6,6.6]", "(6.6,7.2]", "(7.2,7.8]", "(7.8,8.4]", "(8.4,9]", "(9,9.6]", "(9.6,10.2]", "(10.2,10.8]", "(10.8,11.4]", "(11.4,12]"), class = "factor"), Freq = c(2L, 1L, 0L, 4L, 4L, 0L, 15L, 0L, 3L, 0L, 0L, 3L, 0L, 10L, 0L, 0L, 0L, 0L, 0L, 1L), xmin = c(0, 0.6, 1.2, 1.8, 2.4, 3, 3.6, 4.2, 4.8, 5.4, 6, 6.6, 7.2, 7.8, 8.4, 9, 9.6, 10.2, 10.8, 11.4), xmax = c(0.6, 1.2, 1.8, 2.4, 3, 3.6, 4.2, 4.8, 5.4, 6, 6.6, 7.2, 7.8, 8.4, 9, 9.6, 10.2, 10.8, 11.4, 12), ymin = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), ymax = c(2L, 1L, 0L, 4L, 4L, 0L, 15L, 0L, 3L, 0L, 0L, 3L, 0L, 10L, 0L, 0L, 0L, 0L, 0L, 1L)), .Names = c("factorV", "Freq", "xmin", "xmax", "ymin", "ymax"), row.names = c(NA, -20L ), class = "data.frame"), vnam = "presidencyYears")
\emini
-
The following suspected missing value codes enter as regular values: \"Inf\".
-
Note that the following possible outlier values were detected: \"0\", \"1\", \"Inf\".
\fullline
ageAtInauguration
\bminione
Feature Result
Variable type character
Number of missing obs. 0 (0 %)
Number of unique values 23
Mode "54"
\emini \bminitwo
ggAggBarplot(data = structure(list(x = structure(1:23, .Label = c("42", "43", "46", "47", "48", "49", "50", "51", "52", "54", "55", "56", "57", "58", "60", "61", "62", "64", "65", "68", "69", "70", "87" ), class = "factor"), y = c(1L, 1L, 2L, 2L, 1L, 2L, 2L, 4L, 2L, 5L, 4L, 3L, 4L, 1L, 1L, 3L, 1L, 2L, 1L, 1L, 1L, 1L, 1L)), .Names = c("x", "y"), row.names = c(NA, -23L), class = "data.frame"), vnam = "ageAtInauguration")
\emini
- Note: The variable consists exclusively of numbers and takes a lot of different values. Is it perhaps a misclassified numeric variable?
\fullline
favoriteNumber
- The variable has class complex which is not supported by dataMaid.
\fullline
Report generation information:
-
Created by Claus Thorn Ekstrøm (username:
cld189). -
Report creation time: Wed Apr 11 2018 01:02:26
-
Report Was run from directory:
/Users/cld189/ku/R/cleanR/latex -
dataMaid v1.1.0 [Pkg: 2018-03-02 from local (ekstroem/dataMaid@NA)]
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R version 3.4.4 (2018-03-15).
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Platform: x86_64-apple-darwin15.6.0 (64-bit)(macOS High Sierra 10.13.3).
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Function call:
makeDataReport(data = presidentData, replace = TRUE, checks = setChecks(character = defaultCharacterChecks(remove = "identifyLoners")), reportTitle = "Dirty president data", treatXasY = list(Name = "character"))
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