rec_with_table: Recode with Table
In recodeflow: Interface Functions for PMML Creation, and Data Recoding
Description
Usage
Arguments
Details
Value
Examples
View source: R/recode-with-table.R
Description
Creates new variables by recoding variables in a dataset using the rules
specified in a variables details sheet
Usage
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rec_with_table(
data,
variables = NULL,
database_name = NULL,
variable_details = NULL,
else_value = NA,
append_to_data = FALSE,
log = FALSE,
notes = TRUE,
var_labels = NULL,
custom_function_path = NULL,
attach_data_name = FALSE,
id_role_name = NULL,
name_of_environment_to_load = NULL,
append_non_db_columns = FALSE
)
Arguments
data
A dataframe containing the variables to be recoded.
Can also be a named list of dataframes.
variables
Character vector containing the names of the new variables
to recode to or a dataframe containing a variables sheet.
database_name
A String containing the name of the database containing
the original variables which should match up with a database from the
databaseStart column in the variables details sheet. Should be a character
vector if data is a named list where each vector item matches a name in the
data list and also matches with a value in the databaseStart column of a
variable details sheet.
variable_details
A dataframe containing the specifications
for recoding.
else_value
Value (string, number, integer, logical or NA) that is used
to replace any values that are outside the specified ranges
(no rules for recoding).
append_to_data
Logical, if TRUE (default), the newly
created variables will be appended to the original dataset.
log
Logical, if FALSE (default), a log containing information
about the recoding will not be printed.
notes
Logical, if FALSE (default), will not print the
content inside the 'Note“ column of the variable being recoded.
var_labels
labels vector to attach to variables in variables
custom_function_path
string containing the path to the file
containing functions to run for derived variables. This file will be sourced
and its functions loaded into the R environment.
attach_data_name
logical to attach name of database to end table
id_role_name
name for the role to be used to generate id column
name_of_environment_to_load
Name of package to load variables and
variable_details from
append_non_db_columns
boolean determening if data not present in
this cycle should be appended as NA
Details
The variable_details
dataframe needs the following columns:
- variable
Name of the new variable created. The name of the new
variable can be the same as the original variable if it does not change
the original variable definition
- toType
type the new variable
cat = categorical, cont = continuous
- databaseStart
Names of the databases that the original variable can
come from. Each database name should be seperated by a comma. For eg.,
"cchs2001_p, cchs2003_p,cchs2005_p,cchs2007_p"
- variableStart
Names of the original variables within each database
specified in the databaseStart column. For eg. ,
"cchs2001_p::RACA_6A,cchs2003_p::RACC_6A,ADL_01". The final variable
specified is the name of the variable for all other databases specified in
databaseStart but not in this column. For eg., ADL_01 would be the original
variable name in the cchs2005_p and cchs2007_p databases.
- fromType
variable type of start variable.
cat = categorical or factor variable
cont = continuous variable (real number or integer)
- recTo
Value to recode to
- recFrom
Value/range being recoded from
Each row in the variables details sheet encodes the rule for recoding
value(s) of the original variable to a category in the new variable. The
categories of the new variable are encoded in the recTo column
and the value(s) of the original variable that recode to this new value
are encoded in the recFrom column. These recode columns follow a
syntax similar to the sjmisc::rec() function. Whereas in the
sjmisc::rec() function the recoding rules are in one string,
in the variables details sheet they are encoded over multiple rows and
columns (recFrom an recTo). For eg., a recoding rule in the sjmisc function
would like like "1=2;2=3" whereas in the variables details sheet this would
be encoded over two rows with recFrom and recTo values of the first row
being 1 and 2 and similarly for the second row it would be 2 and 3.
The rules for describing recoding pairs are shown below:
- recode pairs
Each recode pair is a row
- multiple values
Multiple values from the old variable that should
be recoded into a new category of the new variable should be separated
with a comma. e.g.,
recFrom = "1,2"; recTo = 1
will recode values of 1 and 2 in the
original variable to 1 in the new variable
- value range
A value range is indicated by a colon, e.g.
recFrom= "1:4"; recTo = 1 will recode all values from 1to4 into 1
- min and max
minimum and maximum values
are indicated by min (or lo) and max (or hi),
e.g. recFrom = "min:4"; recTo = 1 will recode all values from the
minimum value of the original variable to 4 into 1
- "else"
All other values, which have not been specified yet,
are indicated by else, e.g. recFrom = "else"; recTo = NA
will recode all other values (not specified in other rows) of the
original variable to "NA")
- "copy"
the else token can be combined with
copy, indicating that all remaining, not yet recoded values should
stay the same (are copied from the original value), e.g.
recFrom = "else"; recTo = "copy"
- NA's
NA values are allowed both for the original
and the new variable, e.g.
recFrom "NA"; recTo = 1. or "recFrom = "3:5"; recTo = "NA"
(recodes all NA into 1,
and all values from 3 to 5 into NA in the new variable)
Value
a dataframe that is recoded according to rules in variable_details.
Examples
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var_details <-
data.frame(
"variable" = c("time", rep("status", times = 3), rep("trt", times = 2),
"age", rep("sex", times = 2), rep("ascites", times = 2),
rep("hepato", times = 2), rep("spiders", times = 2),
rep("edema", times = 3),
"bili", "chol", "albumin", "copper", "alk.phos", "ast",
"trig", "platelet", "protime", rep("stage", times = 4)),
"dummyVariable" = c("NA", "status0", "status1","status2", "trt1","trt2"
,"NA","sexM","sexF", "ascites0", "ascites1","hepato0","hepato1","
spiders0","spiders1","edema0.0","edema0.5","edema1.0",
rep("NA",times = 9), "stage1", "stage2","stage3","stage4"),
"toType" = c("cont", rep("cat", times = 3), rep("cat", times = 2),
"cont", rep("cat", times = 2), rep("cat", times = 2),
rep("cat", times = 2),rep("cat", times = 2), rep("cat", times = 3),
rep("cont", times = 9), rep("cat", times = 4)),
"databaseStart" = rep("tester1, tester2", times = 31),
"variableStart" = c("[time]", rep("[status]", times = 3), rep("[trt]",
times = 2), "[age]", rep("[sex]", times = 2), rep("[ascites]",
times = 2), rep("[hepato]", times = 2), rep("[spiders]", times = 2),
rep("[edema]", times = 3), "[bili]", "[chol]", "[albumin]", "[copper]",
"[alk.phos]", "[ast]", "[trig]", "[platelet]", "[protime]",
rep("[stage]", times = 4)), "fromType" = c("cont", rep("cat", times = 3),
rep("cat", times = 2), "cont", rep("cat", times = 2),
rep("cat", times = 2), rep("cat", times = 2),rep("cat", times = 2),
rep("cat", times = 3), rep("cont", times = 9), rep("cat", times = 4)),
"recTo" = c("copy", "0", "1","2", "1","2","copy","m","f", "0", "1","0",
"1","0","1","0.0","0.5","1.0",rep("copy",times = 9), "1", "2","3","4"),
"catLabel" = c("", "status 0", "status 1","status 2", "trt 1","trt 2","",
"sex m","sex f", "ascites 0", "ascites 1","hepato 0","hepato 1",
"spiders 0","spiders 1","edema 0.0","edema 0.5","edema 1.0",
rep("",times = 9), "stage 1", "stage 2","stage 3","stage 4"),
"catLabelLong" = c("", "status 0", "status 1","status 2", "trt 1",
"trt 2","","sex m","sex f", "ascites 0", "ascites 1","hepato 0","
hepato 1","spiders 0","spiders 1","edema 0.0","edema 0.5","edema 1.0",
rep("",times = 9), "stage 1", "stage 2","stage 3","stage 4"),
"recFrom" = c("else", "0", "1","2", "1","2","else","m","f", "0", "1","0",
"1","0","1","0.0","0.5","1.0",rep("else",times = 9), "1", "2","3","4"),
"catStartLabel" = c("", "status 0", "status 1","status 2", "trt 1",
"trt 2","","sex m","sex f", "ascites 0", "ascites 1","hepato 0",
"hepato 1","spiders 0","spiders 1","edema 0.0","edema 0.5","edema 1.0",
rep("",times = 9), "stage 1", "stage 2","stage 3","stage 4"),
"variableStartShortLabel" = c("time", rep("status", times = 3),
rep("trt", times = 2), "age", rep("sex", times = 2),
rep("ascites", times = 2), rep("hepato", times = 2),
rep("spiders", times = 2), rep("edema", times = 3), "bili", "chol",
"albumin", "copper", "alk.phos", "ast", "trig", "platelet", "protime",
rep("stage", times = 4)),
"variableStartLabel" = c("time", rep("status", times = 3),
rep("trt", times = 2), "age", rep("sex", times = 2),
rep("ascites", times = 2), rep("hepato", times = 2),
rep("spiders", times = 2), rep("edema", times = 3), "bili", "chol",
"albumin", "copper", "alk.phos", "ast", "trig", "platelet", "protime",
rep("stage", times = 4)),
"units" = rep("NA", times = 31),
"notes" = rep("This is sample survival pbc data", times = 31)
)
var_sheet <-
data.frame(
"variable" = c("time","status","trt", "age","sex","ascites","hepato",
"spiders", "edema", "bili", "chol", "albumin", "copper", "alk.phos",
"ast", "trig", "platelet", "protime", "stage"),
"label" = c("time","status","trt", "age","sex","ascites","hepato",
"spiders", "edema", "bili", "chol", "albumin", "copper", "alk.phos",
"ast", "trig", "platelet", "protime", "stage"),
"labelLong" = c("time","status","trt", "age","sex","ascites","hepato",
"spiders", "edema", "bili", "chol", "albumin", "copper", "alk.phos",
"ast", "trig", "platelet", "protime", "stage"),
"section" = rep("tester", times=19),
"subject" = rep("tester",times = 19),
"variableType" = c("cont", "cat", "cat", "cont","cat", "cat", "cat",
"cat", "cat", rep("cont", times = 9), "cat"),
"databaseStart" = rep("tester1, tester2", times = 19),
"units" = rep("NA", times = 19),
"variableStart" = c("[time]","[status]", "[trt]", "[age]", "[sex]",
"[ascites]","[hepato]","[spiders]","[edema]", "[bili]", "[chol]",
"[albumin]", "[copper]", "[alk.phos]", "[ast]", "[trig]", "[platelet]",
"[protime]","[stage]")
)
library(survival)
tester1 <- survival::pbc[1:209,]
tester2 <- survival::pbc[210:418,]
db_name1 <- "tester1"
db_name2 <- "tester2"
rec_sample1 <- rec_with_table(data = tester1,
variables = var_sheet,
variable_details = var_details,
database_name = db_name1)
rec_sample2 <- rec_with_table(data = tester2,
variables = var_sheet,
variable_details = var_details,
database_name = db_name2)
recodeflow documentation built on June 9, 2021, 9:07 a.m.
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Description Usage Arguments Details Value Examples
View source: R/recode-with-table.R
Description
Creates new variables by recoding variables in a dataset using the rules specified in a variables details sheet
Usage
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | rec_with_table(
data,
variables = NULL,
database_name = NULL,
variable_details = NULL,
else_value = NA,
append_to_data = FALSE,
log = FALSE,
notes = TRUE,
var_labels = NULL,
custom_function_path = NULL,
attach_data_name = FALSE,
id_role_name = NULL,
name_of_environment_to_load = NULL,
append_non_db_columns = FALSE
)
|
Arguments
data |
A dataframe containing the variables to be recoded. Can also be a named list of dataframes. |
variables |
Character vector containing the names of the new variables to recode to or a dataframe containing a variables sheet. |
database_name |
A String containing the name of the database containing the original variables which should match up with a database from the databaseStart column in the variables details sheet. Should be a character vector if data is a named list where each vector item matches a name in the data list and also matches with a value in the databaseStart column of a variable details sheet. |
variable_details |
A dataframe containing the specifications for recoding. |
else_value |
Value (string, number, integer, logical or NA) that is used to replace any values that are outside the specified ranges (no rules for recoding). |
append_to_data |
Logical, if |
log |
Logical, if |
notes |
Logical, if |
var_labels |
labels vector to attach to variables in variables |
custom_function_path |
string containing the path to the file containing functions to run for derived variables. This file will be sourced and its functions loaded into the R environment. |
attach_data_name |
logical to attach name of database to end table |
id_role_name |
name for the role to be used to generate id column |
name_of_environment_to_load |
Name of package to load variables and variable_details from |
append_non_db_columns |
boolean determening if data not present in this cycle should be appended as NA |
Details
The variable_details dataframe needs the following columns:
- variable
Name of the new variable created. The name of the new variable can be the same as the original variable if it does not change the original variable definition
- toType
type the new variable cat = categorical, cont = continuous
- databaseStart
Names of the databases that the original variable can come from. Each database name should be seperated by a comma. For eg., "cchs2001_p, cchs2003_p,cchs2005_p,cchs2007_p"
- variableStart
Names of the original variables within each database specified in the databaseStart column. For eg. , "cchs2001_p::RACA_6A,cchs2003_p::RACC_6A,ADL_01". The final variable specified is the name of the variable for all other databases specified in databaseStart but not in this column. For eg., ADL_01 would be the original variable name in the cchs2005_p and cchs2007_p databases.
- fromType
variable type of start variable. cat = categorical or factor variable cont = continuous variable (real number or integer)
- recTo
Value to recode to
- recFrom
Value/range being recoded from
Each row in the variables details sheet encodes the rule for recoding value(s) of the original variable to a category in the new variable. The categories of the new variable are encoded in the recTo column and the value(s) of the original variable that recode to this new value are encoded in the recFrom column. These recode columns follow a syntax similar to the sjmisc::rec() function. Whereas in the sjmisc::rec() function the recoding rules are in one string, in the variables details sheet they are encoded over multiple rows and columns (recFrom an recTo). For eg., a recoding rule in the sjmisc function would like like "1=2;2=3" whereas in the variables details sheet this would be encoded over two rows with recFrom and recTo values of the first row being 1 and 2 and similarly for the second row it would be 2 and 3. The rules for describing recoding pairs are shown below:
- recode pairs
Each recode pair is a row
- multiple values
Multiple values from the old variable that should be recoded into a new category of the new variable should be separated with a comma. e.g., recFrom = "1,2"; recTo = 1
will recode values of 1 and 2 in the original variable to 1 in the new variable
- value range
A value range is indicated by a colon, e.g. recFrom= "1:4"; recTo = 1 will recode all values from 1to4 into 1
- min and max
minimum and maximum values are indicated by min (or lo) and max (or hi), e.g. recFrom = "min:4"; recTo = 1 will recode all values from the minimum value of the original variable to 4 into 1
- "else"
All other values, which have not been specified yet, are indicated by else, e.g. recFrom = "else"; recTo = NA will recode all other values (not specified in other rows) of the original variable to "NA")
- "copy"
the else token can be combined with copy, indicating that all remaining, not yet recoded values should stay the same (are copied from the original value), e.g. recFrom = "else"; recTo = "copy"
- NA's
NA values are allowed both for the original and the new variable, e.g. recFrom "NA"; recTo = 1. or "recFrom = "3:5"; recTo = "NA" (recodes all NA into 1, and all values from 3 to 5 into NA in the new variable)
Value
a dataframe that is recoded according to rules in variable_details.
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 | var_details <-
data.frame(
"variable" = c("time", rep("status", times = 3), rep("trt", times = 2),
"age", rep("sex", times = 2), rep("ascites", times = 2),
rep("hepato", times = 2), rep("spiders", times = 2),
rep("edema", times = 3),
"bili", "chol", "albumin", "copper", "alk.phos", "ast",
"trig", "platelet", "protime", rep("stage", times = 4)),
"dummyVariable" = c("NA", "status0", "status1","status2", "trt1","trt2"
,"NA","sexM","sexF", "ascites0", "ascites1","hepato0","hepato1","
spiders0","spiders1","edema0.0","edema0.5","edema1.0",
rep("NA",times = 9), "stage1", "stage2","stage3","stage4"),
"toType" = c("cont", rep("cat", times = 3), rep("cat", times = 2),
"cont", rep("cat", times = 2), rep("cat", times = 2),
rep("cat", times = 2),rep("cat", times = 2), rep("cat", times = 3),
rep("cont", times = 9), rep("cat", times = 4)),
"databaseStart" = rep("tester1, tester2", times = 31),
"variableStart" = c("[time]", rep("[status]", times = 3), rep("[trt]",
times = 2), "[age]", rep("[sex]", times = 2), rep("[ascites]",
times = 2), rep("[hepato]", times = 2), rep("[spiders]", times = 2),
rep("[edema]", times = 3), "[bili]", "[chol]", "[albumin]", "[copper]",
"[alk.phos]", "[ast]", "[trig]", "[platelet]", "[protime]",
rep("[stage]", times = 4)), "fromType" = c("cont", rep("cat", times = 3),
rep("cat", times = 2), "cont", rep("cat", times = 2),
rep("cat", times = 2), rep("cat", times = 2),rep("cat", times = 2),
rep("cat", times = 3), rep("cont", times = 9), rep("cat", times = 4)),
"recTo" = c("copy", "0", "1","2", "1","2","copy","m","f", "0", "1","0",
"1","0","1","0.0","0.5","1.0",rep("copy",times = 9), "1", "2","3","4"),
"catLabel" = c("", "status 0", "status 1","status 2", "trt 1","trt 2","",
"sex m","sex f", "ascites 0", "ascites 1","hepato 0","hepato 1",
"spiders 0","spiders 1","edema 0.0","edema 0.5","edema 1.0",
rep("",times = 9), "stage 1", "stage 2","stage 3","stage 4"),
"catLabelLong" = c("", "status 0", "status 1","status 2", "trt 1",
"trt 2","","sex m","sex f", "ascites 0", "ascites 1","hepato 0","
hepato 1","spiders 0","spiders 1","edema 0.0","edema 0.5","edema 1.0",
rep("",times = 9), "stage 1", "stage 2","stage 3","stage 4"),
"recFrom" = c("else", "0", "1","2", "1","2","else","m","f", "0", "1","0",
"1","0","1","0.0","0.5","1.0",rep("else",times = 9), "1", "2","3","4"),
"catStartLabel" = c("", "status 0", "status 1","status 2", "trt 1",
"trt 2","","sex m","sex f", "ascites 0", "ascites 1","hepato 0",
"hepato 1","spiders 0","spiders 1","edema 0.0","edema 0.5","edema 1.0",
rep("",times = 9), "stage 1", "stage 2","stage 3","stage 4"),
"variableStartShortLabel" = c("time", rep("status", times = 3),
rep("trt", times = 2), "age", rep("sex", times = 2),
rep("ascites", times = 2), rep("hepato", times = 2),
rep("spiders", times = 2), rep("edema", times = 3), "bili", "chol",
"albumin", "copper", "alk.phos", "ast", "trig", "platelet", "protime",
rep("stage", times = 4)),
"variableStartLabel" = c("time", rep("status", times = 3),
rep("trt", times = 2), "age", rep("sex", times = 2),
rep("ascites", times = 2), rep("hepato", times = 2),
rep("spiders", times = 2), rep("edema", times = 3), "bili", "chol",
"albumin", "copper", "alk.phos", "ast", "trig", "platelet", "protime",
rep("stage", times = 4)),
"units" = rep("NA", times = 31),
"notes" = rep("This is sample survival pbc data", times = 31)
)
var_sheet <-
data.frame(
"variable" = c("time","status","trt", "age","sex","ascites","hepato",
"spiders", "edema", "bili", "chol", "albumin", "copper", "alk.phos",
"ast", "trig", "platelet", "protime", "stage"),
"label" = c("time","status","trt", "age","sex","ascites","hepato",
"spiders", "edema", "bili", "chol", "albumin", "copper", "alk.phos",
"ast", "trig", "platelet", "protime", "stage"),
"labelLong" = c("time","status","trt", "age","sex","ascites","hepato",
"spiders", "edema", "bili", "chol", "albumin", "copper", "alk.phos",
"ast", "trig", "platelet", "protime", "stage"),
"section" = rep("tester", times=19),
"subject" = rep("tester",times = 19),
"variableType" = c("cont", "cat", "cat", "cont","cat", "cat", "cat",
"cat", "cat", rep("cont", times = 9), "cat"),
"databaseStart" = rep("tester1, tester2", times = 19),
"units" = rep("NA", times = 19),
"variableStart" = c("[time]","[status]", "[trt]", "[age]", "[sex]",
"[ascites]","[hepato]","[spiders]","[edema]", "[bili]", "[chol]",
"[albumin]", "[copper]", "[alk.phos]", "[ast]", "[trig]", "[platelet]",
"[protime]","[stage]")
)
library(survival)
tester1 <- survival::pbc[1:209,]
tester2 <- survival::pbc[210:418,]
db_name1 <- "tester1"
db_name2 <- "tester2"
rec_sample1 <- rec_with_table(data = tester1,
variables = var_sheet,
variable_details = var_details,
database_name = db_name1)
rec_sample2 <- rec_with_table(data = tester2,
variables = var_sheet,
variable_details = var_details,
database_name = db_name2)
|
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