Recode (stylized as recode; formerly Re/code) is a technology news website that focused on the business of Silicon Valley. Walt Mossberg and Kara Swisher founded it in January 2014, after they left Dow Jones and the similar website they had previously co-founded, All Things Digital. Vox Media acquired Recode in May 2015, and in May 2019, The Recode website was integrated into Vox. Recode still exists today, but it can only be read through the Vox website.
recode() is superseded in favor of case_match(), which handles the mostimportant cases of recode() with a more elegant interface.recode_factor() is also superseded, however, its direct replacement is notcurrently available but will eventually live inforcats. For creating new variables basedon logical vectors, use if_else(). For even more complicated criteria, usecase_when().
recode() is a vectorised version of switch(): you can replace numericvalues based on their position or their name, and character or factor valuesonly by their name. This is an S3 generic: dplyr provides methods fornumeric, character, and factors. You can use recode() directly withfactors; it will preserve the existing order of levels while changing thevalues. Alternatively, you can use recode_factor(), which will change theorder of levels to match the order of replacements.
A vector the same length as .x, and the same type asthe first of ..., .default, or .missing.recode_factor() returns a factor whose levels are in the same order asin .... The levels in .default and .missing come last.
Recodes a numeric vector, character vector, or factor according to simple recode specifications. Recodeis an alias for recode that avoids name clasheswith packages, such as Hmisc, that have a recode function.
Recode specifications appear in a character string, separated by default bysemicolons (see the examples below), each of the form input=output(where = may be replaced by a non-default value of theto.value argument, e.g., input -> output). Spaces may beused for clarity.If an input value satisfies more than one specification, then the first (from left to right) applies.If no specification is satisfied, then the input value is carriedover to the result. NA is allowed on input and output.Several recode specifications are supported:
For example, 7:9 = 'C'. The special values loand hi may appear in a range. For example, lo:10=1. Note: : isnot the R sequence operator. In addition, you may not use : with the c function within a recode specification, so for example c(1, 3, 5:7) will cause an error. The : is the default value of the recode interval operator; a non-default value may be specified.
everything that does not fit a previous specification.For example, else = NA. Note that else matches all otherwiseunspecified values on input, including NA, and if present should appear last among the recode specifications.
Character data and factor levels on the left-hand side of a recode specification must be quoted. Thus,e.g., c(a, b, c) = 'low' is not allowed, and should be c('a', 'b', 'c') = 'low'. Similarly, the colon is reserved for numeric data, and, e.g., c('a':'c') = 'low' is not allowed. If the var argument is a character variable with (some) values that are character representations of numbers, or a factorwith (some) levels that are numbers (e.g., '12' or '-2'), then these too must be quoted and cannot be used with colons (e.g., '15':'19' = '15 to 19' is not allowed, and could bespecified as c('15', '16', '17', '18', '19') = '15 to 19', assuming that all values are the character representation of whole numbers).
To test the genomically recoded organism (GRO), the scientists included UAG codons in the sequence for a green fluorescent protein. They found that the GROs successfully incorporated NSAAs into the proteins.
The recode rules can be read from standard input (i.e., from thekeyboard, redirected from a file, or piped through another program) byentering rules=-.Rules are defined in one of these formats:old_low:old_high:new_low:new_highold_low:old_high:new_val (i.e. new_high == new_low)*:old_val:new_val (interval [inf, old_val])old_val:*:new_val (interval [old_val, inf])r.recode is loosely basedon r.reclass and uses the GRASSReclass Library to convert the rasters. It has routines for convertingto every possible combination of raster (eg. CELL to DCELL, DCELL toFCELL, etc). Standard floating point raster precision is float(FCELL), with -d double precision (DCELL) will be written.There are four basic routines that it accepts: old-low to old-high is reclassed to new-low to new high , where the user provides all four values. The program figures on the fly what type of raster should be created. old-low to old-high is reclassed to a single new value. Anything outside the range is null. * to old-high will reclass everything less than old-high to a single new value. old-low to * will reclass everything greater than old-low to a single new value.These four sets of arguments can be given on the command line, orpiped via stdin or a file. More than one set of arguments is accepted.EXAMPLESMap type conversionTo simply convert a raster between formats (eg. int to float) the userwould use the first argument. For example10:1500:0.1:15.0would convert an input raster map with range between 10 and 1500 to afloat raster raster with range between 0.1 and 15.0.Value replacementr.recode can be used to replace existing cell values byothers. The formatting is as described above. In following example thevalues 1, 2 and 3 are replaced by 1.1, 7.5 resp. 0.4:r.recode input=oldmap output=newmap rules=-
By default, any --recode option, and also --make-bedwill preserve all genotypes exactly as they are. To set to missingMendel errors or heterozygous haploid calls, use theoptions --set-me-missing and --set-hh-missingrespectively. For the former, you will also need to specify --me 11 (i.e. to invole an evalation of Mendel errors, which does notoccur by default, by not excluding any individuals or SNPs based onthe results, i.e. if you only want to zero-out certain genotypes).
It is sometimes useful to have a PED file that is tab-delimited,except that between alleles of the same genotype a space instead of atab is used. A file formatted in this way can load into Excel, forexample, as a tab-delimited file, but with one genotype per columninstead of one allele per column. Use the option --tab aswell as --recode or --recode12 to achieve thiseffect.
B New Name field and Add New Name button: These fields will activate after at least one variable has been added to the Variable -> New Name box. You will need to supply a new variable name and click Add New Name for each variable being recoded.
C Recode Starting from: Should the new category numbering be in alphabetical order (Lowest value) or reverse alphabetical order (Highest value) with respect to the original values? This setting is applied to all of the variables being recoded.
In the output, the recoded blank values are correctly counted as missing, but show their assigned numeric code in the Value Labels column in the output. You can improve the appearance of the missing value category by simply adding a value label (e.g. "Missing") for that particular code.
Here, you can see that observations originally coded as "999" have been recoded to the numeric indicator 4 with the value label "999". The letter M indicates that the label or code is a missing value indicator.
As you can see from the syntax, SPSS first alphabetizes all possible unique nonmissing category values across the two variables, then assigns numeric codes to each category. Notice that the "missing" category ("999") was recoded last, even though it is alphabetically before the category names.
The following example two numeric variables x and y are recodedin place.Zero is recoded to 99, the values 1 to 10 inclusive are unchanged,values 1000 and higher are recoded to the system-missing value and all othervalues are changed to 999:
Here we have two recodings. The first affects the source variablea and recodes in-place the value 2 into 22 and all other values to 99.The second recoding copies the values of b into the variable z,changing any instances of 1 into 3.
rec() recodes values of variables, where variable selection is based on variable names or column position, or on select helpers (see documentation on ...). rec_if() is a scoped variant of rec(), where recoding will be applied only to those variables that match the logical condition of predicate.
Optional character vector, to set value label attributesof recoded variable (see vignette Labelled Data and the sjlabelled-Package).If NULL (default), no value labels will be set. Value labelscan also be directly defined in the rec-syntax, see'Details'.
x with recoded categories. If x is a data frame, for append = TRUE, x including the recoded variables as new columns is returned; if append = FALSE, only the recoded variables will be returned. If append = TRUE andsuffix = "", recoded variables will replace (overwrite) existing variables.
for double vectors (with fractional part), all values within the specified range are recoded; e.g. 1:2.5=1;2.6:3=2 recodes 1 to 2.5 into 1 and 2.6 to 3 into 2, but 2.55 would not be recoded (since it's not included in any of the specified ranges)
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. "3=1; 1=2; else=copy" (recodes 3 into 1, 1 into 2 and all other values like 2, 4 or 5 etc. will not be recoded, but copied, see 'Examples')
value labels for new values can be assigned inside the recode pattern by writing the value label in square brackets after defining the new value in a recode pair, e.g. "15:30=1 [young aged]; 31:55=2 [middle aged]; 56:max=3 [old aged]". See 'Examples'.
Variable label attributes (see, for instance, get_label) are preserved (unless changed via var.label-argument), however, value label attributes are removed (except for "rev", where present value labels will be automatically reversed as well). Use val.labels-argument to add labels for recoded values. 041b061a72