RStudio Addin to quickly and roughly convert nested ifelse() statements to
dplyr::case_when().
Contents
- Installation and requirements
- Before and after
- Motivation
- Features
- Limitations
- Examples
- TODO
- License
Install
devtools::install_github("erictleung/unnestIfElse")Requirements
dplyr
magrittr
stringr
rstudioapi
Before:
ifelse(statement, TRUE, FALSE)
After:
case_when(
statement ~ TRUE
TRUE ~ FALSE
)
Inspired by:
#rstats does someone have a magic function to turn nested ifelse statements into dplyr::casewhen?
— Gordon Shotwell (@gshotwell) October 25, 2019
- Changes highlighted text in place
- Highlighted text should be complete
ifelse()expression
- Only works for highlighted text, cannot convert an entire script
- Highlighted text has to exclusively include complete
ifelse()statement - Lacking any error handling
- Doesn't handle the case if the last "no" value is some function call with
parentheses (e.g.,
ifelse(1 != 1, -4, abs(-4))) - Limited test coverage for use
- Code formatting will fail with any text with commas (see below)
# Addin will fail with this example
# Source:
# https://github.com/Sean-Hughes/Relational_Complexity_Derivation/blob/master/Analyses/independent%20t%20test%20-%20IAT%20D1.R
nhst <- ifelse(t_test_p < 0.05,
paste("A Welch's independent t test demonstrated significant differences of ", d_interpretation, " effect size in ", DV_name, " between ", sep = ""),
paste("A Welch's independent t test demonstrated non-significant differences of ", d_interpretation, " effect size between ", sep = ""))
# Another example that will fail
# Source: https://github.com/wmlutz/r-lesson/blob/master/hold_temp.R
aw$cert_Admin <- ifelse("Admin" %in% raw[,"Certifications"], 1,0)I did a quick advanced GitHub search of ifelse language:R to find these
examples. I've tried to pick a mix of short to long examples. I also wanted to
make sure this function works on code in the "wild".
Source: https://github.com/Anis-Bensaid/SBT13/blob/master/Script%20R%20Final.R
Before:
data$a1 <- ifelse(bd1$A1=="Pas du tout", 0, ifelse(bd1$A1=="Un peu", 1,ifelse(bd1$A1== "Beaucoup", 2,ifelse(bd1$A1 == "Enormément", 3,NA))))After:
data$a1 <- case_when(
bd1$A1=="Pas du tout" ~ 0,
bd1$A1=="Un peu" ~ 1,
bd1$A1== "Beaucoup" ~ 2,
bd1$A1 == "Enormément" ~ 3,
TRUE ~ NA
)Source: https://github.com/ajpelu/qpyr_resilience/blob/master/R/getComposite.R
Before:
getComposite_nonleap <- function(m,d){
# m = month
# d = day
ifelse(m == 1 & d < 17, 1,
ifelse(m == 1 & d >= 17, 2,
ifelse(m == 2 & d < 2, 2,
ifelse(m == 2 & d < 18, 3,
ifelse(m == 2 & d >= 18, 4,
ifelse(m == 3 & d < 6, 4,
ifelse(m == 3 & d < 22, 5,
ifelse(m == 3 & d >= 22, 6,
ifelse(m == 4 & d < 7, 6,
ifelse(m == 4 & d < 23, 7,
ifelse(m == 4 & d >= 23, 8,
ifelse(m == 5 & d < 9, 8,
ifelse(m == 5 & d < 25, 9,
ifelse(m == 5 & d >= 25, 10,
ifelse(m == 6 & d < 10, 10,
ifelse(m == 6 & d < 26, 11,
ifelse(m == 6 & d >= 26, 12,
ifelse(m == 7 & d < 12, 12,
ifelse(m == 7 & d < 28, 13,
ifelse(m == 7 & d >= 28, 14,
ifelse(m == 8 & d < 13, 14,
ifelse(m == 8 & d < 29, 15,
ifelse(m == 8 & d >= 29, 16,
ifelse(m == 9 & d < 14, 16,
ifelse(m == 9 & d < 30, 17,
ifelse(m == 9 & d >= 30, 18,
ifelse(m == 10 & d < 16, 18,
ifelse(m == 10 & d >= 16, 19,
ifelse(m == 11 & d < 17, 20,
ifelse(m == 11 & d >= 17, 21,
ifelse(m == 12 & d < 3, 21,
ifelse(m == 12 & d < 19, 22, 23))))))))))))))))))))))))))))))))
}After:
getComposite_nonleap <- function(m,d){
# m = month
# d = day
case_when(
m == 1 & d < 17 ~ 1,
m == 1 & d >= 17 ~ 2,
m == 2 & d < 2 ~ 2,
m == 2 & d < 18 ~ 3,
m == 2 & d >= 18 ~ 4,
m == 3 & d < 6 ~ 4,
m == 3 & d < 22 ~ 5,
m == 3 & d >= 22 ~ 6,
m == 4 & d < 7 ~ 6,
m == 4 & d < 23 ~ 7,
m == 4 & d >= 23 ~ 8,
m == 5 & d < 9 ~ 8,
m == 5 & d < 25 ~ 9,
m == 5 & d >= 25 ~ 10,
m == 6 & d < 10 ~ 10,
m == 6 & d < 26 ~ 11,
m == 6 & d >= 26 ~ 12,
m == 7 & d < 12 ~ 12,
m == 7 & d < 28 ~ 13,
m == 7 & d >= 28 ~ 14,
m == 8 & d < 13 ~ 14,
m == 8 & d < 29 ~ 15,
m == 8 & d >= 29 ~ 16,
m == 9 & d < 14 ~ 16,
m == 9 & d < 30 ~ 17,
m == 9 & d >= 30 ~ 18,
m == 10 & d < 16 ~ 18,
m == 10 & d >= 16 ~ 19,
m == 11 & d < 17 ~ 20,
m == 11 & d >= 17 ~ 21,
m == 12 & d < 3 ~ 21,
m == 12 & d < 19 ~ 22,
TRUE ~ 23
)
}Source: https://github.com/WWF-ConsEvidence/ACES/blob/master/Mozambique/Harmonized_Demographic_Data.R
Before:
Community2008 <- ifelse(dat2008$Community_code == 241601, "Fuzi",
ifelse(dat2008$Community_code == 41602, "Moebase",
ifelse(dat2008$Community_code==41603, "Txotxo",
ifelse(dat2008$Community_code ==41604, "Monudo/Murudo",
ifelse(dat2008$Community_code ==41605, "Namige",
ifelse(dat2008$Community_code ==41606, "Solulo",
ifelse(dat2008$Community_code ==41607, "Magene",
ifelse(dat2008$Community_code ==41608, "Murateia",
ifelse(dat2008$Community_code ==41609, "Namaquete",
ifelse(dat2008$Community_code ==31101, "Mtopa",
ifelse(dat2008$Community_code ==31102, "Hori",
ifelse(dat2008$Community_code ==31103, "Mecane (Oua)",
ifelse(dat2008$Community_code ==31104, "Nacocolo",
ifelse(dat2008$Community_code ==31105, "Pacone",
ifelse(dat2008$Community_code ==31106, "Ampuitine",
ifelse(dat2008$Community_code ==31107, "Corane",
ifelse(dat2008$Community_code ==31108, "Lalaue",
ifelse(dat2008$Community_code ==31109, "Mavele",
ifelse(dat2008$Community_code ==31110, "Mucoroma",
ifelse(dat2008$Community_code ==31111, "Nacalela",
ifelse(dat2008$Community_code ==31112, "Nambui",
ifelse(dat2008$Community_code ==31113, "Namichir",
ifelse(dat2008$Community_code ==31114, "Nanheua",
ifelse(dat2008$Community_code ==31115, "Natere",
ifelse(dat2008$Community_code ==31116, "Tipane",
ifelse(dat2008$Community_code ==30101, "Iarupa",
ifelse(dat2008$Community_code ==30102, "Mituco",
ifelse(dat2008$Community_code ==30103, "Macogone",
ifelse(dat2008$Community_code ==30104, "Munar",
ifelse(dat2008$Community_code ==30105, "Namiepe",
ifelse(dat2008$Community_code ==30106, "Nauluco",
ifelse(dat2008$Community_code ==30107, "Pulizica",
ifelse(dat2008$Community_code ==30108, "Naheco",
ifelse(dat2008$Community_code ==30109, "Namame",NA))))))))))))))))))))))))))))))))))After:
Community2008 <- case_when(
dat2008$Community_code == 241601 ~ "Fuzi",
dat2008$Community_code == 41602 ~ "Moebase",
dat2008$Community_code==41603 ~ "Txotxo",
dat2008$Community_code ==41604 ~ "Monudo/Murudo",
dat2008$Community_code ==41605 ~ "Namige",
dat2008$Community_code ==41606 ~ "Solulo",
dat2008$Community_code ==41607 ~ "Magene",
dat2008$Community_code ==41608 ~ "Murateia",
dat2008$Community_code ==41609 ~ "Namaquete",
dat2008$Community_code ==31101 ~ "Mtopa",
dat2008$Community_code ==31102 ~ "Hori",
dat2008$Community_code ==31103 ~ "Mecane (Oua)",
dat2008$Community_code ==31104 ~ "Nacocolo",
dat2008$Community_code ==31105 ~ "Pacone",
dat2008$Community_code ==31106 ~ "Ampuitine",
dat2008$Community_code ==31107 ~ "Corane",
dat2008$Community_code ==31108 ~ "Lalaue",
dat2008$Community_code ==31109 ~ "Mavele",
dat2008$Community_code ==31110 ~ "Mucoroma",
dat2008$Community_code ==31111 ~ "Nacalela",
dat2008$Community_code ==31112 ~ "Nambui",
dat2008$Community_code ==31113 ~ "Namichir",
dat2008$Community_code ==31114 ~ "Nanheua",
dat2008$Community_code ==31115 ~ "Natere",
dat2008$Community_code ==31116 ~ "Tipane",
dat2008$Community_code ==30101 ~ "Iarupa",
dat2008$Community_code ==30102 ~ "Mituco",
dat2008$Community_code ==30103 ~ "Macogone",
dat2008$Community_code ==30104 ~ "Munar",
dat2008$Community_code ==30105 ~ "Namiepe",
dat2008$Community_code ==30106 ~ "Nauluco",
dat2008$Community_code ==30107 ~ "Pulizica",
dat2008$Community_code ==30108 ~ "Naheco",
dat2008$Community_code ==30109 ~ "Namame",
TRUE ~ NA
)- Convert multiple
ifelsestatements that span multiple lines (e.g., https://github.com/Anis-Bensaid/SBT13/blob/master/Script%20R%20Final.R)
MIT
