Category: R

How to generate data from a model – Part 1

A Short R Package Review: RQDA – Musings on R – A blog on all things R and Data Science by Martin Chan (martinctc.github.io)

Thanks for helping me with R's ifelse.

This creates a fake dataset.
test = expand.grid(a = c(1, 2, 3, 4), b = c(1, 2, 3))

What I want to do is to something like this:

if a=3 then do;

if b=1 then news="3 and 1";

if b=2 then news="3 and 2";

end;

This below does half of the job.  Could you advise?

test$news <- ifelse(test$a == 3,ifelse(test$b == 1, "3 and 1",""),"")

Please email me at k u e k a w a @gmail.com .

Thanks.

library(broom)
library(compute.es)
library(dplyr)
library(forcats)
library(FSA)
library(gapminder)
library(ggplot2)
library(gmodels)
library(haven)
library(here)
library(leaflet)
library(magrittr)
library(markdown)
library(MatchIt)
library(plyr)
library(psych)
library(purrr)
library(readr)
library(readxl)
library(sas7bdat)
library(sf)
library(sqldf)
library(stringr)
library(summarytools)
library(tidyverse)
library(tmap)
library(tmaptools)
library(descr)
library(writexl)

library(tidyverse)

table1

show_example<-function(var1,var2){

var1_d <-deparse(substitute(var1))
var2_d <-deparse(substitute(var2))

table1 %>%
mutate(prop_cases=table1[[var1_d]]/table1[[var2_d]]) -> temp123
Summarize(temp123$prop_cases ~ country, data= temp123) -> kaz

}

result1<-show_example(var1=cases,var2=population)
result2<-show_example(var1=cases,var2=cases)

https://campus.datacamp.com/courses/introduction-to-writing-functions-in-r/all-about-arguments?ex=2

# Set the default for n to 5
cut_by_quantile <- function(x, n, na.rm, labels, interval_type) {
probs <- seq(0, 1, length.out = n + 1)
qtiles <- quantile(x, probs, na.rm = na.rm, names = FALSE)
right <- switch(interval_type, "(lo, hi]" = TRUE, "[lo, hi)" = FALSE)
cut(x, qtiles, labels = labels, right = right, include.lowest = TRUE)
}

# Remove the n argument from the call
cut_by_quantile(
n_visits,
n = 5,
na.rm = FALSE,
labels = c("very low", "low", "medium", "high", "very high"),
interval_type = "(lo, hi]"
)

http://www.sthda.com/english/wiki/writing-data-from-r-to-excel-files-xls-xlsx

library(writexl)

write_xlsx(list(both = both), "GA.xlsx")

When two variables are similar but different by training empty spaces, do this.

levels(as.factor(main$county))

levels(as.factor(arc$county))

I tried to merge two data tables that contain the same variable county.   The simple merge did not work.  It turns out that one variable had trailing empty spaces.

https://notstatschat.rbind.io/2018/07/30/quoting-and-macros-in-r/

Also

#id dups
#create fake data
junk <- c(1, "J", 1, "J", 1, "K", 2, "K", 3, "K", 3, "T", 3, "T", 3, "T")
junk_mat <- data.frame(matrix(junk,ncol=2, byrow=T))
#install.packages("data.table") # install it
library(data.table)
junk_tab <- data.table(junk_mat)
colnames(junk_tab) <- c("num_var", "char_var")
junk_tab$num_var <- as.numeric(junk_tab$num_var)
junk_tab

library(psych)

#this one works with char_var in quotes
kaz_macro1<-function(var1,var2){
var1<-describeBy(x=as.numeric(junk_tab$num_var), group=junk_tab[[var2]])
print(var1)
}
kaz_macro1(var1=kc1a,var2="char_var")

#this one works without char_var in quotes
kaz_macro1<-function(var1,var2){
temp_var <-deparse(substitute(var2))
var1<-describeBy(x=as.numeric(junk_tab$num_var), group=junk_tab[[temp_var]])
print(var1)
}
kaz_macro1(var1=kc1a,var2=char_var)