## Dummy variable "switch-point" in R

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I have a dummy variable that serves as a flag for a number of conditions in my data set. **I can't figure out how to write a function that marks the spot in which the flag assumes a "final switch" -- a value that will not change for the rest of the data frame.** *In the example below, everything after the 7th observation is a "y".*

dplyr::tibble( observation = c(seq(1,10)), crop = c(runif(3,1,25), runif(1,50,100), runif(2,1,10), runif(4,50,100)), flag = c(rep("n", 3), rep("y", 1), rep("n", 2), rep("y", 4)))

Which yields:

observation crop flag <int> <dbl> <chr> 1 1 13.3 n 2 2 4.34 n 3 3 17.1 n 4 4 80.5 y 5 5 9.62 n 6 6 8.39 n 7 7 92.6 y 8 8 74.1 y 9 9 95.3 y 10 10 69.9 y

I've tried creating a second flag that marks every switch and returns the "final" switch/flag variable, but over my whole data frame that will likely be highly inefficient. Any suggestions are welcome and appreciated.

One way to do this may be to create a flag that cumulatively sums occurrences of flag switches.

cumsum_na <- function(x){ x[which(is.na(x))] <- 0 return(cumsum(x)) } df <- dplyr::tibble( observation = c(seq(1,10)), crop = c(runif(3,1,25), runif(1,50,100), runif(2,1,10), runif(4,50,100)), flag = c(rep("n", 3), rep("y", 1), rep("n", 2), rep("y", 4))) df %>% mutate(flag2 = ifelse(flag != lag(flag), 1, 0) %>% cumsum_na) # A tibble: 10 x 4 observation crop flag flag2 <int> <dbl> <chr> <dbl> 1 1 12.1 n 0 2 2 11.2 n 0 3 3 4.66 n 0 4 4 61.6 y 1 5 5 6.00 n 2 6 6 9.54 n 2 7 7 67.6 y 3 8 8 86.7 y 3 9 9 91.6 y 3 10 10 84.5 y 3

You can then do whatever you need to using the `flag2`

column (eg. filter for max value, take first row, which will give you the first occurrence of constant state).

**Dummy variable (statistics),** takes on a value 1 its coefficient acts to alter the intercept. A dummy variable (aka, an indicator variable) is a numeric variable that represents categorical data, such as gender, race, political affiliation, etc. Technically, dummy variables are dichotomous, quantitative variables. Their range of values is small; they can take on only two quantitative values.

i count all the "n" first, and when when the final "n" is met, i get the index of the next obs

i=0 j=1 while (i<table(df$flag)["n"]) { if (as.character(df[j,3]) =="n" ) { i=i+1 j=j+1 } else j=j+1 }

You are looking for j

**Dummy Variables - Social Research Methods,** act like 'switches' that turn various parameters on and off in an equation. A dummy variable is a numerical variable used in regression analysis to represent subgroups of the sample in your study. In research design, a dummy variable is often used to distinguish different treatment groups.

We can make use of `rleid`

from `data.table`

library(data.table) setDT(df)[, flag2 := rleid(flag)] df # observation crop flag flag2 # 1: 1 21.472985 n 1 # 2: 2 21.563190 n 1 # 3: 3 1.393184 n 1 # 4: 4 88.422562 y 2 # 5: 5 6.383627 n 3 # 6: 6 8.484030 n 3 # 7: 7 86.998953 y 4 # 8: 8 62.220592 y 4 # 9: 9 93.141503 y 4 #10: 10 96.006885 y 4

**Creating Dummy Variables in SPSS - Quick Tutorial,** A dummy variable (aka, an indicator variable) is a numeric variable that represents categorical data, such as gender, race, political affiliation, etc. Researchers use� A dummy variable is a variable that takes values of 0 and 1, where the values indicate the presence or absence of something (e.g., a 0 may indicate a placebo and 1 may indicate a drug). Where a categorical variable has more than two categories, it can be represented by a set of dummy variables, with one variable for each category.

**Dummy Variable: Definition,** A dummy variable is a numerical variable used in regression analysis to represent subgroups of the sample in your study. A dummy variableis commonly used in statistics and econometrics and regression analysis. This indicator variable takes on the value of 1 or 0 to indicate the availability or lack of some effect that would change the outcome of whatever is being tested.

**Dummy Variables,** This video introduces the concept of dummy variables, and explains how we interpret their Duration: 4:47
Posted: Jun 23, 2013 dummy variables, each of which has two levels. The first step in this process is to decide the number of dummy variables. This is easy; it's simply k-1, where k is the number of levels of the original variable. You could also create dummy variables for all levels in the original variable, and simply drop one from each analysis.

**Dummy variables - an introduction,** In this video we learn about dummy variables: what the are, why we use them, and how we Duration: 20:59
Posted: Jan 7, 2015 What Is a Dummy Variable? In regression analysis, a dummy is a variable that is used to include categorical data into a regression model. In previous tutorials, we have only used numerical data. We did that when we first introduced linear regressions and again when we were exploring the adjusted R-squared.

##### Comments

- By constant, I mean never to switch again for the rest of the data frame/observations. Will clarify that in original question.
- I edited my answer; let me know if this doesn't solve your problem!
- Appreciate your help on this.
- rleid seems useful. I'm trying to keep most of my operations in tibbles/dplyr, but I appreciate you offering this answer. Good to know about.
- @BSHuniversity. No problem, You can just change the syntax to
`df %>% mutate(flag2 = rleid(flag))`