replace ALL... if the first...

[dario_gd]

i have a dataframe like :

subj  Gender	    act
 101   Male      801-walking forward
 101   Male      802-walking backward
 205   Female    909 back-sitting
 208   Male      914 right-recovery

I would like to replace the values ​​starting with "8 ..." with "0" and those starting with "9 .." with "1"

in this case

subj  Gender	    act
 101   Male          0
 101   Male          0
 205   Female        1
 208   Male          1

I thought with something like "case_when" or "str_replace" or "mutate" ... but I can not write a regular expression to say this.

[andresrcs]

Again, please ask your questions with a reproducible example or at least some sample data on a copy/paste friendly format.

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

[dario_gd]

sorry, i think reproducibile example is the "dataframe" that i have put.

so...
the dataframe is:

subj  Gender	    act
 101   Male      801-walking forward
 101   Male      802-walking backward
 205   Female    909 back-sitting
 208   Male      914 right-recovery

if i write a code like:

dataframe$act <- str_replace_all(dataframe$act, "^8", "0")

dataframe becomes

subj  Gender	    act
 101   Male      001-walking forward
 101   Male      002-walking backward
 205   Female    009 back-sitting
 208   Male      014 right-recovery

only the first number ( 8 or 9) is replaced with 0

dataframe$act<- case_when(dataframe$act== "^8" ~ "0", dataframe$act=="^9" ~ "1")

the columns dataframe$act becomes all NA..

[andresrcs]

Have you read the link I gave you? That is not reproducible because I can't just copy your code paste it on my rstudio session and reproduce your issue.

[dario_gd]

I'm sorry ... I do not want to be disrespectful, it's that I'm not very practical with either the system or the language. tell me, is that ok?

df <- data.frame(subject= c("101","102","103"), gender = c("male","male","male"), act = c("801-sadsa", "802-dasdas", "905-dsad"))
View(df)

df$act<- case_when(df$act== "^8" ~ "0", df$act=="^9" ~ "1")

df$act <- str_replace_all(df$act, "^8", "0")

[andresrcs]

It's better but not OK jet, because you forgot to include the calls to the libraries that you are using, take a look at the way I'm sharing the solution.

library(stringr)
library(dplyr)

df <- data.frame(subject= c("101","102","103"),
                 gender = c("male","male","male"),
                 act = c("801-sadsa", "802-dasdas", "905-dsad")
)

args <- c("^8.*" = "0",
          "^9.*" = "1")

df %>% 
    mutate(act = str_replace_all(act, args))
#>   subject gender act
#> 1     101   male   0
#> 2     102   male   0
#> 3     103   male   1

^{Created on 2019-02-17 by the reprex package (v0.2.1)}

[dario_gd]

ok, thanks...I will try to be more and more precise.