CODEWITHSUNDEEP
rloopsfor-loop
SoccerAnalytics26
SoccerAnalytics26

Reputation: 171

Using a loop on r to create and populate new columns

I am trying to write a loop that takes variables in a column of one table (table x) and use those names as column names in another table (table y) and then populate those columns based on certain criteria. Here is my code. I have been attempting to use a For Loop.

for(player in x)
  {
  y$paste0(x$player)<-ifelse(y$Playing=="True", 1, 0)
  }

The error I am getting is "invalid function in complex assignment"

I am working with sports data. My end goal is to count the amount of passes each player was on the field for. I will need to assign the variable 1 for players while they are on the field and a 0 if they are on the bench. Any help would be greatly appreciated.

Upvotes: 0

Views: 1675

Answers (2)

Mako212
Mako212

Reputation: 7292

How about just:

#  create df1 with 10 random TRUE/FALSE values
df1 <- data.frame(Player= sample(c(TRUE,FALSE),10,TRUE))

df1$playing <- sapply(df1$Player, function(x) ifelse(x==TRUE,1,0))

Update:

require(tidyr)

df1 <- data.frame(ID = seq(1,35),Player= sample(c("TRUE","FALSE"),35,TRUE))
df1$playing <- sapply(df1$Player, function(x) ifelse(x==TRUE,1,0))
df1 <- df1[,-2]

spread(df1, ID, playing)

And generalized to multiple games (i.e. multiple rows for each player ID)

df1 <- data.frame(ID = rep(1:35,each=3),GameID=rep(1:3,35),Player= sample(c("TRUE","FALSE"),105,TRUE))
df1$playing <- sapply(df1$Player, function(x) ifelse(x==TRUE,1,0))
df1 <- df1[,-3]

spread(df1, ID, playing)

Sample output

  GameID   1 2 3 4
       1   0 1 0 0
       2   0 0 1 0
       3   0 1 0 0

Upvotes: 1

Rui Barradas
Rui Barradas

Reputation: 76402

You don't need paste0 in this case . For what I understand of your attempted code, something like the following might do the job.

First let's make up the data frames x and y.

set.seed(1)   # make it reproducible
x <- data.frame(A = 1:5, B = rnorm(5))
y <- data.frame(Playing = sample(c("True","False"), 10, TRUE))

Now, create the new columns.

for(player in names(x)) {
    y[[player]] <- ifelse(y$Playing == "True", 1, 0)
}

The columns were created.

str(y)
'data.frame':   10 obs. of  3 variables:
 $ Playing: Factor w/ 2 levels "False","True": 2 2 1 2 1 2 1 1 2 1
 $ A      : num  1 1 0 1 0 1 0 0 1 0
 $ B      : num  1 1 0 1 0 1 0 0 1 0

Upvotes: 1

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