Mixing
R: How to make extra rows from a column?
3
I have a data-set of human hands, where currently a single person is defined as a single observation. I want to reshape dataframe to have hands as individual observations. I tried something with "dplyr" package and "gather" function but had no success at all.
So from this, where each person is on one row :
id Gender Age Present_R Present_L Dominant
1 F 2 TRUE TRUE R
2 F 5 TRUE FALSE L
3 M 8 FALSE FALSE R
to this, where each hand is on one row:
id Gender Age Hand Present Dominant
1 F 2 R TRUE TRUE
2 F 2 L TRUE FALSE
3 F 5 R TRUE FALSE
4 F 5 L FALSE TRUE
5 M 8 R FALSE TRUE
6 M 8 L FALSE FALSE
Note that hand dominance becomes logical.
r dataframe
asked Jan 1 at 21:01
user2021713user2021713
186
add a comment |
3
I have a data-set of human hands, where currently a single person is defined as a single observation. I want to reshape dataframe to have hands as individual observations. I tried something with "dplyr" package and "gather" function but had no success at all.
So from this, where each person is on one row :
id Gender Age Present_R Present_L Dominant
1 F 2 TRUE TRUE R
2 F 5 TRUE FALSE L
3 M 8 FALSE FALSE R
to this, where each hand is on one row:
id Gender Age Hand Present Dominant
1 F 2 R TRUE TRUE
2 F 2 L TRUE FALSE
3 F 5 R TRUE FALSE
4 F 5 L FALSE TRUE
5 M 8 R FALSE TRUE
6 M 8 L FALSE FALSE
Note that hand dominance becomes logical.
r dataframe
asked Jan 1 at 21:01
user2021713user2021713
186
What's the logic behind Dominance?
– NelsonGon
Jan 1 at 21:08
"Dominance" means hand dominance. Each person has a dominant hand and if hands are separated then each hand will be dominant (TRUE) or nondominant (FALSE).
– user2021713
Jan 1 at 21:17
3
and for old times sake:r = reshape(dat, direction="long", varying=c("Present_R", "Present_L"), sep="_", timevar="hand"), then set Dominant to how you wantr$Dominant <- r$Dominant == r$hand
– user20650
Jan 1 at 22:19
add a comment |
3
3
3
I have a data-set of human hands, where currently a single person is defined as a single observation. I want to reshape dataframe to have hands as individual observations. I tried something with "dplyr" package and "gather" function but had no success at all.
So from this, where each person is on one row :
id Gender Age Present_R Present_L Dominant
1 F 2 TRUE TRUE R
2 F 5 TRUE FALSE L
3 M 8 FALSE FALSE R
to this, where each hand is on one row:
id Gender Age Hand Present Dominant
1 F 2 R TRUE TRUE
2 F 2 L TRUE FALSE
3 F 5 R TRUE FALSE
4 F 5 L FALSE TRUE
5 M 8 R FALSE TRUE
6 M 8 L FALSE FALSE
Note that hand dominance becomes logical.
r dataframe
asked Jan 1 at 21:01
user2021713user2021713
186
I have a data-set of human hands, where currently a single person is defined as a single observation. I want to reshape dataframe to have hands as individual observations. I tried something with "dplyr" package and "gather" function but had no success at all.
So from this, where each person is on one row :
id Gender Age Present_R Present_L Dominant
1 F 2 TRUE TRUE R
2 F 5 TRUE FALSE L
3 M 8 FALSE FALSE R
to this, where each hand is on one row:
id Gender Age Hand Present Dominant
1 F 2 R TRUE TRUE
2 F 2 L TRUE FALSE
3 F 5 R TRUE FALSE
4 F 5 L FALSE TRUE
5 M 8 R FALSE TRUE
6 M 8 L FALSE FALSE
Note that hand dominance becomes logical.
r dataframe
r dataframe
asked Jan 1 at 21:01
user2021713user2021713
186
asked Jan 1 at 21:01
user2021713user2021713
186
asked Jan 1 at 21:01
user2021713user2021713
186
asked Jan 1 at 21:01
user2021713user2021713
186
asked Jan 1 at 21:01
user2021713user2021713
186
186
What's the logic behind Dominance?
– NelsonGon
Jan 1 at 21:08
"Dominance" means hand dominance. Each person has a dominant hand and if hands are separated then each hand will be dominant (TRUE) or nondominant (FALSE).
– user2021713
Jan 1 at 21:17
3
and for old times sake:r = reshape(dat, direction="long", varying=c("Present_R", "Present_L"), sep="_", timevar="hand"), then set Dominant to how you wantr$Dominant <- r$Dominant == r$hand
– user20650
Jan 1 at 22:19
add a comment |
What's the logic behind Dominance?
– NelsonGon
Jan 1 at 21:08
"Dominance" means hand dominance. Each person has a dominant hand and if hands are separated then each hand will be dominant (TRUE) or nondominant (FALSE).
– user2021713
Jan 1 at 21:17
3
and for old times sake:r = reshape(dat, direction="long", varying=c("Present_R", "Present_L"), sep="_", timevar="hand"), then set Dominant to how you wantr$Dominant <- r$Dominant == r$hand
– user20650
Jan 1 at 22:19
What's the logic behind Dominance?
– NelsonGon
Jan 1 at 21:08
What's the logic behind Dominance?
– NelsonGon
Jan 1 at 21:08
"Dominance" means hand dominance. Each person has a dominant hand and if hands are separated then each hand will be dominant (TRUE) or nondominant (FALSE).
– user2021713
Jan 1 at 21:17
"Dominance" means hand dominance. Each person has a dominant hand and if hands are separated then each hand will be dominant (TRUE) or nondominant (FALSE).
– user2021713
Jan 1 at 21:17
3
3
and for old times sake:
r = reshape(dat, direction="long", varying=c("Present_R", "Present_L"), sep="_", timevar="hand"), then set Dominant to how you want r$Dominant <- r$Dominant == r$hand– user20650
Jan 1 at 22:19
and for old times sake:
r = reshape(dat, direction="long", varying=c("Present_R", "Present_L"), sep="_", timevar="hand"), then set Dominant to how you want r$Dominant <- r$Dominant == r$hand– user20650
Jan 1 at 22:19
add a comment |
2 Answers
2
active
oldest
votes
5
We can gather into 'long' format, arrange by 'id', then create the 'Dominant' by unlisting the 'Present' columns, 'Hand' by removing the substring of the 'Hand' column
library(tidyverse)
gather(df1, Hand, Present, Present_R:Present_L) %>%
arrange(id) %>%
mutate(Dominant = unlist(df1[c("Present_L", "Present_R")]),
id = row_number(),
Hand = str_remove(Hand, ".*_"))
# id Gender Age Dominant Hand Present
#1 1 F 2 TRUE R TRUE
#2 2 F 2 FALSE L TRUE
#3 3 F 5 FALSE R TRUE
#4 4 F 5 TRUE L FALSE
#5 5 M 8 TRUE R FALSE
#6 6 M 8 FALSE L FALSE
Based on the OP' comments, it seems like we need to compare the 'Dominant' with the 'Hand'
gather(df1, Hand, Present, Present_R:Present_L) %>%
arrange(id) %>%
mutate(id = row_number(),
Hand = str_remove(Hand, ".*_"),
Dominant = Dominant == Hand)
# id Gender Age Dominant Hand Present
#1 1 F 2 TRUE R TRUE
#2 2 F 2 FALSE L TRUE
#3 3 F 5 FALSE R TRUE
#4 4 F 5 TRUE L FALSE
#5 5 M 8 TRUE R FALSE
#6 6 M 8 FALSE L FALSE
answered Jan 1 at 21:21
akrunakrun
414k13201275
1
mutate function looks amazing!
– Farah Nazifa
Jan 1 at 21:41
1
Nice. What's the logic that led you to unlist?
– NelsonGon
Jan 1 at 22:17
Should row_number() function have an argument? For me it produces error: Error in rank(x, ties.method = "first", na.last = "keep") : argument "x" is missing, with no default
– user2021713
Jan 1 at 22:23
2
@NelsonGon Thanks. For me, I was initially checking the expected output. But now, by looking at the comments the OP made, I think it is more correct to havegather(df1, Hand, Present, Present_R:Present_L) %>%arrange(id) %>% mutate(id = row_number(), Hand = str_remove(Hand, ".*_"), Dominant = Dominant == Hand)
– akrun
Jan 1 at 22:24
1
@user2021713 No, it should work without any argument. I am usingR 3.5.1anddplyr_0.7.6
– akrun
Jan 1 at 22:27
|
show 3 more comments
0
With a small data frame (i.e., few variables, regardless of the number of cases), "hand-coding" may be the easiest approach:
with(df, data.frame(id = c(id,id), Gender=c(Gender,Gender), Age=c(Age, Age),
Hand = c(rep("R", nrow(df)), rep("L", nrow(df))),
Present = c(Present_R, Present_L),
Dominant = c(Dominant=="R", Dominant=="L")
))
answered Jan 1 at 21:28
lebatsnoklebatsnok
4,42621118
This solution almost seems to work, but for me for some reason Age will be incremented by 1 and Gender will be represented by numbers 1 and 2.
– user2021713
Jan 2 at 10:55
1
Well, I can't think of any other reason than Age and Gender being factors in your data frame. You can bypass this usingas.numeric(as.character(df$Age))andas.character(df$Gender)
– lebatsnok
Jan 2 at 11:26
Yes that was the reason. Thanks!
– user2021713
Jan 2 at 13:06
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
5
We can gather into 'long' format, arrange by 'id', then create the 'Dominant' by unlisting the 'Present' columns, 'Hand' by removing the substring of the 'Hand' column
library(tidyverse)
gather(df1, Hand, Present, Present_R:Present_L) %>%
arrange(id) %>%
mutate(Dominant = unlist(df1[c("Present_L", "Present_R")]),
id = row_number(),
Hand = str_remove(Hand, ".*_"))
# id Gender Age Dominant Hand Present
#1 1 F 2 TRUE R TRUE
#2 2 F 2 FALSE L TRUE
#3 3 F 5 FALSE R TRUE
#4 4 F 5 TRUE L FALSE
#5 5 M 8 TRUE R FALSE
#6 6 M 8 FALSE L FALSE
Based on the OP' comments, it seems like we need to compare the 'Dominant' with the 'Hand'
gather(df1, Hand, Present, Present_R:Present_L) %>%
arrange(id) %>%
mutate(id = row_number(),
Hand = str_remove(Hand, ".*_"),
Dominant = Dominant == Hand)
# id Gender Age Dominant Hand Present
#1 1 F 2 TRUE R TRUE
#2 2 F 2 FALSE L TRUE
#3 3 F 5 FALSE R TRUE
#4 4 F 5 TRUE L FALSE
#5 5 M 8 TRUE R FALSE
#6 6 M 8 FALSE L FALSE
answered Jan 1 at 21:21
akrunakrun
414k13201275
1
mutate function looks amazing!
– Farah Nazifa
Jan 1 at 21:41
1
Nice. What's the logic that led you to unlist?
– NelsonGon
Jan 1 at 22:17
Should row_number() function have an argument? For me it produces error: Error in rank(x, ties.method = "first", na.last = "keep") : argument "x" is missing, with no default
– user2021713
Jan 1 at 22:23
2
@NelsonGon Thanks. For me, I was initially checking the expected output. But now, by looking at the comments the OP made, I think it is more correct to havegather(df1, Hand, Present, Present_R:Present_L) %>%arrange(id) %>% mutate(id = row_number(), Hand = str_remove(Hand, ".*_"), Dominant = Dominant == Hand)
– akrun
Jan 1 at 22:24
1
@user2021713 No, it should work without any argument. I am usingR 3.5.1anddplyr_0.7.6
– akrun
Jan 1 at 22:27
|
show 3 more comments
5
We can gather into 'long' format, arrange by 'id', then create the 'Dominant' by unlisting the 'Present' columns, 'Hand' by removing the substring of the 'Hand' column
library(tidyverse)
gather(df1, Hand, Present, Present_R:Present_L) %>%
arrange(id) %>%
mutate(Dominant = unlist(df1[c("Present_L", "Present_R")]),
id = row_number(),
Hand = str_remove(Hand, ".*_"))
# id Gender Age Dominant Hand Present
#1 1 F 2 TRUE R TRUE
#2 2 F 2 FALSE L TRUE
#3 3 F 5 FALSE R TRUE
#4 4 F 5 TRUE L FALSE
#5 5 M 8 TRUE R FALSE
#6 6 M 8 FALSE L FALSE
Based on the OP' comments, it seems like we need to compare the 'Dominant' with the 'Hand'
gather(df1, Hand, Present, Present_R:Present_L) %>%
arrange(id) %>%
mutate(id = row_number(),
Hand = str_remove(Hand, ".*_"),
Dominant = Dominant == Hand)
# id Gender Age Dominant Hand Present
#1 1 F 2 TRUE R TRUE
#2 2 F 2 FALSE L TRUE
#3 3 F 5 FALSE R TRUE
#4 4 F 5 TRUE L FALSE
#5 5 M 8 TRUE R FALSE
#6 6 M 8 FALSE L FALSE
answered Jan 1 at 21:21
akrunakrun
414k13201275
1
mutate function looks amazing!
– Farah Nazifa
Jan 1 at 21:41
1
Nice. What's the logic that led you to unlist?
– NelsonGon
Jan 1 at 22:17
Should row_number() function have an argument? For me it produces error: Error in rank(x, ties.method = "first", na.last = "keep") : argument "x" is missing, with no default
– user2021713
Jan 1 at 22:23
2
@NelsonGon Thanks. For me, I was initially checking the expected output. But now, by looking at the comments the OP made, I think it is more correct to havegather(df1, Hand, Present, Present_R:Present_L) %>%arrange(id) %>% mutate(id = row_number(), Hand = str_remove(Hand, ".*_"), Dominant = Dominant == Hand)
– akrun
Jan 1 at 22:24
1
@user2021713 No, it should work without any argument. I am usingR 3.5.1anddplyr_0.7.6
– akrun
Jan 1 at 22:27
|
show 3 more comments
5
5
5
We can gather into 'long' format, arrange by 'id', then create the 'Dominant' by unlisting the 'Present' columns, 'Hand' by removing the substring of the 'Hand' column
library(tidyverse)
gather(df1, Hand, Present, Present_R:Present_L) %>%
arrange(id) %>%
mutate(Dominant = unlist(df1[c("Present_L", "Present_R")]),
id = row_number(),
Hand = str_remove(Hand, ".*_"))
# id Gender Age Dominant Hand Present
#1 1 F 2 TRUE R TRUE
#2 2 F 2 FALSE L TRUE
#3 3 F 5 FALSE R TRUE
#4 4 F 5 TRUE L FALSE
#5 5 M 8 TRUE R FALSE
#6 6 M 8 FALSE L FALSE
Based on the OP' comments, it seems like we need to compare the 'Dominant' with the 'Hand'
gather(df1, Hand, Present, Present_R:Present_L) %>%
arrange(id) %>%
mutate(id = row_number(),
Hand = str_remove(Hand, ".*_"),
Dominant = Dominant == Hand)
# id Gender Age Dominant Hand Present
#1 1 F 2 TRUE R TRUE
#2 2 F 2 FALSE L TRUE
#3 3 F 5 FALSE R TRUE
#4 4 F 5 TRUE L FALSE
#5 5 M 8 TRUE R FALSE
#6 6 M 8 FALSE L FALSE
answered Jan 1 at 21:21
akrunakrun
414k13201275
We can gather into 'long' format, arrange by 'id', then create the 'Dominant' by unlisting the 'Present' columns, 'Hand' by removing the substring of the 'Hand' column
library(tidyverse)
gather(df1, Hand, Present, Present_R:Present_L) %>%
arrange(id) %>%
mutate(Dominant = unlist(df1[c("Present_L", "Present_R")]),
id = row_number(),
Hand = str_remove(Hand, ".*_"))
# id Gender Age Dominant Hand Present
#1 1 F 2 TRUE R TRUE
#2 2 F 2 FALSE L TRUE
#3 3 F 5 FALSE R TRUE
#4 4 F 5 TRUE L FALSE
#5 5 M 8 TRUE R FALSE
#6 6 M 8 FALSE L FALSE
Based on the OP' comments, it seems like we need to compare the 'Dominant' with the 'Hand'
gather(df1, Hand, Present, Present_R:Present_L) %>%
arrange(id) %>%
mutate(id = row_number(),
Hand = str_remove(Hand, ".*_"),
Dominant = Dominant == Hand)
# id Gender Age Dominant Hand Present
#1 1 F 2 TRUE R TRUE
#2 2 F 2 FALSE L TRUE
#3 3 F 5 FALSE R TRUE
#4 4 F 5 TRUE L FALSE
#5 5 M 8 TRUE R FALSE
#6 6 M 8 FALSE L FALSE
answered Jan 1 at 21:21
akrunakrun
414k13201275
edited Jan 1 at 22:25
answered Jan 1 at 21:21
akrunakrun
414k13201275
answered Jan 1 at 21:21
akrunakrun
414k13201275
answered Jan 1 at 21:21
akrunakrun
414k13201275
414k13201275
1
mutate function looks amazing!
– Farah Nazifa
Jan 1 at 21:41
1
Nice. What's the logic that led you to unlist?
– NelsonGon
Jan 1 at 22:17
Should row_number() function have an argument? For me it produces error: Error in rank(x, ties.method = "first", na.last = "keep") : argument "x" is missing, with no default
– user2021713
Jan 1 at 22:23
2
@NelsonGon Thanks. For me, I was initially checking the expected output. But now, by looking at the comments the OP made, I think it is more correct to havegather(df1, Hand, Present, Present_R:Present_L) %>%arrange(id) %>% mutate(id = row_number(), Hand = str_remove(Hand, ".*_"), Dominant = Dominant == Hand)
– akrun
Jan 1 at 22:24
1
@user2021713 No, it should work without any argument. I am usingR 3.5.1anddplyr_0.7.6
– akrun
Jan 1 at 22:27
|
show 3 more comments
1
mutate function looks amazing!
– Farah Nazifa
Jan 1 at 21:41
1
Nice. What's the logic that led you to unlist?
– NelsonGon
Jan 1 at 22:17
Should row_number() function have an argument? For me it produces error: Error in rank(x, ties.method = "first", na.last = "keep") : argument "x" is missing, with no default
– user2021713
Jan 1 at 22:23
2
@NelsonGon Thanks. For me, I was initially checking the expected output. But now, by looking at the comments the OP made, I think it is more correct to havegather(df1, Hand, Present, Present_R:Present_L) %>%arrange(id) %>% mutate(id = row_number(), Hand = str_remove(Hand, ".*_"), Dominant = Dominant == Hand)
– akrun
Jan 1 at 22:24
1
@user2021713 No, it should work without any argument. I am usingR 3.5.1anddplyr_0.7.6
– akrun
Jan 1 at 22:27
1
1
mutate function looks amazing!
– Farah Nazifa
Jan 1 at 21:41
mutate function looks amazing!
– Farah Nazifa
Jan 1 at 21:41
1
1
Nice. What's the logic that led you to unlist?
– NelsonGon
Jan 1 at 22:17
Nice. What's the logic that led you to unlist?
– NelsonGon
Jan 1 at 22:17
Should row_number() function have an argument? For me it produces error: Error in rank(x, ties.method = "first", na.last = "keep") : argument "x" is missing, with no default
– user2021713
Jan 1 at 22:23
Should row_number() function have an argument? For me it produces error: Error in rank(x, ties.method = "first", na.last = "keep") : argument "x" is missing, with no default
– user2021713
Jan 1 at 22:23
2
2
@NelsonGon Thanks. For me, I was initially checking the expected output. But now, by looking at the comments the OP made, I think it is more correct to have
gather(df1, Hand, Present, Present_R:Present_L) %>%arrange(id) %>% mutate(id = row_number(), Hand = str_remove(Hand, ".*_"), Dominant = Dominant == Hand)– akrun
Jan 1 at 22:24
@NelsonGon Thanks. For me, I was initially checking the expected output. But now, by looking at the comments the OP made, I think it is more correct to have
gather(df1, Hand, Present, Present_R:Present_L) %>%arrange(id) %>% mutate(id = row_number(), Hand = str_remove(Hand, ".*_"), Dominant = Dominant == Hand)– akrun
Jan 1 at 22:24
1
1
@user2021713 No, it should work without any argument. I am using
R 3.5.1 and dplyr_0.7.6– akrun
Jan 1 at 22:27
@user2021713 No, it should work without any argument. I am using
R 3.5.1 and dplyr_0.7.6– akrun
Jan 1 at 22:27
|
show 3 more comments
0
With a small data frame (i.e., few variables, regardless of the number of cases), "hand-coding" may be the easiest approach:
with(df, data.frame(id = c(id,id), Gender=c(Gender,Gender), Age=c(Age, Age),
Hand = c(rep("R", nrow(df)), rep("L", nrow(df))),
Present = c(Present_R, Present_L),
Dominant = c(Dominant=="R", Dominant=="L")
))
answered Jan 1 at 21:28
lebatsnoklebatsnok
4,42621118
This solution almost seems to work, but for me for some reason Age will be incremented by 1 and Gender will be represented by numbers 1 and 2.
– user2021713
Jan 2 at 10:55
1
Well, I can't think of any other reason than Age and Gender being factors in your data frame. You can bypass this usingas.numeric(as.character(df$Age))andas.character(df$Gender)
– lebatsnok
Jan 2 at 11:26
Yes that was the reason. Thanks!
– user2021713
Jan 2 at 13:06
add a comment |
0
With a small data frame (i.e., few variables, regardless of the number of cases), "hand-coding" may be the easiest approach:
with(df, data.frame(id = c(id,id), Gender=c(Gender,Gender), Age=c(Age, Age),
Hand = c(rep("R", nrow(df)), rep("L", nrow(df))),
Present = c(Present_R, Present_L),
Dominant = c(Dominant=="R", Dominant=="L")
))
answered Jan 1 at 21:28
lebatsnoklebatsnok
4,42621118
This solution almost seems to work, but for me for some reason Age will be incremented by 1 and Gender will be represented by numbers 1 and 2.
– user2021713
Jan 2 at 10:55
1
Well, I can't think of any other reason than Age and Gender being factors in your data frame. You can bypass this usingas.numeric(as.character(df$Age))andas.character(df$Gender)
– lebatsnok
Jan 2 at 11:26
Yes that was the reason. Thanks!
– user2021713
Jan 2 at 13:06
add a comment |
0
0
0
With a small data frame (i.e., few variables, regardless of the number of cases), "hand-coding" may be the easiest approach:
with(df, data.frame(id = c(id,id), Gender=c(Gender,Gender), Age=c(Age, Age),
Hand = c(rep("R", nrow(df)), rep("L", nrow(df))),
Present = c(Present_R, Present_L),
Dominant = c(Dominant=="R", Dominant=="L")
))
answered Jan 1 at 21:28
lebatsnoklebatsnok
4,42621118
With a small data frame (i.e., few variables, regardless of the number of cases), "hand-coding" may be the easiest approach:
with(df, data.frame(id = c(id,id), Gender=c(Gender,Gender), Age=c(Age, Age),
Hand = c(rep("R", nrow(df)), rep("L", nrow(df))),
Present = c(Present_R, Present_L),
Dominant = c(Dominant=="R", Dominant=="L")
))
answered Jan 1 at 21:28
lebatsnoklebatsnok
4,42621118
answered Jan 1 at 21:28
lebatsnoklebatsnok
4,42621118
answered Jan 1 at 21:28
lebatsnoklebatsnok
4,42621118
answered Jan 1 at 21:28
lebatsnoklebatsnok
4,42621118
4,42621118
This solution almost seems to work, but for me for some reason Age will be incremented by 1 and Gender will be represented by numbers 1 and 2.
– user2021713
Jan 2 at 10:55
1
Well, I can't think of any other reason than Age and Gender being factors in your data frame. You can bypass this usingas.numeric(as.character(df$Age))andas.character(df$Gender)
– lebatsnok
Jan 2 at 11:26
Yes that was the reason. Thanks!
– user2021713
Jan 2 at 13:06
add a comment |
This solution almost seems to work, but for me for some reason Age will be incremented by 1 and Gender will be represented by numbers 1 and 2.
– user2021713
Jan 2 at 10:55
1
Well, I can't think of any other reason than Age and Gender being factors in your data frame. You can bypass this usingas.numeric(as.character(df$Age))andas.character(df$Gender)
– lebatsnok
Jan 2 at 11:26
Yes that was the reason. Thanks!
– user2021713
Jan 2 at 13:06
This solution almost seems to work, but for me for some reason Age will be incremented by 1 and Gender will be represented by numbers 1 and 2.
– user2021713
Jan 2 at 10:55
This solution almost seems to work, but for me for some reason Age will be incremented by 1 and Gender will be represented by numbers 1 and 2.
– user2021713
Jan 2 at 10:55
1
1
Well, I can't think of any other reason than Age and Gender being factors in your data frame. You can bypass this using
as.numeric(as.character(df$Age)) and as.character(df$Gender)– lebatsnok
Jan 2 at 11:26
Well, I can't think of any other reason than Age and Gender being factors in your data frame. You can bypass this using
as.numeric(as.character(df$Age)) and as.character(df$Gender)– lebatsnok
Jan 2 at 11:26
Yes that was the reason. Thanks!
– user2021713
Jan 2 at 13:06
Yes that was the reason. Thanks!
– user2021713
Jan 2 at 13:06
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What's the logic behind Dominance?
– NelsonGon
Jan 1 at 21:08
"Dominance" means hand dominance. Each person has a dominant hand and if hands are separated then each hand will be dominant (TRUE) or nondominant (FALSE).
– user2021713
Jan 1 at 21:17
3
and for old times sake:
r = reshape(dat, direction="long", varying=c("Present_R", "Present_L"), sep="_", timevar="hand"), then set Dominant to how you wantr$Dominant <- r$Dominant == r$hand– user20650
Jan 1 at 22:19