for loop on multiple data frames with different lengths
I'm trying to add a new column to multiple data frames with different lengths.
For example, I have three data frames as below:
iris1 <- iris[iris$Species=="setosa" & iris$Petal.Width == 0.2,]
iris2 <- iris[iris$Species=="versicolor",]
iris3 <- iris[iris$Species=="virginica",]
I could add a column to an individual dataframe by using the following line:
iris1$Sepal <- rowMeans(iris1[, c("Sepal.Length", "Sepal.Width")], na.rm = T)
So I tried to write a for loop to repeat this for multiple dataframe like below, but it just created a new dataframe i, and I'm having trouble figuring out writing the right loop.
iris.list <- list(iris1, iris2, iris3)
for (i in iris.list)
i$Sepal <- rowMeans(i[, c("Sepal.Length", "Sepal.Width")], na.rm = T)
(I was searching on StackOverflow and noted that people also advised to use apply if possible instead of a for loop but couldn't get apply to work with my dataframes that have different lengths.)
r for-loop
asked Nov 12 '18 at 23:58
JenJen
144
add a comment |
I'm trying to add a new column to multiple data frames with different lengths.
For example, I have three data frames as below:
iris1 <- iris[iris$Species=="setosa" & iris$Petal.Width == 0.2,]
iris2 <- iris[iris$Species=="versicolor",]
iris3 <- iris[iris$Species=="virginica",]
I could add a column to an individual dataframe by using the following line:
iris1$Sepal <- rowMeans(iris1[, c("Sepal.Length", "Sepal.Width")], na.rm = T)
So I tried to write a for loop to repeat this for multiple dataframe like below, but it just created a new dataframe i, and I'm having trouble figuring out writing the right loop.
iris.list <- list(iris1, iris2, iris3)
for (i in iris.list)
i$Sepal <- rowMeans(i[, c("Sepal.Length", "Sepal.Width")], na.rm = T)
(I was searching on StackOverflow and noted that people also advised to use apply if possible instead of a for loop but couldn't get apply to work with my dataframes that have different lengths.)
r for-loop
asked Nov 12 '18 at 23:58
JenJen
144
add a comment |
I'm trying to add a new column to multiple data frames with different lengths.
For example, I have three data frames as below:
iris1 <- iris[iris$Species=="setosa" & iris$Petal.Width == 0.2,]
iris2 <- iris[iris$Species=="versicolor",]
iris3 <- iris[iris$Species=="virginica",]
I could add a column to an individual dataframe by using the following line:
iris1$Sepal <- rowMeans(iris1[, c("Sepal.Length", "Sepal.Width")], na.rm = T)
So I tried to write a for loop to repeat this for multiple dataframe like below, but it just created a new dataframe i, and I'm having trouble figuring out writing the right loop.
iris.list <- list(iris1, iris2, iris3)
for (i in iris.list)
i$Sepal <- rowMeans(i[, c("Sepal.Length", "Sepal.Width")], na.rm = T)
(I was searching on StackOverflow and noted that people also advised to use apply if possible instead of a for loop but couldn't get apply to work with my dataframes that have different lengths.)
r for-loop
asked Nov 12 '18 at 23:58
JenJen
144
I'm trying to add a new column to multiple data frames with different lengths.
For example, I have three data frames as below:
iris1 <- iris[iris$Species=="setosa" & iris$Petal.Width == 0.2,]
iris2 <- iris[iris$Species=="versicolor",]
iris3 <- iris[iris$Species=="virginica",]
I could add a column to an individual dataframe by using the following line:
iris1$Sepal <- rowMeans(iris1[, c("Sepal.Length", "Sepal.Width")], na.rm = T)
So I tried to write a for loop to repeat this for multiple dataframe like below, but it just created a new dataframe i, and I'm having trouble figuring out writing the right loop.
iris.list <- list(iris1, iris2, iris3)
for (i in iris.list)
i$Sepal <- rowMeans(i[, c("Sepal.Length", "Sepal.Width")], na.rm = T)
(I was searching on StackOverflow and noted that people also advised to use apply if possible instead of a for loop but couldn't get apply to work with my dataframes that have different lengths.)
r for-loop
r for-loop
asked Nov 12 '18 at 23:58
JenJen
144
asked Nov 12 '18 at 23:58
JenJen
144
asked Nov 12 '18 at 23:58
JenJen
144
asked Nov 12 '18 at 23:58
JenJen
144
asked Nov 12 '18 at 23:58
JenJen
144
144
add a comment |
add a comment |
2 Answers
2
active
oldest
votes
Using lapply:
iris.list <- lapply(iris.list, function(x) cbind(x, Sepal = rowMeans(x[, c("Sepal.Length", "Sepal.Width")], na.rm = T)))
answered Nov 13 '18 at 0:18
DiceboyTDiceboyT
84511
add a comment |
This may not be the best way, but I like to use this method to make it easier to read when I come back to my code:
for (i in 1:length(iris.list))
currIris <- iris.list[[i]]
currIris$Sepal <- rowMeans(currIris[, c("Sepal.Length", "Sepal.Width")], na.rm = T)
iris.list[[i]] <- currIris
answered Nov 13 '18 at 0:02
QwfqwfQwfqwf
30818
add a comment |
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2 Answers
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active
oldest
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2 Answers
2
active
oldest
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active
oldest
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active
oldest
votes
Using lapply:
iris.list <- lapply(iris.list, function(x) cbind(x, Sepal = rowMeans(x[, c("Sepal.Length", "Sepal.Width")], na.rm = T)))
answered Nov 13 '18 at 0:18
DiceboyTDiceboyT
84511
add a comment |
Using lapply:
iris.list <- lapply(iris.list, function(x) cbind(x, Sepal = rowMeans(x[, c("Sepal.Length", "Sepal.Width")], na.rm = T)))
answered Nov 13 '18 at 0:18
DiceboyTDiceboyT
84511
add a comment |
Using lapply:
iris.list <- lapply(iris.list, function(x) cbind(x, Sepal = rowMeans(x[, c("Sepal.Length", "Sepal.Width")], na.rm = T)))
answered Nov 13 '18 at 0:18
DiceboyTDiceboyT
84511
Using lapply:
iris.list <- lapply(iris.list, function(x) cbind(x, Sepal = rowMeans(x[, c("Sepal.Length", "Sepal.Width")], na.rm = T)))
answered Nov 13 '18 at 0:18
DiceboyTDiceboyT
84511
answered Nov 13 '18 at 0:18
DiceboyTDiceboyT
84511
answered Nov 13 '18 at 0:18
DiceboyTDiceboyT
84511
answered Nov 13 '18 at 0:18
DiceboyTDiceboyT
84511
84511
add a comment |
add a comment |
This may not be the best way, but I like to use this method to make it easier to read when I come back to my code:
for (i in 1:length(iris.list))
currIris <- iris.list[[i]]
currIris$Sepal <- rowMeans(currIris[, c("Sepal.Length", "Sepal.Width")], na.rm = T)
iris.list[[i]] <- currIris
answered Nov 13 '18 at 0:02
QwfqwfQwfqwf
30818
add a comment |
This may not be the best way, but I like to use this method to make it easier to read when I come back to my code:
for (i in 1:length(iris.list))
currIris <- iris.list[[i]]
currIris$Sepal <- rowMeans(currIris[, c("Sepal.Length", "Sepal.Width")], na.rm = T)
iris.list[[i]] <- currIris
answered Nov 13 '18 at 0:02
QwfqwfQwfqwf
30818
add a comment |
This may not be the best way, but I like to use this method to make it easier to read when I come back to my code:
for (i in 1:length(iris.list))
currIris <- iris.list[[i]]
currIris$Sepal <- rowMeans(currIris[, c("Sepal.Length", "Sepal.Width")], na.rm = T)
iris.list[[i]] <- currIris
answered Nov 13 '18 at 0:02
QwfqwfQwfqwf
30818
This may not be the best way, but I like to use this method to make it easier to read when I come back to my code:
for (i in 1:length(iris.list))
currIris <- iris.list[[i]]
currIris$Sepal <- rowMeans(currIris[, c("Sepal.Length", "Sepal.Width")], na.rm = T)
iris.list[[i]] <- currIris
answered Nov 13 '18 at 0:02
QwfqwfQwfqwf
30818
answered Nov 13 '18 at 0:02
QwfqwfQwfqwf
30818
answered Nov 13 '18 at 0:02
QwfqwfQwfqwf
30818
answered Nov 13 '18 at 0:02
QwfqwfQwfqwf
30818
30818
add a comment |
add a comment |
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