for loop on multiple data frames with different lengths










0















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.)










share|improve this question


























    0















    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.)










    share|improve this question
























      0












      0








      0








      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.)










      share|improve this question














      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






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      asked Nov 12 '18 at 23:58









      JenJen

      144




      144






















          2 Answers
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          0














          Using lapply:



          iris.list <- lapply(iris.list, function(x) cbind(x, Sepal = rowMeans(x[, c("Sepal.Length", "Sepal.Width")], na.rm = T)))





          share|improve this answer






























            0














            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






            share|improve this answer






















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              2 Answers
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              2 Answers
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              0














              Using lapply:



              iris.list <- lapply(iris.list, function(x) cbind(x, Sepal = rowMeans(x[, c("Sepal.Length", "Sepal.Width")], na.rm = T)))





              share|improve this answer



























                0














                Using lapply:



                iris.list <- lapply(iris.list, function(x) cbind(x, Sepal = rowMeans(x[, c("Sepal.Length", "Sepal.Width")], na.rm = T)))





                share|improve this answer

























                  0












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                  0







                  Using lapply:



                  iris.list <- lapply(iris.list, function(x) cbind(x, Sepal = rowMeans(x[, c("Sepal.Length", "Sepal.Width")], na.rm = T)))





                  share|improve this answer













                  Using lapply:



                  iris.list <- lapply(iris.list, function(x) cbind(x, Sepal = rowMeans(x[, c("Sepal.Length", "Sepal.Width")], na.rm = T)))






                  share|improve this answer












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                  answered Nov 13 '18 at 0:18









                  DiceboyTDiceboyT

                  84511




                  84511























                      0














                      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






                      share|improve this answer



























                        0














                        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






                        share|improve this answer

























                          0












                          0








                          0







                          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






                          share|improve this answer













                          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







                          share|improve this answer












                          share|improve this answer



                          share|improve this answer










                          answered Nov 13 '18 at 0:02









                          QwfqwfQwfqwf

                          30818




                          30818



























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