Making a new dataframe based on certain conditions












-2














I have a dataframe object in R, sample of which is as follows:



4   5   3
4 5 9
4 5 2
4 6 4
4 10 4
4 10 3
4 10 7
4 10 2
4 9 3
4 9 7
4 10 4
4 10 3
4 6 8
4 5 4
12 3 6
12 4 1
12 4 2
12 4 7


From this dataframe, I want to create a new dataframe of 20 columns, as follows:




  1. Only one row in the new dataframe,for each unique value in $1. Hence for this sample data, the new dataframe should have 2 rows(unique 4,12).


  2. $2 represents the column number of the new dataframe, in which the value of $3(of this dataframe) is to be filled. If there are repeating cases, the median of the values of $3 is to be taken. For example, for
    $1 value 4, 5 is repeated 4 times, and in the new dataframe, column 5 of the first row should have the value median(3,9,2,4) =3.


  3. All other column values are zero.



A sample output for this data would be as follows:



0 0 0 0 3 4 0 0 3 4 0 0 0 0 0 0 0 0 0 0
0 0 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0


How can we do this in R? A huge thanks in advance!










share|improve this question


















  • 1




    how can the median of (3,9,2,4) be 3 and how can the median of c(4,8) be 4??
    – Onyambu
    Nov 21 '18 at 17:23
















-2














I have a dataframe object in R, sample of which is as follows:



4   5   3
4 5 9
4 5 2
4 6 4
4 10 4
4 10 3
4 10 7
4 10 2
4 9 3
4 9 7
4 10 4
4 10 3
4 6 8
4 5 4
12 3 6
12 4 1
12 4 2
12 4 7


From this dataframe, I want to create a new dataframe of 20 columns, as follows:




  1. Only one row in the new dataframe,for each unique value in $1. Hence for this sample data, the new dataframe should have 2 rows(unique 4,12).


  2. $2 represents the column number of the new dataframe, in which the value of $3(of this dataframe) is to be filled. If there are repeating cases, the median of the values of $3 is to be taken. For example, for
    $1 value 4, 5 is repeated 4 times, and in the new dataframe, column 5 of the first row should have the value median(3,9,2,4) =3.


  3. All other column values are zero.



A sample output for this data would be as follows:



0 0 0 0 3 4 0 0 3 4 0 0 0 0 0 0 0 0 0 0
0 0 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0


How can we do this in R? A huge thanks in advance!










share|improve this question


















  • 1




    how can the median of (3,9,2,4) be 3 and how can the median of c(4,8) be 4??
    – Onyambu
    Nov 21 '18 at 17:23














-2












-2








-2







I have a dataframe object in R, sample of which is as follows:



4   5   3
4 5 9
4 5 2
4 6 4
4 10 4
4 10 3
4 10 7
4 10 2
4 9 3
4 9 7
4 10 4
4 10 3
4 6 8
4 5 4
12 3 6
12 4 1
12 4 2
12 4 7


From this dataframe, I want to create a new dataframe of 20 columns, as follows:




  1. Only one row in the new dataframe,for each unique value in $1. Hence for this sample data, the new dataframe should have 2 rows(unique 4,12).


  2. $2 represents the column number of the new dataframe, in which the value of $3(of this dataframe) is to be filled. If there are repeating cases, the median of the values of $3 is to be taken. For example, for
    $1 value 4, 5 is repeated 4 times, and in the new dataframe, column 5 of the first row should have the value median(3,9,2,4) =3.


  3. All other column values are zero.



A sample output for this data would be as follows:



0 0 0 0 3 4 0 0 3 4 0 0 0 0 0 0 0 0 0 0
0 0 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0


How can we do this in R? A huge thanks in advance!










share|improve this question













I have a dataframe object in R, sample of which is as follows:



4   5   3
4 5 9
4 5 2
4 6 4
4 10 4
4 10 3
4 10 7
4 10 2
4 9 3
4 9 7
4 10 4
4 10 3
4 6 8
4 5 4
12 3 6
12 4 1
12 4 2
12 4 7


From this dataframe, I want to create a new dataframe of 20 columns, as follows:




  1. Only one row in the new dataframe,for each unique value in $1. Hence for this sample data, the new dataframe should have 2 rows(unique 4,12).


  2. $2 represents the column number of the new dataframe, in which the value of $3(of this dataframe) is to be filled. If there are repeating cases, the median of the values of $3 is to be taken. For example, for
    $1 value 4, 5 is repeated 4 times, and in the new dataframe, column 5 of the first row should have the value median(3,9,2,4) =3.


  3. All other column values are zero.



A sample output for this data would be as follows:



0 0 0 0 3 4 0 0 3 4 0 0 0 0 0 0 0 0 0 0
0 0 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0


How can we do this in R? A huge thanks in advance!







r dataframe






share|improve this question













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share|improve this question




share|improve this question










asked Nov 21 '18 at 16:52









rishirishi

317




317








  • 1




    how can the median of (3,9,2,4) be 3 and how can the median of c(4,8) be 4??
    – Onyambu
    Nov 21 '18 at 17:23














  • 1




    how can the median of (3,9,2,4) be 3 and how can the median of c(4,8) be 4??
    – Onyambu
    Nov 21 '18 at 17:23








1




1




how can the median of (3,9,2,4) be 3 and how can the median of c(4,8) be 4??
– Onyambu
Nov 21 '18 at 17:23




how can the median of (3,9,2,4) be 3 and how can the median of c(4,8) be 4??
– Onyambu
Nov 21 '18 at 17:23












2 Answers
2






active

oldest

votes


















0














Are you sure that your expected outcome is correct? I think there is an error in calculating the median in your question, as also pointed out in the comments. You could do it as follows:



library(dplyr)

df$V1 <- as.numeric(as.factor(df$V1))
values <- df %>% group_by(V1,V2) %>% summarise(median=median(V3))
new_df <- matrix(0,nrow=length(unique(df$V1)), ncol=20)

for(i in 1:nrow(new_df)){
for(j in 1:ncol(new_df)){
value <- values$median[values$V1==i & values$V2==j]
if(length(value)>0){
new_df[i,j] = value
}
}
}

new_df

[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 3.5 6 0 0 5 3.5 0 0 0 0 0 0 0 0 0 0
[2,] 0 0 6 2 0.0 0 0 0 0 0.0 0 0 0 0 0 0 0 0 0 0


The outcome is slightly different though.






share|improve this answer





























    0














    df = transform(df,V1=factor(V1))
    fill = matrix(0,length(levels(df$V1)),20)
    df2=aggregate(V3~.,df,function(x)floor(median(x)))
    fill[cbind(as.integer(df2$V1),df2$V2)]=df2$V3
    fill
    [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14]
    [1,] 0 0 0 0 3 6 0 0 5 3 0 0 0 0
    [2,] 0 0 6 2 0 0 0 0 0 0 0 0 0 0
    [,15] [,16] [,17] [,18] [,19] [,20]
    [1,] 0 0 0 0 0 0
    [2,] 0 0 0 0 0 0





    share|improve this answer





















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      2 Answers
      2






      active

      oldest

      votes








      2 Answers
      2






      active

      oldest

      votes









      active

      oldest

      votes






      active

      oldest

      votes









      0














      Are you sure that your expected outcome is correct? I think there is an error in calculating the median in your question, as also pointed out in the comments. You could do it as follows:



      library(dplyr)

      df$V1 <- as.numeric(as.factor(df$V1))
      values <- df %>% group_by(V1,V2) %>% summarise(median=median(V3))
      new_df <- matrix(0,nrow=length(unique(df$V1)), ncol=20)

      for(i in 1:nrow(new_df)){
      for(j in 1:ncol(new_df)){
      value <- values$median[values$V1==i & values$V2==j]
      if(length(value)>0){
      new_df[i,j] = value
      }
      }
      }

      new_df

      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20]
      [1,] 0 0 0 0 3.5 6 0 0 5 3.5 0 0 0 0 0 0 0 0 0 0
      [2,] 0 0 6 2 0.0 0 0 0 0 0.0 0 0 0 0 0 0 0 0 0 0


      The outcome is slightly different though.






      share|improve this answer


























        0














        Are you sure that your expected outcome is correct? I think there is an error in calculating the median in your question, as also pointed out in the comments. You could do it as follows:



        library(dplyr)

        df$V1 <- as.numeric(as.factor(df$V1))
        values <- df %>% group_by(V1,V2) %>% summarise(median=median(V3))
        new_df <- matrix(0,nrow=length(unique(df$V1)), ncol=20)

        for(i in 1:nrow(new_df)){
        for(j in 1:ncol(new_df)){
        value <- values$median[values$V1==i & values$V2==j]
        if(length(value)>0){
        new_df[i,j] = value
        }
        }
        }

        new_df

        [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20]
        [1,] 0 0 0 0 3.5 6 0 0 5 3.5 0 0 0 0 0 0 0 0 0 0
        [2,] 0 0 6 2 0.0 0 0 0 0 0.0 0 0 0 0 0 0 0 0 0 0


        The outcome is slightly different though.






        share|improve this answer
























          0












          0








          0






          Are you sure that your expected outcome is correct? I think there is an error in calculating the median in your question, as also pointed out in the comments. You could do it as follows:



          library(dplyr)

          df$V1 <- as.numeric(as.factor(df$V1))
          values <- df %>% group_by(V1,V2) %>% summarise(median=median(V3))
          new_df <- matrix(0,nrow=length(unique(df$V1)), ncol=20)

          for(i in 1:nrow(new_df)){
          for(j in 1:ncol(new_df)){
          value <- values$median[values$V1==i & values$V2==j]
          if(length(value)>0){
          new_df[i,j] = value
          }
          }
          }

          new_df

          [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20]
          [1,] 0 0 0 0 3.5 6 0 0 5 3.5 0 0 0 0 0 0 0 0 0 0
          [2,] 0 0 6 2 0.0 0 0 0 0 0.0 0 0 0 0 0 0 0 0 0 0


          The outcome is slightly different though.






          share|improve this answer












          Are you sure that your expected outcome is correct? I think there is an error in calculating the median in your question, as also pointed out in the comments. You could do it as follows:



          library(dplyr)

          df$V1 <- as.numeric(as.factor(df$V1))
          values <- df %>% group_by(V1,V2) %>% summarise(median=median(V3))
          new_df <- matrix(0,nrow=length(unique(df$V1)), ncol=20)

          for(i in 1:nrow(new_df)){
          for(j in 1:ncol(new_df)){
          value <- values$median[values$V1==i & values$V2==j]
          if(length(value)>0){
          new_df[i,j] = value
          }
          }
          }

          new_df

          [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20]
          [1,] 0 0 0 0 3.5 6 0 0 5 3.5 0 0 0 0 0 0 0 0 0 0
          [2,] 0 0 6 2 0.0 0 0 0 0 0.0 0 0 0 0 0 0 0 0 0 0


          The outcome is slightly different though.







          share|improve this answer












          share|improve this answer



          share|improve this answer










          answered Nov 21 '18 at 17:46









          otwtmotwtm

          35810




          35810

























              0














              df = transform(df,V1=factor(V1))
              fill = matrix(0,length(levels(df$V1)),20)
              df2=aggregate(V3~.,df,function(x)floor(median(x)))
              fill[cbind(as.integer(df2$V1),df2$V2)]=df2$V3
              fill
              [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14]
              [1,] 0 0 0 0 3 6 0 0 5 3 0 0 0 0
              [2,] 0 0 6 2 0 0 0 0 0 0 0 0 0 0
              [,15] [,16] [,17] [,18] [,19] [,20]
              [1,] 0 0 0 0 0 0
              [2,] 0 0 0 0 0 0





              share|improve this answer


























                0














                df = transform(df,V1=factor(V1))
                fill = matrix(0,length(levels(df$V1)),20)
                df2=aggregate(V3~.,df,function(x)floor(median(x)))
                fill[cbind(as.integer(df2$V1),df2$V2)]=df2$V3
                fill
                [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14]
                [1,] 0 0 0 0 3 6 0 0 5 3 0 0 0 0
                [2,] 0 0 6 2 0 0 0 0 0 0 0 0 0 0
                [,15] [,16] [,17] [,18] [,19] [,20]
                [1,] 0 0 0 0 0 0
                [2,] 0 0 0 0 0 0





                share|improve this answer
























                  0












                  0








                  0






                  df = transform(df,V1=factor(V1))
                  fill = matrix(0,length(levels(df$V1)),20)
                  df2=aggregate(V3~.,df,function(x)floor(median(x)))
                  fill[cbind(as.integer(df2$V1),df2$V2)]=df2$V3
                  fill
                  [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14]
                  [1,] 0 0 0 0 3 6 0 0 5 3 0 0 0 0
                  [2,] 0 0 6 2 0 0 0 0 0 0 0 0 0 0
                  [,15] [,16] [,17] [,18] [,19] [,20]
                  [1,] 0 0 0 0 0 0
                  [2,] 0 0 0 0 0 0





                  share|improve this answer












                  df = transform(df,V1=factor(V1))
                  fill = matrix(0,length(levels(df$V1)),20)
                  df2=aggregate(V3~.,df,function(x)floor(median(x)))
                  fill[cbind(as.integer(df2$V1),df2$V2)]=df2$V3
                  fill
                  [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14]
                  [1,] 0 0 0 0 3 6 0 0 5 3 0 0 0 0
                  [2,] 0 0 6 2 0 0 0 0 0 0 0 0 0 0
                  [,15] [,16] [,17] [,18] [,19] [,20]
                  [1,] 0 0 0 0 0 0
                  [2,] 0 0 0 0 0 0






                  share|improve this answer












                  share|improve this answer



                  share|improve this answer










                  answered Nov 21 '18 at 17:57









                  OnyambuOnyambu

                  15.4k1519




                  15.4k1519






























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