StackOverflow2013

Note that there are some explanatory texts on larger screens.

plurals

POMelt in reshape2
primarykey
Id
16639087
data
AcceptedAnswerId
0
AnswerCount
0
ClosedDate
CommentCount
6
CommunityOwnedDate
CreationDate
2013-05-19T20:19:22.820
FavoriteCount
0
LastActivityDate
2013-05-19T21:02:39.483
LastEditDate
2013-05-19T21:02:39.483
LastEditorUserId
338745
OwnerUserId
338745
ParentId
0
PostTypeId
1
Score
0
ViewCount
633
LastEditorDisplayName
text
Body
I have a dataframe for plotting the results of an ordinal regression model. I´d like to melt my dataframe, but the results are not correct. When I create a toy dataframe from the original dataframe with fewer columns I get the correct answers. Any idea what I´m doing wrong here? Please see attached code and output. <pre><code>> fivenum(diff.mod[,11]) [1] -2.250835e-06 -2.558362e-07 -3.719817e-08 1.670986e-07 2.644583e-06 > fivenum(diff.mod[,12]) [1] -0.237450499 -0.021690233 0.001226833 0.019041952 0.277317128 </code></pre> This should be reproduced in the molten dataframe (diff.mod.graf) <pre><code>> diff.mod.graf<-melt(diff.mod,measure.vars=c(11,12)) > by(data=diff.mod.graf,INDICES=diff.mod.graf$variable, function(x) fivenum(x$value)) diff.mod.graf$variable: onp [1] 0.0002978989 0.0675580767 0.1793394876 0.6058061575 0.9984103955 ---------------------------------------------------------------- diff.mod.graf$variable: op [1] 0.0002978989 0.0675580767 0.1793394876 0.6058061575 0.9984103955 </code></pre> For some reason the same values occur for both variables (onp and on).. But when I do the same with fewer variables in the dataframe I get: <pre><code> > df<-diff.mod[,c(1,2,7,11,12)] > df2<-melt(df,measure.vars=c(4,5)) #Identical to variables 11 and 12 above > by(data=df2,INDICES=df2$variable,function(x) fivenum(x$value)) df2$variable: onp [1] -2.250835e-06 -2.558362e-07 -3.719817e-08 1.670986e-07 2.644583e-06 ---------------------------------------------------------------------- df2$variable: op [1] -0.237450499 -0.021690233 0.001226833 0.019041952 0.277317128 </code></pre> Any idea what is wrong with the code in the second codebit?? EDIT. @Dwin request. Also tried using formal column names instead of numbers without any luck. <pre><code>> str(diff.mod) 'data.frame': 73200 obs. of 12 variables: $ ao : num 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 ... $ as : Factor w/ 5 levels "Bo 1","Bo 2",..: 1 1 1 1 1 1 1 1 1 1 ... $ age : num 0 0 0 0 0 0 0 0 0 0 ... $ sex : Factor w/ 2 levels "Female","Male": 1 1 1 1 1 1 1 1 1 1 ... $ Sx : Factor w/ 2 levels "No","Yes": 1 1 1 1 1 1 1 1 1 1 ... $ Hy : Factor w/ 2 levels "No","Yes": 1 1 1 1 1 1 1 1 1 1 ... $ Yu : Factor w/ 3 levels "fit.[ 13, 29)",..: 1 1 1 1 1 1 1 1 1 1 ... $ value : num 0.0461 0.0477 0.0492 0.0509 0.0526 ... $ non.prop : num 0.0461 0.0477 0.0492 0.0509 0.0526 ... $ prop : num 0.0466 0.0479 0.0493 0.0506 0.0521 ... $ onp : num 7.84e-08 7.37e-08 6.87e-08 6.32e-08 5.73e-08 ... $ op : num -4.86e-04 -2.60e-04 -2.09e-05 2.32e-04 5.00e-04 ... </code></pre> Edit- @Baptiste <pre><code>> diff.mod.graf<-melt(diff.mod,id.vars=c(1:10),measure.vars=c("onp","op")) > by(data=diff.mod.graf,INDICES=diff.mod.graf$variable,function(x) fivenum(x$value)) diff.mod.graf$variable: onp [1] 0.0002978989 0.0675580767 0.1793394876 0.6058061575 0.9984103955 ------------------------------------------------------------------------------------------------------------------------------------------------------------ diff.mod.graf$variable: op [1] 0.0002978989 0.0675580767 0.1793394876 0.6058061575 0.9984103955 </code></pre> EDIT- @ Baptiste <pre><code>> diff.mod.graf<-melt(diff.mod,id.vars=c(1:10),measure.vars=c("onp","op")) > by(data=diff.mod.graf,INDICES=diff.mod.graf$variable,function(x) fivenum(x$value)) diff.mod.graf$variable: onp [1] -2.250835e-06 -2.558362e-07 -3.719817e-08 1.670986e-07 2.644583e-06 ------------------------------------------------------------------------------------------------------------------------------------------------------------ diff.mod.graf$variable: op [1] -0.237450499 -0.021690233 0.001226833 0.019041952 0.277317128 </code></pre> Edit- SOLUTION @Baptiste <pre><code> >names(diff.mod)[8]<-"J" > diff.mod.graf<-melt(diff.mod,id.vars=c(1:10),measure.vars=c("onp","op")) > by(data=diff.mod.graf,INDICES=diff.mod.graf$variable,function(x) fivenum(x$value)) diff.mod.graf$variable: onp [1] -2.250835e-06 -2.558362e-07 -3.719817e-08 1.670986e-07 2.644583e-06 ------------------------------------------------------------------------------------ diff.mod.graf$variable: op [1] -0.237450499 -0.021690233 0.001226833 0.019041952 0.277317128 </code></pre>
Tags
<r><reshape2>
Title
Melt in reshape2
singulars
PostAcceptedAnswerId
1. This table or related slice is empty.
PostParentId
1. This table or related slice is empty.
PostTypePostTypeId
1. PTQuestion
UserLastEditorUserId
1. USMisha
UserOwnerUserId
1. USMisha
plurals
PostLinksPostIdRelatedPostId
1. This table or related slice is empty.
PostLinksRelatedPostIdPostId
1. This table or related slice is empty.
PostsAcceptedAnswerId
1. This table or related slice is empty.
PostsParentIdCreationDate
1. This table or related slice is empty.
VotesPostIdCreationDate
1. This table or related slice is empty.
CommentsPostId

Querying!

Guidance

A row detail

Detail views are divided into sections. All the information in the data section comes from columns in the selected row. The other sections display data from other, related rows.

Related data can be related in a to-one or a to-many fashion. Captions of data related in a to-many fashion link to a list view showing a filtered view of the table.

Try moving around until you find a non-empty to-many entry and click on the label to get to one. You can move back to the root by clicking on the database name in the header.