StackOverflow2013

Note that there are some explanatory texts on larger screens.

plurals

PO
primarykey
Id
14604025
data
AcceptedAnswerId
0
AnswerCount
0
ClosedDate
CommentCount
2
CommunityOwnedDate
CreationDate
2013-01-30T12:28:17.487
FavoriteCount
0
LastActivityDate
2013-01-30T15:24:02.417
LastEditDate
2013-01-30T15:24:02.417
LastEditorUserId
1270695
OwnerUserId
1270695
ParentId
14603457
PostTypeId
2
Score
5
ViewCount
0
LastEditorDisplayName
text
Body
Please try to post your data in an easy to copy-and-paste format, like I've done below: <pre><code>mydata <- structure(list(col1 = c(84L, 94L, 188L, 245L, 114L, 71L, 118L, 162L, 123L, 115L, 125L, 119L, 106L, 146L), col2 = c(88.242, 107.571, 240.288, 371.005, 131.599, 100.751, 138.543, 203.435, 152.032, 126.945, 134.178, 138.926, 129.19, 162.319), col3 = c(9.833, 10.917, 16.917, 22.333, 9.167, 8.167, 11.167, 14.667, 12.167, 11.667, 10, 9.5, 9.833, 9.833), col4 = c(4.194, 3.708, 6.333, 10.389, 4.25, 3, 4.278, 6.444, 4.639, 5.056, 4.639, 4.222, 3.833, 4.118), cr = structure(c(1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 1L), .Label = c("A", "B"), class = "factor")), .Names = c("col1", "col2", "col3", "col4", "cr"), class = "data.frame", row.names = c(NA, -14L)) </code></pre> Now. to address your question. You need to first <code>aggregate</code> the data, then convert it to a <code>matrix</code>, then calculate each value in the matrix as a proportion to the total in that column (using <code>prop.table</code>): <pre><code>mydataAgg <- aggregate(cbind(col1, col2, col3, col4) ~ cr, mydata, sum) mydata2 <- as.matrix(mydata1[-1]) rownames(mydata2) <- mydataAgg[[1]] mydata2 # col1 col2 col3 col4 # A 1235 1527.057 110.250 46.673 # B 575 697.967 55.918 22.430 prop.table(mydata2, 2) # col1 col2 col3 col4 # A 0.6823204 0.6863103 0.6634851 0.6754121 # B 0.3176796 0.3136897 0.3365149 0.3245879 </code></pre> Plotting is then easy: <pre><code>barplot(prop.table(mydata2, 2)) </code></pre> Or, with colors: <pre><code>barplot(prop.table(mydata2, 2), col = c("slateblue", "palevioletred")) </code></pre> <img src="https://i.stack.imgur.com/goMMM.png" alt="enter image description here"> Hmmm. Not the most interesting plot, but I guess definitely a clear pattern in proportions.... <hr> <h2><code>lattice</code></h2> @Arun showed the <code>ggplot2</code> solution in the name of completeness, but if that's the case, then we should at least add <code>barchart</code> from "lattice". ;) For this, we need to transpose the output of <code>prop.table(mydata2, 2)</code> that we calculated earlier: <pre><code>barchart(t(prop.table(mydata2, 2)), stack = TRUE, horizontal = FALSE) </code></pre> Here's the result: <img src="https://i.stack.imgur.com/KPsZn.png" alt="enter image description here">
Tags
Title
singulars
PostAcceptedAnswerId
1. This table or related slice is empty.
PostParentId
1. POstacked barplots of the same height
 singulars
 PostTypePostTypeId
 PTQuestion
PostTypePostTypeId
1. PTAnswer
UserLastEditorUserId
1. USA5C1D2H2I1M1N2O1R2T1
UserOwnerUserId
1. USA5C1D2H2I1M1N2O1R2T1
plurals
PostLinksPostIdRelatedPostId
1. This table or related slice is empty.
PostLinksRelatedPostIdPostId
1. This table or related slice is empty.
PostsAcceptedAnswerId
1. POstacked barplots of the same height
 singulars
 PostTypePostTypeId
 PTQuestion
PostsParentIdCreationDate
1. This table or related slice is empty.
VotesPostIdCreationDate
1. VO
 singulars
 PostPostId
 PO
 UserUserId
 This table or related slice is empty.
 VoteTypeVoteTypeId
 VTUpMod
2. VO
 singulars
 PostPostId
 PO
 UserUserId
 This table or related slice is empty.
 VoteTypeVoteTypeId
 VTUpMod
3. VO
 singulars
 PostPostId
 PO
 UserUserId
 This table or related slice is empty.
 VoteTypeVoteTypeId
 VTUpMod
CommentsPostId
1. CO(+1) especially for the reaction after looking at the plot. `Hmmm.. not the most interesting plot..` :)
 singulars
 PostPostId
 PO
 UserUserId
 USArun
2. COI wish I could (+1). I've got to learn `lattice`!
 singulars
 PostPostId
 PO
 UserUserId
 USArun

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.