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Last data update: 2014.03.03

R: Converts a dataset from database-format to a cross table

Reshaping to a crosstable

R Documentation

Converts a dataset from database-format to a cross table

Description

Reshapes data arranged in 3 columns to a “crosstable” matrix.

Usage

db2cross (input, row = 1, col = 2, value = 3, subset = NULL,
  df.row = NA, df.col = NA, out.row = NA, out.col = NA, 
  full.out = FALSE)

Arguments

`input`	A `matrix` in database format, (x,y,z) .
`row`	Number or name of the column in `input`, to be used as rows in the result.
`col`	Number or name of the column in `input`, to be used as columns in the result.
`value`	Number or name of the column in `input`, to be used as values in the result.
`subset`	Logical expression indicating elements or rows to keep; missing values are taken as `FALSE`
`df.row, df.col`	Maximal distance in row and column values that should be considered the same. The default is to use each unique row or column value in `input` as a row or column value in the crosstable. Overrruled when `out.row` or `out.col` are defined.
`out.row, out.col`	Values of rows and columns to be used in the cross table. The default is to use each unique row or column value in `input` as a row or column value in the crosstable. Each value in `input` is mapped to `out.row` and `out.col` to which it is closest. Overrrules `df.row` or `df.col`.
`full.out`	If `TRUE`, will also output how the input values were mapped to the output values. This is only relevant if either of `df.row`, `df.col`, `out.row` or `out.col` is not `NULL`.

Details

Uses a simple fortran function.

rows and columns are generated by the unique values in each x- and y-column.

Value

a list containing:

`x`	The values of the rows.
`y`	The values of the columns.
`z`	The crosstable, a matrix.

and if full.out = TRUE also

map

The mapping of the x and y values, consisting of var.input, factor, var.output, with the original values, how they are mapped, and the resulting values respectively.

Author(s)

Karline Soetaert <karline.soetaert@nioz.nl>

Examples

## =======================================================================
## test the function on a small data set
## =======================================================================

 df3 <- data.frame(school = rep(c("a","b","c"), each = 4), 
                   class = rep(9:10, 6),
                   time = rep(c(1,1,2,2), 3),  
                   score = rnorm(12))
 head(df3)
 db2cross(df3, val = 4)

## =======================================================================
## Defining the output rows
## =======================================================================
Samples <- data.frame(time = c(1, 1.1, 1.2, 2, 2.1, 2.2, 4, 4.1, 4.2),
                      var = rep(c("O2", "NO3", "NH3"), 3), 
                      val = 1:9)
Samples

db2cross(Samples)
db2cross(Samples, df.row = 0.5)
db2cross(Samples, out.row = c(1, 2, 4))
db2cross(Samples, out.row = 1:4)

## =======================================================================
## A larger dataset; requires OceanView.Data
## =======================================================================
## Not run: 
 data (pp.aug2009.db)
 crosstab <- db2cross(pp.aug2009.db)
 crosstab$z[crosstab$z>1000] <- 1000
 crosstab$z[crosstab$z<0]    <- NA

 image2D(z = crosstab$z, x = crosstab$x, y = crosstab$y,
       main = "primary production august 2009 mgC/m2/d", 
       NAcol = "black")
 
## End(Not run)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

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Type 'contributors()' for more information and
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Type 'demo()' for some demos, 'help()' for on-line help, or
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Type 'q()' to quit R.

> library(OceanView)
Loading required package: plot3D
Loading required package: plot3Drgl
Loading required package: rgl
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/OceanView/db2cross.Rd_%03d_medium.png", width=480, height=480)
> ### Name: Reshaping to a crosstable
> ### Title: Converts a dataset from database-format to a cross table
> ### Aliases: db2cross
> ### Keywords: utility
> 
> ### ** Examples
> 
> ## =======================================================================
> ## test the function on a small data set
> ## =======================================================================
> 
>  df3 <- data.frame(school = rep(c("a","b","c"), each = 4), 
+                    class = rep(9:10, 6),
+                    time = rep(c(1,1,2,2), 3),  
+                    score = rnorm(12))
>  head(df3)
  school class time      score
1      a     9    1 -0.5454374
2      a    10    1 -1.3987476
3      a     9    2  2.9634141
4      a    10    2  1.7738502
5      b     9    1 -1.7033760
6      b    10    1 -0.1322221
>  db2cross(df3, val = 4)
$x
[1] a b c
Levels: a b c

$y
[1]  9 10

$z
          9         10
a  1.208988  0.1875513
b -1.165530  0.6216704
c -0.611236 -0.6438269

> 
> ## =======================================================================
> ## Defining the output rows
> ## =======================================================================
> Samples <- data.frame(time = c(1, 1.1, 1.2, 2, 2.1, 2.2, 4, 4.1, 4.2),
+                       var = rep(c("O2", "NO3", "NH3"), 3), 
+                       val = 1:9)
> Samples
  time var val
1  1.0  O2   1
2  1.1 NO3   2
3  1.2 NH3   3
4  2.0  O2   4
5  2.1 NO3   5
6  2.2 NH3   6
7  4.0  O2   7
8  4.1 NO3   8
9  4.2 NH3   9
> 
> db2cross(Samples)
$x
[1] 1.0 1.1 1.2 2.0 2.1 2.2 4.0 4.1 4.2

$y
[1] NH3 NO3 O2 
Levels: NH3 NO3 O2

$z
    NH3 NO3 O2
1    NA  NA  1
1.1  NA   2 NA
1.2   3  NA NA
2    NA  NA  4
2.1  NA   5 NA
2.2   6  NA NA
4    NA  NA  7
4.1  NA   8 NA
4.2   9  NA NA

> db2cross(Samples, df.row = 0.5)
$x
[1] 1.1 2.1 4.1

$y
[1] NH3 NO3 O2 
Levels: NH3 NO3 O2

$z
    NH3 NO3 O2
1.1   3   2  1
2.1   6   5  4
4.1   9   8  7

> db2cross(Samples, out.row = c(1, 2, 4))
$x
[1] 1 2 4

$y
[1] NH3 NO3 O2 
Levels: NH3 NO3 O2

$z
  NH3 NO3 O2
1   3   2  1
2   6   5  4
4   9   8  7

> db2cross(Samples, out.row = 1:4)
$x
[1] 1 2 3 4

$y
[1] NH3 NO3 O2 
Levels: NH3 NO3 O2

$z
  NH3 NO3 O2
1   3   2  1
2   6   5  4
3  NA  NA NA
4   9   8  7

> 
> ## =======================================================================
> ## A larger dataset; requires OceanView.Data
> ## =======================================================================
> ## Not run: 
> ##D  data (pp.aug2009.db)
> ##D  crosstab <- db2cross(pp.aug2009.db)
> ##D  crosstab$z[crosstab$z>1000] <- 1000
> ##D  crosstab$z[crosstab$z<0]    <- NA
> ##D 
> ##D  image2D(z = crosstab$z, x = crosstab$x, y = crosstab$y,
> ##D        main = "primary production august 2009 mgC/m2/d", 
> ##D        NAcol = "black")
> ##D  
> ## End(Not run)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>