#+TITLE: Manipulation of data-frame data with dutility functions
#+AUTHOR: Klaus Holst & Thomas Scheike
#+PROPERTY: header-args:R  :session *R* :cache no :width 550 :height 450
#+PROPERTY: header-args  :eval never-export :exports both :results output :tangle yes :comments yes 
#+PROPERTY: header-args:R+ :colnames yes :rownames no :hlines yes
#+INCLUDE: header.org
#+OPTIONS: toc:nil timestamp:nil

#+BEGIN_SRC emacs-lisp :results silent :exports results :eval
(setq org-latex-listings t)
(setq org-latex-compiler-file-string 
"%%\\VignetteIndexEntry{Manipulation of data-frame data with dutility functions}\n%%\\VignetteEngine{R.rsp::tex}\n%%\\VignetteKeyword{R}\n%%\\VignetteKeyword{package}\n%%\\VignetteKeyword{vignette}\n%%\\VignetteKeyword{LaTeX}\n")
#+END_SRC

----- 
# +LaTeX: \clearpage


* Simple data manipulation for data-frames 

   -  Renaming variables, Deleting variables
   -  Looking at the data
   -  Making new variales for the analysis
   -  Making factors (groupings)
   -  Working with factors
   -  Making a factor from existing numeric variable and vice versa


Here are some key data-manipulation steps on a data-frame which is how we typically 
organize our data in R. 
After having read the data into R it will typically be a data-frame, if not we 
can force it to be a data-frame.   The basic idea of the utility functions is 
to get a simple and easy to type way of making simple data-manipulation on a 
data-frame much like what is possible in SAS or STATA.  

The functions, say,  dcut, dfactor and so on are all functions that basically does what 
the base R cut, factor do, but are easier to use in the context of data-frames 
and have additional functionality. 

#+BEGIN_SRC R :results no :exports code :session *R* :cache no 
library(mets)
data(melanoma)
#+END_SRC

#+RESULTS:
#+begin_example
Loading required package: timereg
Loading required package: survival
Loading required package: lava
mets version 1.2.8

Attaching package: ‘mets’

The following object is masked _by_ ‘.GlobalEnv’:

    object.defined
#+end_example


#+BEGIN_SRC R :results output  :exports both :session *R* :cache no 
is.data.frame(melanoma)
#+END_SRC

#+RESULTS:
: [1] TRUE

Here we work on the melanoma data that is already read into R and is 
a data-frame.


* dUtility functions 

The structure for all functions 
is  

-  dfunction(dataframe,y~x|ifcond,...)

to use the function on y in a dataframe grouped by x if 
condition ifcond is valid. The basic functions are 

Data processing
    - dsort
    - dreshape
    - dcut
    - drm, drename, ddrop, dkeep, dsubset
    - drelevel
    - dlag
    - dfactor, dnumeric
Data aggregation
    - dby, dby2
    - dscalar, deval, daggregate
    - dmean, dsd, dsum, dquantile, dcor
    - dtable, dcount
Data summaries
    - dhead, dtail, 
    - dsummary, 
    - dprint, dlist, dlevels, dunique


A generic function daggregate, daggr,  can be called with a function as the 
argument 


-  daggregate(dataframe,y~x|ifcond,fun=function,...)

without the grouping variable (x)

-  daggregate(dataframe,~y|ifcond,fun=function,...)

A useful feature is that y and x as well as the subset condition
can be specified using regular-expressions or by wildcards (default).
Here to illustrate this, we compute the means of certain variables. 

First just oveall 
#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dmean(melanoma,~thick+I(log(thick)))
#+END_SRC

#+RESULTS:
:         thick I(log(thick)) 
:    291.985366      5.223341

now only when days>500
#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dmean(melanoma,~thick+I(log(thick))|I(days>500))
#+END_SRC

#+RESULTS:
:         thick I(log(thick)) 
:    271.582011      5.168691

and now after sex but only when days>500
#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dmean(melanoma,thick+I(log(thick))~sex|I(days>500))
#+END_SRC

#+RESULTS:
:   sex    thick I(log(thick))
: 1   0 242.9580      5.060086
: 2   1 320.2429      5.353321

and finally after quartiles of days (via the dcut function)
#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dmean(melanoma,thick+I(log(thick))~I(dcut(days)))
#+END_SRC

#+RESULTS:
:         I(dcut(days))    thick I(log(thick))
: 1       [10,1.52e+03] 482.1731      5.799525
: 2    (1.52e+03,2e+03] 208.5490      4.987652
: 3    (2e+03,3.04e+03] 223.2941      4.974759
: 4 (3.04e+03,5.56e+03] 250.1961      5.120129

or summary of all variables starting with "s" and that contains "a"

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dmean(melanoma,"s*"+"*a*"~sex|I(days>500))
#+END_SRC

#+RESULTS:
:   sex   status     days
: 1   0 1.831933 2399.143
: 2   1 1.714286 2169.800


* Renaming, deleting, keeping, dropping  variables

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
melanoma=drename(melanoma,tykkelse~thick)
names(melanoma)
#+END_SRC

#+RESULTS:
: [1] "no"       "status"   "days"     "ulc"      "tykkelse" "sex"


Deleting variables

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
data(melanoma)
melanoma=drm(melanoma,~thick+sex)
names(melanoma)
#+END_SRC

#+RESULTS:
: [1] "no"     "status" "days"   "ulc"

or sas style

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
data(melanoma)
melanoma=ddrop(melanoma,~thick+sex)
names(melanoma)
#+END_SRC

#+RESULTS:
: [1] "no"     "status" "days"   "ulc"

alternatively we can also keep certain variables

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
data(melanoma)
melanoma=dkeep(melanoma,~thick+sex+status+days)
names(melanoma)
#+END_SRC

#+RESULTS:
: [1] "thick"  "sex"    "status" "days"


This can also be done with direct asignment 

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
data(melanoma)
ddrop(melanoma) <- ~thick+sex
names(melanoma)
#+END_SRC

#+RESULTS:
: [1] "no"     "status" "days"   "ulc"


* Looking at the data 

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
data(melanoma)
dstr(melanoma)
#+END_SRC

#+RESULTS:
#+begin_example
'data.frame':	205 obs. of  6 variables:
 $ no    : int  789 13 97 16 21 469 685 7 932 944 ...
 $ status: int  3 3 2 3 1 1 1 1 3 1 ...
 $ days  : int  10 30 35 99 185 204 210 232 232 279 ...
 $ ulc   : int  1 0 0 0 1 1 1 1 1 1 ...
 $ thick : int  676 65 134 290 1208 484 516 1288 322 741 ...
 $ sex   : int  1 1 1 0 1 1 1 1 0 0 ...
Warning message:
In structure(res, ngroupvar = 0, class = c("daggregate", class(res))) :
  Calling 'structure(NULL, *)' is deprecated, as NULL cannot have attributes.
  Consider 'structure(list(), *)' instead.
#+end_example

The data can in Rstudio be seen as a data-table but to list certain parts of 
the data in output window 

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dlist(melanoma)
#+END_SRC

#+RESULTS:
#+begin_example
    no  status days ulc thick sex
1   789 3       10  1    676  1  
2    13 3       30  0     65  1  
3    97 2       35  0    134  1  
4    16 3       99  0    290  0  
5    21 1      185  1   1208  1  
---                              
201 317 2      4492 1   706   1  
202 798 2      4668 0   612   0  
203 806 2      4688 0    48   0  
204 606 2      4926 0   226   0  
205 328 2      5565 0   290   0
#+end_example

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dlist(melanoma, ~.|sex==1)
#+END_SRC

#+RESULTS:
#+begin_example
    no  status days ulc thick
1   789 3       10  1    676 
2    13 3       30  0     65 
3    97 2       35  0    134 
5    21 1      185  1   1208 
6   469 1      204  1    484 
---                          
191 445 2      3909 1   806  
195 415 2      4119 0    65  
197 175 2      4207 0    65  
198 493 2      4310 0   210  
201 317 2      4492 1   706
#+end_example

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dlist(melanoma, ~ulc+days+thick+sex|sex==1)
#+END_SRC

#+RESULTS:
#+begin_example
    ulc days thick sex
1   1    10   676  1  
2   0    30    65  1  
3   0    35   134  1  
5   1   185  1208  1  
6   1   204   484  1  
---                   
191 1   3909 806   1  
195 0   4119  65   1  
197 0   4207  65   1  
198 0   4310 210   1  
201 1   4492 706   1
#+end_example


Getting summaries

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dsummary(melanoma)
#+END_SRC

#+RESULTS:
#+begin_example
       no            status          days           ulc            thick     
 Min.   :  2.0   Min.   :1.00   Min.   :  10   Min.   :0.000   Min.   :  10  
 1st Qu.:222.0   1st Qu.:1.00   1st Qu.:1525   1st Qu.:0.000   1st Qu.:  97  
 Median :469.0   Median :2.00   Median :2005   Median :0.000   Median : 194  
 Mean   :463.9   Mean   :1.79   Mean   :2153   Mean   :0.439   Mean   : 292  
 3rd Qu.:731.0   3rd Qu.:2.00   3rd Qu.:3042   3rd Qu.:1.000   3rd Qu.: 356  
 Max.   :992.0   Max.   :3.00   Max.   :5565   Max.   :1.000   Max.   :1742  
      sex        
 Min.   :0.0000  
 1st Qu.:0.0000  
 Median :0.0000  
 Mean   :0.3854  
 3rd Qu.:1.0000  
 Max.   :1.0000
#+end_example

or for specfic variables

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dsummary(melanoma,~thick+status+sex)
#+END_SRC

#+RESULTS:
:      thick          status          sex        
:  Min.   :  10   Min.   :1.00   Min.   :0.0000  
:  1st Qu.:  97   1st Qu.:1.00   1st Qu.:0.0000  
:  Median : 194   Median :2.00   Median :0.0000  
:  Mean   : 292   Mean   :1.79   Mean   :0.3854  
:  3rd Qu.: 356   3rd Qu.:2.00   3rd Qu.:1.0000  
:  Max.   :1742   Max.   :3.00   Max.   :1.0000

Summaries in different groups (sex)

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dsummary(melanoma,thick+days+status~sex)
#+END_SRC

#+RESULTS:
#+begin_example
sex: 0
     thick             days          status     
 Min.   :  10.0   Min.   :  99   Min.   :1.000  
 1st Qu.:  97.0   1st Qu.:1636   1st Qu.:2.000  
 Median : 162.0   Median :2059   Median :2.000  
 Mean   : 248.6   Mean   :2283   Mean   :1.833  
 3rd Qu.: 306.0   3rd Qu.:3131   3rd Qu.:2.000  
 Max.   :1742.0   Max.   :5565   Max.   :3.000  
------------------------------------------------------------ 
sex: 1
     thick             days          status     
 Min.   :  16.0   Min.   :  10   Min.   :1.000  
 1st Qu.: 105.0   1st Qu.:1052   1st Qu.:1.000  
 Median : 258.0   Median :1860   Median :2.000  
 Mean   : 361.1   Mean   :1946   Mean   :1.722  
 3rd Qu.: 484.0   3rd Qu.:2784   3rd Qu.:2.000  
 Max.   :1466.0   Max.   :4492   Max.   :3.000
#+end_example

and only among those with thin-tumours or only females (sex==1)

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dsummary(melanoma,thick+days+status~sex|thick<97)
#+END_SRC

#+RESULTS:
#+begin_example
sex: 0
     thick            days          status     
 Min.   :10.00   Min.   : 355   Min.   :1.000  
 1st Qu.:32.00   1st Qu.:1762   1st Qu.:2.000  
 Median :64.00   Median :2227   Median :2.000  
 Mean   :51.48   Mean   :2425   Mean   :2.034  
 3rd Qu.:65.00   3rd Qu.:3185   3rd Qu.:2.000  
 Max.   :81.00   Max.   :4688   Max.   :3.000  
------------------------------------------------------------ 
sex: 1
     thick            days          status     
 Min.   :16.00   Min.   :  30   Min.   :1.000  
 1st Qu.:30.00   1st Qu.:1820   1st Qu.:2.000  
 Median :65.00   Median :2886   Median :2.000  
 Mean   :55.75   Mean   :2632   Mean   :1.875  
 3rd Qu.:81.00   3rd Qu.:3328   3rd Qu.:2.000  
 Max.   :81.00   Max.   :4207   Max.   :3.000
#+end_example

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dsummary(melanoma,thick+status~+1|sex==1)
#+END_SRC

#+RESULTS:
:      thick            status     
:  Min.   :  16.0   Min.   :1.000  
:  1st Qu.: 105.0   1st Qu.:1.000  
:  Median : 258.0   Median :2.000  
:  Mean   : 361.1   Mean   :1.722  
:  3rd Qu.: 484.0   3rd Qu.:2.000  
:  Max.   :1466.0   Max.   :3.000


or 

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dsummary(melanoma,~thick+status|sex==1)
#+END_SRC

#+RESULTS:
:      thick            status     
:  Min.   :  16.0   Min.   :1.000  
:  1st Qu.: 105.0   1st Qu.:1.000  
:  Median : 258.0   Median :2.000  
:  Mean   : 361.1   Mean   :1.722  
:  3rd Qu.: 484.0   3rd Qu.:2.000  
:  Max.   :1466.0   Max.   :3.000


To make more complex conditions need to use the I() 

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dsummary(melanoma,thick+days+status~sex|I(thick<97 & sex==1))
#+END_SRC

#+RESULTS:
: sex: 1
:      thick            days          status     
:  Min.   :16.00   Min.   :  30   Min.   :1.000  
:  1st Qu.:30.00   1st Qu.:1820   1st Qu.:2.000  
:  Median :65.00   Median :2886   Median :2.000  
:  Mean   :55.75   Mean   :2632   Mean   :1.875  
:  3rd Qu.:81.00   3rd Qu.:3328   3rd Qu.:2.000  
:  Max.   :81.00   Max.   :4207   Max.   :3.000



Tables between variables

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dtable(melanoma,~status+sex)
#+END_SRC

#+RESULTS:
: 
:        sex  0  1
: status          
: 1          28 29
: 2          91 43
: 3           7  7

All bivariate tables

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dtable(melanoma,~status+sex+ulc,level=2)
#+END_SRC

#+RESULTS:
#+begin_example

   status
sex  1  2  3
  0 28 91  7
  1 29 43  7

   status
ulc  1  2  3
  0 16 92  7
  1 41 42  7

   sex
ulc  0  1
  0 79 36
  1 47 43
#+end_example

All univariate tables

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dtable(melanoma,~status+sex+ulc,level=1)
#+END_SRC

#+RESULTS:
#+begin_example

status
  1   2   3 
 57 134  14 

sex
  0   1 
126  79 

ulc
  0   1 
115  90
#+end_example

and with new variables 

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dtable(melanoma,~status+sex+ulc+dcut(days)+I(days>300),level=1)
#+END_SRC

#+RESULTS:
#+begin_example

status
  1   2   3 
 57 134  14 

sex
  0   1 
126  79 

ulc
  0   1 
115  90 

dcut(days)
      [10,1.52e+03]    (1.52e+03,2e+03]    (2e+03,3.04e+03] (3.04e+03,5.56e+03] 
                 52                  51                  51                  51 

I(days > 300)
FALSE  TRUE 
   11   194
#+end_example

* Sorting the data

To sort the data 

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
data(melanoma)
mel= dsort(melanoma,~days)
dsort(melanoma) <- ~days
head(mel)
#+END_SRC

#+RESULTS:
:    no status days ulc thick sex
: 1 789      3   10   1   676   1
: 2  13      3   30   0    65   1
: 3  97      2   35   0   134   1
: 4  16      3   99   0   290   0
: 5  21      1  185   1  1208   1
: 6 469      1  204   1   484   1

and to sort after multiple variables increasing and decreasing 

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dsort(melanoma) <- ~days-status
head(melanoma)
#+END_SRC

#+RESULTS:
:    no status days ulc thick sex
: 1 789      3   10   1   676   1
: 2  13      3   30   0    65   1
: 3  97      2   35   0   134   1
: 4  16      3   99   0   290   0
: 5  21      1  185   1  1208   1
: 6 469      1  204   1   484   1



* Making new variales for the analysis

To define a bunch of new covariates within a data-frame

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
data(melanoma)
melanoma= transform(melanoma, thick2=thick^2, lthick=log(thick) ) 
dhead(melanoma)
#+END_SRC

#+RESULTS:
:    no status days ulc thick sex  thick2   lthick
: 1 789      3   10   1   676   1  456976 6.516193
: 2  13      3   30   0    65   1    4225 4.174387
: 3  97      2   35   0   134   1   17956 4.897840
: 4  16      3   99   0   290   0   84100 5.669881
: 5  21      1  185   1  1208   1 1459264 7.096721
: 6 469      1  204   1   484   1  234256 6.182085


When the above definitions are done using a condition this can be achieved 
using the dtransform function that extends transform with a possible condition  

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
 melanoma=dtransform(melanoma,ll=thick*1.05^ulc,sex==1)  
 melanoma=dtransform(melanoma,ll=thick,sex!=1)  
 dmean(melanoma,ll~sex+ulc)
#+END_SRC

#+RESULTS:
:   sex ulc       ll
: 1   0   0 173.7342
: 2   1   0 197.3611
: 3   0   1 374.5532
: 4   1   1 523.1198



* Making factors (groupings)

On the melanoma data the variable thick gives the thickness of the melanom tumour. For some analyses we would like to make a factor depending on the thickness. This can be done in several different ways

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
melanoma=dcut(melanoma,~thick,breaks=c(0,200,500,800,2000))
#+END_SRC

#+RESULTS:

New variable is named thickcat.0 by default.

To see levels of factors in data-frame
#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dlevels(melanoma)
#+END_SRC

#+RESULTS:
: thickcat.0 #levels=:4 
: [1] "[0,200]"     "(200,500]"   "(500,800]"   "(800,2e+03]"
: -----------------------------------------

Checking group sizes 
#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dtable(melanoma,~thickcat.0)
#+END_SRC

#+RESULTS:
: 
: thickcat.0
:     [0,200]   (200,500]   (500,800] (800,2e+03] 
:         109          64          20          12

With adding to the data-frame directly 
#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dcut(melanoma,breaks=c(0,200,500,800,2000)) <- gr.thick1~thick
dlevels(melanoma)
#+END_SRC

#+RESULTS:
: thickcat.0 #levels=:4 
: [1] "[0,200]"     "(200,500]"   "(500,800]"   "(800,2e+03]"
: -----------------------------------------
: gr.thick1 #levels=:4 
: [1] "[0,200]"     "(200,500]"   "(500,800]"   "(800,2e+03]"
: -----------------------------------------

new variable is named thickcat.0 (after first cut-point), 
or to get quartiles with default names thick.cat.4 

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dcut(melanoma) <- ~ thick  # new variable is thickcat.4
dlevels(melanoma)
#+END_SRC

#+RESULTS:
: thickcat.0 #levels=:4 
: [1] "[0,200]"     "(200,500]"   "(500,800]"   "(800,2e+03]"
: -----------------------------------------
: gr.thick1 #levels=:4 
: [1] "[0,200]"     "(200,500]"   "(500,800]"   "(800,2e+03]"
: -----------------------------------------
: thickcat.4 #levels=:4 
: [1] "[10,97]"        "(97,194]"       "(194,356]"      "(356,1.74e+03]"
: -----------------------------------------

or median groups, here starting again with the original data, 

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
data(melanoma)
dcut(melanoma,breaks=2) <- ~ thick  # new variable is thick.2
dlevels(melanoma)
#+END_SRC

#+RESULTS:
: thickcat.2 #levels=:2 
: [1] "[10,194]"       "(194,1.74e+03]"
: -----------------------------------------



to control new names

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
data(melanoma)
mela= dcut(melanoma,thickcat4+dayscat4~thick+days,breaks=4)
dlevels(mela)
#+END_SRC

#+RESULTS:
: thickcat4 #levels=:4 
: [1] "[10,97]"        "(97,194]"       "(194,356]"      "(356,1.74e+03]"
: -----------------------------------------
: dayscat4 #levels=:4 
: [1] "[10,1.52e+03]"       "(1.52e+03,2e+03]"    "(2e+03,3.04e+03]"   
: [4] "(3.04e+03,5.56e+03]"
: -----------------------------------------

or

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
data(melanoma)
dcut(melanoma,breaks=4) <- thickcat4+dayscat4~thick+days
dlevels(melanoma)
#+END_SRC

#+RESULTS:
: thickcat4 #levels=:4 
: [1] "[10,97]"        "(97,194]"       "(194,356]"      "(356,1.74e+03]"
: -----------------------------------------
: dayscat4 #levels=:4 
: [1] "[10,1.52e+03]"       "(1.52e+03,2e+03]"    "(2e+03,3.04e+03]"   
: [4] "(3.04e+03,5.56e+03]"
: -----------------------------------------

This can also be typed out more specifically

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
melanoma$gthick = cut(melanoma$thick,breaks=c(0,200,500,800,2000))
melanoma$gthick = cut(melanoma$thick,breaks=quantile(melanoma$thick),include.lowest=TRUE)
#+END_SRC

#+RESULTS:


* Working with factors

To see levels of covariates in data-frame

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
data(melanoma)
dcut(melanoma,breaks=4) <- thickcat4~thick
dlevels(melanoma) 
#+END_SRC

#+RESULTS:
: thickcat4 #levels=:4 
: [1] "[10,97]"        "(97,194]"       "(194,356]"      "(356,1.74e+03]"
: -----------------------------------------

To relevel the factor

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dtable(melanoma,~thickcat4)
melanoma = drelevel(melanoma,~thickcat4,ref="(194,356]")
dlevels(melanoma)
#+END_SRC

#+RESULTS:
#+begin_example

thickcat4
       [10,97]       (97,194]      (194,356] (356,1.74e+03] 
            56             53             45             51
thickcat4 #levels=:4 
[1] "[10,97]"        "(97,194]"       "(194,356]"      "(356,1.74e+03]"
-----------------------------------------
thickcat4.(194,356] #levels=:4 
[1] "(194,356]"      "[10,97]"        "(97,194]"       "(356,1.74e+03]"
-----------------------------------------
#+end_example

or to take the third level in the list of levels, same as above, 

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
melanoma = drelevel(melanoma,~thickcat4,ref=2)
dlevels(melanoma)
#+END_SRC

#+RESULTS:
: thickcat4 #levels=:4 
: [1] "[10,97]"        "(97,194]"       "(194,356]"      "(356,1.74e+03]"
: -----------------------------------------
: thickcat4.(194,356] #levels=:4 
: [1] "(194,356]"      "[10,97]"        "(97,194]"       "(356,1.74e+03]"
: -----------------------------------------
: thickcat4.2 #levels=:4 
: [1] "(97,194]"       "[10,97]"        "(194,356]"      "(356,1.74e+03]"
: -----------------------------------------


To combine levels of a factor (first combinining first 3 groups into one)

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
melanoma = drelevel(melanoma,~thickcat4,newlevels=1:3)
dlevels(melanoma)
#+END_SRC

#+RESULTS:
#+begin_example
thickcat4 #levels=:4 
[1] "[10,97]"        "(97,194]"       "(194,356]"      "(356,1.74e+03]"
-----------------------------------------
thickcat4.(194,356] #levels=:4 
[1] "(194,356]"      "[10,97]"        "(97,194]"       "(356,1.74e+03]"
-----------------------------------------
thickcat4.2 #levels=:4 
[1] "(97,194]"       "[10,97]"        "(194,356]"      "(356,1.74e+03]"
-----------------------------------------
thickcat4.1:3 #levels=:2 
[1] "[10,97]-(194,356]" "(356,1.74e+03]"   
-----------------------------------------
#+end_example

or to combine groups 1 and 2 into one group and 3 and 4 into another

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dkeep(melanoma) <- ~thick+thickcat4
melanoma = drelevel(melanoma,gthick2~thickcat4,newlevels=list(1:2,3:4))
dlevels(melanoma)
#+END_SRC

#+RESULTS:
: thickcat4 #levels=:4 
: [1] "[10,97]"        "(97,194]"       "(194,356]"      "(356,1.74e+03]"
: -----------------------------------------
: gthick2 #levels=:2 
: [1] "[10,97]-(97,194]"         "(194,356]-(356,1.74e+03]"
: -----------------------------------------


Changing order of factor levels 

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
dfactor(melanoma,levels=c(3,1,2,4)) <-  thickcat4.2~thickcat4
dlevel(melanoma,~ "thickcat4*")
dtable(melanoma,~thickcat4+thickcat4.2)
#+END_SRC

#+RESULTS:
#+begin_example
thickcat4 #levels=:4 
[1] "[10,97]"        "(97,194]"       "(194,356]"      "(356,1.74e+03]"
-----------------------------------------
thickcat4.2 #levels=:4 
[1] "(194,356]"      "[10,97]"        "(97,194]"       "(356,1.74e+03]"
-----------------------------------------

               thickcat4.2 (194,356] [10,97] (97,194] (356,1.74e+03]
thickcat4                                                           
[10,97]                            0      56        0              0
(97,194]                           0       0       53              0
(194,356]                         45       0        0              0
(356,1.74e+03]                     0       0        0             51
#+end_example

Combine levels but now control factor-level names 
#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
melanoma=drelevel(melanoma,gthick3~thickcat4,newlevels=list(group1.2=1:2,group3.4=3:4))
dlevels(melanoma)
#+END_SRC

#+RESULTS:
#+begin_example
thickcat4 #levels=:4 
[1] "[10,97]"        "(97,194]"       "(194,356]"      "(356,1.74e+03]"
-----------------------------------------
gthick2 #levels=:2 
[1] "[10,97]-(97,194]"         "(194,356]-(356,1.74e+03]"
-----------------------------------------
thickcat4.2 #levels=:4 
[1] "(194,356]"      "[10,97]"        "(97,194]"       "(356,1.74e+03]"
-----------------------------------------
gthick3 #levels=:2 
[1] "group1.2" "group3.4"
-----------------------------------------
#+end_example


* Making a factor from existing numeric variable and vice versa

A numeric variable "status" with values 1,2,3 into a factor by

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
data(melanoma)
melanoma = dfactor(melanoma,~status, labels=c("malignant-melanoma","censoring","dead-other"))
melanoma = dfactor(melanoma,sexl~sex,labels=c("females","males"))
dtable(melanoma,~sexl+status.f)
#+END_SRC

#+RESULTS:
: 
:         status.f malignant-melanoma censoring dead-other
: sexl                                                    
: females                          28        91          7
: males                            29        43          7

A gender factor with values "M", "F" can be converted into numerics by

#+BEGIN_SRC R :results output :exports both :session *R* :cache no 
melanoma = dnumeric(melanoma,~sexl)
dstr(melanoma,"sex*")
dtable(melanoma,~'sex*',level=2)
#+END_SRC

#+RESULTS:
#+begin_example
'data.frame':	205 obs. of  3 variables:
 $ sex   : int  1 1 1 0 1 1 1 1 0 0 ...
 $ sexl  : Factor w/ 2 levels "females","males": 2 2 2 1 2 2 2 2 1 1 ...
 $ sexl.n: num  2 2 2 1 2 2 2 2 1 1 ...
Warning message:
In structure(res, ngroupvar = 0, class = c("daggregate", class(res))) :
  Calling 'structure(NULL, *)' is deprecated, as NULL cannot have attributes.
  Consider 'structure(list(), *)' instead.

         sex
sexl        0   1
  females 126   0
  males     0  79

      sex
sexl.n   0   1
     1 126   0
     2   0  79

      sexl
sexl.n females males
     1     126     0
     2       0    79
#+end_example


