# gcontract

Efficiently make dataset of frequencies and percentages

gcontract replaces the dataset in memory with a new dataset consisting of all combinations of varlist that exist in the data and a new variable that contains the frequency of each combination. The user can optionally request percentages and cumulative counts and percentages.

Important

Run gtools, upgrade to update gtools to the latest stable version.

## Syntax

This is a fast option to Stata's contract.

gcontract varlist [if] [in] [weight] [, options ]

fweights are allowed; see help weights. Further, instead of a varlist, it is possible to specify

[+|-] varname [[+|-] varname ...]


This will not affect the results, but it will affect the sort order of the final data.

## Options

• freq(newvar) specifies a name for the frequency variable. If not specified, _freq is used.

• cfreq(newvar) specifies a name for the cumulative frequency variable. If not specified, no cumulative frequency variable is created.

• percent(newvar) specifies a name for the percentage variable. If not specified, no percent variable is created.

• cpercent(newvar) specifies a name for the cumulative percentage variable. If not specified, no cumulative percentage variable is created.

• float specifies that the percentage variables specified by percent() and cpercent() will be stored as variables of type float. This only affects the Stata storage type; gtools does all computations internally in double precision. If float is not specified, these variables will be generated as variables of type double. All generated variables are compressed to the smallest storage type possible without loss of precision; see [D] compress.

• format(format) specifies a display format for the generated percentage variables specified by percent() and cpercent(). If format() is not specified, these variables will have the display format %8.2f.

• zero specifies that combinations with frequency zero be included. This is VERY slow.

• nomiss specifies that observations with missing values on any variable in varlist be dropped. If nomiss is not specified, all observations possible are used.

### Extras

• fast specifies that gcollapse not restore the original dataset should the user press Break.

• unsorted Do not sort resulting data set. Saves speed.

### Gtools options

(Note: These are common to every gtools command.)

• compress Try to compress strL to str#. The Stata Plugin Interface has only limited support for strL variables. In Stata 13 and earlier (version 2.0) there is no support, and in Stata 14 and later (version 3.0) there is read-only support. The user can try to compress strL variables using this option.

• forcestrl Skip binary variable check and force gtools to read strL variables (14 and above only). Gtools gives incorrect results when there is binary data in strL variables. This option was included because on some windows systems Stata detects binary data even when there is none. Only use this option if you are sure you do not have binary data in your strL variables.

• verbose prints some useful debugging info to the console.

• benchmark or bench(level) prints how long in seconds various parts of the program take to execute. Level 1 is the same as benchmark. Levels 2 and 3 additionally prints benchmarks for internal plugin steps.

• hashmethod(str) Hash method to use. default automagically chooses the algorithm. biject tries to biject the inputs into the natural numbers. spooky hashes the data and then uses the hash.

• oncollision(str) How to handle collisions. A collision should never happen but just in case it does gtools will try to use native commands. The user can specify it throw an error instead by passing oncollision(error).

## Stored results

gcontract stores the following in r():

r(N)       number of non-missing observations
r(J)       number of groups
r(minJ)    largest group size
r(maxJ)    smallest group size


## Examples

The options here are essentially the same as Stata's contract, save for the standard gtools options.

sysuse auto, clear
gen long id = _n * 1000
expand id
gcontract rep78, verbose

Bijection OK with all integers (i.e. no extended miss val)? Yes.
Counting sort on hash; min = 1, max = 6
N = 2,775,000; 6 unbalanced groups of sizes 88,000 to 833,000

l

+----------------+
| rep78    _freq |
|----------------|
1. |     1    88000 |
2. |     2   211000 |
3. |     3   833000 |
4. |     4   824000 |
5. |     5   649000 |
|----------------|
6. |     .   170000 |
+----------------+


You can add frequencies, percentages, and so on:

sysuse auto, clear
gen long id = _n * 1000
expand id
gcontract rep78, freq(f) cfreq(cf) percent(p) cpercent(cp) bench

Added target variables; .161 seconds
Parsed by variables; .004 seconds
Plugin runtime; .28 seconds
Total runtime (internals); .285 seconds

l

+-------------------------------------------+
| rep78        f        cf       p       cp |
|-------------------------------------------|
1. |     1    88000     88000    3.17     3.17 |
2. |     2   211000    299000    7.60    10.77 |
3. |     3   833000   1132000   30.02    40.79 |
4. |     4   824000   1956000   29.69    70.49 |
5. |     5   649000   2605000   23.39    93.87 |
|-------------------------------------------|
6. |     .   170000   2775000    6.13   100.00 |
+-------------------------------------------+


Last, with multiple variables you can "fill in" missing groups. This option has not been implemented internally and as such is very slow:

sysuse auto, clear
gen long id = _n * 1000
expand id
gcontract foreign rep78, ///
freq(f) cfreq(cf) percent(p) cpercent(cp) bench(3) zero

Added target variables; .137 seconds
Parsed by variables; .002 seconds
Plugin step 1: Read in by variables; 0.116 seconds.
Plugin step 2.1: Determined hashing strategy; 0.036 seconds.
Plugin step 2.3: Bijected integers to natural numbers; 0.026 seconds.
Plugin step 2.4: Sorted integer-only hash; 0.057 seconds.
Plugin step 2: Hashed by variables; 0.120 seconds.
Plugin step 3: Set up panel; 0.013 seconds.
Plugin step 4.2: Keep only one row per group; 0.000 seconds.
Plugin step 4: Created indexed array with sorted by vars; 0.003 seconds.
Plugin step 5: Generated output array; 0.000 seconds.
Plugin step 6: Copied collapsed data to stata; 0.000 seconds.
Plugin runtime; .262 seconds
Total runtime (internals); .265 seconds

l

+------------------------------------------------------+
| rep78    foreign        f        cf       p       cp |
|------------------------------------------------------|
1. |     1   Domestic    88000     88000    3.17     3.17 |
2. |     2   Domestic   211000    299000    7.60    10.77 |
3. |     3   Domestic   654000    953000   23.57    34.34 |
4. |     4   Domestic   256000   1209000    9.23    43.57 |
5. |     5   Domestic    63000   1272000    2.27    45.84 |
|------------------------------------------------------|
6. |     .   Domestic   106000   1378000    3.82    49.66 |
7. |     1    Foreign        0   1378000    0.00    49.66 |
8. |     2    Foreign        0   1378000    0.00    49.66 |
9. |     3    Foreign   179000   1557000    6.45    56.11 |
10. |     4    Foreign   568000   2125000   20.47    76.58 |
|------------------------------------------------------|
11. |     5    Foreign   586000   2711000   21.12    97.69 |
12. |     .    Foreign    64000   2775000    2.31   100.00 |
+------------------------------------------------------+


You will note a few levels have 0 frequency, which means they did not appear in the full data.