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Re: st: Conditional infile statements

From   Steven Samuels <>
Subject   Re: st: Conditional infile statements
Date   Mon, 21 Nov 2011 10:39:20 -0500

Correction: I needed to -use- the first data set for the -merge- to work.  


There's no need to create the record-type data sets or append them, since the -forvalues- code goes through the entire data set each time. Here's the result, with multiple records per ID in the example. 


**************CODE BEGINS*************
/* my.txt is

1 100 John Smith
2 100 40
2 100 50
1 101 Bob Jones
2 101 45

local rt1  "rtype 1  id 3-5 str10 name  7-16"
local rt2  "rtype 1  id 3-5       age   7-8"

forvalues i = 1/2{
quietly infix `rt`i'' using my.txt if rtype== `i', clear
sort id
quietly save t`i', replace emptyok

use t1, clear
merge 1:m id using t2
drop _merge rtype
sort id age
**************CODE ENDS**************

On Nov 20, 2011, at 7:40 AM, Gordon Hughes wrote:

I would like to read a *very* large dataset using conditional infile statements.  With some oversimplification the structure of the data is as follows:

Line 1: type1 id 1 2 3 4 5
Line 2: type1 id 3 4 5 6 7
Line 3: type2 id ABC DEF FGH
Line 4: type1 id 5 6 7 8 9
Line 5: type3 id IJK 3 4 XYZ

The format of the data on each line is fixed but the formatting varies according the value of the first variable on the line.  For practical purposes the data may be treated as having one line per observation but with different variables recorded for the different line types.  There is no consistent pattern of the occurrence of lines of different types.

In high level programming languages, SAS and some other languages it is possible to read such data using the following generic code:

read str ltype @
if ltype=="type1" {read id str type var1-var5}
if ltype=="type2" {read id str type str char1 str char2 str char3}
if ltype=="type3" {read id str char4 var6 var7 str char5}

where the @ character holds the current line for re-reading.  As far as I can work out this is not possible, at least directly, in Stata.

In fact the problem is even worse than this description implies because many of the variables have the form "123*" where 123 is a value and "*" may or may not be present and indicates a flag or note.

There is a way of doing this but to my mind it is clumsy:

infix str sline 1-30 using ...
gen ltype=substr(sline, 1, 5)
gen var1=real(substr(sline, 6, 2)) if ltype=="type1"

The user-written routine -strparse- can also be deployed for free format data, but again it involves the use of sub-string manipulation.  I cannot locate any other user-written routine which provides a better way of doing this, but my -net search- terms may not pick up the right keywords.

I would appreciate any suggestions as to a better way of doing this - or should I just resign myself to writing the code required to parse each line.  (Incidentally, one reason for my reluctance to do this is that it increases the maximum memory size required to hold the initial pass through the data.)

Gordon Hughes

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