Reading space delimited text file into SAS - input

Question

I have a following .txt file:
Mark1[Country1]
type1=1 type2=5
type1=1.50 EUR type2=21.00 EUR
Mark2[Country2]
type1=2 type2=1 type3=1
type1=197.50 EUR type2=201.00 EUR type3= 312.50 EUR
....
I am trying to input it in my SAS program, so that it would look something like that:
Mark Country Type Count Price
1 Mark1 Country1 type1 1 1.50
2 Mark1 Country1 type2 5 21.00
3 Mark1 Country1 type3 NA NA
4 Mark2 Country2 type1 2 197.50
5 Mark2 Country2 type2 2 201.00
6 Mark2 Country2 type3 1 312.50
Or maybe something else, but i need it to be possible to print two way report
Country1 Country2
Type1 ... ...
Type2 ... ...
Type3 ... ...
But the question is how to read that kind of txt file:
read and separate Mark1[Country1] to two columns Mark and Country;
retain Mark and Country and read info for each Type (+somehow ignoring type1=, maybe using formats) and input it in a table.
Maybe there is a way to use some kind of input templates to achive that or nasted queries.

Answer 1

You have 3 name/value pairs, but the pairs are split between two rows. An unusual text file requiring creative input. The INPUT statement has a line control feature # to read relative future rows within the implicit DATA Step loop.
Example (Proc REPORT)
Read the mark and country from the current row (relative row #1), the counts from relative row #2 using #2 and the prices from relative row #3. After the name/value inputs are made for a given mark country perform an array based pivot, transposing two variables (count and price) at a time into a categorical (type) data form.
Proc REPORT produces a 'two-way' listing. The listing is actually a summary report (cells under count and price are a default SUM aggregate), but each cell has only one contributing value so the SUM is the original individual value.
data have(keep=Mark Country Type Count Price);
attrib mark country length=$10;
infile cards delimiter='[ ]' missover;
input mark country;
input #2 #'type1=' count_1 #'type2=' count_2 #'type3=' count_3;
input #3 #'type1=' price_1 #'type2=' price_2 #'type3=' price_3;
array counts count_:;
array prices price_:;
do _i_ = 1 to dim(counts);
Type = cats('type',_i_);
Count = counts(_i_);
Price = prices(_i_);
output;
end;
datalines;
Mark1[Country1]
type1=1 type2=5
type1=1.50 EUR type2=21.00 EUR
Mark2[Country2]
type1=2 type2=1 type3=1
type1=197.50 EUR type2=201.00 EUR type3= 312.50 EUR
;
ods html file='twoway.html';
proc report data=have;
column type country,(count price);
define type / group;
define country / ' ' across;
run;
ods html close;
Output image
Combined aggregation
proc means nway data=have noprint;
class type country;
var count price;
output out=stats max(price)=price_max sum(count)=count_sum;
run;
data cells;
set stats;
if not missing(price_max) then
cell = cats(price_max,'(',count_sum,')');
run;
proc transpose data=cells out=twoway(drop=_name_);
by type;
id country;
var cell;
run;
proc print noobs data=twoway;
run;

Answer 2

You can specify the name of variable with the DLM= option on the INFILE statement. That way you can change the delimiter depending on the type of line being read.
It looks like you have three lines per group. The first one have the MARK and COUNTRY values. The second one has a list of COUNT values and the third one has a list of PRICE values. So something like this should work.
data want ;
length dlm $2 ;
length Mark $8 Country $20 rectype $8 recno 8 type $10 value1 8 value2 $8 ;
infile cards dlm=dlm truncover ;
dlm='[]';
input mark country ;
dlm='= ';
do rectype='Count','Price';
do recno=1 by 1 until(type=' ');
input type value1 #;
if rectype='Price' then input value2 #;
if type ne ' ' then output;
end;
input;
end;
cards;
Mark1[Country1]
type1=1 type2=5
type1=1.50 EUR type2=21.00 EUR
Mark2[Country2]
type1=2 type2=1 type3=1
type1=197.50 EUR type2=201.00 EUR type3= 312.50 EUR
;
Results:
Obs Mark Country rectype recno type value1 value2
1 Mark1 Country1 Count 1 type1 1.0
2 Mark1 Country1 Count 2 type2 5.0
3 Mark1 Country1 Price 1 type1 1.5 EUR
4 Mark1 Country1 Price 2 type2 21.0 EUR
5 Mark2 Country2 Count 1 type1 2.0
6 Mark2 Country2 Count 2 type2 1.0
7 Mark2 Country2 Count 3 type3 1.0
8 Mark2 Country2 Price 1 type1 197.5 EUR
9 Mark2 Country2 Price 2 type2 201.0 EUR
10 Mark2 Country2 Price 3 type3 312.5 EUR