SPSSX Discussion

ELIMINATIONG ZEROS

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Nardos Ghebremedhin

ELIMINATIONG ZEROS

HELLO!

WOULD ANY ONE PLEASE HELP ME WITH THE FOLLOWING PROBLEM?

I just want to take out all the zeros from the data given below (part of
an observation). As you can notice one item is collected from three
outlets (quotations), and it may happen that this item is priced only in
one or two or all the three quotations. Now what I want is, as it is
displayed below I want to extract all the non zero prices without
disturbing the data. Please notice that the structure of the data view
is as depicted below. I want to take out only the zero's, it could be
from only one quotation or two or three conditionally. For example for
the observations in blue color, item green pepper (price of the 9th
month,p9), I want to takeout the 3rd quotation and keep the other two in
order to compute average prices. Similarly, for the item couli flower
since all the quotations are zero, I want to takeout the whole item for
this specific month (p9).

All I want is how to do such things using syntax (SPSS 11).

Actually I have tried to do such things while the observations are
arranged raw wise. By just writing " select if p(?) ne 0" . what if they
are arranged as below? Is there any way to proceed?

All the best!

Itemno itemname quotation unit
p1 p2 p3 p4 p5 p6 p7
p8 p9 p10 p11 p12

03002 Cabbage 1 KG.
3.00 3.00 2.50 2.00 2.00 1.50 2.00
2.00 4.00 3.00 4.00 4.00

03002 Cabbage 2 KG.
2.00 2.50 2.00 3.00 2.00 3.00 3.00
2.00 3.50 4.00 4.00 4.00

03002 Cabbage 3 KG.
3.00 2.00 2.00 2.00 2.00 1.50 1.50
1.50 3.00 2.50 4.00 3.00

03003 Lettuce 1 KG.
4.50 4.00 5.00 3.00 4.00 6.00 7.00
8.00 8.00 8.00 7.00 5.00

03003 Lettuce 2 KG.
5.00 5.00 5.00 4.00 5.00 8.00 8.00
8.00 8.00 8.00 8.00 6.00

03003 Lettuce 3 KG.
5.00 4.00 5.00 5.00 4.00 6.00 6.50
7.00 7.00 7.00 8.00 5.00

03004 Carrot 1 KG.
5.00 6.00 6.00 4.00 4.00 5.00 5.00
5.00 10.00 6.00 7.00 6.00

03004 Carrot 2 KG.
5.00 5.00 5.00 4.00 5.00 5.00 6.00
6.00 10.00 8.00 7.00 6.00

03004 Carrot 3 KG.
6.00 5.00 5.00 5.00 4.00 4.50 4.50
5.00 10.00 6.00 6.00 5.00

03005 Potatos 1 KG.
5.00 5.00 7.00 5.00 6.00 7.00 7.50
7.00 7.00 5.00 4.00 8.00

03005 Potatos 2 KG.
5.00 5.00 7.00 6.00 7.00 7.00 7.50
8.00 7.00 5.00 6.00 6.00

03005 Potatos 3 KG.
5.00 5.00 7.00 5.00 6.00 7.00 7.00
8.50 7.00 3.50 5.00 6.00

03006 Tomatos 1 KG.
6.00 4.00 3.50 3.50 5.00 5.50 7.00
8.00 10.00 6.00 3.00 3.50

03006 Tomatos 2 KG.
6.00 4.00 3.50 3.50 6.50 7.00 7.00
9.00 10.00 5.50 3.00 3.00

03006 Tomatos 3 KG.
6.00 4.50 3.50 4.00 6.00 4.00 5.00
8.00 10.00 6.00 3.00 3.00

03007 Onions 1 KG.
7.50 6.00 4.00 3.50 4.00 4.50 5.00
4.00 6.00 6.00 7.00 6.00

03007 Onions 2 KG.
7.00 9.00 4.00 4.00 4.00 4.50 5.00
4.00 6.00 6.00 8.00 7.00

03007 Onions 3 KG.
7.00 6.00 4.50 4.50 4.00 3.50 4.00
5.50 7.00 5.50 8.00 6.00

03008 Garlic 1 KG.
30.00 40.00 30.00 15.00 20.00 20.00 40.00 35.00
40.00 40.00 25.00 30.00

03008 Garlic 2 KG.
30.00 25.00 25.00 20.00 20.00 20.00 30.00 35.00
30.00 22.00 30.00 40.00

03008 Garlic 3 KG.
30.00 30.00 25.00 25.00 20.00 12.00 30.00 32.00
40.00 24.00 30.00 28.00

03009 Pepper green 1 KG.
10.00 10.00 7.00 7.00 .00 10.00 10.00 8.00
12.00 12.00 10.00 14.00

03009 Pepper green 2 KG.
7.00 8.00 6.00 10.00 .00 11.00 12.00 9.00
10.00 12.00 14.00 10.00

03009 Pepper green 3 KG.
10.00 5.00 6.00 8.00 12.00 10.00 10.00 12.00
.00 11.00 .00 13.00

03011 Couli flower 1 KG.
8.00 15.00 10.00 8.00 .00 10.00 13.00 14.00
.00 .00 16.00 10.00

03011 Couli flower 2 KG.
8.00 10.00 8.00 7.00 10.00 .00 12.00 12.00
.00 .00 15.00 10.00

03011 Couli flower 3 KG.
6.00 10.00 5.00 7.00 8.00 .00 .00
.00 .00 .00 .00 .00

03012 Pumpkin 1 KG.
5.00 5.00 4.00 3.00 4.00 6.00 4.00
5.00 4.50 2.50 4.00 4.00

03012 Pumpkin 2 KG.
5.00 4.00 4.00 2.50 3.00 5.00 4.00
5.00 4.50 2.50 5.00 4.00

03012 Pumpkin 3 KG.
5.00 3.54 5.00 3.00 3.00 4.00 3.50
4.60 4.50 2.30 5.00 3.50

03013 Zukini 1 KG.
5.00 6.00 7.00 8.00 5.00 5.00 5.00
6.00 12.00 7.00 7.00 7.00

03013 Zukini 2 KG.
5.00 6.00 7.00 8.00 5.00 5.00 6.00
6.00 10.00 8.00 10.00 8.00

03013 Zukini 3 KG.
7.00 6.00 7.00 8.00 5.00 5.00 5.00
6.00 11.00 6.00 8.00 6.00

03017 Spinach 1 KG.
6.00 6.00 8.00 7.00 3.00 6.00 .00
.00 10.00 10.00 10.00 5.00

03017 Spinach 2 KG.
7.00 5.50 7.50 6.00 4.00 6.00 6.00
.00 8.00 .00 10.00 6.00

03017 Spinach 3 KG.
6.00 7.00 8.00 6.00 4.00 .00 .00
.00 8.00 .00 .00 .00

03018 Chikoria 1 KG.
4.00 5.00 5.00 4.00 .00 4.00 .00
.00 4.00 5.00 4.00 3.00

03018 Chikoria 2 KG.
4.00 3.50 4.00 4.00 .00 4.00 4.00
.00 6.00 5.00 5.00 5.00

03018 Chikoria 3 KG.
5.00 6.00 4.00 4.00 4.00 .00 .00
.00 .00 .00 5.00 3.00

03019 Cabbage 1 KG.
4.00 3.00 2.00 2.00 1.50 2.00 2.00
2.60 4.00 5.00 4.00 4.00

03019 Cabbage 2 KG.
3.00 3.00 3.00 2.00 2.00 2.50 2.00
2.50 3.50 5.00 4.00 4.00

03019 Cabbage 3 KG.
4.00 1.50 2.00 2.00 2.00 2.00 2.50
3.50 4.00 4.50 5.00 3.00

03020 Bamia 1 KG.
10.00 10.00 12.00 13.00 13.00 14.00 .00 20.00
12.00 10.00 12.00 .00

03020 Bamia 2 KG.
10.00 9.00 10.00 12.00 14.00 13.00 .00 15.00
12.00 12.00 12.00 10.00

03020 Bamia 3 KG.
10.00 10.00 10.00 13.00 13.00 .00 .00 .00
10.00 .00 12.00 16.00

04001 Bananas 1 KG.
4.00 4.00 4.00 3.50 4.00 3.50 3.50
3.50 4.50 4.00 4.00 5.00

04001 Bananas 2 KG.
4.00 3.80 4.00 3.50 3.00 3.50 3.50
4.00 4.00 4.00 4.50 4.50

04001 Bananas 3 KG.
4.00 4.00 4.00 3.50 3.50 3.50 3.50
4.00 4.00 4.00 4.50 4.50

04002 Oranges 1 KG.
8.00 9.00 11.00 11.00 11.00 13.00 14.00 12.00
13.00 12.00 10.00 9.00

04002 Oranges 2 KG.
8.00 9.50 11.00 12.00 12.00 14.00 13.00 14.00
12.00 12.00 10.00 9.00

04002 Oranges 3 KG.
8.00 9.00 11.00 12.00 12.00 13.00 12.00 13.00
12.00 11.00 8.00 9.00

04003 Lemons 1 KG.
10.00 10.00 15.00 14.00 .00 19.00 15.00 15.00
14.00 14.00 12.00 12.00

04003 Lemons 2 KG.
10.00 10.00 15.00 12.00 .00 20.00 18.00 12.00
12.00 13.00 15.00 12.00

04003 Lemons 3 KG.
15.00 10.00 8.00 13.00 16.00 20.00 16.00 13.00
12.00 12.00 13.00 12.00

04005 Papayas 1 KG.
7.00 8.00 7.00 4.50 6.00 6.00 6.00
8.00 11.00 11.00 12.00 10.00

04005 Papayas 2 KG.
7.00 6.50 6.00 6.00 6.00 6.00 6.50
6.00 10.00 10.00 13.00 10.00

04005 Papayas 3 KG.
8.00 6.00 6.00 5.50 6.00 5.00 6.00
7.50 10.00 12.00 12.00 9.00

04009 Apples 1 KG.
20.00 50.00 50.00 50.00 48.00 50.00 50.00 50.00
50.00 50.00 50.00 48.00

04009 Apples 2 KG.
20.00 50.00 50.00 50.00 50.00 50.00 50.00 50.00
50.00 50.00 50.00 50.00

04009 Apples 3 KG.
20.00 .00 50.00 50.00 50.00 50.00 50.00 .00
50.00 48.00 50.00 50.00

Nardos Ghebremedhin

Nardos Ghebremedhin

Marta García-Granero

Re: ELIMINATIONG ZEROS

Hi

I see you've posted your question again, since nobody answered. The
reason for not answering might be that the data you listed were all
scrambled, the layout was difficult to understand. For future
questions: if you order the data and present just a small sample (we
don't need the whole dataset to get an idea of your question), you are
more likely to get an answer.

Anyway, I've tried to solve the puzzle, and this is my idea of the
situation:

DATA LIST LIST/Itemno(F5) itemname(A15) quotation(F8) unit(A3) p1 TO p12 (12 Comma8.1).
BEGIN DATA
03002 'Cabbage' 1 KG. 3.0 3.0 2.5 2.0 2.0 1.5 2.0 2.0 4.0 3.0 4.0 4.0
03002 'Cabbage' 2 KG. 2.0 2.5 2.0 3.0 2.0 3.0 3.0 2.0 3.5 4.0 4.0 4.0
03002 'Cabbage' 3 KG. 3.0 2.0 2.0 2.0 2.0 1.5 1.5 1.5 3.0 2.5 4.0 3.0
03003 'Lettuce' 1 KG. 4.5 4.0 5.0 3.0 4.0 6.0 7.0 8.0 8.0 8.0 7.0 5.0
03003 'Lettuce' 2 KG. 5.0 5.0 5.0 4.0 5.0 8.0 8.0 8.0 8.0 8.0 8.0 6.0
03003 'Lettuce' 3 KG. 5.0 4.0 5.0 5.0 4.0 6.0 6.5 7.0 7.0 7.0 8.0 5.0
03004 'Carrot' 1 KG. 5.0 6.0 6.0 4.0 4.0 5.0 5.0 5.0 10.0 6.0 7.0 6.0
03004 'Carrot' 2 KG. 5.0 5.0 5.0 4.0 5.0 5.0 6.0 6.0 10.0 8.0 7.0 6.0
03004 'Carrot' 3 KG. 6.0 5.0 5.0 5.0 4.0 4.5 4.5 5.0 10.0 6.0 6.0 5.0
03005 'Potatos' 1 KG. 5.0 5.0 7.0 5.0 6.0 7.0 7.5 7.0 7.0 5.0 4.0 8.0
03005 'Potatos' 2 KG. 5.0 5.0 7.0 6.0 7.0 7.0 7.5 8.0 7.0 5.0 6.0 6.0
03005 'Potatos' 3 KG. 5.0 5.0 7.0 5.0 6.0 7.0 7.0 8.5 7.0 3.5 5.0 6.0
03006 'Tomatos' 1 KG. 6.0 4.0 3.5 3.5 5.0 5.5 7.0 8.0 10.0 6.0 3.0 3.5
03006 'Tomatos' 2 KG. 6.0 4.0 3.5 3.5 6.5 7.0 7.0 9.0 10.0 5.5 3.0 3.0
03006 'Tomatos' 3 KG. 6.0 4.5 3.5 4.0 6.0 4.0 5.0 8.0 10.0 6.0 3.0 3.0
03007 'Onions' 1 KG. 7.5 6.0 4.0 3.5 4.0 4.5 5.0 4.0 6.0 6.0 7.0 6.0
03007 'Onions' 2 KG. 7.0 9.0 4.0 4.0 4.0 4.5 5.0 4.0 6.0 6.0 8.0 7.0
03007 'Onions' 3 KG. 7.0 6.0 4.5 4.5 4.0 3.5 4.0 5.5 7.0 5.5 8.0 6.0
03008 'Garlic' 1 KG. 30.0 40.0 30.0 15.0 20.0 20.0 40.0 35.0 40.0 40.0 25.0 30.0
03008 'Garlic' 2 KG. 30.0 25.0 25.0 20.0 20.0 20.0 30.0 35.0 30.0 22.0 30.0 40.0
03008 'Garlic' 3 KG. 30.0 30.0 25.0 25.0 20.0 12.0 30.0 32.0 40.0 24.0 30.0 28.0
03009 'Pepper green' 1 KG. 10.0 10.0 7.0 7.0 .0 10.0 10.0 8.0 12.0 12.0 10.0 14.0
03009 'Pepper green' 2 KG. 7.0 8.0 6.0 10.0 .0 11.0 12.0 9.0 10.0 12.0 14.0 10.0
03009 'Pepper green' 3 KG. 10.0 5.0 6.0 8.0 12.0 10.0 10.0 12.0 .0 11.0 .0 13.0
03011 'Couli flower' 1 KG. 8.0 15.0 10.0 8.0 .0 10.0 13.0 14.0 .0 .0 16.0 10.0
03011 'Couli flower' 2 KG. 8.0 10.0 8.0 7.0 10.0 .0 12.0 12.0 .0 .0 15.0 10.0
03011 'Couli flower' 3 KG. 6.0 10.0 5.0 7.0 8.0 .0 .0 .0 .0 .0 .0 .0
03012 'Pumpkin' 1 KG. 5.0 5.0 4.0 3.0 4.0 6.0 4.0 5.0 4.5 2.5 4.0 4.0
03012 'Pumpkin' 2 KG. 5.0 4.0 4.0 2.5 3.0 5.0 4.0 5.0 4.5 2.5 5.0 4.0
03012 'Pumpkin' 3 KG. 5.0 3.5 5.0 3.0 3.0 4.0 3.5 4.6 4.5 2.3 5.0 3.5
03013 'Zukini' 1 KG. 5.0 6.0 7.0 8.0 5.0 5.0 5.0 6.0 12.0 7.0 7.0 7.0
03013 'Zukini' 2 KG. 5.0 6.0 7.0 8.0 5.0 5.0 6.0 6.0 10.0 8.0 10.0 8.0
03013 'Zukini' 3 KG. 7.0 6.0 7.0 8. 0 5.0 5.0 5.0 6.0 11. 6.0 8.0 6.0
END DATA.

I hope my interpretation is correct (it took some time and I had to
reorder a lot of lines). As you see, only a sample of your data are
presented in this test dataset. If I understand you correctly, you
want to replace the ".0" by missing values:

RECODE p1 TO p12 (0=SYSMIS) .
EXECUTE .

Now you can proceed with any statistical analysis you want.

If this is not what you need, please write again and explain your
problem a bit more.

HTH,

Marta Garcia-Granero, PhD
Statistician

NG> WOULD ANY ONE PLEASE HELP ME WITH THE FOLLOWING PROBLEM?

NG> I just want to take out all the zeros from the data given below (part of
NG> an observation). As you can notice one item is collected from three
NG> outlets (quotations), and it may happen that this item is priced only in
NG> one or two or all the three quotations. Now what I want is, as it is
NG> displayed below I want to extract all the non zero prices without
NG> disturbing the data. Please notice that the structure of the data view
NG> is as depicted below. I want to take out only the zero's, it could be
NG> from only one quotation or two or three conditionally. For example for
NG> the observations in blue color, item green pepper (price of the 9th
NG> month,p9), I want to takeout the 3rd quotation and keep the other two in
NG> order to compute average prices. Similarly, for the item couli flower
NG> since all the quotations are zero, I want to takeout the whole item for
NG> this specific month (p9).

NG> All I want is how to do such things using syntax (SPSS 11).

NG> Actually I have tried to do such things while the observations are
NG> arranged raw wise. By just writing " select if p(?) ne 0" . what if they
NG> are arranged as below? Is there any way to proceed?

NG> All the best!

NG> Itemno itemname quotation unit
NG> p1 p2 p3 p4 p5 p6 p7
NG> p8 p9 p10 p11 p12

NG> 03002 Cabbage 1 KG.
NG> 3.00 3.00 2.50 2.00 2.00 1.50 2.00
NG> 2.00 4.00 3.00 4.00 4.00

NG> 03002 Cabbage 2 KG.
NG> 2.00 2.50 2.00 3.00 2.00 3.00 3.00
NG> 2.00 3.50 4.00 4.00 4.00

NG> 03002 Cabbage 3 KG.
NG> 3.00 2.00 2.00 2.00 2.00 1.50 1.50
NG> 1.50 3.00 2.50 4.00 3.00

NG> 03003 Lettuce 1 KG.
NG> 4.50 4.00 5.00 3.00 4.00 6.00 7.00
NG> 8.00 8.00 8.00 7.00 5.00

NG> 03003 Lettuce 2 KG.
NG> 5.00 5.00 5.00 4.00 5.00 8.00 8.00
NG> 8.00 8.00 8.00 8.00 6.00

NG> 03003 Lettuce 3 KG.
NG> 5.00 4.00 5.00 5.00 4.00 6.00 6.50
NG> 7.00 7.00 7.00 8.00 5.00

NG> 03004 Carrot 1 KG.
NG> 5.00 6.00 6.00 4.00 4.00 5.00 5.00
NG> 5.00 10.00 6.00 7.00 6.00

NG> 03004 Carrot 2 KG.
NG> 5.00 5.00 5.00 4.00 5.00 5.00 6.00
NG> 6.00 10.00 8.00 7.00 6.00

NG> 03004 Carrot 3 KG.
NG> 6.00 5.00 5.00 5.00 4.00 4.50 4.50
NG> 5.00 10.00 6.00 6.00 5.00

NG> 03005 Potatos 1 KG.
NG> 5.00 5.00 7.00 5.00 6.00 7.00 7.50
NG> 7.00 7.00 5.00 4.00 8.00

NG> 03005 Potatos 2 KG.
NG> 5.00 5.00 7.00 6.00 7.00 7.00 7.50
NG> 8.00 7.00 5.00 6.00 6.00

NG> 03005 Potatos 3 KG.
NG> 5.00 5.00 7.00 5.00 6.00 7.00 7.00
NG> 8.50 7.00 3.50 5.00 6.00

NG> 03006 Tomatos 1 KG.
NG> 6.00 4.00 3.50 3.50 5.00 5.50 7.00
NG> 8.00 10.00 6.00 3.00 3.50

NG> 03006 Tomatos 2 KG.
NG> 6.00 4.00 3.50 3.50 6.50 7.00 7.00
NG> 9.00 10.00 5.50 3.00 3.00

NG> 03006 Tomatos 3 KG.
NG> 6.00 4.50 3.50 4.00 6.00 4.00 5.00
NG> 8.00 10.00 6.00 3.00 3.00

NG> 03007 Onions 1 KG.
NG> 7.50 6.00 4.00 3.50 4.00 4.50 5.00
NG> 4.00 6.00 6.00 7.00 6.00

NG> 03007 Onions 2 KG.
NG> 7.00 9.00 4.00 4.00 4.00 4.50 5.00
NG> 4.00 6.00 6.00 8.00 7.00

NG> 03007 Onions 3 KG.
NG> 7.00 6.00 4.50 4.50 4.00 3.50 4.00
NG> 5.50 7.00 5.50 8.00 6.00

NG> 03008 Garlic 1 KG.
NG> 30.00 40.00 30.00 15.00 20.00 20.00 40.00 35.00
NG> 40.00 40.00 25.00 30.00

NG> 03008 Garlic 2 KG.
NG> 30.00 25.00 25.00 20.00 20.00 20.00 30.00 35.00
NG> 30.00 22.00 30.00 40.00

NG> 03008 Garlic 3 KG.
NG> 30.00 30.00 25.00 25.00 20.00 12.00 30.00 32.00
NG> 40.00 24.00 30.00 28.00

NG> 03009 Pepper green 1 KG.
NG> 10.00 10.00 7.00 7.00 .00 10.00 10.00 8.00
NG> 12.00 12.00 10.00 14.00

NG> 03009 Pepper green 2 KG.
NG> 7.00 8.00 6.00 10.00 .00 11.00 12.00 9.00
NG> 10.00 12.00 14.00 10.00

NG> 03009 Pepper green 3 KG.
NG> 10.00 5.00 6.00 8.00 12.00 10.00 10.00 12.00
NG> .00 11.00 .00 13.00

NG> 03011 Couli flower 1 KG.
NG> 8.00 15.00 10.00 8.00 .00 10.00 13.00 14.00
NG> .00 .00 16.00 10.00

NG> 03011 Couli flower 2 KG.
NG> 8.00 10.00 8.00 7.00 10.00 .00 12.00 12.00
NG> .00 .00 15.00 10.00

NG> 03011 Couli flower 3 KG.
NG> 6.00 10.00 5.00 7.00 8.00 .00 .00
NG> .00 .00 .00 .00 .00

NG> 03012 Pumpkin 1 KG.
NG> 5.00 5.00 4.00 3.00 4.00 6.00 4.00
NG> 5.00 4.50 2.50 4.00 4.00

NG> 03012 Pumpkin 2 KG.
NG> 5.00 4.00 4.00 2.50 3.00 5.00 4.00
NG> 5.00 4.50 2.50 5.00 4.00

NG> 03012 Pumpkin 3 KG.
NG> 5.00 3.54 5.00 3.00 3.00 4.00 3.50
NG> 4.60 4.50 2.30 5.00 3.50

NG> 03013 Zukini 1 KG.
NG> 5.00 6.00 7.00 8.00 5.00 5.00 5.00
NG> 6.00 12.00 7.00 7.00 7.00

NG> 03013 Zukini 2 KG.
NG> 5.00 6.00 7.00 8.00 5.00 5.00 6.00
NG> 6.00 10.00 8.00 10.00 8.00

NG> 03013 Zukini 3 KG.
NG> 7.00 6.00 7.00 8.00 5.00 5.00 5.00
NG> 6.00 11.00 6.00 8.00 6.00

NG> 03017 Spinach 1 KG.
NG> 6.00 6.00 8.00 7.00 3.00 6.00 .00
NG> .00 10.00 10.00 10.00 5.00

NG> 03017 Spinach 2 KG.
NG> 7.00 5.50 7.50 6.00 4.00 6.00 6.00
NG> .00 8.00 .00 10.00 6.00

NG> 03017 Spinach 3 KG.
NG> 6.00 7.00 8.00 6.00 4.00 .00 .00
NG> .00 8.00 .00 .00 .00

NG> 03018 Chikoria 1 KG.
NG> 4.00 5.00 5.00 4.00 .00 4.00 .00
NG> .00 4.00 5.00 4.00 3.00

NG> 03018 Chikoria 2 KG.
NG> 4.00 3.50 4.00 4.00 .00 4.00 4.00
NG> .00 6.00 5.00 5.00 5.00

NG> 03018 Chikoria 3 KG.
NG> 5.00 6.00 4.00 4.00 4.00 .00 .00
NG> .00 .00 .00 5.00 3.00

NG> 03019 Cabbage 1 KG.
NG> 4.00 3.00 2.00 2.00 1.50 2.00 2.00
NG> 2.60 4.00 5.00 4.00 4.00

NG> 03019 Cabbage 2 KG.
NG> 3.00 3.00 3.00 2.00 2.00 2.50 2.00
NG> 2.50 3.50 5.00 4.00 4.00

NG> 03019 Cabbage 3 KG.
NG> 4.00 1.50 2.00 2.00 2.00 2.00 2.50
NG> 3.50 4.00 4.50 5.00 3.00

NG> 03020 Bamia 1 KG.
NG> 10.00 10.00 12.00 13.00 13.00 14.00 .00 20.00
NG> 12.00 10.00 12.00 .00

NG> 03020 Bamia 2 KG.
NG> 10.00 9.00 10.00 12.00 14.00 13.00 .00 15.00
NG> 12.00 12.00 12.00 10.00

NG> 03020 Bamia 3 KG.
NG> 10.00 10.00 10.00 13.00 13.00 .00 .00 .00
NG> 10.00 .00 12.00 16.00

NG> 04001 Bananas 1 KG.
NG> 4.00 4.00 4.00 3.50 4.00 3.50 3.50
NG> 3.50 4.50 4.00 4.00 5.00

NG> 04001 Bananas 2 KG.
NG> 4.00 3.80 4.00 3.50 3.00 3.50 3.50
NG> 4.00 4.00 4.00 4.50 4.50

NG> 04001 Bananas 3 KG.
NG> 4.00 4.00 4.00 3.50 3.50 3.50 3.50
NG> 4.00 4.00 4.00 4.50 4.50

NG> 04002 Oranges 1 KG.
NG> 8.00 9.00 11.00 11.00 11.00 13.00 14.00 12.00
NG> 13.00 12.00 10.00 9.00

NG> 04002 Oranges 2 KG.
NG> 8.00 9.50 11.00 12.00 12.00 14.00 13.00 14.00
NG> 12.00 12.00 10.00 9.00

NG> 04002 Oranges 3 KG.
NG> 8.00 9.00 11.00 12.00 12.00 13.00 12.00 13.00
NG> 12.00 11.00 8.00 9.00

NG> 04003 Lemons 1 KG.
NG> 10.00 10.00 15.00 14.00 .00 19.00 15.00 15.00
NG> 14.00 14.00 12.00 12.00

NG> 04003 Lemons 2 KG.
NG> 10.00 10.00 15.00 12.00 .00 20.00 18.00 12.00
NG> 12.00 13.00 15.00 12.00

NG> 04003 Lemons 3 KG.
NG> 15.00 10.00 8.00 13.00 16.00 20.00 16.00 13.00
NG> 12.00 12.00 13.00 12.00

NG> 04005 Papayas 1 KG.
NG> 7.00 8.00 7.00 4.50 6.00 6.00 6.00
NG> 8.00 11.00 11.00 12.00 10.00

NG> 04005 Papayas 2 KG.
NG> 7.00 6.50 6.00 6.00 6.00 6.00 6.50
NG> 6.00 10.00 10.00 13.00 10.00

NG> 04005 Papayas 3 KG.
NG> 8.00 6.00 6.00 5.50 6.00 5.00 6.00
NG> 7.50 10.00 12.00 12.00 9.00

NG> 04009 Apples 1 KG.
NG> 20.00 50.00 50.00 50.00 48.00 50.00 50.00 50.00
NG> 50.00 50.00 50.00 48.00

NG> 04009 Apples 2 KG.
NG> 20.00 50.00 50.00 50.00 50.00 50.00 50.00 50.00
NG> 50.00 50.00 50.00 50.00

NG> 04009 Apples 3 KG.
NG> 20.00 .00 50.00 50.00 50.00 50.00 50.00 .00
NG> 50.00 48.00 50.00 50.00

NG> Nardos Ghebremedhin

NG> Nardos Ghebremedhin

NG> __________ Información de NOD32, revisión 1.1626 (20060626) __________

NG> Este mensaje ha sido analizado con NOD32 antivirus system
NG> http://www.nod32.com

--
Saludos,
Marta mailto:[hidden email]

Richard Ristow

Re: ELIMINATIONG ZEROS

In reply to this post by Nardos Ghebremedhin

At 01:42 AM 6/27/2006, Nardos Ghebremedhin wrote:

>WOULD ANY ONE PLEASE HELP ME WITH THE FOLLOWING PROBLEM?
>
>I just want to take out all the zeros from the data given below

Did you miss the previous response?

>>Reply-To: Richard Ristow <[hidden email]>
>>Subject: Re: Eliminating zeroes from data
>>Comments: To: Nardos Ghebremedhin <[hidden email]>
>>To: [hidden email]

It was sent to you and to the list. I'd changed the subject line from
"how to proceed with such things!", which wasn't very informative.

As you'll see, my recommendation agrees with Marta's.