Stata syntaxes on Early Childhood Development Index measures*(dofile/commandos)

[Fallon Kathleen Lambert]

Hi everyone

Can you help me a student out with some commandos?

I need help coverting those SPSS syntaxes to Stata to make my own calculations
Any tips are more than welcome
Or is there a dofile somewhere


******************************************* *********** from SPSS
* Encoding: windows-1252.
***.
* v02 - 2020-04-14. Labels in French and Spanish have been removed.
***.


* Responses to questions EC6-EC15 are used to determine whether children are developmentally on track in four domains:
Literacy-numeracy: Developmentally on track if at least two of the following are true:
EC6=1 (Can identify/name at least ten letters of the alphabet),
EC7=1 (Can read at least four simple, popular words),
EC8=1 (Knows the name and recognizes the symbol of all numbers from 1 to 10).
* Physical: Developmentally on track if one or both of the following is true:
EC9=1 (Can pick up a small object with two fingers, like a stick or a rock from the ground),
EC10=2 (Is not sometimes too sick to play).
* Social-emotional: Developmentally on track if at least two of the following are true:
EC13=1 (Gets along well with other children),
EC14=2 (Does not kick, bite, or hit other children),
EC15=2 (Does not get distracted easily).
* Learning: Developmentally on track if one or both of the following is true:
EC11=1 (Follows simple directions on how to do something correctly),
EC12=1 (When given something to do, is able to do it independently).

* MICS indicator TC.53 is calculated as the percentage of children who are developmentally on track in at least three of the four component domains (literacy-numeracy, physical, social-emotional, and learning).

***.

* Call include file for the working directory and the survey name.
include "surveyname.sps".

* open children dataset.
get file = 'ch.sav'.

include "CommonVarsCH.sps".

* Select completed interviews.
select if (UF17 = 1).

* Select children 36+ months old.
select if (UB2 >= 3).

* Weight the data by the children weight.
weight by chweight.

* Generate number of children age 36-59 months.
compute numChildren = 1.
value labels numChildren 1 "".
variable labels numChildren "Number of children age 3-4 years".

* Compute indicators.
recode EC6 (1 = 100) (else = 0).
recode EC7 (1 = 100) (else = 0).
recode EC8 (1 = 100) (else = 0).

count langcog = EC8 EC7 EC6 (100).

recode langcog (2,3 = 100) (0,1 = 0) into langcog2.
variable labels langcog2 "Literacy-numeracy".

recode EC9 (1 = 100) (else = 0).
recode EC10 (2 = 100) (else = 0).

count physical = EC10 EC9 (100).

recode physical (1,2 = 100) (0 = 0) into physical2.
variable labels physical2 "Physical".

recode EC13 (1 = 100) (else = 0).
recode EC14 (2 = 100) (else = 0).
recode EC15 (2 = 100) (else = 0).

count socemo = EC15 EC14 EC13 (100).

recode socemo (2,3 = 100) (0,1 = 0) into socemo2.
variable labels socemo2 "Social-Emotional".

recode EC11 (1 = 100) (else = 0).
recode EC12 (1 = 100) (else = 0).

count learn = EC12 EC11 (100).

recode learn (1,2 = 100) (0 = 0) into learn2.
variable labels learn2 "Learning".

count develop = langcog2 physical2 socemo2 learn2 (100).

recode develop (3,4 = 100) (0,1,2 = 0) into target.

variable labels target "Early child development index score [1]".

recode UB8 (1 = 1) (9 = 8) (else = 2).
variable labels UB8 "Attendance to early childhood education".
value labels UB8
1 "Attending"
2 "Not attending "
8 "Missing".

variable labels ub2 "Age".
value labels ub2 3 "3" 4 "4".

compute layer = 0.
variable labels layer "".
value labels layer 0 "Percentage of children age 3-4 years who are developmentally on track for indicated domains".

compute total = 1.
variable labels total "Total".
value labels total 1" ".

variable labels cdisability "Functional difficulties".

* Ctables command in English.
ctables
/vlabels variables = layer
display = none
/table total [c]
+ hl4 [c]
+ hh6 [c]
+ hh7 [c]
+ ub2 [c]
+ ub8 [c]
+ melevel [c]
+ cdisability [c]
+ ethnicity [c]
+ windex5[c]
by
layer [c] > (
langcog2 [s] [mean '' f5.1]
+ physical2 [s] [mean '' f5.1]
+ socemo2 [s] [mean '' f5.1]
+ learn2 [s] [mean '' f5.1] )
+ target[s] [mean '' f5.1]
+ numChildren [s] [sum '' f5.0]
/categories variables=all empty=exclude
/slabels position=column visible = no
/titles title=
"Table TC.11.1: Early child development index"
"Percentage of children age 3-4 years who are developmentally on track in literacy-numeracy, physical, " +
"social-emotional, and learning domains, and the early child development index score, " + surveyname
caption=
"[1] MICS indicator TC.53 - Early child development index"
.

new file.

I found this on the unicef website http://mics.unicef.org/tools?round=mics6

[Leonardo Guizzetti]

Hi Fallon, and welcome to the Stata Forum. You will be unlikely for someone to come along and translate SPSS syntax into Stata syntax for an entire program, much less without a reproducible data example. Since you seem to want to use Stata for analysis, I would suggest that you open the PDF documentation that comes with your Stata installation (Help > PDF Documentation), and follow the "Getting Started" link. When many of us users wanted to get started with Stata in a serious way, this was a great way to begin that journey. You needn't take much time, a good weekend reading and experimenting will get you quite far.

[Mike Lacy]

I'm sympathetic to your situation, as someone who moved from many years using SPSS to becoming a Stata user some years ago. The two languages are quite similar, but with notable differences. I'd agree with Leonardo that asking for a translation of a whole program is too much. However, I can offer some pointers, per below. Also, I'd say that if you plunge into the translation yourself, it's appropriate to ask for help here with particular pieces of SPSS syntax whose translation you can't handle. That's what I did when I was new.

Here are some basic translations that you can use. For each of them, you'll want to use the Stata help facility to start learning about it..

0) Starting on the lighter side: Although Stata probably gets used by military personnel and veterans, we call them "commands" rather than "commandos." I will, with some effort, refrain from making bad jokes about the (American?) slang term "going commando." I will restrict myself to noting that, although I lack any empirical data whatsoever, I suspect that the prevalence of this practice is likely comparable among SPSS and Stata users.
1) Comments, particularly "*". See -help comments- in Stata.
2) Re the end of command delimiter of "." in SPSS: Stata doesn't have this. An end of line ends a command in Stata unless you use the line continuation indicator "///" described in -help comments- (There is a way to use Stata with ";" used as a delimiter like "." is in SPSS, but the ";" usage is not common, and you would do better to get used to "///".)
3) recode in SPSS is quite similar in Stata. -help recode-
4) compute translates to -generate- and -replace-. -help generate-
5) variable labels is -label var- in Stata. -help labels-
6) values labels in Stata work differently, but see -label values- under -help labels-
7) get file and new file in SPSS are respectively -use- and -clear- in Stata.
8) I never used ctables in SPSS. -help table- may be relevant.
9) For the SPSS count command, I believe the -anycount- or some other function in -egen- would work. See -help egen-
10) select if in SPSS is -keep if- in Stata.
11) SPSS's include is -include- in Stata.

When using Stata's help, you'll do well to a) look at the examples ("remarks and examples"), rather than getting scared off by the syntax diagrams; and b) make sure to click through to the PDF help files. One of the things I liked better about Stata than SPSS when I migrated was that the documentation was more easily accessible in Stata, at least back then.

If you don't want to work through this yourself, it is appropriate on StataList (though not common) to post requests to hire someone to do a Stata task.

[Vukile Mnisi]

I've been trying to develop the same index but the count command does not work, im also a student that is trying to develop the same index for my country. I was browsing through this do file and i cannot seem to get how the lancog variable was computed and how the count variable works with respect to how it was used in this do file. Your kind assistance will be appreciated.

[Chen Samulsion]

You can try the following code and correct at any time when you find wrong.

* open children dataset. 

import spss using "ch.sav"

* Or if you have translated ch.sav into ch.dta using StatTransfer or other software or command in Stata.
use "ch.dta"

* Select completed interviews.
keep if UF17 == 1

* Select children 36+ months old.
keep if UB2 >= 3

* Weight the data by the children weight. Notice you should apply this carefully and maybe its wrong.
svyset _n [pweight = chweight]

* Generate number of children age 36-59 months.
generate numChildren = 1
label define numChildren 1 ""
label values numChildren numChildren
label variable numChildren "Number of children age 3-4 years"

* Compute indicators.
recode EC6 (1 = 100) (else = 0), gen(N_EC6)
recode EC7 (1 = 100) (else = 0), gen(N_EC7)
recode EC8 (1 = 100) (else = 0), gen(N_EC8)

drop EC6 EC7 EC8
rename N_EC# EC#

egen langcog = anycount(EC8 EC7 EC6), values(100)

recode langcog (2 3 = 100) (0 1 = 0), gen(langcog2)
label variable langcog2 "Literacy-numeracy"

recode EC9 (1 = 100) (else = 0), gen(N_EC9)
recode EC10 (2 = 100) (else = 0), gen(N_EC10)

drop EC9 EC10
rename N_EC# EC#

egen physical = anycount(EC10 EC9), values(100)

recode physical (1 2 = 100) (0 = 0), gen(physical2)
label variable physical2 "Physical"

recode EC13 (1 = 100) (else = 0), gen(N_EC13)
recode EC14 (2 = 100) (else = 0), gen(N_EC14)
recode EC15 (2 = 100) (else = 0), gen(N_EC15)

drop EC13 EC14 EC15
rename N_EC# EC#

egen socemo = anycount(EC15 EC14 EC13), values(100)

recode socemo (2 3 = 100) (0 1 = 0), gen(socemo2)
label variable socemo2 "Social-Emotional"

recode EC11 (1 = 100) (else = 0), gen(N_EC11)
recode EC12 (1 = 100) (else = 0), gen(N_EC12)

drop EC11 EC12
rename N_EC# EC#

egen learn = anycount(EC12 EC11), values(100)

recode learn (1 2 = 100) (0 = 0), gen(learn2)
label variable learn2 "Learning"

egen develop = anycount(langcog2 physical2 socemo2 learn2), values(100)

recode develop (3 4 = 100) (0 1 2 = 0), gen(target)

label variable target "Early child development index score [1]"

recode UB8 (1 = 1) (9 = 8) (else = 2), gen(N_UB8)

drop UB8
rename N_UB8 UB8

label variable UB8 "Attendance to early childhood education"
label define UB8 1 "Attending" 2 "Not attending " 8 "Missing"
label values UB8 UB8

label variable ub2 "Age"
label define ub2 3 "3" 4 "4"
label values ub2 ub2

generate layer = 0
label variable layer "Percentage of children age 3-4 years who are developmentally on track for indicated domains"
label define layer 0 ""
label values layer layer

generate total = 1
label variable total "Total"
label define total 1 ""
label values total total

label variable cdisability "Functional difficulties"

* Ctables command in English.
* No translation here for not familiar with ctable.

[Vukile Mnisi]

Thank you very much, I will engage with my data and see how it goes. In the meantime, may I get help in creating a variable for family involvement for children between ages 3-4 in stimulating activities such as reading books, playing with children and more. I am using MICS 5 and variables have been divided into mother, father, other and no one. In each activity, its either the mother, father, other family members or no one has engaged in a certain activity with children.

Variables i intended on using were string variables and I encoded them but im not sure whether i encoded them correctly because they give different numerical values, sometimes 1 or 2. Below is what i did to encode them


keep AG2 EC5 EC7AA EC7AB EC7AX EC7AY EC7BA EC7BB EC7BX EC7BY EC7CA EC7CB EC7CX EC7CY EC7DA EC7DB EC7DX EC7DY EC7EA EC7EB EC7EX EC7EY EC7FA EC7FB EC7FX EC7FY EC8 EC9 EC10 EC11 EC12 EC13 EC14 EC15 EC16 EC17 HH6 HL4 melevel windex5 EC1

encode EC7AA, gen(EC7AA_1) **Read Books-Mother**
encode EC7AB, gen(EC7AB_1) **Read Book-Father**
encode EC7AX, gen(EC7AX_1) **Read Books-Other**
encode EC7AY, gen(EC7AY_1) **Read Books-No one**
encode EC7BA, gen(EC7BA_1) **Tell stories - Mother**
encode EC7BB, gen(EC7BB_1) **Tell stories - Father**
encode EC7BX, gen(EC7BX_1) **Tell stories - Other**
encode EC7BY, gen(EC7BY_1) **Tell stories - No one**
encode EC7CA, gen(EC7CA_1) **Sang songs - Mother**
encode EC7CB, gen(EC7CB_1) **Sang songs - Father**
encode EC7CX, gen(EC7CX_1) **Sang songs - Other**
encode EC7CY, gen(EC7CY_1) **Sang songs - No one**
encode EC7DA, gen(EC7DA_1) **Took outside - Mother**
encode EC7DB, gen(EC7DB_1) **Took outside - Father**
encode EC7DX, gen(EC7DX_1) **Took outside - Other**
encode EC7DY, gen(EC7DY_1) **Took outside - No one**
encode EC7EA, gen(EC7EA_1) **Played with - Mother**
encode EC7EB, gen(EC7EB_1) **Played with - Father**
encode EC7EX, gen(EC7EX_1) **Played with - Other**
encode EC7EY, gen(EC7EY_1) **Played with - No one**
encode EC7FA, gen(EC7FA_1) **Named/counted - Mother**
encode EC7FB, gen(EC7FB_1) **Named/counted - Father**
encode EC7FX, gen(EC7FX_1) **Named/counted - Other**
encode EC7FY, gen(EC7FY_1) **Named/counted - No one**

What I want to do is create one variable using all these variables which will be a measure for family involvement

This is what i have thus far but it does not seem to work.

/*Main Independent Variable. Family involvement is measured as the number of activities that family members engage in with their children. There six activities that the MICS dataset uses namely reading books, telling stories, singing songs, playing with, and naming/counting all done by family members with children.
Family_Involvement=1 if activities engaged with children >=4
Family_Involvement=0 if activities engaged with children <4*/
gen read_books=0
gen tell_stories=0
gen sang_songs=0
gen played_with=0
gen took_outside=0
gen named_counted=0
replace read_books=1 if EC7AA_1+EC7AB_1+EC7AX_1>=1
replace tell_stories=1 if EC7BA_1+EC7BB_1+EC7BX_1>=1
replace sang_songs=1 if EC7CA_1+EC7CB_1+EC7CX_1>=1
replace played_with=1 if EC7EA_1+EC7EB_1+EC7EX_1>=1
replace took_outside=1 if EC7DA_1+EC7DB_1+EC7DX_1>=1
replace named_counted=1 if EC7FA_1+EC7FB_1+EC7FX_1>=1

Your kind assistance will be of great help.

[Jared Greathouse]

For us to better help you, you must provide us an example of your data using the dataex command. Then after showing us your data (that successfully reproduces the issue you're having), then we can discuss solutions. But, we really need that data example first, otherwise all the advice we give is just guessing at what might be the problem.

[Vukile Mnisi]

* Example generated by -dataex-. For more info, type help dataex
clear
input str1(EC7AA EC7AB EC7AX EC7AY EC7BA EC7BB EC7BX EC7BY EC7CA EC7CB EC7CX EC7CY EC7DA EC7DB EC7DX EC7DY EC7EA EC7EB EC7EX EC7EY EC7FA EC7FB EC7FX EC7FY)
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  "Y" ""  "" ""  "Y" ""  "" ""  "Y" ""  ""  ""  "Y" ""  "" "X" ""  ""  ""  ""  "Y"
""  "" ""  "Y" ""  "" ""  "Y" ""  "" ""  "Y" ""  ""  ""  "Y" ""  "" ""  "Y" ""  ""  ""  "Y"
""  "" ""  "Y" ""  "" ""  "Y" ""  "" ""  "Y" ""  ""  ""  "Y" ""  "" ""  "Y" ""  ""  ""  "Y"
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
"A" "" ""  ""  "A" "" ""  ""  "A" "" ""  ""  "A" ""  ""  ""  "A" "" ""  ""  "A" ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  "Y" ""  "" ""  "Y" ""  "" ""  "Y" "A" ""  ""  ""  ""  "" ""  "Y" ""  ""  ""  "Y"
""  "" ""  "Y" ""  "" ""  "Y" ""  "" ""  "Y" ""  ""  ""  "Y" ""  "" ""  "Y" ""  ""  ""  "Y"
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  "Y" ""  "" "X" ""  ""  "" "X" ""  "A" ""  ""  ""  ""  "" "X" ""  ""  ""  "X" "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  "Y" "A" "" ""  ""  "A" "" ""  ""  ""  ""  "X" ""  ""  "" "X" ""  ""  ""  ""  "Y"
""  "" ""  "Y" ""  "" ""  "Y" ""  "" ""  "Y" ""  ""  ""  "Y" ""  "" "X" ""  ""  ""  ""  "Y"
"A" "" ""  ""  ""  "" ""  "Y" "A" "" ""  ""  "A" ""  ""  ""  ""  "" ""  "Y" ""  ""  ""  "Y"
""  "" ""  "Y" ""  "" ""  "Y" ""  "" "X" ""  ""  ""  "X" ""  ""  "" "X" ""  ""  ""  "X" "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" "X" ""  ""  "" "X" ""  ""  "" "X" ""  ""  ""  "X" ""  ""  "" "X" ""  ""  ""  "X" "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" "X" ""  ""  "" "X" ""  ""  "" "X" ""  ""  ""  "X" ""  ""  "" "X" ""  ""  ""  "X" "" 
""  "" ""  "Y" ""  "" ""  "Y" "A" "" "X" ""  "A" ""  ""  ""  ""  "" "X" ""  "A" ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
"A" "" ""  ""  ""  "" ""  "Y" "A" "" ""  ""  "A" ""  ""  ""  "A" "" ""  ""  "A" ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  "Y" ""  "" "X" ""  ""  "" ""  "Y" ""  ""  ""  "Y" ""  "" "X" ""  ""  ""  ""  "Y"
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  "Y" ""  "" "X" ""  ""  "" "X" ""  ""  ""  "X" ""  ""  "" "X" ""  ""  ""  "X" "" 
""  "" ""  "Y" ""  "" ""  "Y" ""  "" ""  "Y" "A" ""  ""  ""  "A" "" "X" ""  "A" "B" "X" "" 
""  "" ""  "Y" ""  "" ""  "Y" ""  "" ""  "Y" ""  "B" ""  ""  ""  "" ""  "Y" ""  ""  ""  "Y"
""  "" "X" ""  ""  "" "X" ""  ""  "" "X" ""  ""  ""  "X" ""  ""  "" "X" ""  ""  ""  "X" "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  "Y" ""  "" ""  "Y" ""  "" ""  "Y" ""  ""  ""  "Y" ""  "" ""  "Y" ""  ""  ""  "Y"
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" "X" ""  ""  "" "X" ""  ""  "" "X" ""  ""  ""  "X" ""  ""  "" "X" ""  ""  ""  "X" "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  "Y" ""  "" ""  "Y" ""  "" "X" ""  ""  ""  "X" ""  ""  "" "X" ""  ""  ""  "X" "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  "Y" ""  "" "X" ""  ""  "" ""  "Y" ""  ""  "X" ""  ""  "" ""  "Y" ""  ""  "X" "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" "X" ""  ""  "" ""  "Y" ""  "" "X" ""  ""  "B" ""  ""  ""  "" "X" ""  ""  ""  "X" "" 
""  "" ""  "Y" ""  "" "X" ""  ""  "" ""  "Y" ""  ""  "X" ""  ""  "" "X" ""  ""  ""  "X" "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" "X" ""  ""  "" "X" ""  ""  "" "X" ""  ""  ""  "X" ""  ""  "" "X" ""  ""  ""  "X" "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  "Y" ""  "" ""  "Y" ""  "" ""  "Y" ""  ""  ""  "Y" ""  "" ""  "Y" ""  ""  ""  "Y"
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
"A" "" "X" ""  ""  "" "X" ""  "A" "" "X" ""  "A" ""  ""  ""  "A" "" "X" ""  "A" ""  ""  "" 
""  "" "X" ""  ""  "" "X" ""  ""  "" "X" ""  ""  ""  "X" ""  ""  "" "X" ""  ""  ""  "X" "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" "X" ""  ""  "" "X" ""  ""  "" "X" ""  ""  ""  "X" ""  ""  "" "X" ""  ""  ""  "X" "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  "Y" ""  "" ""  "Y" "A" "" ""  ""  "A" ""  ""  ""  "A" "" ""  ""  "A" ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" "X" ""  ""  "" "X" ""  ""  "" "X" ""  ""  ""  "X" ""  ""  "" "X" ""  ""  ""  "X" "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  "Y" ""  "" ""  "Y" ""  "" "X" ""  ""  ""  "X" ""  ""  "" "X" ""  ""  ""  "X" "" 
""  "" ""  "Y" ""  "" "X" ""  "A" "" ""  ""  "A" ""  ""  ""  "A" "" "X" ""  "A" ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  "Y" ""  "" ""  "Y" ""  "" ""  "Y" ""  ""  ""  "Y" ""  "" ""  "Y" ""  ""  ""  "Y"
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  "Y" ""  "" "X" ""  "A" "" ""  ""  ""  ""  ""  "Y" "A" "" ""  ""  "A" ""  "X" "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  "Y" ""  "" ""  "Y" ""  "" ""  "Y" ""  ""  ""  "Y" ""  "" ""  "Y" ""  ""  ""  "Y"
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  "Y" ""  "" ""  "Y" ""  "" "X" ""  ""  ""  "X" ""  ""  "" "X" ""  ""  ""  "X" "" 
""  "" ""  "Y" ""  "" ""  "Y" ""  "" ""  "Y" ""  ""  "X" ""  ""  "" "X" ""  ""  ""  ""  "Y"
""  "" ""  "Y" ""  "" ""  "Y" ""  "" ""  "Y" ""  ""  ""  "Y" ""  "" ""  "Y" ""  ""  ""  "Y"
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
""  "" ""  ""  ""  "" ""  ""  ""  "" ""  ""  ""  ""  ""  ""  ""  "" ""  ""  ""  ""  ""  "" 
end

This is the data. With kind regards.