itsp

census2.dta census2b.dta census2c.dta		ch2.0.do:29
census2.dta census2b.dta census2c.dta		ch2.0.do:28
	→	census2c.dta	↘
		ch3.01.do:1
		ch2.0.do:4		census2c.dta
		ch2.0.do:31
		ch2.0.do:155
		ch11.01.do:487

```
census2c.dta open
file:data:dta
```

All properties
key	content
N	21
datasignature	21:7(49180):3233925751:2462268840
date	Wed Sep 23 21:31:41 EST 2015
lastmodified	1443007901000
variables	7

Variable Graph Type N Descriptives Label

[+] divr
@census2c.dta

identifier
(double)

21
(21)

Divorces, '000

All properties
key	content
N	21
N_unique	21
class	identifier
example0	13.488
histh	.03501986, .01273449, .00955087, .00955087
histw	9.6207504, 24.578251, 39.535751, 54.493252
label	Divorces, '000
max	61.972
mean	22.179
min	2.142
sd	19.311
type	double

file # command

ch2.0.do:

76 [+]

summarize medage marr divr if region==1

77 [+]

summarize medage marr divr if region==2

80 [+]

by region: summarize medage marr divr

85 [+]

bysort region popsize: summarize medage marr divr

file # command

ch2.0.do:

12 [+]

rename divorce divr

22 [+]

label var divr "Divorces, '000"

26 [+]

keep state region pop popurb medage marr divr

114 [+]

generate netmarr2x = cond(marr/divr > 2.0, 1, 2)

115 [+]

label define netmarr2xc 1 "marr > 2 divr" 2 "marr <= 2 divr"

Script Output


divr:  Divorces, '000                           Number of Observations
---------------------                       ------------------------------
                                            Total   Integers   Nonintegers
|  #                         Negative           -         -          -
|  #                         Zero               -         -          -
|  #                         Positive          21         -         21
|  #                                        -----     -----      -----
|  #                         Total             21         -         21
|  #   #   #   #   #         Missing            -
+----------------------                     -----
2.142            61.972                        21
  (21 unique values)

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
        divr |        21    22.17948    19.31113      2.142     61.972
@mean    22.179
@sd    19.311
@min     2.142
@max    61.972
@example0 13.488
@histh .03501986, .01273449, .00955087, .00955087
@histw 9.6207504, 24.578251, 39.535751, 54.493252
@type double
@label Divorces, '000
@class identifier
@N_unique 21
@N 21

[+] marr
@census2c.dta

identifier
(double)

21
(21)

Marriages, '000

All properties
key	content
N	21
N_unique	21
class	identifier
example0	26.048
histh	.01504206, .0068373, .00410238, .00273492
histw	22.637501, 57.460499, 92.283501, 127.1065
label	Marriages, '000
max	144.518
mean	46.169
min	5.226
sd	39.906
type	double

file # command

ch2.0.do:

76 [+]

summarize medage marr divr if region==1

77 [+]

summarize medage marr divr if region==2

80 [+]

by region: summarize medage marr divr

85 [+]

bysort region popsize: summarize medage marr divr

file # command

ch2.0.do:

11 [+]

rename marriage marr

21 [+]

label var marr "Marriages, '000"

26 [+]

keep state region pop popurb medage marr divr

114 [+]

generate netmarr2x = cond(marr/divr > 2.0, 1, 2)

115 [+]

label define netmarr2xc 1 "marr > 2 divr" 2 "marr <= 2 divr"

Script Output


marr:  Marriages, '000                          Number of Observations
----------------------                      ------------------------------
                                            Total   Integers   Nonintegers
|  #                         Negative           -         -          -
|  #                         Zero               -         -          -
|  #                         Positive          21         -         21
|  #   #                                    -----     -----      -----
|  #   #                     Total             21         -         21
|  #   #   .   #   .         Missing            -
+----------------------                     -----
5.226           144.518                        21
  (21 unique values)

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
        marr |        21    46.16905     39.9059      5.226    144.518
@mean    46.169
@sd    39.906
@min     5.226
@max   144.518
@example0 26.048
@histh .01504206, .0068373, .00410238, .00273492
@histw 22.637501, 57.460499, 92.283501, 127.1065
@type double
@label Marriages, '000
@class identifier
@N_unique 21
@N 21

[+] medage
@census2c.dta

category
(float)

21
(17)

"28.29999923706055", "28.79999923..20000076293945"

Median age, years

All properties
key	content
N	21
N_unique	17
class	category
freq	1, 1, 1, 2, 2, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1
label	Median age, years
max	32.200
mean	30.257
min	28.300
names	"28.29999923706055", "28.79999923706055", "28.89999961853027", "29.20000076293945", "29.39999961853027", "29.70000076293945", "29.89999961853027", "30", "30.10000038146973", "30.39999961853027", "30.89999961853027", "31.20000076293945", "31.79999923706055", "31.89999961853027", "32", "32.09999847412109", "32.20000076293945"
sd	1.200
type	float
values	28.299999, 28.799999, 28.9, 29.200001, 29.4, 29.700001, 29.9, 30, 30.1, 30.4, 30.9, 31.200001, 31.799999, 31.9, 32, 32.099998, 32.200001

file # command

ch2.0.do:

57 [+]

summarize medage if pop > 5000

76 [+]

summarize medage marr divr if region==1

77 [+]

summarize medage marr divr if region==2

80 [+]

by region: summarize medage marr divr

82 [+]

tabstat medage , by(region) statistics(N mean sd min max)

85 [+]

bysort region popsize: summarize medage marr divr

100 [+]

bysort popsize: summarize medage

117 [+]

tabstat pop medage , by(netmarr2x)

ch3.01.do:

5 [+]

list state pop medage if medage >= 32

28 [+]

list state medage pop if newengland , sep(0)

30 [+]

list state medage pop if inrange(pop, 5000, 9999) , sep(0)

39 [+]

tabstat medage , stat(n mean min max) by(medagequart)

file # command

ch2.0.do:

19 [+]

label var medage "Median age, years"

26 [+]

keep state region pop popurb medage marr divr

52 [+]

generate medagel = medage if pop > 5000

119 [+]

generate medagebrack = recode(medage, 28, 29, 30, 31, 32, 33)

ch3.01.do:

32 [+]

generate medagebrack = recode(medage, 29, 30, 31, 32, 33)

35 [+]

generate medagebracknr = irecode(medage, 29, 30, 31, 32, 33)

Script Output


medage:  Median age, years                      Number of Observations
--------------------------                  ------------------------------
                                            Total   Integers   Nonintegers
|          #                 Negative           -         -          -
|      #   #       #         Zero               -         -          -
|      #   #       #         Positive          21         2         19
|  #   #   #       #                        -----     -----      -----
|  #   #   #   #   #         Total             21         2         19
|  #   #   #   #   #         Missing            -
+----------------------                     -----
28.3               32.2                        21
  (17 unique values)

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
      medage |        21    30.25714    1.199821       28.3       32.2
@mean    30.257
@sd     1.200
@min    28.300
@max    32.200
@values 28.299999, 28.799999, 28.9, 29.200001, 29.4, 29.700001, 29.9, 30, 30.1, 30.4, 30.9, 31.200001, 31.799999, 31.9, 32, 32.099998, 32.200001
@names "28.29999923706055", "28.79999923706055", "28.89999961853027", "29.20000076293945", "29.39999961853027", "29.70000076293945", "29.89999961853027", "30", "30.10000038146973", "30.39999961853027", "30.89999961853027", "31.20000076293945", "31.79999923706055", "31.89999961853027", "32", "32.09999847412109", "32.20000076293945"
@freq 1, 1, 1, 2, 2, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1
@type float
@label Median age, years
@class category
@N_unique 17
@N 21

[+] pop
@census2c.dta

identifier
(double)

21
(21)

1980 Population, '000

All properties
key	content
N	21
N_unique	21
class	identifier
example0	3107.576
histh	.00013409, .0000447, .0000447, .00001117
histw	2642.283, 6903.937, 11165.591, 15427.245
label	1980 Population, '000
max	17558.072
mean	5142.903
min	511.456
sd	4675.152
type	double

file # command

ch2.0.do:

43 [+]

list region state pop , sepby(region)

46 [+]

list state region pop in 1/5

47 [+]

list state region pop in -5/l

50 [+]

list state region pop in 1/5

54 [+]

list state region pop medagel , sep(0)

57 [+]

summarize medage if pop > 5000

63 [+]

list state pop smallpop largepop , sep(0)

95 [+]

describe pop smallpop largepop popsize urbanized

117 [+]

tabstat pop medage , by(netmarr2x)

129 [+]

list region state pop totpop , sepby(region)

134 [+]

list region state pop meanpop , sepby(region)

141 [+]

list region popsize state pop meanpop2 , sepby(region popsize)

156 [+]

summarize pop

159 [+]

mean pop popurb

ch3.01.do:

2 [+]

summarize pop*

4 [+]

list state pop in 1/5

5 [+]

list state pop medage if medage >= 32

20 [+]

tabstat pop , stat(mean min max) by(size)

28 [+]

list state medage pop if newengland , sep(0)

30 [+]

list state medage pop if inrange(pop, 5000, 9999) , sep(0)

45 [+]

list state pop avgpop popratio if size == 0 , sep(0)

file # command

ch2.0.do:

17 [+]

label var pop "1980 Population, '000"

26 [+]

keep state region pop popurb medage marr divr

36 [+]

generate urbanized = popurb / pop

52 [+]

generate medagel = medage if pop > 5000

60 [+]

replace smallpop = 1 if pop <= 5000 & !missing(pop)

62 [+]

replace largepop = 1 if pop > 5000 & !missing(pop)

67 [+]

generate smallpop = (pop <= 5000)

68 [+]

generate largepop = (pop > 5000)

71 [+]

generate smallpop = (pop <= 5000) if !missing(pop)

72 [+]

generate largepop = (pop > 5000) if !missing(pop)

92 [+]

label variable smallpop "States with <= 5 million pop, 1980"

93 [+]

label variable largepop "States with > 5 million pop, 1980"

128 [+]

by region: generate totpop = sum(pop)

133 [+]

by region: egen meanpop = mean(pop)

140 [+]

bysort region popsize: egen meanpop2 = mean(pop)

ch3.01.do:

17 [+]

generate size=irecode(pop, 1000, 4000, 8000, 20000)

42 [+]

bysort size: egen avgpop = mean(pop)

43 [+]

generate popratio = 100 * pop / avgpop

Script Output


pop:  1980 Population, '000                     Number of Observations
---------------------------                 ------------------------------
                                            Total   Integers   Nonintegers
|  #                         Negative           -         -          -
|  #                         Zero               -         -          -
|  #                         Positive          21         -         21
|  #   #                                    -----     -----      -----
|  #   #                     Total             21         -         21
|  #   #   #   #   .         Missing            -
+----------------------                     -----
511.456        17558.07                        21
  (21 unique values)

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
         pop |        21    5142.903    4675.152    511.456   17558.07
@mean  5142.903
@sd  4675.152
@min   511.456
@max 17558.072
@example0 3107.576
@histh .00013409, .0000447, .0000447, .00001117
@histw 2642.283, 6903.937, 11165.591, 15427.245
@type double
@label 1980 Population, '000
@class identifier
@N_unique 21
@N 21

[+] popurb
@census2c.dta

identifier
(double)

21
(21)

1980 Urban population, '000

All properties
key	content
N	21
N_unique	21
class	identifier
example0	2449.774
histh	.00018159, .00003891, .00003891, .00001297
histw	2008.4016, 5679.7349, 9351.0684, 13022.401
label	1980 Urban population, '000
max	14858.068
mean	3829.776
min	172.735
sd	3851.458
type	double

file # command

ch2.0.do:

159 [+]

mean pop popurb

ch3.01.do:

2 [+]

summarize pop*

file # command

ch2.0.do:

10 [+]

rename popurban popurb

18 [+]

label var popurb "1980 Urban population, '000"

26 [+]

keep state region pop popurb medage marr divr

36 [+]

generate urbanized = popurb / pop

Script Output


popurb:  1980 Urban population, '000            Number of Observations
------------------------------------        ------------------------------
                                            Total   Integers   Nonintegers
|  #                         Negative           -         -          -
|  #                         Zero               -         -          -
|  #                         Positive          21         -         21
|  #                                        -----     -----      -----
|  #       #                 Total             21         -         21
|  #   #   #   .   .         Missing            -
+----------------------                     -----
172.735        14858.07                        21
  (21 unique values)

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
      popurb |        21    3829.776    3851.458    172.735   14858.07
@mean  3829.776
@sd  3851.458
@min   172.735
@max 14858.068
@example0 2449.774
@histh .00018159, .00003891, .00003891, .00001297
@histw 2008.4016, 5679.7349, 9351.0684, 13022.401
@type double
@label 1980 Urban population, '000
@class identifier
@N_unique 21
@N 21

[+] region
@census2c.dta

dummy
(byte)

21
(2)

"NE", "N Cntrl"

Census region

All properties
key	content
N	21
N_unique	2
class	dummy
freq	9, 12
label	Census region
max	2
mean	1.571
min	1
names	"NE", "N Cntrl"
sd	0.507
type	byte
values	1, 2

file # command

ch2.0.do:

43 [+]

list region state pop , sepby(region)

46 [+]

list state region pop in 1/5

47 [+]

list state region pop in -5/l

50 [+]

list state region pop in 1/5

54 [+]

list state region pop medagel , sep(0)

76 [+]

summarize medage marr divr if region==1

77 [+]

summarize medage marr divr if region==2

80 [+]

by region: summarize medage marr divr

82 [+]

tabstat medage , by(region) statistics(N mean sd min max)

85 [+]

bysort region popsize: summarize medage marr divr

87 [+]

describe region

129 [+]

list region state pop totpop , sepby(region)

131 [+]

by region: list region totpop if _n == _N

134 [+]

list region state pop meanpop , sepby(region)

141 [+]

list region popsize state pop meanpop2 , sepby(region popsize)

file # command

ch2.0.do:

5 [+]

keep if region < 3 // =="N Cntrl" | region == "NE"

26 [+]

keep state region pop popurb medage marr divr

128 [+]

by region: generate totpop = sum(pop)

133 [+]

by region: egen meanpop = mean(pop)

140 [+]

bysort region popsize: egen meanpop2 = mean(pop)

ch11.01.do:

488 [+]

generate z_factor = 10 * region

Script Output


region:  Census region                          Number of Observations
----------------------                      ------------------------------
                                            Total   Integers   Nonintegers
|      #                     Negative           -         -          -
|      #                     Zero               -         -          -
|  #   #                     Positive          21        21          -
|  #   #                                    -----     -----      -----
|  #   #                     Total             21        21          -
|  #   #                     Missing            -
+----------------------                     -----
1                     2                        21
   (2 unique values)

      region is labeled and all values are documented in the label.

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
      region |        21    1.571429    .5070926          1          2
@mean     1.571
@sd     0.507
@min         1
@max         2
@values 1, 2
@names "NE", "N Cntrl"
@freq 9, 12
@type byte
@label Census region
@class dummy
@N_unique 2
@N 21

[+] state
@census2c.dta

identifier
(str13)

21
(21)

State

All properties
key	content
N	21
N_unique	21
class	identifier
example0	Connecticut
freq	1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1
label	State
type	str13
values	"Connecticut", "Illinois", "Indiana", "Iowa", "Kansas", "Maine", "Massachusetts", "Michigan", "Minnesota", "Missouri", "N. Dakota", "Nebraska", "New Hampshire", "New Jersey", "New York", "Ohio", "Pennsylvania", "Rhode Island", "S. Dakota", "Vermont", "Wisconsin"

file # command

ch2.0.do:

43 [+]

list region state pop , sepby(region)

46 [+]

list state region pop in 1/5

47 [+]

list state region pop in -5/l

50 [+]

list state region pop in 1/5

54 [+]

list state region pop medagel , sep(0)

63 [+]

list state pop smallpop largepop , sep(0)

129 [+]

list region state pop totpop , sepby(region)

134 [+]

list region state pop meanpop , sepby(region)

141 [+]

list region popsize state pop meanpop2 , sepby(region popsize)

ch3.01.do:

4 [+]

list state pop in 1/5

5 [+]

list state pop medage if medage >= 32

8 [+]

describe state stateid

9 [+]

list state stateid in 1/5

28 [+]

list state medage pop if newengland , sep(0)

30 [+]

list state medage pop if inrange(pop, 5000, 9999) , sep(0)

45 [+]

list state pop avgpop popratio if size == 0 , sep(0)

file # command

ch2.0.do:

16 [+]

label var state "State"

26 [+]

keep state region pop popurb medage marr divr

ch3.01.do:

7 [+]

encode state , generate(stateid)

25 [+]

generate byte newengland = inlist(state, "Connecticut", "Maine", /// "Massachusetts", "New Hampshire", "Rhode Island", "Vermont")

Script Output

@freq 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1
@values "Connecticut", "Illinois", "Indiana", "Iowa", "Kansas", "Maine", "Massachusetts", "Michigan", "Minnesota", "Missouri", "N. Dakota", "Nebraska", "New Hampshire", "New Jersey", "New York", "Ohio", "Pennsylvania", "Rhode Island", "S. Dakota", "Vermont", "Wisconsin"
@example0 Connecticut
@type str13
@label State
@class identifier
@N_unique 21
@N 21

Content



>  * A do file to run the standard stats for a whole data set. 
>  *
>  * Note that you must delete the files in the derived directory
>  * for changes to be reflected in the output.
>  *
>  * @version 0.1
> */
(1980 Census data for NE and NC states)

Contains data from /Users/mas/Dropbox/Stata_conference_2015/itsp/census2c.dta
  obs:            21                          1980 Census data for NE and NC states
 vars:             7                          30 Jan 2009 14:59
 size:         1,050                          
Sorted by:  
@N 21
@variables 7
  21:7(49180):3233925751:2462268840
@datasignature 21:7(49180):3233925751:2462268840
panel variable not set; use xtset varname ...
. 
  2. 
  3. qui {
  4. local category_cutoff = 30
  5. 
  6. local unique = ""
  7. local total = ""
  8. local class = ""
  9. 
 10. local label : variable label `var' 
 11. 
 12. 
 13. if ( !_rc ) {
 14.     // we now it is a string
 15.     capture tab `var', matcell( freq )
 16.     if ( !_rc ) {
 17.     
 18.         local unique = r(r)
 19. 
 20.         forvalues i=1/`unique' {
 21.             if ( `i' == 1 ) {
 22.                 noi di "@freq " _continue
 23.             }
 24.             noi di freq[`i',1] _continue
 25.             if ( `i' == `unique' ) {
 26.                 noi di ""
 27.             }
 28.             else {
 29.                 noi di ", " _continue
 30.             }
 31.         }
 32. 
 33.         local i = 1
 34.         foreach l of local levels {
 35.             if ( `i' == 1 ) {
 36.                 noi di "@values " _continue
 37.             }
 38.             noi di `""`l'""' _continue
 39.             if ( `i' == `unique' ) {
 40.                 noi di ""
 41.             }
 42.             else {
 43.                 noi di ", " _continue
 44.             }
 45.             local i = `i' + 1
 46.         }
 47.         }
 48.         
 49.             local class = "empty"
 50.         }
 51.         else if ( `unique' == 1 ) {
 52.             local class = "constant"
 53.         }
 54.         else if ( `unique' == 2 ) {
 55.             local class = "dummy"
 56.         }
 57.         else if ( `unique' < `category_cutoff' & `unique' < `total' ) {
 58.             local class = "category"
 59.         }
 60.         else if (`unique' == `total') {
 61.             local class = "identifier"
 62.         } 
 63.         else {
 64.             local class = "string"
 65.         }        
 66.     }
 67.     else {
 68.         // lots of observations, not sure what to do yet
 69.     }
 70. }
 71. else {
 72.     // else assume it is numeric
 73. 
 74.     local unique = r(N_unique)
 75. 
 76.         local cat = "YES"
 77.     }
 78. 
 79.         if ( `total' == 0 ) {
 80.             local class = "empty"
 81.         }
 82.         else if ( `unique' == 1 ) {
 83.             local class = "constant"
 84.         }
 85.         else if ( `unique' == 2 ) {
 86.             local class = "dummy"
 87.         }
 88.         else if ( `unique' < `category_cutoff' & `unique' < `total' ) {
 89.             capture confirm string variable `var'
 90.             if ( !_rc ) {
 91.                 local class = "other"
 92.             } 
 93.             else {
 94.                 local class = "category"
 95.             }
 96.         }
 97.         else if (`r(N_unique)' == `r(N)') {
 98.             local class = "identifier"
 99.         }
100.     }
101. 
102.     local min = r(min)
103.     local max = r(max)
104.     local nobs = r(N)
105.     
106.         noi di "@mean " %9.0f r(mean)
107.     } 
108.     else {
109.         noi di "@mean " %9.3f r(mean)
110.     }
111.     noi di "@sd " %9.3f `r(sd)'
112.     // noi di "@skewness " %9.3f `r(skewness)'
113.       noi di "@min " %9.3f `r(min)'
114.       noi di "@max " %9.3f `r(max)'
115.       // noi di "@p50 " %9.3f `r(p50)'
116.     else {
117.       noi di "@min " %9.0f `r(min)'
118.       noi di "@max " %9.0f `r(max)'
119.       // noi di "@p50 " %9.0f `r(p50)'
120. }
121. 
122.     noi di "@values " `var'[1]
123. }
124. else if ( "`class'" == "category" | "`class'" == "dummy" ) {
125.     cap noi {
126.         if ( "`isstr'" != "YES" ) {
127.             cap tab `var', matcell( freq ) matrow( name )
128.             if ( _rc != 0 | ("`r(r)'" != "`unique'") ) {
129.                 local class = "other"
130.                 local unique = r(r)
131.             }
132.             else {
133.                 forvalues i=1/`unique' {
134.                     if ( `i' == 1 ) {
135.                         noi di "@values " _continue
136.                     }
137.                     noi di name[`i',1] _continue
138.                     if ( `i' == `unique' ) {
139.                         noi di ""
140.                     }
141.                     else {
142.                         noi di ", " _continue
143.                     }
144.                 }
145.                 forvalues i=1/`unique' {
146.                     if ( `i' == 1 ) {
147.                         noi di "@names " _continue
148.                     }
149.                     local val = name[`i',1]
150.                     local lab :label (`var') `val'
151.                     noi di `""`lab'""' _continue
152.                     if ( `i' == `unique' ) {
153.                         noi di ""
154.                     }
155.                     else {
156.                         noi di ", " _continue
157.                     }
158.                 }
159.                 forvalues i=1/`unique' {
160.                     if ( `i' == 1 ) {
161.                         noi di "@freq " _continue
162.                     }
163.                     noi di freq[`i',1] _continue
164.                     if ( `i' == `unique' ) {
165.                         noi di ""
166.                     }
167.                     else {
168.                         noi di ", " _continue
169.                     }
170.                 }
171.             }
172.         }
173.     }
174. }
175. else {
176.     noi di "@example0 " `var'[1]
177. }
178. 
179. cap noi {
180.     tempvar h w
181.     twoway__histogram_gen `var', gen( `h' `w' )
182.     forvalues i=1/`=r(n_x)' {
183.         if ( `i' == 1 ) {
184.             noi di "@histh " _continue
185.         }
186.         noi di `h'[`i'] _continue
187.         if ( `i' == `=r(n_x)' ) {
188.             noi di ""
189.         }
190.         else {
191.             noi di ", " _continue
192.         }
193.     }
194.     forvalues i=1/`=r(n_x)' {
195.         if ( `i' == 1 ) {
196.             noi di "@histw " _continue
197.         }
198.         noi di `w'[`i'] _continue
199.         if ( `i' == `=r(n_x)' ) {
200.             noi di ""
201.         }
202.         else {
203.             noi di ", " _continue
204.         }
205.     }
206.     }
207. }
208. 
209. noi di "@label `label'"
210. noi di "@class `class'"
211. noi di "@N_unique `unique'"
212. noi di "@N `total'"
213. 
214. noi di "_@NOTES"
215. 
216. 
217. }
218.

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    census census dta dta

File census2c.dta

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