AT_BANNER([DESCRIPTIVES procedure])

AT_SETUP([DESCRIPTIVES basics])
AT_DATA([descriptives.sps],
  [title 'Test DESCRIPTIVES procedure'.

data list / V0 to V16 1-17.
begin data.
12128989012389023
34128080123890128
56127781237893217
78127378123793112
90913781237892318
37978547878935789
52878237892378279
12377912789378932
26787654347894348
29137178947891888
end data.

descript all/stat=all/format=serial.
])
AT_CHECK([pspp -O format=csv descriptives.sps], [0],
  [Title: Test DESCRIPTIVES procedure

Table: Reading 1 record from INLINE.
Variable,Record,Columns,Format
V0,1,1-  1,F1.0
V1,1,2-  2,F1.0
V2,1,3-  3,F1.0
V3,1,4-  4,F1.0
V4,1,5-  5,F1.0
V5,1,6-  6,F1.0
V6,1,7-  7,F1.0
V7,1,8-  8,F1.0
V8,1,9-  9,F1.0
V9,1,10- 10,F1.0
V10,1,11- 11,F1.0
V11,1,12- 12,F1.0
V12,1,13- 13,F1.0
V13,1,14- 14,F1.0
V14,1,15- 15,F1.0
V15,1,16- 16,F1.0
V16,1,17- 17,F1.0

Table: Valid cases = 10; cases with missing value(s) = 0.
Variable,Valid N,Missing N,Mean,S.E. Mean,Std Dev,Variance,Kurtosis,S.E. Kurt,Skewness,S.E. Skew,Range,Minimum,Maximum,Sum
V0,10,0,3.80,.84,2.66,7.07,-.03,1.33,.89,.69,8.00,1.00,9.00,38.00
V1,10,0,4.60,.96,3.03,9.16,-1.39,1.33,-.03,.69,9.00,.00,9.00,46.00
V2,10,0,4.10,1.16,3.67,13.43,-2.02,1.33,.48,.69,8.00,1.00,9.00,41.00
V3,10,0,4.10,.87,2.77,7.66,-2.05,1.33,.42,.69,7.00,1.00,8.00,41.00
V4,10,0,7.00,.47,1.49,2.22,7.15,1.33,-2.52,.69,5.00,3.00,8.00,70.00
V5,10,0,4.90,1.03,3.25,10.54,-1.40,1.33,-.20,.69,9.00,.00,9.00,49.00
V6,10,0,5.90,.80,2.51,6.32,-.29,1.33,-.96,.69,7.00,1.00,8.00,59.00
V7,10,0,4.70,1.10,3.47,12.01,-1.99,1.33,-.16,.69,9.00,.00,9.00,47.00
V8,10,0,4.10,1.10,3.48,12.10,-1.93,1.33,.37,.69,9.00,.00,9.00,41.00
V9,10,0,4.30,.87,2.75,7.57,-.87,1.33,.73,.69,8.00,1.00,9.00,43.00
V10,10,0,5.50,.85,2.68,7.17,-1.84,1.33,-.33,.69,7.00,2.00,9.00,55.00
V11,10,0,6.50,.78,2.46,6.06,-1.28,1.33,-.89,.69,6.00,3.00,9.00,65.00
V12,10,0,7.90,.60,1.91,3.66,5.24,1.33,-2.21,.69,6.00,3.00,9.00,79.00
V13,10,0,4.30,.99,3.13,9.79,-1.25,1.33,.33,.69,9.00,.00,9.00,43.00
V14,10,0,3.60,1.01,3.20,10.27,-.96,1.33,.81,.69,9.00,.00,9.00,36.00
V15,10,0,3.70,.92,2.91,8.46,-1.35,1.33,.71,.69,7.00,1.00,8.00,37.00
V16,10,0,6.40,.91,2.88,8.27,-1.14,1.33,-.92,.69,7.00,2.00,9.00,64.00
])
AT_CLEANUP

m4_define([DESCRIPTIVES_MISSING_DATA],
  [data list notable / V1 TO V3 1-3.
mis val v1 to v3 (1).
begin data.
111
   
 1 
1 1
112
123
234
end data.
])

AT_SETUP([DESCRIPTIVES -- excluding missing data])
AT_DATA([descriptives.sps],
  [DESCRIPTIVES_MISSING_DATA
descript all/stat=all/format=serial.
])
AT_CHECK([pspp -O format=csv descriptives.sps], [0],
  [Table: Valid cases = 7; cases with missing value(s) = 6.
Variable,Valid N,Missing N,Mean,S.E. Mean,Std Dev,Variance,Kurtosis,S.E. Kurt,Skewness,S.E. Skew,Range,Minimum,Maximum,Sum
V1,1,6,2.00,.  ,.  ,.  ,.  ,.  ,.  ,.  ,.00,2.00,2.00,2.00
V2,2,5,2.50,.50,.71,.50,.  ,.  ,.  ,.  ,1.00,2.00,3.00,5.00
V3,3,4,3.00,.58,1.00,1.00,.  ,.  ,.00,1.22,2.00,2.00,4.00,9.00
])
AT_CLEANUP

AT_SETUP([DESCRIPTIVES -- including missing data])
AT_DATA([descriptives.sps],
  [DESCRIPTIVES_MISSING_DATA
descript all/stat=all/format=serial/missing=include.
])
AT_CHECK([pspp -O format=csv descriptives.sps], [0],
  [Table: Valid cases = 7; cases with missing value(s) = 3.
Variable,Valid N,Missing N,Mean,S.E. Mean,Std Dev,Variance,Kurtosis,S.E. Kurt,Skewness,S.E. Skew,Range,Minimum,Maximum,Sum
V1,5,2,1.20,.20,.45,.20,5.00,2.00,2.24,.91,1.00,1.00,2.00,6.00
V2,5,2,1.60,.40,.89,.80,.31,2.00,1.26,.91,2.00,1.00,3.00,8.00
V3,5,2,2.20,.58,1.30,1.70,-1.49,2.00,.54,.91,3.00,1.00,4.00,11.00
])
AT_CLEANUP

AT_SETUP([DESCRIPTIVES -- excluding missing data listwise])
AT_DATA([descriptives.sps],
  [DESCRIPTIVES_MISSING_DATA
descript all/stat=all/format=serial/missing=listwise.
])
AT_CHECK([pspp -O format=csv descriptives.sps], [0],
  [Table: Valid cases = 1; cases with missing value(s) = 6.
Variable,Valid N,Missing N,Mean,S.E. Mean,Std Dev,Variance,Kurtosis,S.E. Kurt,Skewness,S.E. Skew,Range,Minimum,Maximum,Sum
V1,1,0,2.00,.  ,.  ,.  ,.  ,.  ,.  ,.  ,.00,2.00,2.00,2.00
V2,1,0,3.00,.  ,.  ,.  ,.  ,.  ,.  ,.  ,.00,3.00,3.00,3.00
V3,1,0,4.00,.  ,.  ,.  ,.  ,.  ,.  ,.  ,.00,4.00,4.00,4.00
])
AT_CLEANUP

AT_SETUP([DESCRIPTIVES -- including missing data listwise])
AT_DATA([descriptives.sps],
  [DESCRIPTIVES_MISSING_DATA
descript all/stat=all/format=serial/missing=listwise include.
])
AT_CHECK([pspp -O format=csv descriptives.sps], [0],
  [Table: Valid cases = 4; cases with missing value(s) = 3.
Variable,Valid N,Missing N,Mean,S.E. Mean,Std Dev,Variance,Kurtosis,S.E. Kurt,Skewness,S.E. Skew,Range,Minimum,Maximum,Sum
V1,4,0,1.25,.25,.50,.25,4.00,2.62,2.00,1.01,1.00,1.00,2.00,5.00
V2,4,0,1.75,.48,.96,.92,-1.29,2.62,.85,1.01,2.00,1.00,3.00,7.00
V3,4,0,2.50,.65,1.29,1.67,-1.20,2.62,.00,1.01,3.00,1.00,4.00,10.00
])
AT_CLEANUP

AT_SETUP([DESCRIPTIVES bug calculating mean only])
AT_DATA([descriptives.sps],
  [SET FORMAT F8.3.

data list notable / X 1.
begin data.
0
1
2
3
4
5
end data.

descript all/stat=mean.
])
AT_CHECK([pspp -O format=csv descriptives.sps], [0],
  [Table: Valid cases = 6; cases with missing value(s) = 0.
Variable,N,Mean
X,6,2.500
])
AT_CLEANUP

dnl Git history shows that this was probably a bug in the PSPP
dnl core regarding multipass procedures, not anything specific
dnl to DESCRIPTIVES.
AT_SETUP([DESCRIPTIVES bug with TEMPORARY])
AT_DATA([descriptives.sps], [dnl
DATA LIST LIST NOTABLE /id * abc *.
BEGIN DATA.
1 3.5
2 2.0
3 2.0
4 3.5
5 3.0
6 4.0
7 5.0
END DATA.

TEMPORARY.
SELECT IF id < 7 .

DESCRIPTIVES /VAR=abc.
])
AT_CHECK([pspp -O format=csv descriptives.sps], [0], [dnl
Table: Valid cases = 6; cases with missing value(s) = 0.
Variable,N,Mean,Std Dev,Minimum,Maximum
abc,6,3.00,.84,2.00,4.00
])
AT_CLEANUP

AT_SETUP([DESCRIPTIVES -- Z scores])
AT_DATA([descriptives.sps], [dnl
DATA LIST LIST NOTABLE /a b.
BEGIN DATA.
1 50
2 60
3 70
END DATA.

DESCRIPTIVES /VAR=a b /SAVE.
LIST.
])
AT_CHECK([pspp -O format=csv descriptives.sps], [0], [dnl
Table: Mapping of variables to corresponding Z-scores.
Source,Target
a,Za
b,Zb

Table: Valid cases = 3; cases with missing value(s) = 0.
Variable,N,Mean,Std Dev,Minimum,Maximum
a,3,2.00,1.00,1.00,3.00
b,3,60.00,10.00,50.00,70.00

Table: Data List
a,b,Za,Zb
1.00,50.00,-1.00,-1.00
2.00,60.00,.00,.00
3.00,70.00,1.00,1.00
])
AT_CLEANUP

AT_SETUP([DESCRIPTIVES -- Z scores with SPLIT FILE])
AT_DATA([descriptives.sps], [dnl
DATA LIST LIST NOTABLE /group a b.
BEGIN DATA.
1 1 50
1 2 60
1 3 70
2 100 6000
2 200 7000
2 400 9000
2 500 10000
END DATA.

SPLIT FILE BY group.
DESCRIPTIVES /VAR=a b /SAVE.
LIST.
])
AT_CHECK([pspp -O format=csv descriptives.sps], [0], [dnl
Table: Mapping of variables to corresponding Z-scores.
Source,Target
a,Za
b,Zb

Variable,Value,Label
group,1.00,

Table: Valid cases = 3; cases with missing value(s) = 0.
Variable,N,Mean,Std Dev,Minimum,Maximum
a,3,2.00,1.00,1.00,3.00
b,3,60.00,10.00,50.00,70.00

Variable,Value,Label
group,2.00,

Table: Valid cases = 4; cases with missing value(s) = 0.
Variable,N,Mean,Std Dev,Minimum,Maximum
a,4,300.00,182.57,100.00,500.00
b,4,8000.00,1825.74,6000.00,10000.00

Variable,Value,Label
group,1.00,

Table: Data List
group,a,b,Za,Zb
1.00,1.00,50.00,-1.00,-1.00
1.00,2.00,60.00,.00,.00
1.00,3.00,70.00,1.00,1.00

Variable,Value,Label
group,2.00,

Table: Data List
group,a,b,Za,Zb
2.00,100.00,6000.00,-1.10,-1.10
2.00,200.00,7000.00,-.55,-.55
2.00,400.00,9000.00,.55,.55
2.00,500.00,10000.00,1.10,1.10
])
AT_CLEANUP