inst/tests/QTables.R

In NumbersInternational/flipTables: Package for handling tables and related objects

## Qtables for testing

####################################################################################################
## Five dimensional: pick any grid x number grid, multiple statistics
q5 <- structure(c(1, 0.9375, 0.923547400611621, 0.0033112582781457,
0, 0.00611620795107034, 2.41721854304636, 2.375, 2.33639143730887,
0.149006622516556, 1, 0.146788990825688, 0.794701986754967, 0.875,
0.764525993883792, 2.98344370860927, 4.14583333333333, 2.89296636085627,
1.77814569536424, 2.9375, 1.74006116207951, 2.70529801324503,
2.9375, 2.64220183486239, 15.9503311258278, 18.625, 15.8012232415902,
0.5, 0.96, 0.923547400611621, 1, 0, 0.00611620795107034, 5.5,
2.36, 2.33639143730887, 0, 0.168, 0.146788990825688, 0, 1, 0.764525993883792,
0.5, 3.364, 2.89296636085627, 1, 1.84, 1.74006116207951, 1, 3.044,
2.64220183486239, 11, 16.832, 15.8012232415902, 0, 0.244623027395041,
0.266128140495266, 0.0575435337648436, 0, 0.0780861484322752,
1.03979052256587, 1.14157412784352, 1.12554954797962, 0.356686029364813,
0, 0.354437809580216, 0.40458962917493, 0.334218682391596, 0.42494496767139,
1.44778123122884, 1.39892942856289, 1.50790740166423, 0.807226006691074,
0.976451456452655, 0.800508271775028, 1.13062403487421, 1.079918239616,
1.14733301667923, 4.27239262713802, 4.3202886034409, 4.34835823708049,
0.707106781186548, 0.196352277469526, 0.266128140495266, 0, 0,
0.0780861484322752, 3.53553390593274, 1.03667680362817, 1.12554954797962,
0, 0.374616269531358, 0.354437809580216, 0, 0, 0.42494496767139,
0.707106781186548, 1.22863426969733, 1.50790740166423, 0, 0.820422067888176,
0.800508271775028, 0, 0.962167900250831, 1.14733301667923, 2.82842712474619,
3.99344040459605, 4.34835823708049, 327, 327, 327, 327, 327,
327, 327, 327, 327, 327, 327, 327, 327, 327, 327, 327, 327, 327,
327, 327, 327, 327, 327, 327, 327, 327, 327, 327, 327, 327, 327,
327, 327, 327, 327, 327, 327, 327, 327, 327, 327, 327, 327, 327,
327, 327, 327, 327, 327, 327, 327, 327, 327, 327), .Dim = c(3L,
3L, 3L, 2L, 3L), .Dimnames = list(c("Zebra", "Llama", "SUM"),
    c("Traditional", "Weight-conscious", "SUM"), c("Coke", "Diet Coke",
    "NET"), c("Traditional", "Weight-conscious"), c("Average",
    "Standard Deviation", "Sample Size")), name = "number grid by PickAnyGrid", questions = c("number grid",
"PickAnyGrid [Colas edited]"))

####################################################################################################
## Four dimensional table, pick any grid x multi cat with multiple statistics
q4.ms <- structure(c(100, 22.2222222222222, 100, 0, 77.7777777777778,
100, 84.375, 15.625, 100, 3.125, 78.125, 100, 90, 16.6666666666667,
100, 0, 76.6666666666667, 100, 96.2962962962963, 11.1111111111111,
100, 0, 85.1851851851852, 100, 94.2028985507246, 14.4927536231884,
100, 1.44927536231884, 72.463768115942, 100, 90, 17.5, 100, 0,
80, 100, 91.304347826087, 17.3913043478261, 100, 0, 78.2608695652174,
100, 89.4736842105263, 5.26315789473684, 100, 0, 78.9473684210526,
100, 92.8571428571429, 21.4285714285714, 100, 0, 78.5714285714286,
100, 92.0689655172414, 14.8275862068966, 100, 0.689655172413793,
78.2758620689655, 100, 9, 9, 9, 9, 9, 9, 32, 32, 32, 32, 32,
32, 30, 30, 30, 30, 30, 30, 54, 54, 54, 54, 54, 54, 69, 69, 69,
69, 69, 69, 40, 40, 40, 40, 40, 40, 23, 23, 23, 23, 23, 23, 19,
19, 19, 19, 19, 19, 14, 14, 14, 14, 14, 14, 290, 290, 290, 290,
290, 290, 267, 43, 290, 2, 227, 290, 267, 43, 290, 2, 227, 290,
267, 43, 290, 2, 227, 290, 267, 43, 290, 2, 227, 290, 267, 43,
290, 2, 227, 290, 267, 43, 290, 2, 227, 290, 267, 43, 290, 2,
227, 290, 267, 43, 290, 2, 227, 290, 267, 43, 290, 2, 227, 290,
267, 43, 290, 2, 227, 290), .Dim = c(3L, 2L, 10L, 3L), .Dimnames = list(
    c("Coke", "Diet Coke", "NET"), c("Traditional", "Weight-conscious"
    ), c("Less than $15,000", "$15,001 to $30,000", "$30,001 to $45,000",
    "$45,001 to $60,000", "$60,001 to $90,000", "$90,001 to $120,000",
    "$120,001 to $150,000", "$150,001 to $200,000", "$200,001 or more",
    "NET"), c("Column %", "Column Sample Size", "Row Sample Size"
    )), name = "PickAnyGrid by Income", questions = c("PickAnyGrid",
                                                      "Income [Colas edited]"))

##########################################################################################
## Four dimensional Qtable numeric grid x cat. grid only one statistic
q4.os <- structure(c(NaN, 0.830769230769231, 0.934426229508197, NaN, 0.0153846153846154,
0, NaN, 2.35384615384615, 2.34426229508197, NaN, 0.138461538461538,
0.229508196721311, NaN, 0.723076923076923, 0.754098360655738,
NaN, 2.70769230769231, 2.80327868852459, NaN, 1.67692307692308,
1.9344262295082, NaN, 2.58461538461538, 2.44262295081967, NaN,
15.4923076923077, 15.6065573770492, NaN, 0.955555555555556, 0.9,
NaN, 0, 0, NaN, 2.22222222222222, 2.6, NaN, 0.177777777777778,
0.3, NaN, 0.866666666666667, 0.9, NaN, 2.97777777777778, 4, NaN,
1.91111111111111, 2, NaN, 2.97777777777778, 2.6, NaN, 16.1555555555556,
17.2, NaN, 0.956521739130435, 1, NaN, 0, 0, NaN, 2.41304347826087,
2, NaN, 0.173913043478261, 0.111111111111111, NaN, 0.760869565217391,
0.888888888888889, NaN, 2.89130434782609, 2.88888888888889, NaN,
1.82608695652174, 1.55555555555556, NaN, 2.54347826086957, 3.33333333333333,
NaN, 15.8913043478261, 15.8888888888889, 0.928571428571429, 0.929824561403509,
1, 0, 0, 0, 2.14285714285714, 2.17543859649123, 1.85714285714286,
0.142857142857143, 0.157894736842105, 0.285714285714286, 0.785714285714286,
0.789473684210526, 0.714285714285714, 2.60714285714286, 2.96491228070175,
3.42857142857143, 1.71428571428571, 1.64912280701754, 1.85714285714286,
2.28571428571429, 2.75438596491228, 2.42857142857143, 14.5357142857143,
15.8245614035088, 15.2857142857143, 0.878787878787879, 0.903225806451613,
0.933333333333333, 0, 0, 0, 2.42424242424242, 2.32258064516129,
2.53333333333333, 0.0303030303030303, 0.0645161290322581, 0.266666666666667,
0.727272727272727, 0.709677419354839, 0.8, 2.3030303030303, 2.80645161290323,
3, 1.60606060606061, 1.51612903225806, 2.06666666666667, 2.45454545454545,
2.25806451612903, 2.6, 14.9090909090909, 14.9354838709677, 16.1333333333333,
0.909090909090909, 0.947368421052632, 0.923076923076923, 0, 0,
0, 2.12727272727273, 2.21052631578947, 2.30769230769231, 0.0909090909090909,
0.157894736842105, 0.153846153846154, 0.727272727272727, 0.789473684210526,
0.692307692307692, 2.78181818181818, 2.92105263157895, 2.92307692307692,
1.65454545454545, 1.73684210526316, 1.69230769230769, 2.58181818181818,
2.89473684210526, 2.69230769230769, 15.1636363636364, 16.1052631578947,
16.0769230769231, 0.918918918918919, 1, 0.863636363636364, 0.0135135135135135,
0, 0, 2.28378378378378, 2.6, 2.45454545454545, 0.162162162162162,
0.05, 0.227272727272727, 0.77027027027027, 0.75, 0.818181818181818,
2.90540540540541, 3, 3.40909090909091, 1.72972972972973, 1.7,
1.59090909090909, 2.64864864864865, 2.45, 2.86363636363636, 15.8378378378378,
16.15, 17.1363636363636, 1, 1, 0.894736842105263, 0, 0, 0, 2.525,
2.63636363636364, 2.57894736842105, 0.1, 0, 0, 0.85, 0.727272727272727,
0.736842105263158, 3.325, 3.36363636363636, 2.52631578947368,
1.675, 1.81818181818182, 1.47368421052632, 2.725, 2.27272727272727,
2.63157894736842, 16.35, 16.3636363636364, 14.3684210526316,
0.917525773195876, 0.928571428571429, 0.923976608187134, 0.0103092783505155,
0.0714285714285714, 0.0116959064327485, 2.44329896907217, 2.78571428571429,
2.29824561403509, 0.22680412371134, 0.357142857142857, 0.0994152046783626,
0.752577319587629, 0.642857142857143, 0.754385964912281, 3.05154639175258,
2.78571428571429, 2.80116959064327, 1.87628865979381, 2.07142857142857,
1.68421052631579, 2.80412371134021, 2.42857142857143, 2.66081871345029,
16.5773195876289, 15.8571428571429, 15.7426900584795, 0.923547400611621,
0.923547400611621, 0.923547400611621, 0.00611620795107034, 0.00611620795107034,
0.00611620795107034, 2.33639143730887, 2.33639143730887, 2.33639143730887,
0.146788990825688, 0.146788990825688, 0.146788990825688, 0.764525993883792,
0.764525993883792, 0.764525993883792, 2.89296636085627, 2.89296636085627,
2.89296636085627, 1.74006116207951, 1.74006116207951, 1.74006116207951,
2.64220183486239, 2.64220183486239, 2.64220183486239, 15.8012232415902,
15.8012232415902, 15.8012232415902), .Dim = c(3L, 3L, 3L, 10L
), statistic = "Average", .Dimnames = list(c("Zebra", "Llama",
"SUM"), c("Traditional", "Weight-conscious", "SUM"), c("Colas (e.g., Coca-Cola, Pepsi Max)?",
"Sparkling mineral water", "Coffee"), c("Never", "Once or twice a year",
"Once every 3 months", "Once a month", "Once every 2 weeks",
"Once a week", "2 to 3 days a week", "4 to 5 days a week", "Every or nearly every day",
"NET")), name = "number grid by Frequency of drinking", questions = c("number grid",
                                                                      "Frequency of drinking [Colas edited]"))


####################################################################################################
## 3D number grid by number multi, one statistic

q3.os <- structure(c(0.0369289728251618, 0.131504664554675, 0.093041801801671,
0.0439694727972306, 0.0169726884306334, 0.131966726589162, 0.084091470328211,
0.146293058399148, 0.161486422480387, 0.117251620544408, -0.00630750396017069,
0.0168233494648191, 0.0397553050422523, -0.0373014560931807,
-0.0585421560181212, 0.0643755747715722, 0.0425420487399761,
0.0216918962919572, 0.053801775908342, -0.0770113571230891, -0.0555014488893757,
0.0810097525975382, -0.0302485143421316, 0.0559014927259978,
0.059570014623343, 0.0412098164128218, 0.0626705618930577), .Dim = c(3L,
3L, 3L), statistic = "Correlation", .Dimnames = list(c("Zebra",
"Llama", "SUM"), c("Traditional", "Weight-conscious", "SUM"),
    c("Colas (e.g., Coca-Cola, Pepsi Max)?", "Sparkling mineral water",
    "SUM")), name = "number grid by Number Multi", questions = c("number grid",
"Number Multi [Colas edited]"))


####################################################################################################
## 3D: categorical by pick1 multi, one statistic

q3.os2 <- structure(c(45.0549450549451, 100, 48.1481481481481, 54.9450549450549,
51.8518518518518, 100, 44, 100, 64.7058823529412, 56, 35.2941176470588,
100, 55.8333333333333, 100, 65, 44.1666666666667, 35, 100, 48.9296636085627,
100, 51.0703363914373, 51.0703363914373, 48.9296636085627, 100
), .Dim = c(3L, 2L, 4L), statistic = "Column %", .Dimnames = list(
    c("Male", "Female", "NET"), c("Pepsi", "Diet Pepsi"), c("Bottom 3",
    "Love", "Like", "NET")), name = "Gender by Pick1multi", questions = c("Gender",
"Pick1multi [Colas edited]"))


####################################################################################################
## 3D: categorical x numeric, multi stat.
q3.ms <- structure(c(7.88888888888889, 7.21875, 6.93333333333333, 7.11111111111111,
6.85507246376811, 7.05, 7.73913043478261, 7.26315789473684, 6.78571428571428,
7.10344827586207, 4.66666666666667, 3.875, 3.1, 4.24074074074074,
3.68115942028986, 3.35, 4.21739130434783, 4, 4.14285714285714,
3.81724137931035, 17.5555555555556, 17.59375, 17.2333333333333,
17.5555555555556, 17.4347826086957, 16.55, 18, 18.7894736842105,
17.6428571428571, 17.4793103448276, 9, 9, 9, 9, 9, 9, 9, 9, 9,
9, 8, 9, 8, 9, 9, 9, 9, 8, 7, 9, 25, 27, 24, 26, 25, 26, 25,
24, 24, 27, 290, 290, 290, 290, 290, 290, 290, 290, 290, 290,
290, 290, 290, 290, 290, 290, 290, 290, 290, 290, 290, 290, 290,
290, 290, 290, 290, 290, 290, 290), .Dim = c(10L, 3L, 3L), .Dimnames = list(
    c("Less than $15,000", "$15,001 to $30,000", "$30,001 to $45,000",
    "$45,001 to $60,000", "$60,001 to $90,000", "$90,001 to $120,000",
    "$120,001 to $150,000", "$150,001 to $200,000", "$200,001 or more",
    "NET"), c("Colas (e.g., Coca-Cola, Pepsi Max)?", "Sparkling mineral water",
    "SUM"), c("Average", "Maximum", "Effective Sample Size")), name = "Income by Number Multi", questions = c("Income",
"Number Multi [Colas edited]"))



####################################################################################################
## 3D: grid, multi stat
q3.ms2 <- structure(c(42, 46.40625, 45.2666666666667, 43.2777777777778,
42.2898550724638, 37.9, 43.1304347826087, 42.0526315789474, 37.5714285714286,
42.4448275862069, 22.3215142855497, 19.2267612138445, 17.0373491003682,
18.072617321665, 13.2444232984339, 11.7643529358822, 13.3937039069791,
12.2178088788935, 14.0642169281549, 15.5253578979502, 21, 21,
21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21,
21, 21, 21, 27, 32, 32, 32, 27, 32, 32, 27, 27, 37, 44.5, 49.5,
39.5, 42, 37, 42, 37, 37, 42, 60, 60, 60, 52, 52, 52, 60, 52,
52, 52, 77, 77, 77, 77, 60, 60, 60, 60, 60, 77, 41.2222222222222,
46.1180555555556, 44.8518518518519, 42.641975308642, 42.2149758454106,
37.6111111111111, 43.4227053140097, 42.2251461988304, 37.2460317460318,
41.7164750957854, 39, 33, 28, 20, 20, 25, 28, 20, 25, 25, -0.311257539269854,
1.15634776417213, 1.05992871083858, 0.115094270110035, -0.287482661005028,
-1.81491578988191, 0.485653200076029, -0.118336715223522, -1.13562094895638,
NaN, 7.4405047618499, 3.39884330864098, 3.11058014078733, 2.45937170859245,
1.594441197411, 1.86010752377383, 2.79278032221769, 2.80295759024162,
3.75882008274441, 0.911680407287864, 0.755604843839129, 0.247538938543036,
0.289177032791909, 0.908370401513562, 0.773742776385985, 0.0695368516133256,
0.627213070362492, 0.905800867224531, 0.256115237513411, NaN), .Dim = c(1L,
10L, 13L), .Dimnames = list("Number", c("Less than $15,000",
"$15,001 to $30,000", "$30,001 to $45,000", "$45,001 to $60,000",
"$60,001 to $90,000", "$90,001 to $120,000", "$120,001 to $150,000",
"$150,001 to $200,000", "$200,001 or more", "NET"), c("Average",
"Standard Deviation", "Minimum", "5th Percentile", "25th Percentile",
"Median", "75th Percentile", "95th Percentile", "Trimmed Average",
"Interquartile Range", "z-Statistic", "Standard Error", "p")), name = "Number by Income", questions = c("Number",
"Income [Colas edited]"))

################################################################################
## 3D, multi statistic taken from regression test:
## Dimension Reduction - Correspondence Anaysis of a Table.Q,
## ROutput correspondence.analysis1

q3.ms3 <- structure(c("25.2327048028994", "31.2881504763389", "30.9835063713764",
    "17.5546469946982", "33.2850525773139", "21.3918060868462", "14.8891326905278",
    "99.999999992966", "32.1856718881157", "39.0384865558457", "38.7008828633533",
    "23.043980297302", "41.2332045095876", "27.6781998955081", "19.7445739902877",
    "99.9999999949984", "19.3901751154243", "24.5030129463578", "24.24112651755",
    "13.1766253337998", "26.232192530017", "16.2453846830681", "11.0864828737829",
    "99.9999999901313", "22.3980226347181", "28.0282076203562", "27.7424891486241",
    "15.4048099182854", "29.9076106591684", "18.8796593933267", "13.0142006255211",
    "99.9999999917754", "25.6383779654847", "31.7498370032718", "31.4427546535753",
    "17.866375634708", "33.7617270166789", "21.753694692716", "15.1622330335653",
    "99.9999999931149", "25.3986416353672", "31.4771442945425", "31.1714948165763",
    "17.682032200925", "33.4802311923131", "21.5397609802415", "15.0006948800344",
    "99.9999999930275", "18.6950249396378", "23.6784065423265", "23.422599150159",
    "12.6692243563911", "25.3689477903583", "15.6411012525024", "10.6496959686249",
    "99.9999999896761", "25.1773988570791", "31.2251150086532", "30.9208084668817",
    "17.5122283403448", "33.2199390423663", "21.342515643933", "14.8519946407419",
    "99.9999999929453", "38.3662387414414", "45.6491679510049", "45.2968741467223",
    "28.1990522244833", "47.9233721374194", "33.4197641302466", "24.3955306686821",
    "99.9999999961865", "87.274341983319", "90.2471601302471", "90.1213865181602",
    "81.22746990624", "91.0222544777148", "84.6863241611387", "78.0460628231802",
    "99.9999999996539", "B I", "C D E F G H", "C D G H", "B I", "C D E F G H",
    "c d g H", "H i", "-", "i", "C D E F G H", "A C D G H", "I",
    "C D E F G H", "A C D G H", "A D e H I", "-", "A B I", "E F H",
    "D H", "B I", "D E F G H", "h", "A B D E F H I", "-", "A B C E F G I",
    "E F H", "h", "A B C E F G I", "F H", "h", "H", "-", "A B C G I",
    "F", "A C D G H", "A B C I", "D F H", "A B C D f G H I", "a D H I",
    "-", "A B C G I", "", "A B C D E G H", "A B C g I", "", "A B C D G H",
    "A D H I", "-", "a B I", "E F H", "D H", "a B c I", "D E F H",
    "", "A B C D E F H I", "-", "A B C D E F G I", "E F", "", "A B C D E F G I",
    "", "", "", "-", "", "A B C D E F G H", "A B C D E G H", "",
    "A B C D E F G H", "A B C D G H", "H", "-", "-", "-", "-", "-",
    "-", "-", "-", "-"), .Dim = c(8L, 10L, 2L), .Dimnames = list(
        c("Coke", "Diet Coke", "Coke Zero", "Pepsi", "Diet Pepsi",
        "Pepsi Max", "None of these", "NET"), c("Feminine", "Health-conscious",
        "Innocent", "Older", "Open to new experiences", "Rebellious",
        "Sleepy", "Traditional", "Weight-conscious", "NET"), c("Expected %",
        "Column Comparisons")), name = "q5", questions = c("q5",
                                                         "SUMMARY"))



####################################################################################################
## 2D: qdate x cat, 1 stat

q2.os <- structure(c(4.05405405405405, 10.8108108108108, 12.1621621621622,
12.1621621621622, 9.45945945945946, 8.10810810810811, 12.1621621621622,
12.1621621621622, 9.45945945945946, 9.45945945945946, 9.45945945945946,
8.10810810810811, 8.10810810810811, 14.8648648648649, 10.8108108108108,
5.40540540540541, 9.45945945945946, 14.8648648648649, 9.45945945945946,
9.45945945945946, 3.44827586206897, 17.2413793103448, 8.62068965517241,
15.5172413793103, 6.89655172413793, 5.17241379310345, 12.0689655172414,
8.62068965517241, 10.3448275862069, 12.0689655172414, 5.47945205479452,
2.73972602739726, 16.4383561643836, 12.3287671232877, 8.21917808219178,
9.58904109589041, 9.58904109589041, 6.84931506849315, 16.4383561643836,
12.3287671232877, 11.7647058823529, 10.2941176470588, 7.35294117647059,
5.88235294117647, 8.82352941176471, 16.1764705882353, 8.82352941176471,
10.2941176470588, 8.82352941176471, 11.7647058823529, 8.33333333333333,
4.16666666666667, 12.5, 12.5, 18.75, 8.33333333333333, 8.33333333333333,
12.5, 8.33333333333333, 6.25, 14.2857142857143, 7.14285714285714,
17.1428571428571, 8.57142857142857, 4.28571428571429, 12.8571428571429,
12.8571428571429, 11.4285714285714, 2.85714285714286, 8.57142857142857,
6.38297872340426, 8.51063829787234, 10.6382978723404, 10.6382978723404,
13.8297872340426, 9.57446808510638, 10.6382978723404, 12.7659574468085,
6.38297872340426, 10.6382978723404, 7.31707317073171, 9.75609756097561,
14.6341463414634, 9.75609756097561, 9.75609756097561, 2.4390243902439,
19.5121951219512, 12.1951219512195, 0, 14.6341463414634, 7.83333333333333,
8.66666666666667, 11.8333333333333, 11.3333333333333, 10, 9,
11.1666666666667, 11.3333333333333, 8.33333333333333, 10.5), .Dim = c(10L,
10L), statistic = "Column %", .Dimnames = list(c("12/26/2011-1/22/2012",
"1/23/2012-2/19/2012", "2/20/2012-3/18/2012", "3/19/2012-4/15/2012",
"4/16/2012-5/13/2012", "5/14/2012-6/10/2012", "6/11/2012-7/8/2012",
"7/9/2012-8/5/2012", "8/6/2012-9/2/2012", "9/3/2012-9/30/2012"
), c("18 to 24", "25 to 29", "30 to 34", "35 to 39", "40 to 44",
"45 to 49", "50 to 54", "55 to 64", "65 +", "NET")), name = "Interview Date by Age Categories", questions = c("Interview Date",
"Age Categories"))

####################################################################################################
## 2D: multi grid, 1 stat
q2.os2 <- structure(c(0, 19.8776758409786, 18.6544342507645, 0, 13.7614678899083,
3.05810397553517, 0, 14.0672782874618, 2.75229357798165, 8.56269113149847,
17.4311926605505, 2.14067278287462, 10.0917431192661, 9.48012232415902,
4.58715596330275, 16.8195718654434, 11.6207951070336, 3.97553516819572,
22.6299694189602, 6.11620795107034, 6.72782874617737, 12.2324159021407,
3.36391437308868, 5.81039755351682, 29.6636085626911, 4.28134556574923,
52.2935779816514, 100, 100, 100), .Dim = c(3L, 10L), statistic = "Row %", .Dimnames = list(
    c("Colas (e.g., Coca-Cola, Pepsi Max)?", "Sparkling mineral water",
    "Coffee"), c("Never", "Once or twice a year", "Once every 3 months",
    "Once a month", "Once every 2 weeks", "Once a week", "2 to 3 days a week",
    "4 to 5 days a week", "Every or nearly every day", "NET")), name = "Frequency of drinking", questions = c("Frequency of drinking",
"SUMMARY"))


####################################################################################################
## 2D: numeric x cat, 1 stat
q2.os3 <- structure(c(21, 27, 32, 37, 42, 47, 52, 60, 77, 42.6238532110092
), .Dim = c(1L, 10L), statistic = "Average", .Dimnames = list(
    "Number", c("18 to 24", "25 to 29", "30 to 34", "35 to 39",
    "40 to 44", "45 to 49", "50 to 54", "55 to 64", "65 or more",
    "NET")), name = "Number by Age", questions = c("Number",
"Age [Colas edited]"))


####################################################################################################
## 2D: multi cat, multi stat

q2.ms <- structure(c(13.4556574923547, 11.9266055045872, 10.0917431192661,
11.0091743119266, 10.7033639143731, 8.25688073394496, 12.2324159021407,
15.5963302752294, 6.72782874617737, 100, 44, 39, 33, 36, 35,
27, 40, 51, 22, 327), .Dim = c(10L, 2L), .Dimnames = list(c("18 to 24",
"25 to 29", "30 to 34", "35 to 39", "40 to 44", "45 to 49", "50 to 54",
"55 to 64", "65 or more", "NET"), c("%", "Count")), name = "Age", questions = c("Age",
"SUMMARY"))

####################################################################################################
## 1D: number multi
q1.os <- structure(c(7.08868501529052, 3.84709480122324, 17.4617737003058
), .Dim = 3L, statistic = "Average", .Dimnames = list(c("Colas (e.g., Coca-Cola, Pepsi Max)?",
"Sparkling mineral water", "SUM")), name = "Number Multi", questions = c("Number Multi",
                                                                         "SUMMARY"))

####################################################################################################
## 1D: number
q1.os2 <- structure(42.6238532110092, .Dim = 1L, statistic = "Average", .Dimnames = list(
    "Number"), name = "Number", questions = c("Number", "SUMMARY"
))