A versatile and computationally more efficient replacement for table. Notably, it also supports tabulations with frequency weights, and computation of a statistic over combinations of variables.

qtab(..., w = NULL, wFUN = NULL, wFUN.args = NULL,
     dnn = "auto", sort = TRUE, na.exclude = TRUE,
     drop = FALSE, method = "auto")

qtable(...) # Long-form: to facilitate replacement of table()

Arguments

...

atomic vectors or factors spanning the table dimensions, (optionally) with tags for the dimension names, or a data frame / list of these. See Examples.

w

a single vector to aggregate over the table dimensions e.g. a vector of frequency weights.

wFUN

a function used to aggregate w over the table dimensions. The default NULL computes the sum of the non-missing weights via an optimized internal algorithm. Fast Statistical Functions also receive vectorized execution.

wFUN.args

a list of (optional) further arguments passed to wFUN. See Examples.

dnn

the names of the table dimensions. Either passed directly as a character vector or list (internally unlist'ed), a function applied to the ... list (e.g. names, or vlabels), or one of the following options:

  • "auto" constructs names based on the ... arguments, or calls names if a single list is passed as input.

  • "namlab" does the same as "auto", but also calls vlabels on the list and appends the names by the variable labels.

dnn = NULL will return a table without dimension names.

sort, na.exclude, drop, method

arguments passed down to qF:

  • sort = FALSE orders table dimensions in first-appearance order of items in the data (can be more efficient if vectors are not factors already). Note that for factors this option will both recast levels in first-appearance order and drop unused levels.

  • na.exclude = FALSE includes NA's in the table (equivalent to table's useNA = "ifany").

  • drop = TRUE removes any unused factor levels (= zero frequency rows or columns).

  • method %in% c("radix", "hash") provides additional control over the algorithm used to convert atomic vectors to factors.

Value

An array of class 'qtab' that inherits from 'table'. Thus all 'table' methods apply to it.

Examples

## Basic use
qtab(iris$Species)
#> iris$Species
#>     setosa versicolor  virginica 
#>         50         50         50 
with(mtcars, qtab(vs, am))
#>    am
#> vs   0  1
#>   0 12  6
#>   1  7  7
qtab(mtcars[.c(vs, am)])
#>    am
#> vs   0  1
#>   0 12  6
#>   1  7  7
 
library(magrittr)
iris %$% qtab(Sepal.Length > mean(Sepal.Length), Species)
#>                                  Species
#> Sepal.Length > mean(Sepal.Length) setosa versicolor virginica
#>                             FALSE     50         24         6
#>                             TRUE       0         26        44
iris %$% qtab(AMSL = Sepal.Length > mean(Sepal.Length), Species)
#>        Species
#> AMSL    setosa versicolor virginica
#>   FALSE     50         24         6
#>   TRUE       0         26        44

## World after 2015
wlda15 <- wlddev %>% fsubset(year >= 2015) %>% collap(~ iso3c)

# Regions and income levels (country frequency)
wlda15 %$% qtab(region, income)
#>                             income
#> region                       High income Low income Lower middle income
#>   East Asia & Pacific                 13          0                  13
#>   Europe & Central Asia               37          1                   4
#>   Latin America & Caribbean           17          1                   4
#>   Middle East & North Africa           8          2                   5
#>   North America                        3          0                   0
#>   South Asia                           0          2                   4
#>   Sub-Saharan Africa                   1         24                  17
#>                             income
#> region                       Upper middle income
#>   East Asia & Pacific                         10
#>   Europe & Central Asia                       16
#>   Latin America & Caribbean                   20
#>   Middle East & North Africa                   6
#>   North America                                0
#>   South Asia                                   2
#>   Sub-Saharan Africa                           6
wlda15 %$% qtab(region, income, dnn = vlabels)
#>                             Income Level
#> Region                       High income Low income Lower middle income
#>   East Asia & Pacific                 13          0                  13
#>   Europe & Central Asia               37          1                   4
#>   Latin America & Caribbean           17          1                   4
#>   Middle East & North Africa           8          2                   5
#>   North America                        3          0                   0
#>   South Asia                           0          2                   4
#>   Sub-Saharan Africa                   1         24                  17
#>                             Income Level
#> Region                       Upper middle income
#>   East Asia & Pacific                         10
#>   Europe & Central Asia                       16
#>   Latin America & Caribbean                   20
#>   Middle East & North Africa                   6
#>   North America                                0
#>   South Asia                                   2
#>   Sub-Saharan Africa                           6
wlda15 %$% qtab(region, income, dnn = "namlab")
#>                             income: Income Level
#> region: Region               High income Low income Lower middle income
#>   East Asia & Pacific                 13          0                  13
#>   Europe & Central Asia               37          1                   4
#>   Latin America & Caribbean           17          1                   4
#>   Middle East & North Africa           8          2                   5
#>   North America                        3          0                   0
#>   South Asia                           0          2                   4
#>   Sub-Saharan Africa                   1         24                  17
#>                             income: Income Level
#> region: Region               Upper middle income
#>   East Asia & Pacific                         10
#>   Europe & Central Asia                       16
#>   Latin America & Caribbean                   20
#>   Middle East & North Africa                   6
#>   North America                                0
#>   South Asia                                   2
#>   Sub-Saharan Africa                           6

# Population (millions)
wlda15 %$% qtab(region, income, w = POP) %>% divide_by(1e6)
#>                             income
#> region                        High income   Low income Lower middle income
#>   East Asia & Pacific         222.3763078    0.0000000         554.5787740
#>   Europe & Central Asia       499.6178162    8.8839460          86.1694676
#>   Latin America & Caribbean    32.1055806   10.9808262          33.3947544
#>   Middle East & North Africa   64.6289084   45.1314580         148.8518602
#>   North America               361.3653800    0.0000000           0.0000000
#>   South Asia                    0.0000000   63.9814276        1706.8229478
#>   Sub-Saharan Africa            0.0956652  530.2676994         450.7138318
#>                             income
#> region                       Upper middle income
#>   East Asia & Pacific               1486.9566064
#>   Europe & Central Asia              319.5918390
#>   Latin America & Caribbean          557.9670800
#>   Middle East & North Africa         182.6471952
#>   North America                        0.0000000
#>   South Asia                          21.9126958
#>   Sub-Saharan Africa                  66.1922298

# Life expectancy (years)
wlda15 %$% qtab(region, income, w = LIFEEX, wFUN = fmean)
#>                             income
#> region                       High income Low income Lower middle income
#>   East Asia & Pacific           81.12986                       69.32372
#>   Europe & Central Asia         80.39692   70.63140            71.44826
#>   Latin America & Caribbean     77.57964   63.26640            73.18650
#>   Middle East & North Africa    78.38796   68.61450            72.73452
#>   North America                 80.67948                               
#>   South Asia                               67.13770            69.81250
#>   Sub-Saharan Africa            73.93805   60.63336            62.37481
#>                             income
#> region                       Upper middle income
#>   East Asia & Pacific                   73.32000
#>   Europe & Central Asia                 74.39151
#>   Latin America & Caribbean             74.69349
#>   Middle East & North Africa            74.78043
#>   North America                                 
#>   South Asia                            77.48130
#>   Sub-Saharan Africa                    65.54593

# Life expectancy (years), weighted by population
wlda15 %$% qtab(region, income, w = LIFEEX, wFUN = fmean,
                  wFUN.args = list(w = POP))
#>                             income
#> region                       High income Low income Lower middle income
#>   East Asia & Pacific           83.47390                       71.19076
#>   Europe & Central Asia         81.31296   70.63140            71.46540
#>   Latin America & Caribbean     78.99973   63.26640            73.01552
#>   Middle East & North Africa    76.84332   68.02666            73.12402
#>   North America                 78.97586                               
#>   South Asia                               66.73455            69.15123
#>   Sub-Saharan Africa            73.93805   62.01679            58.97093
#>                             income
#> region                       Upper middle income
#>   East Asia & Pacific                   76.43505
#>   Europe & Central Asia                 73.96995
#>   Latin America & Caribbean             75.44067
#>   Middle East & North Africa            74.93824
#>   North America                                 
#>   South Asia                            76.68486
#>   Sub-Saharan Africa                    63.79719

# GDP per capita (constant 2010 US$): median
wlda15 %$% qtab(region, income, w = PCGDP, wFUN = fmedian,
                  wFUN.args = list(na.rm = TRUE))
#>                             income
#> region                       High income Low income Lower middle income
#>   East Asia & Pacific         37527.1689                      1863.8773
#>   Europe & Central Asia       44340.1356  1026.2292           2654.3445
#>   Latin America & Caribbean   16514.1173  1266.0910           2323.2438
#>   Middle East & North Africa  31003.0939   677.4104           3134.9231
#>   North America               53790.1303                               
#>   South Asia                               677.2265           1558.9751
#>   Sub-Saharan Africa          14057.6452   635.8458           1657.2758
#>                             income
#> region                       Upper middle income
#>   East Asia & Pacific                  5364.0199
#>   Europe & Central Asia                6552.2411
#>   Latin America & Caribbean            6824.2245
#>   Middle East & North Africa           5920.2114
#>   North America                                 
#>   South Asia                           5883.8904
#>   Sub-Saharan Africa                   8578.7116

# GDP per capita (constant 2010 US$): median, weighted by population
wlda15 %$% qtab(region, income, w = PCGDP, wFUN = fmedian,
                  wFUN.args = list(w = POP))
#>                             income
#> region                       High income Low income Lower middle income
#>   East Asia & Pacific         48194.0408                      3038.6464
#>   Europe & Central Asia       42912.4250  1026.2292           3010.4318
#>   Latin America & Caribbean   14888.7707  1266.0910           2483.3969
#>   Middle East & North Africa  20945.0874   677.4104           2840.9586
#>   North America               53790.1303                               
#>   South Asia                               570.9192           1970.4413
#>   Sub-Saharan Africa          14057.6452   543.6803           2430.1368
#>                             income
#> region                       Upper middle income
#>   East Asia & Pacific                  7360.8953
#>   Europe & Central Asia               11623.6264
#>   Latin America & Caribbean           10231.2777
#>   Middle East & North Africa           6255.4776
#>   North America                                 
#>   South Asia                           3846.9157
#>   Sub-Saharan Africa                   7457.1928

# Including OECD membership
tab <- wlda15 %$% qtab(region, income, OECD)
tab
#> , , OECD = FALSE
#> 
#>                             income
#> region                       High income Low income Lower middle income
#>   East Asia & Pacific                  9          0                  13
#>   Europe & Central Asia               11          1                   4
#>   Latin America & Caribbean           16          1                   4
#>   Middle East & North Africa           7          2                   5
#>   North America                        1          0                   0
#>   South Asia                           0          2                   4
#>   Sub-Saharan Africa                   1         24                  17
#>                             income
#> region                       Upper middle income
#>   East Asia & Pacific                         10
#>   Europe & Central Asia                       15
#>   Latin America & Caribbean                   19
#>   Middle East & North Africa                   6
#>   North America                                0
#>   South Asia                                   2
#>   Sub-Saharan Africa                           6
#> 
#> , , OECD = TRUE
#> 
#>                             income
#> region                       High income Low income Lower middle income
#>   East Asia & Pacific                  4          0                   0
#>   Europe & Central Asia               26          0                   0
#>   Latin America & Caribbean            1          0                   0
#>   Middle East & North Africa           1          0                   0
#>   North America                        2          0                   0
#>   South Asia                           0          0                   0
#>   Sub-Saharan Africa                   0          0                   0
#>                             income
#> region                       Upper middle income
#>   East Asia & Pacific                          0
#>   Europe & Central Asia                        1
#>   Latin America & Caribbean                    1
#>   Middle East & North Africa                   0
#>   North America                                0
#>   South Asia                                   0
#>   Sub-Saharan Africa                           0
#> 

# Various 'table' methods
tab %>% addmargins()
#> , , OECD = FALSE
#> 
#>                             income
#> region                       High income Low income Lower middle income
#>   East Asia & Pacific                  9          0                  13
#>   Europe & Central Asia               11          1                   4
#>   Latin America & Caribbean           16          1                   4
#>   Middle East & North Africa           7          2                   5
#>   North America                        1          0                   0
#>   South Asia                           0          2                   4
#>   Sub-Saharan Africa                   1         24                  17
#>   Sum                                 45         30                  47
#>                             income
#> region                       Upper middle income Sum
#>   East Asia & Pacific                         10  32
#>   Europe & Central Asia                       15  31
#>   Latin America & Caribbean                   19  40
#>   Middle East & North Africa                   6  20
#>   North America                                0   1
#>   South Asia                                   2   8
#>   Sub-Saharan Africa                           6  48
#>   Sum                                         58 180
#> 
#> , , OECD = TRUE
#> 
#>                             income
#> region                       High income Low income Lower middle income
#>   East Asia & Pacific                  4          0                   0
#>   Europe & Central Asia               26          0                   0
#>   Latin America & Caribbean            1          0                   0
#>   Middle East & North Africa           1          0                   0
#>   North America                        2          0                   0
#>   South Asia                           0          0                   0
#>                             income
#> region                       Upper middle income Sum
#>   East Asia & Pacific                          0   4
#>   Europe & Central Asia                        1  27
#>   Latin America & Caribbean                    1   2
#>   Middle East & North Africa                   0   1
#>   North America                                0   2
#>   South Asia                                   0   0
#> 
#>  [ reached getOption("max.print") -- omitted 2 row(s) and 1 matrix slice(s) ]
tab %>% marginSums(margin = c("region", "income"))
#>                             income
#> region                       High income Low income Lower middle income
#>   East Asia & Pacific                 13          0                  13
#>   Europe & Central Asia               37          1                   4
#>   Latin America & Caribbean           17          1                   4
#>   Middle East & North Africa           8          2                   5
#>   North America                        3          0                   0
#>   South Asia                           0          2                   4
#>   Sub-Saharan Africa                   1         24                  17
#>                             income
#> region                       Upper middle income
#>   East Asia & Pacific                         10
#>   Europe & Central Asia                       16
#>   Latin America & Caribbean                   20
#>   Middle East & North Africa                   6
#>   North America                                0
#>   South Asia                                   2
#>   Sub-Saharan Africa                           6
tab %>% proportions()
#> , , OECD = FALSE
#> 
#>                             income
#> region                       High income  Low income Lower middle income
#>   East Asia & Pacific        0.041666667 0.000000000         0.060185185
#>   Europe & Central Asia      0.050925926 0.004629630         0.018518519
#>   Latin America & Caribbean  0.074074074 0.004629630         0.018518519
#>   Middle East & North Africa 0.032407407 0.009259259         0.023148148
#>   North America              0.004629630 0.000000000         0.000000000
#>   South Asia                 0.000000000 0.009259259         0.018518519
#>   Sub-Saharan Africa         0.004629630 0.111111111         0.078703704
#>                             income
#> region                       Upper middle income
#>   East Asia & Pacific                0.046296296
#>   Europe & Central Asia              0.069444444
#>   Latin America & Caribbean          0.087962963
#>   Middle East & North Africa         0.027777778
#>   North America                      0.000000000
#>   South Asia                         0.009259259
#>   Sub-Saharan Africa                 0.027777778
#> 
#> , , OECD = TRUE
#> 
#>                             income
#> region                       High income  Low income Lower middle income
#>   East Asia & Pacific        0.018518519 0.000000000         0.000000000
#>   Europe & Central Asia      0.120370370 0.000000000         0.000000000
#>   Latin America & Caribbean  0.004629630 0.000000000         0.000000000
#>   Middle East & North Africa 0.004629630 0.000000000         0.000000000
#>   North America              0.009259259 0.000000000         0.000000000
#>   South Asia                 0.000000000 0.000000000         0.000000000
#>   Sub-Saharan Africa         0.000000000 0.000000000         0.000000000
#>                             income
#> region                       Upper middle income
#>   East Asia & Pacific                0.000000000
#>   Europe & Central Asia              0.004629630
#>   Latin America & Caribbean          0.004629630
#>   Middle East & North Africa         0.000000000
#>   North America                      0.000000000
#>   South Asia                         0.000000000
#>   Sub-Saharan Africa                 0.000000000
#> 
tab %>% proportions(margin = "income")
#> , , OECD = FALSE
#> 
#>                             income
#> region                       High income Low income Lower middle income
#>   East Asia & Pacific         0.11392405 0.00000000          0.27659574
#>   Europe & Central Asia       0.13924051 0.03333333          0.08510638
#>   Latin America & Caribbean   0.20253165 0.03333333          0.08510638
#>   Middle East & North Africa  0.08860759 0.06666667          0.10638298
#>   North America               0.01265823 0.00000000          0.00000000
#>   South Asia                  0.00000000 0.06666667          0.08510638
#>   Sub-Saharan Africa          0.01265823 0.80000000          0.36170213
#>                             income
#> region                       Upper middle income
#>   East Asia & Pacific                 0.16666667
#>   Europe & Central Asia               0.25000000
#>   Latin America & Caribbean           0.31666667
#>   Middle East & North Africa          0.10000000
#>   North America                       0.00000000
#>   South Asia                          0.03333333
#>   Sub-Saharan Africa                  0.10000000
#> 
#> , , OECD = TRUE
#> 
#>                             income
#> region                       High income Low income Lower middle income
#>   East Asia & Pacific         0.05063291 0.00000000          0.00000000
#>   Europe & Central Asia       0.32911392 0.00000000          0.00000000
#>   Latin America & Caribbean   0.01265823 0.00000000          0.00000000
#>   Middle East & North Africa  0.01265823 0.00000000          0.00000000
#>   North America               0.02531646 0.00000000          0.00000000
#>   South Asia                  0.00000000 0.00000000          0.00000000
#>   Sub-Saharan Africa          0.00000000 0.00000000          0.00000000
#>                             income
#> region                       Upper middle income
#>   East Asia & Pacific                 0.00000000
#>   Europe & Central Asia               0.01666667
#>   Latin America & Caribbean           0.01666667
#>   Middle East & North Africa          0.00000000
#>   North America                       0.00000000
#>   South Asia                          0.00000000
#>   Sub-Saharan Africa                  0.00000000
#> 
as.data.frame(tab) %>% head(10)
#>                        region      income  OECD Freq
#> 1         East Asia & Pacific High income FALSE    9
#> 2       Europe & Central Asia High income FALSE   11
#> 3   Latin America & Caribbean High income FALSE   16
#> 4  Middle East & North Africa High income FALSE    7
#> 5               North America High income FALSE    1
#> 6                  South Asia High income FALSE    0
#> 7          Sub-Saharan Africa High income FALSE    1
#> 8         East Asia & Pacific  Low income FALSE    0
#> 9       Europe & Central Asia  Low income FALSE    1
#> 10  Latin America & Caribbean  Low income FALSE    1
ftable(tab, row.vars = c("region", "OECD"))
#>                                  income High income Low income Lower middle income Upper middle income
#> region                     OECD                                                                       
#> East Asia & Pacific        FALSE                  9          0                  13                  10
#>                            TRUE                   4          0                   0                   0
#> Europe & Central Asia      FALSE                 11          1                   4                  15
#>                            TRUE                  26          0                   0                   1
#> Latin America & Caribbean  FALSE                 16          1                   4                  19
#>                            TRUE                   1          0                   0                   1
#> Middle East & North Africa FALSE                  7          2                   5                   6
#>                            TRUE                   1          0                   0                   0
#> North America              FALSE                  1          0                   0                   0
#>                            TRUE                   2          0                   0                   0
#> South Asia                 FALSE                  0          2                   4                   2
#>                            TRUE                   0          0                   0                   0
#> Sub-Saharan Africa         FALSE                  1         24                  17                   6
#>                            TRUE                   0          0                   0                   0

# Other options
tab %>% fsum(TRA = "%")    # Percentage table (on a matrix use fsum.default)
#> , , OECD = FALSE
#> 
#>                             income
#> region                       High income Low income Lower middle income
#>   East Asia & Pacific          4.1666667  0.0000000           6.0185185
#>   Europe & Central Asia        5.0925926  0.4629630           1.8518519
#>   Latin America & Caribbean    7.4074074  0.4629630           1.8518519
#>   Middle East & North Africa   3.2407407  0.9259259           2.3148148
#>   North America                0.4629630  0.0000000           0.0000000
#>   South Asia                   0.0000000  0.9259259           1.8518519
#>   Sub-Saharan Africa           0.4629630 11.1111111           7.8703704
#>                             income
#> region                       Upper middle income
#>   East Asia & Pacific                  4.6296296
#>   Europe & Central Asia                6.9444444
#>   Latin America & Caribbean            8.7962963
#>   Middle East & North Africa           2.7777778
#>   North America                        0.0000000
#>   South Asia                           0.9259259
#>   Sub-Saharan Africa                   2.7777778
#> 
#> , , OECD = TRUE
#> 
#>                             income
#> region                       High income Low income Lower middle income
#>   East Asia & Pacific          1.8518519  0.0000000           0.0000000
#>   Europe & Central Asia       12.0370370  0.0000000           0.0000000
#>   Latin America & Caribbean    0.4629630  0.0000000           0.0000000
#>   Middle East & North Africa   0.4629630  0.0000000           0.0000000
#>   North America                0.9259259  0.0000000           0.0000000
#>   South Asia                   0.0000000  0.0000000           0.0000000
#>   Sub-Saharan Africa           0.0000000  0.0000000           0.0000000
#>                             income
#> region                       Upper middle income
#>   East Asia & Pacific                  0.0000000
#>   Europe & Central Asia                0.4629630
#>   Latin America & Caribbean            0.4629630
#>   Middle East & North Africa           0.0000000
#>   North America                        0.0000000
#>   South Asia                           0.0000000
#>   Sub-Saharan Africa                   0.0000000
#> 
tab %/=% (sum(tab)/100)    # Another way (division by reference, preserves integers)
tab
#> , , OECD = FALSE
#> 
#>                             income
#> region                       High income Low income Lower middle income
#>   East Asia & Pacific                  4          0                   6
#>   Europe & Central Asia                5          0                   2
#>   Latin America & Caribbean            8          0                   2
#>   Middle East & North Africa           3          1                   2
#>   North America                        0          0                   0
#>   South Asia                           0          1                   2
#>   Sub-Saharan Africa                   0         12                   8
#>                             income
#> region                       Upper middle income
#>   East Asia & Pacific                          5
#>   Europe & Central Asia                        7
#>   Latin America & Caribbean                    9
#>   Middle East & North Africa                   3
#>   North America                                0
#>   South Asia                                   1
#>   Sub-Saharan Africa                           3
#> 
#> , , OECD = TRUE
#> 
#>                             income
#> region                       High income Low income Lower middle income
#>   East Asia & Pacific                  2          0                   0
#>   Europe & Central Asia               13          0                   0
#>   Latin America & Caribbean            0          0                   0
#>   Middle East & North Africa           0          0                   0
#>   North America                        1          0                   0
#>   South Asia                           0          0                   0
#>   Sub-Saharan Africa                   0          0                   0
#>                             income
#> region                       Upper middle income
#>   East Asia & Pacific                          0
#>   Europe & Central Asia                        0
#>   Latin America & Caribbean                    0
#>   Middle East & North Africa                   0
#>   North America                                0
#>   South Asia                                   0
#>   Sub-Saharan Africa                           0
#> 

rm(tab, wlda15)