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as_base_r converts xlr objects, xlr_table, xlr_numeric, xlr_integer, xlr_percent, and xlr_format to their base R type.

Usage

as_base_r(x)

Arguments

x

a xlr object

Value

The base type of the base R object.

Details

as_base_r is a generic. It is a wrapper around vec_data but will convert every object to its base type.

Examples

library(xlr)

# We create a xlr objects
a <- xlr_numeric(1:100)
b <- xlr_percent(1:100/100)
tab <- xlr_table(mtcars,"a title","a footnote")

# now lets convert them back to their base types
as_base_r(a)
#>   [1]   1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18
#>  [19]  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36
#>  [37]  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54
#>  [55]  55  56  57  58  59  60  61  62  63  64  65  66  67  68  69  70  71  72
#>  [73]  73  74  75  76  77  78  79  80  81  82  83  84  85  86  87  88  89  90
#>  [91]  91  92  93  94  95  96  97  98  99 100
as_base_r(b)
#>   [1] 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15
#>  [16] 0.16 0.17 0.18 0.19 0.20 0.21 0.22 0.23 0.24 0.25 0.26 0.27 0.28 0.29 0.30
#>  [31] 0.31 0.32 0.33 0.34 0.35 0.36 0.37 0.38 0.39 0.40 0.41 0.42 0.43 0.44 0.45
#>  [46] 0.46 0.47 0.48 0.49 0.50 0.51 0.52 0.53 0.54 0.55 0.56 0.57 0.58 0.59 0.60
#>  [61] 0.61 0.62 0.63 0.64 0.65 0.66 0.67 0.68 0.69 0.70 0.71 0.72 0.73 0.74 0.75
#>  [76] 0.76 0.77 0.78 0.79 0.80 0.81 0.82 0.83 0.84 0.85 0.86 0.87 0.88 0.89 0.90
#>  [91] 0.91 0.92 0.93 0.94 0.95 0.96 0.97 0.98 0.99 1.00
as_base_r(tab)
#>     mpg cyl  disp  hp drat    wt  qsec vs am gear carb
#> 1  21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
#> 2  21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
#> 3  22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
#> 4  21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
#> 5  18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
#> 6  18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
#> 7  14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
#> 8  24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
#> 9  22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
#> 10 19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
#> 11 17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
#> 12 16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
#> 13 17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
#> 14 15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
#> 15 10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
#> 16 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
#> 17 14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
#> 18 32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
#> 19 30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
#> 20 33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1
#> 21 21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
#> 22 15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
#> 23 15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
#> 24 13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
#> 25 19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
#> 26 27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1
#> 27 26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
#> 28 30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
#> 29 15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
#> 30 19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
#> 31 15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8
#> 32 21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2