Exploration

library(basetable)

dims(iris)

## # basetable: 1 x 2
##   rows cols
## 1  150    5

types(iris)

## # basetable: 5 x 3
##         column   class  typeof
## 1 Sepal.Length numeric  double
## 2  Sepal.Width numeric  double
## 3 Petal.Length numeric  double
## 4  Petal.Width numeric  double
## 5      Species  factor integer

describe(iris)

## # basetable: 5 x 14
##         column   class   n missing missing_prop distinct     mean        sd min
## 1 Sepal.Length numeric 150       0            0       35 5.843333 0.8280661 4.3
## 2  Sepal.Width numeric 150       0            0       23 3.057333 0.4358663 2.0
## 3 Petal.Length numeric 150       0            0       43 3.758000 1.7652982 1.0
## 4  Petal.Width numeric 150       0            0       22 1.199333 0.7622377 0.1
## 5      Species  factor 150       0            0        3       NA        NA  NA
##   q25 median q75 max                                          top
## 1 5.1   5.80 6.4 7.9                                             
## 2 2.8   3.00 3.3 4.4                                             
## 3 1.6   4.35 5.1 6.9                                             
## 4 0.3   1.30 1.8 2.5                                             
## 5  NA     NA  NA  NA setosa (50), versicolor (50), virginica (50)

missingness(airquality)

## # basetable: 6 x 4
##    column missing missing_prop complete
## 1   Ozone      37   0.24183007      116
## 2 Solar.R       7   0.04575163      146
## 3    Wind       0   0.00000000      153
## 4    Temp       0   0.00000000      153
## 5   Month       0   0.00000000      153
## 6     Day       0   0.00000000      153

freq(iris, "Species", prop = TRUE)

## # basetable: 3 x 3
##      Species  n      prop
## 1     setosa 50 0.3333333
## 2 versicolor 50 0.3333333
## 3  virginica 50 0.3333333

summarytab(
  transform(mtcars, am = factor(am, labels = c("Automatic", "Manual"))),
  vars = c("mpg", "hp"),
  by = "am",
  p_value = TRUE
)

## # basetable: 2 x 6
##   variable     level    Automatic       Manual      Overall p_value
## 1      mpg Mean (SD)   17.1 (3.8)   24.4 (6.2)   20.1 (6.0) 0.00137
## 2       hp Mean (SD) 160.3 (53.9) 126.8 (84.1) 146.7 (68.6)   0.221

compare(mtcars, transform(mtcars, mpg = mpg * 1.1))

## $dims
## # basetable: 2 x 3
##   object rows cols
## 1      x   32   11
## 2      y   32   11
## 
## $names
## # basetable: 11 x 3
##    column in_x in_y
## 1     mpg TRUE TRUE
## 2     cyl TRUE TRUE
## 3    disp TRUE TRUE
## 4      hp TRUE TRUE
## 5    drat TRUE TRUE
## 6      wt TRUE TRUE
## 7    qsec TRUE TRUE
## 8      vs TRUE TRUE
## 9      am TRUE TRUE
## 10   gear TRUE TRUE
## # 1 more rows
## 
## $types
## # basetable: 11 x 5
##    column class.x typeof.x class.y typeof.y
## 1     mpg numeric   double numeric   double
## 2     cyl numeric   double numeric   double
## 3    disp numeric   double numeric   double
## 4      hp numeric   double numeric   double
## 5    drat numeric   double numeric   double
## 6      wt numeric   double numeric   double
## 7    qsec numeric   double numeric   double
## 8      vs numeric   double numeric   double
## 9      am numeric   double numeric   double
## 10   gear numeric   double numeric   double
## # 1 more rows
## 
## $missing
## # basetable: 11 x 7
##    column missing.x missing_prop.x complete.x missing.y missing_prop.y
## 1     mpg         0              0         32         0              0
## 2     cyl         0              0         32         0              0
## 3    disp         0              0         32         0              0
## 4      hp         0              0         32         0              0
## 5    drat         0              0         32         0              0
## 6      wt         0              0         32         0              0
## 7    qsec         0              0         32         0              0
## 8      vs         0              0         32         0              0
## 9      am         0              0         32         0              0
## 10   gear         0              0         32         0              0
##    complete.y
## 1          32
## 2          32
## 3          32
## 4          32
## 5          32
## 6          32
## 7          32
## 8          32
## 9          32
## 10         32
## # 1 more rows