Data frames in dplyr style.
library(tibble)
tbl_df(iris)
#> Source: local data frame [150 x 5]
#>
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> (dbl) (dbl) (dbl) (dbl) (fctr)
#> 1 5.1 3.5 1.4 0.2 setosa
#> 2 4.9 3.0 1.4 0.2 setosa
#> 3 4.7 3.2 1.3 0.2 setosa
#> 4 4.6 3.1 1.5 0.2 setosa
#> 5 5.0 3.6 1.4 0.2 setosa
#> 6 5.4 3.9 1.7 0.4 setosa
#> 7 4.6 3.4 1.4 0.3 setosa
#> 8 5.0 3.4 1.5 0.2 setosa
#> 9 4.4 2.9 1.4 0.2 setosa
#> 10 4.9 3.1 1.5 0.1 setosa
#> .. ... ... ... ... ...
glimpse(iris)
#> Observations: 150
#> Variables: 5
#> $ Sepal.Length (dbl) 5.1, 4.9, 4.7, 4.6, 5.0, 5.4, 4.6, 5.0, 4.4, 4.9,...
#> $ Sepal.Width (dbl) 3.5, 3.0, 3.2, 3.1, 3.6, 3.9, 3.4, 3.4, 2.9, 3.1,...
#> $ Petal.Length (dbl) 1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4, 1.5,...
#> $ Petal.Width (dbl) 0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3, 0.2, 0.2, 0.1,...
#> $ Species (fctr) setosa, setosa, setosa, setosa, setosa, setosa, ...
head(rownames_to_column(mtcars, "model"))
#> model mpg cyl disp hp drat wt qsec vs am gear carb
#> 1 Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
#> 2 Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
#> 3 Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
#> 4 Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
#> 5 Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
#> 6 Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
trunc_mat(iris)| Sepal.Length | Sepal.Width | Petal.Length | Petal.Width | Species |
|---|---|---|---|---|
| (dbl) | (dbl) | (dbl) | (dbl) | (fctr) |
| 5.1 | 3.5 | 1.4 | 0.2 | setosa |
| 4.9 | 3.0 | 1.4 | 0.2 | setosa |
| 4.7 | 3.2 | 1.3 | 0.2 | setosa |
| 4.6 | 3.1 | 1.5 | 0.2 | setosa |
| 5.0 | 3.6 | 1.4 | 0.2 | setosa |
| 5.4 | 3.9 | 1.7 | 0.4 | setosa |
| 4.6 | 3.4 | 1.4 | 0.3 | setosa |
| 5.0 | 3.4 | 1.5 | 0.2 | setosa |
| 4.4 | 2.9 | 1.4 | 0.2 | setosa |
| 4.9 | 3.1 | 1.5 | 0.1 | setosa |
| ... | ... | ... | ... | ... |