Used in particular for compatibility with the tidyverse
Usage
as_df(x, ...)
# S3 method for Coo
as_df(x, ...)
# S3 method for Coe
as_df(x, ...)
# S3 method for PCA
as_df(x, retain, ...)
# S3 method for LDA
as_df(x, retain, ...)Arguments
- x
an object, typically a Momocs object
- ...
useless here
- retain
numeric for use with scree methods. Defaut to all. If
<1, enough axes to retain this proportion of variance; if>1, this number of axes.
Examples
# first, some (baby) objects
b <- bot %>% coo_sample(12)
bf <- b %>% efourier(5, norm=TRUE)
# Coo object
b %>% as_df
#> # A tibble: 40 × 3
#> coo type fake
#> <named list> <fct> <fct>
#> 1 <dbl [12 × 2]> whisky a
#> 2 <dbl [12 × 2]> whisky a
#> 3 <dbl [12 × 2]> whisky a
#> 4 <dbl [12 × 2]> whisky a
#> 5 <dbl [12 × 2]> whisky a
#> 6 <dbl [12 × 2]> whisky a
#> 7 <dbl [12 × 2]> whisky a
#> 8 <dbl [12 × 2]> whisky a
#> 9 <dbl [12 × 2]> whisky a
#> 10 <dbl [12 × 2]> whisky a
#> # ℹ 30 more rows
# Coe object
bf %>% as_df
#> # A tibble: 40 × 22
#> type fake A1 A2 A3 A4 A5 B1 B2 B3
#> <fct> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 whisky a 1 0.0120 0.0917 0.0124 0.0248 0 -0.00112 -0.00100
#> 2 whisky a 1 0.0110 0.0918 0.0124 0.0224 0 -0.00125 -0.00280
#> 3 whisky a 1 0.0213 0.0770 0.0240 0.0140 0 -0.00637 0.00124
#> 4 whisky a 1 0.00905 0.0960 0.00971 0.0263 0 -0.000555 -0.00204
#> 5 whisky a 1 0.0208 0.0913 0.0208 0.0193 0 -0.00108 0.00113
#> 6 whisky a 1 0.0200 0.0722 0.0213 0.0119 0 -0.00215 0.00349
#> 7 whisky a 1 0.00998 0.0912 0.0122 0.0248 0 -0.000172 -0.00124
#> 8 whisky a 1 0.0197 0.0845 0.0217 0.0164 0 -0.000464 -0.00144
#> 9 whisky a 1 0.0194 0.0864 0.0214 0.0191 0 -0.00288 -0.00196
#> 10 whisky a 1 0.0128 0.0929 0.0141 0.0236 0 -0.000998 -0.00170
#> # ℹ 30 more rows
#> # ℹ 12 more variables: B4 <dbl>, B5 <dbl>, C1 <dbl>, C2 <dbl>, C3 <dbl>,
#> # C4 <dbl>, C5 <dbl>, D1 <dbl>, D2 <dbl>, D3 <dbl>, D4 <dbl>, D5 <dbl>
# PCA object
bf %>% PCA %>% as_df # all PCs by default
#> `retain` is too ambitious. All axes returned
#> # A tibble: 40 × 22
#> type fake PC1 PC2 PC3 PC4 PC5 PC6 PC7
#> <fct> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 whisky a -0.0520 -0.0226 0.00517 -0.00866 1.31e-2 -1.09e-3 -5.06e-3
#> 2 whisky a -0.0356 0.00197 -0.00880 -0.00800 1.67e-3 4.14e-3 3.06e-5
#> 3 whisky a 0.0811 -0.00232 -0.00202 0.00307 7.56e-4 3.99e-3 -3.37e-3
#> 4 whisky a -0.0694 -0.00396 -0.0115 -0.00718 -1.72e-3 4.63e-3 -1.78e-3
#> 5 whisky a -0.0146 0.0455 -0.00662 0.00305 -2.45e-5 -1.69e-2 1.31e-3
#> 6 whisky a 0.121 -0.0208 -0.00168 -0.0115 2.42e-3 2.48e-3 2.55e-3
#> 7 whisky a -0.0428 -0.0170 -0.00359 -0.000329 -3.13e-3 -1.78e-3 -4.73e-3
#> 8 whisky a 0.0343 0.00950 -0.000959 -0.00764 6.12e-3 -2.03e-3 5.70e-4
#> 9 whisky a 0.0114 0.00619 0.00207 0.00298 5.44e-3 2.31e-4 -3.57e-3
#> 10 whisky a -0.0440 0.00410 -0.00285 -0.00367 3.75e-3 -7.95e-4 2.55e-4
#> # ℹ 30 more rows
#> # ℹ 13 more variables: PC8 <dbl>, PC9 <dbl>, PC10 <dbl>, PC11 <dbl>,
#> # PC12 <dbl>, PC13 <dbl>, PC14 <dbl>, PC15 <dbl>, PC16 <dbl>, PC17 <dbl>,
#> # PC18 <dbl>, PC19 <dbl>, PC20 <dbl>
bf %>% PCA %>% as_df(2) # or 2
#> # A tibble: 40 × 4
#> type fake PC1 PC2
#> <fct> <fct> <dbl> <dbl>
#> 1 whisky a -0.0520 -0.0226
#> 2 whisky a -0.0356 0.00197
#> 3 whisky a 0.0811 -0.00232
#> 4 whisky a -0.0694 -0.00396
#> 5 whisky a -0.0146 0.0455
#> 6 whisky a 0.121 -0.0208
#> 7 whisky a -0.0428 -0.0170
#> 8 whisky a 0.0343 0.00950
#> 9 whisky a 0.0114 0.00619
#> 10 whisky a -0.0440 0.00410
#> # ℹ 30 more rows
bf %>% PCA %>% as_df(0.99) # or enough for 99%
#> # A tibble: 40 × 8
#> type fake PC1 PC2 PC3 PC4 PC5 PC6
#> <fct> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 whisky a -0.0520 -0.0226 0.00517 -0.00866 0.0131 -0.00109
#> 2 whisky a -0.0356 0.00197 -0.00880 -0.00800 0.00167 0.00414
#> 3 whisky a 0.0811 -0.00232 -0.00202 0.00307 0.000756 0.00399
#> 4 whisky a -0.0694 -0.00396 -0.0115 -0.00718 -0.00172 0.00463
#> 5 whisky a -0.0146 0.0455 -0.00662 0.00305 -0.0000245 -0.0169
#> 6 whisky a 0.121 -0.0208 -0.00168 -0.0115 0.00242 0.00248
#> 7 whisky a -0.0428 -0.0170 -0.00359 -0.000329 -0.00313 -0.00178
#> 8 whisky a 0.0343 0.00950 -0.000959 -0.00764 0.00612 -0.00203
#> 9 whisky a 0.0114 0.00619 0.00207 0.00298 0.00544 0.000231
#> 10 whisky a -0.0440 0.00410 -0.00285 -0.00367 0.00375 -0.000795
#> # ℹ 30 more rows
# LDA object
bf %>% LDA(~fake) %>% as_df
#> removed these collinear columns:A1, B1, C1
#> # A tibble: 40 × 8
#> actual predicted posterior type fake LD1 LD2 LD3
#> <fct> <fct> <dbl> <fct> <fct> <dbl> <dbl> <dbl>
#> 1 a a 1.00 whisky a -4.19 1.84 -1.56
#> 2 a a 0.997 whisky a -2.74 1.68 -0.0456
#> 3 a a 0.878 whisky a -2.26 0.171 -0.293
#> 4 a a 0.935 whisky a -3.17 -0.527 -0.611
#> 5 a a 0.997 whisky a -2.97 1.54 0.665
#> 6 a a 0.989 whisky a -4.64 -0.937 0.385
#> 7 a d 0.620 whisky a -0.109 2.26 -0.0356
#> 8 a a 0.999 whisky a -4.20 0.797 0.520
#> 9 a a 0.994 whisky a -2.97 0.925 -0.640
#> 10 a b 0.826 whisky a -1.52 -0.749 0.113
#> # ℹ 30 more rows
# same options apply