add logo

README.Rmd

@@ -13,7 +13,7 @@ knitr::opts_chunk$set(
 )
 ```
 
-# tidyclust
+# tidyclust <img src="man/figures/logo.svg" align="right" height="139" />
 
 <!-- badges: start -->
 [![Codecov test coverage](https://codecov.io/gh/EmilHvitfeldt/tidyclust/branch/main/graph/badge.svg)](https://app.codecov.io/gh/EmilHvitfeldt/tidyclust?branch=main)

README.md

@@ -1,7 +1,7 @@
 
 <!-- README.md is generated from README.Rmd. Please edit that file -->
 
-# tidyclust
+# tidyclust <img src="man/figures/logo.svg" align="right" height="139" />
 
 <!-- badges: start -->
 
@@ -56,38 +56,38 @@ kmeans_spec_fit <- kmeans_spec %>%
 kmeans_spec_fit
 #> tidyclust cluster object
 #> 
-#> K-means clustering with 3 clusters of sizes 9, 7, 16
+#> K-means clustering with 3 clusters of sizes 9, 16, 7
 #> 
 #> Cluster means:
 #>        mpg      cyl     disp       hp     drat       wt     qsec        vs
 #> 1 14.64444 8.000000 388.2222 232.1111 3.343333 4.161556 16.40444 0.0000000
-#> 2 17.01429 7.428571 276.0571 150.7143 2.994286 3.601429 18.11857 0.2857143
-#> 3 24.50000 4.625000 122.2937  96.8750 4.002500 2.518000 18.54312 0.7500000
+#> 2 24.50000 4.625000 122.2937  96.8750 4.002500 2.518000 18.54312 0.7500000
+#> 3 17.01429 7.428571 276.0571 150.7143 2.994286 3.601429 18.11857 0.2857143
 #>          am     gear     carb
 #> 1 0.2222222 3.444444 4.000000
-#> 2 0.0000000 3.000000 2.142857
-#> 3 0.6875000 4.125000 2.437500
+#> 2 0.6875000 4.125000 2.437500
+#> 3 0.0000000 3.000000 2.142857
 #> 
 #> Clustering vector:
 #>           Mazda RX4       Mazda RX4 Wag          Datsun 710      Hornet 4 Drive 
-#>                   3                   3                   3                   2 
+#>                   2                   2                   2                   3 
 #>   Hornet Sportabout             Valiant          Duster 360           Merc 240D 
-#>                   1                   2                   1                   3 
+#>                   1                   3                   1                   2 
 #>            Merc 230            Merc 280           Merc 280C          Merc 450SE 
-#>                   3                   3                   3                   2 
+#>                   2                   2                   2                   3 
 #>          Merc 450SL         Merc 450SLC  Cadillac Fleetwood Lincoln Continental 
-#>                   2                   2                   1                   1 
+#>                   3                   3                   1                   1 
 #>   Chrysler Imperial            Fiat 128         Honda Civic      Toyota Corolla 
-#>                   1                   3                   3                   3 
+#>                   1                   2                   2                   2 
 #>       Toyota Corona    Dodge Challenger         AMC Javelin          Camaro Z28 
-#>                   3                   2                   2                   1 
+#>                   2                   3                   3                   1 
 #>    Pontiac Firebird           Fiat X1-9       Porsche 914-2        Lotus Europa 
-#>                   1                   3                   3                   3 
+#>                   1                   2                   2                   2 
 #>      Ford Pantera L        Ferrari Dino       Maserati Bora          Volvo 142E 
-#>                   1                   3                   1                   3 
+#>                   1                   2                   1                   2 
 #> 
 #> Within cluster sum of squares by cluster:
-#> [1] 46659.32 11846.09 32838.00
+#> [1] 46659.32 32838.00 11846.09
 #>  (between_SS / total_SS =  85.3 %)
 #> 
 #> Available components:
@@ -139,7 +139,7 @@ extract_centroids(kmeans_spec_fit)
 #> # A tibble: 3 × 12
 #>   .cluster    mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
 #>   <chr>     <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
-#> 1 Cluster_1  24.5  4.62  122.  96.9  4.00  2.52  18.5 0.75  0.688  4.12  2.44
-#> 2 Cluster_2  17.0  7.43  276. 151.   2.99  3.60  18.1 0.286 0      3     2.14
-#> 3 Cluster_3  14.6  8     388. 232.   3.34  4.16  16.4 0     0.222  3.44  4
+#> 1 Cluster_1  17.0  7.43  276. 151.   2.99  3.60  18.1 0.286 0      3     2.14
+#> 2 Cluster_2  14.6  8     388. 232.   3.34  4.16  16.4 0     0.222  3.44  4   
+#> 3 Cluster_3  24.5  4.62  122.  96.9  4.00  2.52  18.5 0.75  0.688  4.12  2.44
 ```