diff --git a/.Rbuildignore b/.Rbuildignore
index a4b65f7a..0324217f 100644
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -1,3 +1,5 @@
+^docs$
+^_pkgdown\.yml$
^.*\.Rproj$
^\.Rproj\.user$
^\.travis\.yml$
diff --git a/.gitignore b/.gitignore
index 68053194..75f33539 100644
--- a/.gitignore
+++ b/.gitignore
@@ -5,3 +5,4 @@
skimr.Rproj
inst/doc
.DS_Store
+docs/
diff --git a/.travis.yml b/.travis.yml
index 6b2494bd..af8ec7e0 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -10,6 +10,13 @@ before_install:
- echo "options(repos = c(CRAN='http://cran.rstudio.com'))" > ~/.Rprofile
r_github_packages:
- jimhester/covr
-
after_success:
- Rscript -e 'covr::codecov(line_exclusions = list("R/skim_print.R" = c(147, 167, 178:180, 190)))'
+before_cache:
+ - Rscript -e 'remotes::install_cran("pkgdown"); remotes::install_github("ropenscilabs/rotemplate")'
+deploy:
+ provider: script
+ script: Rscript -e 'pkgdown::deploy_site_github()'
+ skip_cleanup: true
+ on:
+ tags: true
diff --git a/README.Rmd b/README.Rmd
index 7cdf7b60..c721edce 100644
--- a/README.Rmd
+++ b/README.Rmd
@@ -3,7 +3,7 @@ output:
md_document
---
-# skimr
+# skimr
```{r set-options, echo=FALSE, message=FALSE}
library(pander)
library(knitr)
@@ -32,7 +32,7 @@ following:
``` r
# install.packages("devtools")
-devtools::install_github("ropenscilabs/skimr")
+devtools::install_github("ropensci/skimr")
```
The APIs for this branch should be considered reasonably stable but still
subject to change if an issue is discovered.
diff --git a/README.md b/README.md
index 7f22c7dd..b6835ae1 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,7 @@
-skimr
-===========================================================================
+
+skimr
+===================================================================
[![Build
Status](https://travis-ci.org/ropensci/skimr.svg?branch=master)](https://travis-ci.org/ropensci/skimr)
@@ -23,7 +24,7 @@ CRAN. If you wish to install the current build of the next release you
can do so using the following:
# install.packages("devtools")
- devtools::install_github("ropenscilabs/skimr")
+ devtools::install_github("ropensci/skimr")
The APIs for this branch should be considered reasonably stable but
still subject to change if an issue is discovered.
@@ -44,7 +45,7 @@ Skim statistics in the console
missing, complete, n, and sd.
- reports each data types separately
- handles dates, logicals, and a variety of other types
-- supports spark-bar and spark-line based on [Hadley Wickham's pillar
+- supports spark-bar and spark-line based on [Hadley Wickham’s pillar
package](https://github.com/hadley/pillar).
### Separates variables by class:
@@ -55,11 +56,11 @@ Skim statistics in the console
## n obs: 71
## n variables: 2
##
- ## ── Variable type:factor ─────────────────────────────────────────────────────────────
+ ## ── Variable type:factor ──────────────────────────────────────────────────────────────
## variable missing complete n n_unique top_counts ordered
## feed 0 71 71 6 soy: 14, cas: 12, lin: 12, sun: 12 FALSE
##
- ## ── Variable type:numeric ────────────────────────────────────────────────────────────
+ ## ── Variable type:numeric ─────────────────────────────────────────────────────────────
## variable missing complete n mean sd p0 p25 p50 p75 p100 hist
## weight 0 71 71 261.31 78.07 108 204.5 258 323.5 423 ▃▅▅▇▃▇▂▂
@@ -71,11 +72,11 @@ Skim statistics in the console
## n obs: 150
## n variables: 5
##
- ## ── Variable type:factor ─────────────────────────────────────────────────────────────
+ ## ── Variable type:factor ──────────────────────────────────────────────────────────────
## variable missing complete n n_unique top_counts ordered
## Species 0 150 150 3 set: 50, ver: 50, vir: 50, NA: 0 FALSE
##
- ## ── Variable type:numeric ────────────────────────────────────────────────────────────
+ ## ── Variable type:numeric ─────────────────────────────────────────────────────────────
## variable missing complete n mean sd p0 p25 p50 p75 p100 hist
## Petal.Length 0 150 150 3.76 1.77 1 1.6 4.35 5.1 6.9 ▇▁▁▂▅▅▃▁
## Petal.Width 0 150 150 1.2 0.76 0.1 0.3 1.3 1.8 2.5 ▇▁▁▅▃▃▂▂
@@ -90,7 +91,7 @@ Skim statistics in the console
## n obs: 87
## n variables: 13
##
- ## ── Variable type:character ──────────────────────────────────────────────────────────
+ ## ── Variable type:character ───────────────────────────────────────────────────────────
## variable missing complete n min max empty n_unique
## eye_color 0 87 87 3 13 0 15
## gender 3 84 87 4 13 0 4
@@ -100,17 +101,17 @@ Skim statistics in the console
## skin_color 0 87 87 3 19 0 31
## species 5 82 87 3 14 0 37
##
- ## ── Variable type:integer ────────────────────────────────────────────────────────────
+ ## ── Variable type:integer ─────────────────────────────────────────────────────────────
## variable missing complete n mean sd p0 p25 p50 p75 p100 hist
## height 6 81 87 174.36 34.77 66 167 180 191 264 ▁▁▁▂▇▃▁▁
##
- ## ── Variable type:list ───────────────────────────────────────────────────────────────
+ ## ── Variable type:list ────────────────────────────────────────────────────────────────
## variable missing complete n n_unique min_length median_length max_length
## films 0 87 87 24 1 1 7
## starships 0 87 87 17 0 0 5
## vehicles 0 87 87 11 0 0 2
##
- ## ── Variable type:numeric ────────────────────────────────────────────────────────────
+ ## ── Variable type:numeric ─────────────────────────────────────────────────────────────
## variable missing complete n mean sd p0 p25 p50 p75 p100 hist
## birth_year 44 43 87 87.57 154.69 8 35 52 72 896 ▇▁▁▁▁▁▁▁
## mass 28 59 87 97.31 169.46 15 55.6 79 84.5 1358 ▇▁▁▁▁▁▁▁
@@ -137,7 +138,7 @@ Skim statistics in the console
## n obs: 150
## n variables: 5
##
- ## ── Variable type:numeric ────────────────────────────────────────────────────────────
+ ## ── Variable type:numeric ─────────────────────────────────────────────────────────────
## variable missing complete n mean sd p0 p25 p50 p75 p100 hist
## Petal.Length 0 150 150 3.76 1.77 1 1.6 4.35 5.1 6.9 ▇▁▁▂▅▅▃▁
## Sepal.Length 0 150 150 5.84 0.83 4.3 5.1 5.8 6.4 7.9 ▂▇▅▇▆▅▂▂
@@ -153,7 +154,7 @@ Skim statistics in the console
## n variables: 5
## group variables: Species
##
- ## ── Variable type:numeric ────────────────────────────────────────────────────────────
+ ## ── Variable type:numeric ─────────────────────────────────────────────────────────────
## Species variable missing complete n mean sd p0 p25 p50 p75 p100 hist
## setosa Petal.Length 0 50 50 1.46 0.17 1 1.4 1.5 1.58 1.9 ▁▁▅▇▇▅▂▁
## setosa Petal.Width 0 50 50 0.25 0.11 0.1 0.2 0.2 0.3 0.6 ▂▇▁▂▂▁▁▁
@@ -162,11 +163,7 @@ Skim statistics in the console
## versicolor Petal.Length 0 50 50 4.26 0.47 3 4 4.35 4.6 5.1 ▁▃▂▆▆▇▇▃
## versicolor Petal.Width 0 50 50 1.33 0.2 1 1.2 1.3 1.5 1.8 ▆▃▇▅▆▂▁▁
## versicolor Sepal.Length 0 50 50 5.94 0.52 4.9 5.6 5.9 6.3 7 ▃▂▇▇▇▃▅▂
- ## versicolor Sepal.Width 0 50 50 2.77 0.31 2 2.52 2.8 3 3.4 ▁▂▃▅▃▇▃▁
- ## virginica Petal.Length 0 50 50 5.55 0.55 4.5 5.1 5.55 5.88 6.9 ▂▇▃▇▅▂▁▂
- ## virginica Petal.Width 0 50 50 2.03 0.27 1.4 1.8 2 2.3 2.5 ▂▁▇▃▃▆▅▃
- ## virginica Sepal.Length 0 50 50 6.59 0.64 4.9 6.23 6.5 6.9 7.9 ▁▁▃▇▅▃▂▃
- ## virginica Sepal.Width 0 50 50 2.97 0.32 2.2 2.8 3 3.18 3.8 ▁▃▇▇▅▃▁▂
+ ## [ reached getOption("max.print") -- omitted 5 rows ]
Knitted results
---------------
@@ -187,7 +184,7 @@ results may differ (see vignettes for details).
### Option for kable.
-Note that the results='asis' chunk option is used and the `skimr::`
+Note that the results=‘asis’ chunk option is used and the `skimr::`
namespace is used to prevent it being replaced by knitr::kable (which
will result in the long skim\_df object being printed.)
@@ -202,24 +199,24 @@ Variable type: factor
-Species |
-0 |
-150 |
-150 |
-3 |
-set: 50, ver: 50, vir: 50, NA: 0 |
-FALSE |
+Species |
+0 |
+150 |
+150 |
+3 |
+set: 50, ver: 50, vir: 50, NA: 0 |
+FALSE |
@@ -229,76 +226,76 @@ Variable type: numeric
-Petal.Length |
-0 |
-150 |
-150 |
-3.76 |
-1.77 |
-1 |
-1.6 |
-4.35 |
-5.1 |
-6.9 |
-▇▁▁▂▅▅▃▁ |
+Petal.Length |
+0 |
+150 |
+150 |
+3.76 |
+1.77 |
+1 |
+1.6 |
+4.35 |
+5.1 |
+6.9 |
+▇▁▁▂▅▅▃▁ |
-Petal.Width |
-0 |
-150 |
-150 |
-1.2 |
-0.76 |
-0.1 |
-0.3 |
-1.3 |
-1.8 |
-2.5 |
-▇▁▁▅▃▃▂▂ |
+Petal.Width |
+0 |
+150 |
+150 |
+1.2 |
+0.76 |
+0.1 |
+0.3 |
+1.3 |
+1.8 |
+2.5 |
+▇▁▁▅▃▃▂▂ |
-Sepal.Length |
-0 |
-150 |
-150 |
-5.84 |
-0.83 |
-4.3 |
-5.1 |
-5.8 |
-6.4 |
-7.9 |
-▂▇▅▇▆▅▂▂ |
+Sepal.Length |
+0 |
+150 |
+150 |
+5.84 |
+0.83 |
+4.3 |
+5.1 |
+5.8 |
+6.4 |
+7.9 |
+▂▇▅▇▆▅▂▂ |
-Sepal.Width |
-0 |
-150 |
-150 |
-3.06 |
-0.44 |
-2 |
-2.8 |
-3 |
-3.3 |
-4.4 |
-▁▂▅▇▃▂▁▁ |
+Sepal.Width |
+0 |
+150 |
+150 |
+3.06 |
+0.44 |
+2 |
+2.8 |
+3 |
+3.3 |
+4.4 |
+▁▂▅▇▃▂▁▁ |
@@ -313,50 +310,50 @@ Skim summary statistics
n obs: 150
n variables: 5
-
+
Table continues below
-
-
-
-
-
+
+
+
+
+
-Species |
-0 |
-150 |
-150 |
-3 |
+Species |
+0 |
+150 |
+150 |
+3 |
-
+
-
-
+
+
-set: 50, ver: 50, vir: 50, NA: 0 |
-FALSE |
+set: 50, ver: 50, vir: 50, NA: 0 |
+FALSE |
@@ -364,110 +361,110 @@ n variables: 5
Table continues below
-
-
-
-
-
-
-
-
-
-
+
+
+
+
+
+
+
+
+
+
-Petal.Length |
-0 |
-150 |
-150 |
-3.76 |
-1.77 |
-1 |
-1.6 |
-4.35 |
-5.1 |
+Petal.Length |
+0 |
+150 |
+150 |
+3.76 |
+1.77 |
+1 |
+1.6 |
+4.35 |
+5.1 |
-Petal.Width |
-0 |
-150 |
-150 |
-1.2 |
-0.76 |
-0.1 |
-0.3 |
-1.3 |
-1.8 |
+Petal.Width |
+0 |
+150 |
+150 |
+1.2 |
+0.76 |
+0.1 |
+0.3 |
+1.3 |
+1.8 |
-Sepal.Length |
-0 |
-150 |
-150 |
-5.84 |
-0.83 |
-4.3 |
-5.1 |
-5.8 |
-6.4 |
+Sepal.Length |
+0 |
+150 |
+150 |
+5.84 |
+0.83 |
+4.3 |
+5.1 |
+5.8 |
+6.4 |
-Sepal.Width |
-0 |
-150 |
-150 |
-3.06 |
-0.44 |
-2 |
-2.8 |
-3 |
-3.3 |
+Sepal.Width |
+0 |
+150 |
+150 |
+3.06 |
+0.44 |
+2 |
+2.8 |
+3 |
+3.3 |
-
+
-
-
+
+
-6.9 |
-▇▁▁▂▅▅▃▁ |
+6.9 |
+▇▁▁▂▅▅▃▁ |
-2.5 |
-▇▁▁▅▃▃▂▂ |
+2.5 |
+▇▁▁▅▃▃▂▂ |
-7.9 |
-▂▇▅▇▆▅▂▂ |
+7.9 |
+▂▇▅▇▆▅▂▂ |
-4.4 |
-▁▂▅▇▃▂▁▁ |
+4.4 |
+▁▂▅▇▃▂▁▁ |
@@ -485,30 +482,24 @@ produces a long, tidy-format `skim_df` object that can be computed on.
print.data.frame(skim(chickwts))
- ## variable type stat level value formatted
- ## 1 weight numeric missing .all 0.0000 0
- ## 2 weight numeric complete .all 71.0000 71
- ## 3 weight numeric n .all 71.0000 71
- ## 4 weight numeric mean .all 261.3099 261.31
- ## 5 weight numeric sd .all 78.0737 78.07
- ## 6 weight numeric p0 .all 108.0000 108
- ## 7 weight numeric p25 .all 204.5000 204.5
- ## 8 weight numeric p50 .all 258.0000 258
- ## 9 weight numeric p75 .all 323.5000 323.5
- ## 10 weight numeric p100 .all 423.0000 423
- ## 11 weight numeric hist .all NA ▃▅▅▇▃▇▂▂
- ## 12 feed factor missing .all 0.0000 0
- ## 13 feed factor complete .all 71.0000 71
- ## 14 feed factor n .all 71.0000 71
- ## 15 feed factor n_unique .all 6.0000 6
- ## 16 feed factor top_counts soybean 14.0000 soy: 14
- ## 17 feed factor top_counts casein 12.0000 cas: 12
- ## 18 feed factor top_counts linseed 12.0000 lin: 12
- ## 19 feed factor top_counts sunflower 12.0000 sun: 12
- ## 20 feed factor top_counts meatmeal 11.0000 mea: 11
- ## 21 feed factor top_counts horsebean 10.0000 hor: 10
- ## 22 feed factor top_counts 0.0000 NA: 0
- ## 23 feed factor ordered .all 0.0000 FALSE
+ ## variable type stat level value formatted
+ ## 1 weight numeric missing .all 0.0000 0
+ ## 2 weight numeric complete .all 71.0000 71
+ ## 3 weight numeric n .all 71.0000 71
+ ## 4 weight numeric mean .all 261.3099 261.31
+ ## 5 weight numeric sd .all 78.0737 78.07
+ ## 6 weight numeric p0 .all 108.0000 108
+ ## 7 weight numeric p25 .all 204.5000 204.5
+ ## 8 weight numeric p50 .all 258.0000 258
+ ## 9 weight numeric p75 .all 323.5000 323.5
+ ## 10 weight numeric p100 .all 423.0000 423
+ ## 11 weight numeric hist .all NA ▃▅▅▇▃▇▂▂
+ ## 12 feed factor missing .all 0.0000 0
+ ## 13 feed factor complete .all 71.0000 71
+ ## 14 feed factor n .all 71.0000 71
+ ## 15 feed factor n_unique .all 6.0000 6
+ ## 16 feed factor top_counts soybean 14.0000 soy: 14
+ ## [ reached 'max' / getOption("max.print") -- omitted 7 rows ]
### Compute on the full `skim_df` object
@@ -555,7 +546,7 @@ data.
## n obs: 150
## n variables: 5
##
- ## ── Variable type:numeric ────────────────────────────────────────────────────────────
+ ## ── Variable type:numeric ─────────────────────────────────────────────────────────────
## variable iqr quantile
## Sepal.Length 1.3 7.7
@@ -611,13 +602,13 @@ knit them to a specific document format. The same session that produces
a correctly rendered HTML document may produce an incorrectly rendered
PDF, for example. This issue can generally be addressed by changing
fonts to one with good building block (for histograms) and Braille
-support (for line graphs). For example, the open font "DejaVu Sans" from
+support (for line graphs). For example, the open font “DejaVu Sans” from
the `extrafont` package supports these. You may also want to try
wrapping your results in `knitr::kable()`. Please see the vignette on
using fonts for details.
Displays in documents of different types will vary. For example, one
-user found that the font "Yu Gothic UI Semilight" produced consistent
+user found that the font “Yu Gothic UI Semilight” produced consistent
results for Microsoft Word and Libre Office Write.
Contributing
diff --git a/_pkgdown.yml b/_pkgdown.yml
new file mode 100644
index 00000000..4c9dd064
--- /dev/null
+++ b/_pkgdown.yml
@@ -0,0 +1,30 @@
+template:
+ package: rotemplate
+
+destination: docs
+
+toc:
+ depth: 3
+
+navbar:
+ title: "skmir"
+ left:
+ - icon: fa-home
+ href: index.html
+ - text: "News"
+ href: news/index.html
+ - text: "Articles"
+ menu:
+ - text: Using skimr
+ href: articles/Using_skimr.html
+ - text: Using fonts
+ href: articles/Using_fonts.html
+ - text: skimr defaults
+ href: articles/Skimr_defaults.html
+ - text: Supporting additional objects
+ href: articles/Supporting_additional_objects.html
+ - text: "Reference"
+ href: reference/index.html
+ right:
+ - icon: fa-github
+href: https://github.com/ropensci/skimr
diff --git a/inst/figures/skimmer_hex.png b/man/figures/logo.png
similarity index 100%
rename from inst/figures/skimmer_hex.png
rename to man/figures/logo.png
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