Tips to avoid or fix common installation problems
+#### Alternative installation -Tips to avoid or fix common installation problems
+If you failed to install __fgeo__ try this instead: + +```R +install.packages("devtools") +devtools::install_github("forestgeo/fgeo.install") +fgeo.install::install_fgeo() +``` + +If this still fails, follow the advice below and then try to install __fgeo__ again. #### Update R, RStudio, and R packages @@ -109,6 +114,10 @@ Press Cmd/Ctrl + Shift + F10 to restart RStudio or go to _Session > Restart R_. #### Increase the rate limit to install from GitHub +If you reach GitHub's rate limit see [`usethis::browse_github_pat()`](https://usethis.r-lib.org/reference/browse_github_pat.html). + +If that was unclear continue reading. This describes the same process but in more detail. + * Ensure you have an account on GitHub (https://github.com/). * Generate a GitHub token named exactly `GITHUB_PAT` by running `usethis::browse_github_pat()` in R. * You will be sent to GitHub and you should see something like this: diff --git a/README.md b/README.md index 2fabcfc..f51cb65 100644 --- a/README.md +++ b/README.md @@ -11,11 +11,11 @@ status](https://codecov.io/gh/forestgeo/fgeo/branch/master/graph/badge.svg)](htt [](https://cran.r-project.org/package=fgeo) -**fgeo** install and loads multiple R packages to analyze forest -diversity and dynamics. It allows you to access, manipulate, and plot -[ForestGEO](https://forestgeo.si.edu/) datasets, and to do common -analyses including abundance, demography, and species-habitats -associations. +**fgeo** helps you to install, load, and access the documentation of +multiple packages to analyze forest diversity and dynamics. It allows +you to manipulate and plot [ForestGEO](http://www.forestgeo.si.edu/) +data, and to do common analyses including abundance, demography, and +species-habitats associations. - [Search functions and datasets](https://forestgeo.github.io/fgeo/articles/siteonly/reference.html) @@ -32,25 +32,16 @@ associations. - No other R session is running - Current R session is clean (click *Session \> Restart R*) -**Option 1: Install directly** +Install the latest stable version of **fgeo** with: -``` r -install.packages("devtools") -devtools::install_github("forestgeo/fgeo", upgrade = "never") -``` - -(If you reach GitHub’s rate limit see -[`usethis::browse_github_pat()`](https://usethis.r-lib.org/reference/browse_github_pat.html)). + install.packages("devtools") + devtools::install_github("forestgeo/fgeo@*release") -**Option 2: Install via -[**fgeo.install**](https://github.com/forestgeo/fgeo.install#-fgeoinstall)** +Or install the development version of **fgeo** with: ``` r install.packages("devtools") -devtools::install_github("forestgeo/fgeo.install") - -# If needed, installs dependencies from CRAN and fgeo packages from GitHub -fgeo.install::install_fgeo() +devtools::install_github("forestgeo/fgeo", upgrade = "never") ``` ----- @@ -63,6 +54,20 @@ fgeo.install::install_fgeo()Tips to avoid or fix common installation problems
+#### Alternative installation + +If you failed to install **fgeo** try this instead: + +``` r +install.packages("devtools") +devtools::install_github("forestgeo/fgeo.install") +fgeo.install::install_fgeo() +``` + +If this still fails, follow the advice below and then try to install +**fgeo** + again. + #### Update R, RStudio, and R packages - [How?](https://fgeo.netlify.com/2018/02/08/2018-02-08-update-r-rstudio-and-r-packages/) @@ -90,6 +95,12 @@ Restart R*. #### Increase the rate limit to install from GitHub +If you reach GitHub’s rate limit see +[`usethis::browse_github_pat()`](https://usethis.r-lib.org/reference/browse_github_pat.html). + +If that was unclear continue reading. This describes the same process +but in more detail. + - Ensure you have an account on GitHub (All vignettes
- Exploratory Data Analysis -
- fgeo 1.0.0 release candidate +
- fgeo 1.0.1 release candidate
- Questions and Answers
- Reference
-
@@ -121,7 +138,7 @@
Adapted for
Mauro Lepore
- 2019-01-11
+ 2019-01-14
Source: vignettes/siteonly/eda.Rmd
eda.Rmd
@@ -138,12 +155,12 @@
You will learn to explore your data systematically by using modern and powerful tools for visualization and transformation. An exploratory data analysis is an iterative process that aims to use data and some research questions to learn something that can help you refine those questions and move forward along the learning spiral.
If you are new to the tidyverse, you may feel a little frustrated at the beginning, but your effort will quickly pay-off. The tools in the tidyverse are powerful, relatively easy to use, and consistent; so once you learn some of the tools, you will learn most other tools intuitively.
library(tidyverse)
-#> -- Attaching packages -------------------------------------------------- tidyverse 1.2.1 --
+#> -- Attaching packages ----------------------------------------------- tidyverse 1.2.1 --
#> v ggplot2 3.1.0 v purrr 0.2.5
-#> v tibble 2.0.0 v dplyr 0.7.8
+#> v tibble 2.0.1 v dplyr 0.7.8
#> v tidyr 0.8.2 v stringr 1.3.1
#> v readr 1.3.1 v forcats 0.3.0
-#> -- Conflicts ----------------------------------------------------- tidyverse_conflicts() --
+#> -- Conflicts -------------------------------------------------- tidyverse_conflicts() --
#> x dplyr::filter() masks stats::filter()
#> x dplyr::lag() masks stats::lag()
We will use the dataset luquillo_stem_random from the fgeo.data package (https://forestgeo.github.io/fgeo.data/), which records trees censused in a forest plot in Luquillo, Puerto Rico.
@@ -607,13 +624,13 @@
p <- ggplot(small_dataset, aes(sp, dbh))
p + geom_point()
-#> Warning: Removed 79 rows containing missing values (geom_point).
+#> Warning: Removed 90 rows containing missing values (geom_point).
+#> Warning: Removed 90 rows containing missing values (geom_point).
eda.Rmdlibrary(tidyverse)
-#> -- Attaching packages -------------------------------------------------- tidyverse 1.2.1 --
+#> -- Attaching packages ----------------------------------------------- tidyverse 1.2.1 --
#> v ggplot2 3.1.0 v purrr 0.2.5
-#> v tibble 2.0.0 v dplyr 0.7.8
+#> v tibble 2.0.1 v dplyr 0.7.8
#> v tidyr 0.8.2 v stringr 1.3.1
#> v readr 1.3.1 v forcats 0.3.0
-#> -- Conflicts ----------------------------------------------------- tidyverse_conflicts() --
+#> -- Conflicts -------------------------------------------------- tidyverse_conflicts() --
#> x dplyr::filter() masks stats::filter()
#> x dplyr::lag() masks stats::lag()luquillo_stem_random from the fgeo.data package (https://forestgeo.github.io/fgeo.data/), which records trees censused in a forest plot in Luquillo, Puerto Rico.
p + ggbeeswarm::geom_quasirandom()
-#> Warning: Removed 79 rows containing missing values (position_quasirandom).
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
index 06bd905..15fbdde 100644
--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@@ -3,7 +3,7 @@ pkgdown: 1.3.0
pkgdown_sha: ~
articles:
eda: siteonly/eda.html
- fgeo-1-0-0-release-candidate: siteonly/fgeo-1-0-0-release-candidate.html
+ fgeo-1-0-1-release-candidate: siteonly/fgeo-1-0-1-release-candidate.html
questions-and-answers: siteonly/questions-and-answers.html
reference: siteonly/reference.html
urls:
diff --git a/docs/reference/fgeo-package.html b/docs/reference/fgeo-package.html
index e04fb0e..a29dec1 100644
--- a/docs/reference/fgeo-package.html
+++ b/docs/reference/fgeo-package.html
@@ -32,9 +32,11 @@
-
+
@@ -65,7 +67,7 @@
@@ -97,6 +99,23 @@
Exploratory data analysis
+
+
+
+
+
+
+
+
+
+
+
+
+ Changelog
+ Source:NEWS.md
+ fgeo: Analyze Forest Diversity and Dynamics
-
diff --git a/docs/reference/fgeo_browse.html b/docs/reference/fgeo_browse.html
index 07b944c..1a2fe38 100644
--- a/docs/reference/fgeo_browse.html
+++ b/docs/reference/fgeo_browse.html
@@ -63,7 +63,7 @@
@@ -95,6 +95,23 @@
Exploratory data analysis
+
+A tool to manipulate and visualize ForestGEO - datasets, and to analyze the abundance, demography, and habitats of - forest trees (<http://www.forestgeo.si.edu/>).
+Install, load, and access the documentation of + multiple packages to analyze forest diversity and dynamics. 'fgeo' + allows you to manipulate and plot ForestGEO data, and to do common + analyses including abundance, demography, and species-habitats + associations (<http://www.forestgeo.si.edu/>).