Translation: So far I have only translated documentation with Google Scholar, so I would appreciate help translating from English to Portuguese or correcting any mistranslations!
This repository houses the bdffpRain package and the raw data and
wrangling code used to produce the bdffp_rain (English) and
pdbff_chuva (Portuguese) datasets.
The bdffpRain R package contains cleaned daily precipitation data from
8 rain gauges at the Biological Dynamics of Forest Fragments Project
between 1987 and 2010.
To install the package run:
install.packages("remotes") remotes::install_github("BrunaLab/bdffpRain")
The data is in bdffp_rain, which looks like this:
library(bdffpRain) data("bdffp_rain") head(bdffp_rain) #> # A tibble: 6 ×ばつ 10 #> site lat lon date doy time observer precip notes flag #> <chr> <dbl> <dbl> <date> <dbl> <chr> <chr> <dbl> <chr> <chr> #> 1 km37 -2.43 -59.8 2004年10月04日 278 14:20 Rogerio 14 <NA> <NA> #> 2 km37 -2.43 -59.8 2004年10月05日 279 <NA> <NA> NA <NA> <NA> #> 3 km37 -2.43 -59.8 2004年10月06日 280 07:30 Rogerio 2.6 <NA> U #> 4 km37 -2.43 -59.8 2004年10月07日 281 <NA> <NA> NA <NA> <NA> #> 5 km37 -2.43 -59.8 2004年10月08日 282 12:30 Apostolo 36.8 <NA> U #> 6 km37 -2.43 -59.8 2004年10月09日 283 07:30 Rogerio 14.8 <NA> <NA>
Check the help file for detailed metadata with ?bdffp_rain.
If you are interested in the raw data or the code used to clean and
wrangle those data, you can fork this repository, or download it with
the green "Code" button on this page. You’ll find the raw data in a
series of .XLS files in the "data_raw" directory and annotated
wrangling code in the "wrangling" directory.
If you wish to use this data for a publication, please cite:
"Scott, Eric R. & Emilio M. Bruna. 2022. BrunaLab/bdffpRain (v0.0.1). Zenodo. https://doi.org/10.5281/zenodo.6557721"If you prefer the citation in .bib format you can copy it here:
@software{eric_r_scott_2022_6557721, author = {Eric R Scott and Emilio M. Bruna}, title = {BrunaLab/bdffpRain}, month = may, year = 2022, publisher = {Zenodo}, version = {v0.0.1}, doi = {10.5281/zenodo.6557721}, url = {https://doi.org/10.5281/zenodo.6557721}, }
The vignette for the package shows an example of how to use imputation to "fill in" missing observations and produce a complete dataset that can be used to produce figures and summary statistics for monthly precipitation at BDFFP.
Additionally, there is old, probably broken code in the "notes"
directory that may be useful.
If you find mistakes or issues or would like to suggest improvements, please file an issue.