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README.Rmd
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---
output: github_document
editor_options:
chunk_output_type: console
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# D6recaptureR
<!-- badges: start -->
<!-- badges: end -->
The goal of D6recaptureR is to help us during swallow recapturing
## Installation
You can install the development version of D6recaptureR from [GitHub](https://github.com/) with:
``` r
# install.packages("devtools")
devtools::install_github("mariusgrabow/D6recaptureR")
```
## Example
This is a basic example which shows you how to handle a recapture:
1. You need a dataframe named cmr (case-sensitive) from the last years (provided by Marius). Here, we will work with one example from one bird (included in the package)
Please note: In this example, cmr has 11 rows
```{r example}
library(D6recaptureR)
cmr<-D6recaptureR::cmr_filter
nrow(cmr)
```
Imagine you recaptured bird (VH59051) and would like to know the capture history:
(You can write vh59051 or VH59051, the package corrects to Uppercase)
```{r recapture}
re(vh59051)
```
Please note, cmr has 12 rows now (one was added with the System date & time)
```{r}
nrow(cmr)
```
Let's look at the last observation, which we just added. Here, there is data missing, although we might collected it manually on the field sheets. However, this should save us a lot of time because we don't have to screen a pile of paper.
```{r}
dplyr::slice_tail(cmr,n=1)
```