README.md

In 044mj/cvera: Utility Functions For Use With bTB Testing Datasets

cvera

cvera is an R package with a collection of utility R functions, useful in exploring Irish bTB datasets collated in CVERA.

Installation

You can install the development version of cvera from GitHub with:

# install.packages("devtools")
devtools::install_github("044mj/cvera")

Example

Extract yearly summary data and visualisations of reactor numbers from master_tb dataset.

Read in data:

library(tidyverse)
# if using readr::read_csv() they use first 1000 rows to guess type. 
# If the first 1,000 are missing, it will default to logical. GIF variables are missing in the first 1000
#because it only came in during May 2019 so include col_types for these variables:
master_tb <- read_csv("data/master_tb_24_Mar_2022.csv", 
                          col_types = cols(.default = "?", 
                                           gif_actual_date = col_date(), 
                                           gif_cases = col_number(),
                                           sequence_number = col_character()))

Using all_cases_per_year from cvera package:

library(cvera)
#drop 2022 figures as we only have 3 months worth of data
cases <- all_cases_per_year(master_tb, drop_years = c(2022))

results in

#> [[1]]
#> # A tibble: 17 × 5
#>     year skin_test_reactors slaughter_detected gif_cases all_cases
#>    <int>              <dbl>              <int>     <int>     <dbl>
#>  1  2005              25975               2709        NA     28684
#>  2  2006              24159               3215        NA     27374
#>  3  2007              27735               3421        NA     31156
#>  4  2008              29901               3003        NA     32904
#>  5  2009              23820               2714        NA     26534
#>  6  2010              20218               2680        NA     22898
#>  7  2011              18557               1905        NA     20462
#>  8  2012              18499               2015        NA     20514
#>  9  2013              15680               1962        NA     17642
#> 10  2014              16139               1709        NA     17848
#> 11  2015              15364               1583        NA     16947
#> 12  2016              16967               1516        NA     18483
#> 13  2017              17336               1628        NA     18964
#> 14  2018              17548               1657        NA     19205
#> 15  2019              14323               1671      2456     18450
#> 16  2020              17685               2048      4920     24653
#> 17  2021              15401               1706      5527     22634
#> 
#> [[2]]
#> Warning: Removed 14 row(s) containing missing values (geom_path).
#> Warning: Removed 14 rows containing missing values (geom_point).

Interactive herd plot:

p <- herd_plot(master_tb, "x1234567") #fake herd
p

Create BD file - summary of all BDs

bd_df <- bd_dataset_fun(master_tb)

Check if BD occured during particular years

bd_df <- bd_during_year(bd_df, years_to_check = c(2005:2006))

Helper function to select core variables

master_tb %>%
 filter(total_reactor_skin > 10) %>%
 core_vars()

Create indicator variable if herd had BD within e.g. 365 days prior to current one

bd_df <- bd_within_time_period(bd_df, 2016, 730)

044mj/cvera documentation built on Feb. 13, 2023, 10:02 p.m.