In al-obrien/farrago: A random collection of helpful code baubles

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farrago

{farrago} is an R package serving as a collection of tools for data workflows and analysis, with focus on health surveillance data. Although {farrago} primarily serves as a personal collection of odds-and-ends picked-up or created over the past several years, it may assist wider audiences as well. The package is organized by general purpose/functionality, which may eventually be separated into discrete packages.

Installation

{farrago} is only available from GitHub and the latest version can be installed with:

``` {r, eval = FALSE}

install.packages("devtools")

devtools::install_github("al-obrien/farrago")

## Use-cases

{farrago} has a variety of functions available. They are roughly organized into the following categories:

1.  **Calculations:** provides algorithms for some routine processes such as...

    -   Determining pregnancy trimesters

    -   Assigning episode periods (e.g. for repeat infections)

    -   Collapsing time-steps

    -   Determining overlaps in time

    -   Basic metrics such as rates, max/min, etc.

2.  **Conversions:** helper functions to convert between common formats in epidemiology

    -   Replace all blank values to NA (e.g. when importing data from SAS)

    -   Switch between flu and calendar weeks

    -   Determine flu season from date

    -   Quickly convert a table to image (png)

    -   Basic conversions such as from numbers to percent, number to factor, etc.

3.  **Creation:** generate new content

    -   Make multi-level factors similar to SAS 'multi-label' functionality

    -   Create hypercubes (i.e. n-dimensional table including group summaries and totals)

    -   Determine break points from set of values

4.  **Transferal:** methods to move objects and data

    -   Easily `stow()` and `retrieve()` data-sets to make efficient use of RAM

    -   File transfer using WinSCP wrapper

    -   Locate files

    -   Pass code and retrieve data from SAS (primarily for use with Classic 9.4)

5.  **Plotting:** helper functions for shared legends and less common plots such as bulls-eye charts and X-splines

6.  **Miscellaneous**

## Example

This is a basic example using a sub-set of functions from {farrago}...

```r
# Load libraries
library(farrago)
library(magrittr)
library(dplyr)
library(lubridate)

# Download from configured SFTP location
transfer_winscp(file ='my_rmt_file.csv'),
               direction = 'download',
               connection = 'sftp://myusername:[e-mail]/'
               rmt_path = './location/',
               drop_location = 'C:/PATH/TO/DESIRED/FOLDER/')

``` {r, message = FALSE}

Non-sense data for example

my_rmt_file <- tibble::tribble(~grp_id, ~date, ~date_of_birth, ~condition, ~date_of_birth_child, 1, '2020-01-01', '1970-06-04', 'alive', '1991-01-01', 1, '2020-01-01', '1980-04-05', '', '1990-02-04', 1, '2020-01-03', '1930-04-05', 'alive', '', 1, '2020-01-04', '1967-04-05', 'alive', '1998-01-21', 2, '2020-01-01', '1978-04-05', 'alive', '1998-06-21', 2, '2020-09-10', '1970-04-05', 'alive', '1992-09-13', 2, '2020-09-21', '1949-04-05', 'dead', '1987-01-03', 3, '2020-01-01', '1977-04-05', '', '1992-01-21', 3, '2020-01-02', '1944-04-05', 'alive', '', 3, '2020-01-21', '1943-06-05', 'alive', '1967-09-12', 3, '2020-01-22', '1969-07-05', 'alive', '2006-12-21', 3, '2020-04-22', '', NA, NA, 3, '2021-06-09', '1978-09-21', 'dead', '1992-01-21') %>% dplyr::mutate_at(vars(contains('date')), ymd)

Remove blanks

my_rmt_file <- convert_blank2NA(my_rmt_file)

Determine episode period based on first date by group

my_rmt_file$episode <- assign_episode(data = my_rmt_file, grp_id = grp_id, date = date, threshold = 10)

Determine age and age group from date

my_rmt_file$age <- calculate_age(my_rmt_file$date_of_birth) my_rmt_file$age_grp <- create_breaks(my_rmt_file$age, breaks = c(0, 10, 20, 30, 40, 50, 60, 70, 80, 90), format = TRUE)

Calculate trimester based on dob (of child)

my_rmt_file <- calculate_trimesters(my_rmt_file, date_of_birth_child)

View final dataset

knitr::kable(my_rmt_file)

```r
# Save file for easy retrieval later
my_rmt_file_stowed <- stow(my_rmt_file, cleanup = TRUE)

al-obrien/farrago documentation built on April 14, 2023, 6:20 p.m.