In the-pudding/puddingR: Pudding Helper Functions

knitr::opts_chunk$set(echo = TRUE)

`r params$filename`.csv

What is this?: ADD A DESCRIPTION OF YOUR DATASET. 1-2 SUCCINCT SENTENCES
Source(s) & Methods: HOW WAS THIS DATA COLLECTED? INCLUDE ALL RELEVANT LINKS AND CODE USED TO PROCESS DATA.
Last Modified: r format(Sys.time(), '%B %d, %Y')
Contact Information: YOUR NAME
Spatial Applicability: ADD INFO ABOUT SPATIAL BOUNDARIES OF DATA (e.g., United States, Global, etc.)
Temporal Applicability: WHAT IS THE TIME RANGE REPRESENTED IN THE DATA? (e.g., if data represents all musical hits from January 2015 - December 2017, this value would be January 01, 2015 - December 31, 2017). The more granular the date range, the better.
Observations (Rows): There are r nrow(params$data) rows in this dataset. DESCRIBE WHAT EACH ROW REPRESENTS.
Variables (Columns): There are r ncol(params$data) columns in this dataset. They are described below:

# DONT EDIT THIS CODE CHUNK
data <- params$data

# gather column names in a table
meta <- tibble::enframe(colnames(data), name = NULL) %>% 
  dplyr::rename("Header" = value) %>% 
  dplyr::rowwise() %>% 
  dplyr::mutate("Description" = case_when(
    class(data[[Header]]) == "factor" ~ paste0("levels: ", paste0(levels(data[[Header]]), sep = "", collapse = ", ")),
    TRUE ~ "ENTER DESCRIPTION OF THIS COLUMN HERE"
  )) %>% 
  dplyr::mutate("Data Type" = class(data[[Header]]))

knitr::kable(meta, format = "markdown")

Other Notes: Include any other relevant notes/calculations/code here.
Analysis Session Info: Including any relevant data processing scripts is great practice (seriously, good job! 🎉), but for anyone who wants to run your script, they need a little more info. At the very least, make sure that you include any of your session info, so things like:
What software you are using (including version number)
What packages are you using (including version number)
anything else that would help someone re-run your analysis given only the information/data provided in this repo.