clean_data: Data cleaning according to Questionnaire Responses.

In bdclean: A User-Friendly Biodiversity Data Cleaning App for the Inexperienced R User

Description

Use run_questionnaire to add Questionnaire Responses and pass it to this function to process the data faster.

Usage

clean_data(data, custom_questionnaire = NULL, clean = TRUE,
  missing = FALSE, report = TRUE, format = c("html_document",
  "pdf_document"))

Arguments

data	Biodiversity data in a data frame
custom_questionnaire	Custom user created questionnaire responses if to pypass answering questions each time.
clean	Whether to clean after flagging. If false only flagging will be done.
missing	How to treat data with missing values. Default: false - will be treated as bad data.
report	Whether to print report of cleaning done.
format	Formats of the cleaning report required. Options are: Markdown, HTML or / and PDF

Details

Use create_default_questionnaire to create default questionnaire object. You can add your custom questions to this questionnaire and then pass it to this function to process the data.

Value

data frame with clean data

Examples

custom_questionnaire <- create_default_questionnaire()

if(interactive()){

library(rgbif)
occdat <- occ_data(
  country = 'AU', # Country code for australia
  classKey = 359, # Class code for mammalia
  limit = 50 # Get only 50 records
)
myData <- occdat$data

responses <- run_questionnaire()
cleaned_data <- clean_data(myData, responses)

cleaned_data2 <- clean_data(myData)

} 

bdclean documentation built on May 1, 2019, 10:54 p.m.