Clean and Standardize Epidemiological Data

---

Documentation for package ‘cleanepi’ version 1.1.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

add_to_dictionary	Add an element to the data dictionary
add_to_report	Add an element to the report object
check_date_sequence	Checks whether the order in a sequence of date events is chronological. order.
check_subject_ids	Check whether the subject IDs comply with the expected format. When incorrect IDs are found, the function sends a warning and the user can call the 'correct_subject_ids' function to correct them.
clean_data	Clean and standardize data
clean_using_dictionary	Perform dictionary-based cleaning
common_na_strings	Common strings representing missing values
convert_numeric_to_date	Convert numeric to date
convert_to_numeric	Convert columns into numeric
correct_misspelled_values	Correct misspelled values by using approximate string matching techniques to compare them against the expected values.
correct_subject_ids	Correct the wrong subject IDs based on the user-provided values.
find_duplicates	Identify and return duplicated rows in a data frame or linelist.
get_default_params	Set and return 'clean_data' default parameters
print_report	Generate report from data cleaning operations
remove_constants	Remove constant data, including empty rows, empty columns, and columns with constant values.
remove_duplicates	Remove duplicates
replace_missing_values	Replace missing values with 'NA'
scan_data	Scan through a data frame and return the proportion of 'missing', 'numeric', 'Date', 'character', 'logical' values.
standardize_column_names	Standardize column names of a data frame or line list
standardize_dates	Standardize date variables
timespan	Calculate time span between dates