R: Clean and Standardize Epidemiological Data

# Clean and Standardize Epidemiological Data

## Documentation for package ‘cleanepi’ version 1.1.2

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## 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