Clean and Standardize Epidemiological Data


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Documentation for package ‘cleanepi’ version 1.0.2

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add_to_dictionary Add an element to the data dictionary
add_to_report Add an element to the report object
check_date_sequence Check whether the order of the sequence of date-events is valid
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_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.
print_report Generate report from data cleaning operations
remove_constants Remove empty rows and columns and constant column
remove_duplicates Remove duplicates
replace_missing_values Replace missing values with 'NA'
scan_data Scan a data frame to determine the percentage of 'missing', 'numeric', 'Date', 'character', and 'logical' values in every column.
standardize_column_names Standardize column names of a data frame or linelist
standardize_dates Standardize date variables
timespan Calculate time span between dates