Detection methods

pdcleaner.detection.basic Module

Basic detectors

Classes

bounded(obj[, detector, lower, upper, inclusive])	Detect values outside of given bounds.
custom(obj[, detector, error_func])	Detect errors using an user-defined callable
duplicated(obj[, detector, subset, keep])	Detect duplicated elements
length(obj[, detector, lower, upper, value, ...])	Detect elements with length outside of given bounds.
missing(obj[, detector, how])	Detect elements containing missing values
quantiles(obj[, detector, lowerq, upperq, ...])	Detect errors values in a Series using quantiles.

pdcleaner.detection.types Module

Detectors related to element types

Classes

castable(obj[, detector, target])	Detect elements that cannot be casted into target type.
types(obj[, detector, ptype])	Detect elements with type errors.

pdcleaner.detection.datetimes Module

Strings detectors

Classes

date_range(obj[, detector, lower, upper, ...])

Detect if date value is between a given range.

pdcleaner.detection.values Module

Values detectors

Classes

associations(obj[, detector, count, freq])	Detects least frequent associations between two category columns
counts(obj[, detector, n])	Detect class values that appear at max n times.
enum(obj[, detector, values, forbidden])	Detect class values not in a given list.
freq(obj[, detector, freq])	Detect class values that appear less than a given freq.
value(obj[, detector, value, check_type, ...])	Detect class values different from a value.

pdcleaner.detection.gaussian Module

Gaussian detectors

Classes

iqr(obj[, detector, threshold, inclusive, ...])	Detect outliers as potential errors in a Series using the IQR method.
modzscore(obj[, detector, threshold, ...])	Detect outliers as potential errors in a Series using the modified Z-score.
zscore(obj[, detector, threshold, ...])	Detect outliers as potential errors in a Series using the Z-score method.

pdcleaner.detection.strings Module

Strings detectors

Classes

alternatives(obj[, detector, keys, keep])	Detect strings that might be alternative representations of the same thing.
pattern(obj[, detector, pattern, mode, ...])	Detect strings that do not match a given pattern.
spaces(obj[, detector, side])	Detect elements whith extra spaces before and/or after the value.

pdcleaner.detection.web Module

Web related detection methods: * email: Detect strings that do not match an email * url: Detect strings that do not match a url * ping: Detect strings that do not match a reachable url

Classes

email(obj[, detector])	'email': Detect strings that do not match an email.
ping(obj[, detector])	Detect strings that do not match a reachable url.
url(obj[, detector, check_protocol])	Detect strings that do not match a url.

pdcleaner.detection.multivariate Module

Multivariate detectors

Classes

outliers(obj[, detector, eps, min_samples])

Detects outliers in a numeric DataFrame using a clustering DBScan algorithm