Index

_

__contains__() (tseda.core.TimeSeries method), [1] (tseda.core.timeseries.TimeSeries method), [1] (tseda.TimeSeries method) __getitem__() (tseda.core.TimeSeries method), [1] (tseda.core.timeseries.TimeSeries method), [1] (tseda.TimeSeries method) __init__() (tseda.anomaly.AnomalyReport method), [1] (tseda.anomaly.detector.AnomalyReport method), [1] (tseda.changepoint.ChangepointReport method) (tseda.changepoint.detector.ChangepointReport method) (tseda.core.TimeSeries method), [1] (tseda.core.timeseries.TimeSeries method), [1] (tseda.decomposition.classical.DecompositionResult method), [1] (tseda.decomposition.DecompositionResult method), [1] (tseda.forecastability.ForecastabilityReport method), [1] (tseda.forecastability.leakage.LeakageReport method), [1] (tseda.forecastability.LeakageReport method), [1] (tseda.forecastability.scorer.ForecastabilityReport method), [1] (tseda.quality.duplicates.FlatlineReport method), [1] (tseda.quality.FlatlineReport method), [1] (tseda.quality.missing.MissingValueReport method), [1] (tseda.quality.MissingValueReport method), [1] (tseda.quality.OutlierReport method), [1] (tseda.quality.outliers.OutlierReport method), [1] (tseda.seasonality.detector.SeasonalityReport method), [1] (tseda.seasonality.SeasonalityReport method), [1] (tseda.statistics.autocorrelation.AutocorrelationResult method), [1] (tseda.statistics.AutocorrelationResult method), [1] (tseda.statistics.descriptive.DescriptiveStats method), [1] (tseda.statistics.DescriptiveStats method), [1] (tseda.statistics.stationarity.StationarityResult method), [1] (tseda.statistics.StationarityResult method), [1] (tseda.TimeSeries method) __len__() (tseda.core.TimeSeries method), [1] (tseda.core.timeseries.TimeSeries method), [1] (tseda.TimeSeries method)

__repr__() (tseda.AggMethod method) (tseda.anomaly.AnomalyReport method), [1] (tseda.anomaly.detector.AnomalyReport method), [1] (tseda.changepoint.ChangepointReport method) (tseda.changepoint.detector.ChangepointReport method) (tseda.core.AggMethod method), [1] (tseda.core.DiffMethod method), [1] (tseda.core.Frequency method), [1] (tseda.core.TimeSeries method), [1] (tseda.core.timeseries.TimeSeries method), [1] (tseda.core.types.AggMethod method) (tseda.core.types.DiffMethod method) (tseda.core.types.Frequency method) (tseda.decomposition.classical.DecompositionResult method), [1] (tseda.decomposition.DecompositionResult method), [1] (tseda.DiffMethod method) (tseda.forecastability.ForecastabilityReport method), [1] (tseda.forecastability.leakage.LeakageReport method), [1] (tseda.forecastability.LeakageReport method), [1] (tseda.forecastability.scorer.ForecastabilityReport method), [1] (tseda.Frequency method) (tseda.quality.duplicates.FlatlineReport method), [1] (tseda.quality.FlatlineReport method), [1] (tseda.quality.missing.MissingValueReport method), [1] (tseda.quality.MissingValueReport method), [1] (tseda.quality.OutlierReport method), [1] (tseda.quality.outliers.OutlierReport method), [1] (tseda.seasonality.detector.SeasonalityReport method), [1] (tseda.seasonality.SeasonalityReport method), [1] (tseda.statistics.autocorrelation.AutocorrelationResult method), [1] (tseda.statistics.AutocorrelationResult method), [1] (tseda.statistics.descriptive.DescriptiveStats method), [1] (tseda.statistics.DescriptiveStats method), [1] (tseda.statistics.stationarity.StationarityResult method), [1] (tseda.statistics.StationarityResult method), [1] (tseda.TimeSeries method)

A

acf (tseda.statistics.autocorrelation.AutocorrelationResult attribute), [1], [2], [3] (tseda.statistics.AutocorrelationResult attribute), [1], [2], [3] acf_periods (tseda.seasonality.detector.SeasonalityReport attribute), [1], [2], [3] (tseda.seasonality.SeasonalityReport attribute), [1], [2], [3] adf() (tseda.statistics.stationarity.StationarityTester method), [1], [2], [3] (tseda.statistics.StationarityTester method), [1], [2], [3] AggMethod (class in tseda) (class in tseda.core), [1] (class in tseda.core.types) alpha (tseda.seasonality.detector.SeasonalityReport attribute), [1], [2], [3] (tseda.seasonality.SeasonalityReport attribute), [1], [2], [3] (tseda.statistics.autocorrelation.AutocorrelationResult attribute), [1], [2], [3] (tseda.statistics.AutocorrelationResult attribute), [1], [2], [3] (tseda.statistics.stationarity.StationarityResult attribute), [1], [2], [3] (tseda.statistics.StationarityResult attribute), [1], [2], [3] analyze() (tseda.quality.missing.MissingValueAnalyzer method), [1], [2], [3] (tseda.quality.MissingValueAnalyzer method), [1], [2], [3] (tseda.statistics.autocorrelation.AutocorrelationAnalyzer method), [1], [2], [3] (tseda.statistics.AutocorrelationAnalyzer method), [1], [2], [3] (tseda.statistics.descriptive.DescriptiveAnalyzer method), [1], [2], [3] (tseda.statistics.DescriptiveAnalyzer method), [1], [2], [3]

ANNUAL_END (tseda.core.Frequency attribute), [1] (tseda.core.types.Frequency attribute) (tseda.Frequency attribute) ANNUAL_START (tseda.core.Frequency attribute), [1] (tseda.core.types.Frequency attribute) (tseda.Frequency attribute) AnomalyDetector (class in tseda.anomaly), [1] (class in tseda.anomaly.detector), [1] AnomalyReport (class in tseda.anomaly), [1] (class in tseda.anomaly.detector), [1] apply() (tseda.core.TimeSeries method), [1] (tseda.core.timeseries.TimeSeries method), [1] (tseda.TimeSeries method) AutocorrelationAnalyzer (class in tseda.statistics), [1] (class in tseda.statistics.autocorrelation), [1] AutocorrelationResult (class in tseda.statistics), [1] (class in tseda.statistics.autocorrelation), [1]

B

binary_segmentation() (tseda.changepoint.ChangepointDetector method), [1] (tseda.changepoint.detector.ChangepointDetector method), [1]

BUSINESS_DAILY (tseda.core.Frequency attribute), [1] (tseda.core.types.Frequency attribute) (tseda.Frequency attribute)

C

candidate_periods (tseda.seasonality.detector.SeasonalityReport attribute), [1], [2], [3] (tseda.seasonality.SeasonalityReport attribute), [1], [2], [3] ChangepointDetector (class in tseda.changepoint) (class in tseda.changepoint.detector) ChangepointReport (class in tseda.changepoint) (class in tseda.changepoint.detector) changepoints (tseda.changepoint.ChangepointReport attribute), [1] (tseda.changepoint.detector.ChangepointReport attribute), [1] check() (tseda.forecastability.leakage.LeakageDetector method), [1], [2], [3] (tseda.forecastability.LeakageDetector method), [1], [2], [3] ClassicalDecomposer (class in tseda.decomposition), [1] (class in tseda.decomposition.classical), [1] clip() (tseda.quality.OutlierDetector method), [1], [2], [3] (tseda.quality.outliers.OutlierDetector method), [1], [2], [3] conf_lower (tseda.statistics.autocorrelation.AutocorrelationResult attribute), [1], [2], [3] (tseda.statistics.AutocorrelationResult attribute), [1], [2], [3]

conf_upper (tseda.statistics.autocorrelation.AutocorrelationResult attribute), [1], [2], [3] (tseda.statistics.AutocorrelationResult attribute), [1], [2], [3] ConsoleReport (class in tseda.report), [1] (class in tseda.report.console_report), [1] copy() (tseda.core.TimeSeries method), [1] (tseda.core.timeseries.TimeSeries method), [1] (tseda.TimeSeries method) COUNT (tseda.AggMethod attribute) (tseda.core.AggMethod attribute), [1] (tseda.core.types.AggMethod attribute) critical_values (tseda.statistics.stationarity.StationarityResult attribute), [1], [2], [3] (tseda.statistics.StationarityResult attribute), [1], [2], [3] cusum() (tseda.changepoint.ChangepointDetector method), [1] (tseda.changepoint.detector.ChangepointDetector method), [1] cv (tseda.statistics.descriptive.DescriptiveStats attribute), [1], [2], [3] (tseda.statistics.DescriptiveStats attribute), [1], [2], [3]

D

DAILY (tseda.core.Frequency attribute), [1] (tseda.core.types.Frequency attribute) (tseda.Frequency attribute) decompose() (tseda.decomposition.classical.ClassicalDecomposer method), [1], [2], [3] (tseda.decomposition.ClassicalDecomposer method), [1], [2], [3] (tseda.decomposition.stl.STLDecomposer method), [1], [2], [3] (tseda.decomposition.STLDecomposer method), [1], [2], [3] DecompositionResult (class in tseda.decomposition), [1] (class in tseda.decomposition.classical), [1] description (tseda.core.TimeSeries property), [1] (tseda.core.timeseries.TimeSeries property), [1] (tseda.TimeSeries property) DescriptiveAnalyzer (class in tseda.statistics), [1] (class in tseda.statistics.descriptive), [1] DescriptiveStats (class in tseda.statistics), [1] (class in tseda.statistics.descriptive), [1]

detect() (tseda.seasonality.detector.SeasonalityDetector method), [1], [2], [3] (tseda.seasonality.SeasonalityDetector method), [1], [2], [3] diff() (tseda.core.TimeSeries method), [1] (tseda.core.timeseries.TimeSeries method), [1] (tseda.TimeSeries method) DiffMethod (class in tseda) (class in tseda.core), [1] (class in tseda.core.types) dominant_period (tseda.forecastability.ForecastabilityReport attribute), [1], [2], [3] (tseda.forecastability.scorer.ForecastabilityReport attribute), [1], [2], [3] (tseda.seasonality.detector.SeasonalityReport attribute), [1], [2], [3] (tseda.seasonality.SeasonalityReport attribute), [1], [2], [3] DuplicateDetector (class in tseda.quality), [1] (class in tseda.quality.duplicates), [1] duration (tseda.core.TimeSeries property), [1] (tseda.core.timeseries.TimeSeries property), [1] (tseda.TimeSeries property)

E

end (tseda.core.TimeSeries property), [1] (tseda.core.timeseries.TimeSeries property), [1] (tseda.TimeSeries property) extract() (tseda.features.spectral.SpectralFeatureExtractor method), [1], [2], [3] (tseda.features.SpectralFeatureExtractor method), [1], [2], [3] (tseda.features.statistical.StatisticalFeatureExtractor method), [1], [2], [3] (tseda.features.StatisticalFeatureExtractor method), [1], [2], [3] (tseda.features.temporal.TemporalFeatureExtractor method), [1], [2], [3] (tseda.features.TemporalFeatureExtractor method), [1], [2], [3]

F

FIRST (tseda.AggMethod attribute) (tseda.core.AggMethod attribute), [1] (tseda.core.types.AggMethod attribute) first (tseda.statistics.descriptive.DescriptiveStats attribute), [1], [2], [3] (tseda.statistics.DescriptiveStats attribute), [1], [2], [3] fisher_g_stat (tseda.seasonality.detector.SeasonalityReport attribute), [1], [2], [3] (tseda.seasonality.SeasonalityReport attribute), [1], [2], [3] fisher_p_value (tseda.seasonality.detector.SeasonalityReport attribute), [1], [2], [3] (tseda.seasonality.SeasonalityReport attribute), [1], [2], [3] flatline() (tseda.quality.DuplicateDetector method), [1], [2], [3] (tseda.quality.duplicates.DuplicateDetector method), [1], [2], [3] FlatlineReport (class in tseda.quality), [1] (class in tseda.quality.duplicates), [1] ForecastabilityReport (class in tseda.forecastability), [1] (class in tseda.forecastability.scorer), [1] ForecastabilityScorer (class in tseda.forecastability), [1] (class in tseda.forecastability.scorer), [1]

freq (tseda.core.TimeSeries property), [1] (tseda.core.timeseries.TimeSeries property), [1] (tseda.TimeSeries property) freq_label (tseda.core.TimeSeries property), [1] (tseda.core.timeseries.TimeSeries property), [1] (tseda.TimeSeries property) Frequency (class in tseda) (class in tseda.core), [1] (class in tseda.core.types) from_arrays() (tseda.core.TimeSeries class method), [1] (tseda.core.timeseries.TimeSeries class method), [1] (tseda.TimeSeries class method) from_dataframe() (tseda.core.TimeSeries class method), [1] (tseda.core.timeseries.TimeSeries class method), [1] (tseda.TimeSeries class method) from_series() (tseda.core.TimeSeries class method), [1] (tseda.core.timeseries.TimeSeries class method), [1] (tseda.TimeSeries class method)

G

gap_locations (tseda.quality.missing.MissingValueReport attribute), [1], [2], [3] (tseda.quality.MissingValueReport attribute), [1], [2], [3] generate() (tseda.report.console_report.ConsoleReport method), [1], [2], [3] (tseda.report.ConsoleReport method), [1], [2], [3] (tseda.report.html_report.HTMLReport method), [1], [2], [3] (tseda.report.HTMLReport method), [1], [2], [3]

gesd() (tseda.anomaly.AnomalyDetector method), [1], [2], [3] (tseda.anomaly.detector.AnomalyDetector method), [1], [2], [3] (tseda.quality.OutlierDetector method), [1], [2], [3] (tseda.quality.outliers.OutlierDetector method), [1], [2], [3]

H

has_nan (tseda.core.TimeSeries property), [1] (tseda.core.timeseries.TimeSeries property), [1] (tseda.TimeSeries property) has_target_leakage (tseda.forecastability.leakage.LeakageReport attribute), [1], [2], [3] (tseda.forecastability.LeakageReport attribute), [1], [2], [3] has_temporal_leakage (tseda.forecastability.leakage.LeakageReport attribute), [1], [2], [3] (tseda.forecastability.LeakageReport attribute), [1], [2], [3]

horizon (tseda.forecastability.leakage.LeakageReport attribute), [1], [2], [3] (tseda.forecastability.LeakageReport attribute), [1], [2], [3] HOURLY (tseda.core.Frequency attribute), [1] (tseda.core.types.Frequency attribute) (tseda.Frequency attribute) HTMLReport (class in tseda.report), [1] (class in tseda.report.html_report), [1]

I

index (tseda.core.TimeSeries property), [1] (tseda.core.timeseries.TimeSeries property), [1] (tseda.TimeSeries property) indices (tseda.anomaly.AnomalyReport attribute), [1], [2], [3] (tseda.anomaly.detector.AnomalyReport attribute), [1], [2], [3] (tseda.quality.OutlierReport attribute), [1], [2], [3] (tseda.quality.outliers.OutlierReport attribute), [1], [2], [3] interpolate() (tseda.quality.missing.MissingValueAnalyzer method), [1], [2], [3] (tseda.quality.MissingValueAnalyzer method), [1], [2], [3] interpretation (tseda.statistics.stationarity.StationarityResult attribute), [1], [2], [3] (tseda.statistics.StationarityResult attribute), [1], [2], [3] iqr() (tseda.quality.OutlierDetector method), [1], [2], [3] (tseda.quality.outliers.OutlierDetector method), [1], [2], [3]

is_monotone_missing (tseda.quality.missing.MissingValueReport attribute), [1], [2], [3] (tseda.quality.MissingValueReport attribute), [1], [2], [3] is_regular (tseda.core.TimeSeries property), [1] (tseda.core.timeseries.TimeSeries property), [1] (tseda.TimeSeries property) is_seasonal (tseda.seasonality.detector.SeasonalityReport attribute), [1], [2], [3] (tseda.seasonality.SeasonalityReport attribute), [1], [2], [3] is_stationary (tseda.forecastability.ForecastabilityReport attribute), [1], [2], [3] (tseda.forecastability.scorer.ForecastabilityReport attribute), [1], [2], [3] (tseda.statistics.stationarity.StationarityResult attribute), [1], [2], [3] (tseda.statistics.StationarityResult attribute), [1], [2], [3] is_white_noise (tseda.statistics.autocorrelation.AutocorrelationResult attribute), [1], [2], [3] (tseda.statistics.AutocorrelationResult attribute), [1], [2], [3]

K

kpss() (tseda.statistics.stationarity.StationarityTester method), [1], [2], [3] (tseda.statistics.StationarityTester method), [1], [2], [3]

kurtosis (tseda.statistics.descriptive.DescriptiveStats attribute), [1], [2], [3] (tseda.statistics.DescriptiveStats attribute), [1], [2], [3]

L

label() (tseda.anomaly.AnomalyDetector method), [1], [2], [3] (tseda.anomaly.detector.AnomalyDetector method), [1], [2], [3] lags (tseda.statistics.autocorrelation.AutocorrelationResult attribute), [1], [2], [3] (tseda.statistics.AutocorrelationResult attribute), [1], [2], [3] LAST (tseda.AggMethod attribute) (tseda.core.AggMethod attribute), [1] (tseda.core.types.AggMethod attribute) last (tseda.statistics.descriptive.DescriptiveStats attribute), [1], [2], [3] (tseda.statistics.DescriptiveStats attribute), [1], [2], [3] lb_pvalue (tseda.statistics.autocorrelation.AutocorrelationResult attribute), [1], [2], [3] (tseda.statistics.AutocorrelationResult attribute), [1], [2], [3] lb_statistic (tseda.statistics.autocorrelation.AutocorrelationResult attribute), [1], [2], [3] (tseda.statistics.AutocorrelationResult attribute), [1], [2], [3] LeakageDetector (class in tseda.forecastability), [1] (class in tseda.forecastability.leakage), [1]

LeakageReport (class in tseda.forecastability), [1] (class in tseda.forecastability.leakage), [1] LOG (tseda.core.DiffMethod attribute), [1], [2], [3] (tseda.core.types.DiffMethod attribute), [1] (tseda.DiffMethod attribute), [1] log() (tseda.core.TimeSeries method), [1] (tseda.core.timeseries.TimeSeries method), [1] (tseda.TimeSeries method) longest_nan_run (tseda.quality.missing.MissingValueReport attribute), [1], [2], [3] (tseda.quality.MissingValueReport attribute), [1], [2], [3] longest_run (tseda.quality.duplicates.FlatlineReport attribute), [1], [2], [3] (tseda.quality.FlatlineReport attribute), [1], [2], [3] lower_bound (tseda.quality.OutlierReport attribute), [1], [2], [3] (tseda.quality.outliers.OutlierReport attribute), [1], [2], [3]

M

mad (tseda.statistics.descriptive.DescriptiveStats attribute), [1], [2], [3] (tseda.statistics.DescriptiveStats attribute), [1], [2], [3] mad() (tseda.quality.OutlierDetector method), [1], [2], [3] (tseda.quality.outliers.OutlierDetector method), [1], [2], [3] mask (tseda.anomaly.AnomalyReport attribute), [1], [2], [3] (tseda.anomaly.detector.AnomalyReport attribute), [1], [2], [3] (tseda.quality.duplicates.FlatlineReport attribute), [1], [2], [3] (tseda.quality.FlatlineReport attribute), [1], [2], [3] (tseda.quality.OutlierReport attribute), [1], [2], [3] (tseda.quality.outliers.OutlierReport attribute), [1], [2], [3] MAX (tseda.AggMethod attribute) (tseda.core.AggMethod attribute), [1] (tseda.core.types.AggMethod attribute) max (tseda.statistics.descriptive.DescriptiveStats attribute), [1], [2], [3] (tseda.statistics.DescriptiveStats attribute), [1], [2], [3] MEAN (tseda.AggMethod attribute) (tseda.core.AggMethod attribute), [1] (tseda.core.types.AggMethod attribute) mean (tseda.statistics.descriptive.DescriptiveStats attribute), [1], [2], [3] (tseda.statistics.DescriptiveStats attribute), [1], [2], [3] MEDIAN (tseda.AggMethod attribute) (tseda.core.AggMethod attribute), [1] (tseda.core.types.AggMethod attribute) median (tseda.statistics.descriptive.DescriptiveStats attribute), [1], [2], [3] (tseda.statistics.DescriptiveStats attribute), [1], [2], [3] method (tseda.anomaly.AnomalyReport attribute), [1], [2], [3] (tseda.anomaly.detector.AnomalyReport attribute), [1], [2], [3] (tseda.changepoint.ChangepointReport attribute), [1] (tseda.changepoint.detector.ChangepointReport attribute), [1] (tseda.decomposition.classical.DecompositionResult attribute), [1], [2], [3] (tseda.decomposition.DecompositionResult attribute), [1], [2], [3] (tseda.quality.OutlierReport attribute), [1], [2], [3] (tseda.quality.outliers.OutlierReport attribute), [1], [2], [3] (tseda.seasonality.detector.SeasonalityReport attribute), [1], [2], [3] (tseda.seasonality.SeasonalityReport attribute), [1], [2], [3] MIN (tseda.AggMethod attribute) (tseda.core.AggMethod attribute), [1] (tseda.core.types.AggMethod attribute) min (tseda.statistics.descriptive.DescriptiveStats attribute), [1], [2], [3] (tseda.statistics.DescriptiveStats attribute), [1], [2], [3] min_run (tseda.quality.duplicates.FlatlineReport attribute), [1], [2], [3] (tseda.quality.FlatlineReport attribute), [1], [2], [3] MINUTELY (tseda.core.Frequency attribute), [1] (tseda.core.types.Frequency attribute) (tseda.Frequency attribute)

MissingValueAnalyzer (class in tseda.quality), [1] (class in tseda.quality.missing), [1] MissingValueReport (class in tseda.quality), [1] (class in tseda.quality.missing), [1] model (tseda.decomposition.classical.DecompositionResult attribute), [1], [2], [3] (tseda.decomposition.DecompositionResult attribute), [1], [2], [3] module tseda tseda.anomaly, [1] tseda.anomaly.detector tseda.changepoint tseda.core, [1] tseda.core.timeseries tseda.core.validator tseda.decomposition, [1] tseda.decomposition.classical tseda.decomposition.stl tseda.features, [1] tseda.features.spectral tseda.features.statistical tseda.features.temporal tseda.forecastability, [1] tseda.forecastability.leakage tseda.forecastability.scorer tseda.quality, [1] tseda.quality.duplicates tseda.quality.missing tseda.quality.outliers tseda.report, [1] tseda.report.console_report tseda.report.html_report tseda.seasonality, [1] tseda.seasonality.detector tseda.statistics, [1] tseda.statistics.autocorrelation tseda.statistics.descriptive tseda.statistics.stationarity tseda.visualization, [1] MONTHLY_END (tseda.core.Frequency attribute), [1] (tseda.core.types.Frequency attribute) (tseda.Frequency attribute) MONTHLY_START (tseda.core.Frequency attribute), [1] (tseda.core.types.Frequency attribute) (tseda.Frequency attribute)

N

n (tseda.core.TimeSeries property), [1] (tseda.core.timeseries.TimeSeries property), [1] (tseda.TimeSeries property) n_anomalies (tseda.anomaly.AnomalyReport attribute), [1], [2], [3] (tseda.anomaly.detector.AnomalyReport attribute), [1], [2], [3] n_changepoints (tseda.changepoint.ChangepointReport attribute), [1] (tseda.changepoint.detector.ChangepointReport attribute), [1] n_features (tseda.forecastability.leakage.LeakageReport attribute), [1], [2], [3] (tseda.forecastability.LeakageReport attribute), [1], [2], [3] n_flatline_runs (tseda.quality.duplicates.FlatlineReport attribute), [1], [2], [3] (tseda.quality.FlatlineReport attribute), [1], [2], [3] n_gaps (tseda.quality.missing.MissingValueReport attribute), [1], [2], [3] (tseda.quality.MissingValueReport attribute), [1], [2], [3] n_lags (tseda.statistics.autocorrelation.AutocorrelationResult attribute), [1], [2], [3] (tseda.statistics.AutocorrelationResult attribute), [1], [2], [3] (tseda.statistics.stationarity.StationarityResult attribute), [1], [2], [3] (tseda.statistics.StationarityResult attribute), [1], [2], [3] n_nan (tseda.core.TimeSeries property), [1] (tseda.core.timeseries.TimeSeries property), [1] (tseda.quality.missing.MissingValueReport attribute), [1], [2], [3] (tseda.quality.MissingValueReport attribute), [1], [2], [3] (tseda.statistics.descriptive.DescriptiveStats attribute), [1], [2], [3] (tseda.statistics.DescriptiveStats attribute), [1], [2], [3] (tseda.TimeSeries property) n_negative (tseda.statistics.descriptive.DescriptiveStats attribute), [1], [2], [3] (tseda.statistics.DescriptiveStats attribute), [1], [2], [3] n_obs (tseda.forecastability.ForecastabilityReport attribute), [1], [2], [3] (tseda.forecastability.leakage.LeakageReport attribute), [1], [2], [3] (tseda.forecastability.LeakageReport attribute), [1], [2], [3] (tseda.forecastability.scorer.ForecastabilityReport attribute), [1], [2], [3] (tseda.seasonality.detector.SeasonalityReport attribute), [1], [2], [3] (tseda.seasonality.SeasonalityReport attribute), [1], [2], [3] (tseda.statistics.autocorrelation.AutocorrelationResult attribute), [1], [2], [3] (tseda.statistics.AutocorrelationResult attribute), [1], [2], [3]

n_obs_used (tseda.decomposition.classical.DecompositionResult attribute), [1], [2], [3] (tseda.decomposition.DecompositionResult attribute), [1], [2], [3] n_outliers (tseda.quality.OutlierReport attribute), [1], [2], [3] (tseda.quality.outliers.OutlierReport attribute), [1], [2], [3] n_positive (tseda.statistics.descriptive.DescriptiveStats attribute), [1], [2], [3] (tseda.statistics.DescriptiveStats attribute), [1], [2], [3] n_total (tseda.statistics.descriptive.DescriptiveStats attribute), [1], [2], [3] (tseda.statistics.DescriptiveStats attribute), [1], [2], [3] n_valid (tseda.statistics.descriptive.DescriptiveStats attribute), [1], [2], [3] (tseda.statistics.DescriptiveStats attribute), [1], [2], [3] n_zeros (tseda.statistics.descriptive.DescriptiveStats attribute), [1], [2], [3] (tseda.statistics.DescriptiveStats attribute), [1], [2], [3] name (tseda.core.TimeSeries property), [1] (tseda.core.timeseries.TimeSeries property), [1] (tseda.TimeSeries property) nan_positions (tseda.quality.missing.MissingValueReport attribute), [1], [2], [3] (tseda.quality.MissingValueReport attribute), [1], [2], [3] nan_run_lengths (tseda.quality.missing.MissingValueReport attribute), [1], [2], [3] (tseda.quality.MissingValueReport attribute), [1], [2], [3] near_zero() (tseda.quality.DuplicateDetector method), [1], [2], [3] (tseda.quality.duplicates.DuplicateDetector method), [1], [2], [3] normalize() (tseda.core.TimeSeries method), [1] (tseda.core.timeseries.TimeSeries method), [1] (tseda.TimeSeries method)

O

original (tseda.decomposition.classical.DecompositionResult attribute), [1], [2], [3] (tseda.decomposition.DecompositionResult attribute), [1], [2], [3] OutlierDetector (class in tseda.quality), [1] (class in tseda.quality.outliers), [1]

OutlierReport (class in tseda.quality), [1] (class in tseda.quality.outliers), [1]

P

p_value (tseda.statistics.stationarity.StationarityResult attribute), [1], [2], [3] (tseda.statistics.StationarityResult attribute), [1], [2], [3] pacf (tseda.statistics.autocorrelation.AutocorrelationResult attribute), [1], [2], [3] (tseda.statistics.AutocorrelationResult attribute), [1], [2], [3] pct_missing (tseda.forecastability.ForecastabilityReport attribute), [1], [2], [3] (tseda.forecastability.scorer.ForecastabilityReport attribute), [1], [2], [3] pct_nan (tseda.quality.missing.MissingValueReport attribute), [1], [2], [3] (tseda.quality.MissingValueReport attribute), [1], [2], [3] (tseda.statistics.descriptive.DescriptiveStats attribute), [1], [2], [3] (tseda.statistics.DescriptiveStats attribute), [1], [2], [3] pct_outlier (tseda.forecastability.ForecastabilityReport attribute), [1], [2], [3] (tseda.forecastability.scorer.ForecastabilityReport attribute), [1], [2], [3] PERCENT (tseda.core.DiffMethod attribute), [1], [2], [3] (tseda.core.types.DiffMethod attribute), [1] (tseda.DiffMethod attribute), [1] period (tseda.decomposition.classical.DecompositionResult attribute), [1], [2], [3] (tseda.decomposition.DecompositionResult attribute), [1], [2], [3] periodogram_periods (tseda.seasonality.detector.SeasonalityReport attribute), [1], [2], [3] (tseda.seasonality.SeasonalityReport attribute), [1], [2], [3] plot_acf_heatmap() (in module tseda.visualization), [1] (in module tseda.visualization.correlation_plots), [1], [2] plot_acf_pacf() (in module tseda.visualization), [1] (in module tseda.visualization.correlation_plots), [1], [2] plot_annual_boxplots() (in module tseda.visualization), [1] (in module tseda.visualization.time_plots), [1], [2] plot_anomalies() (in module tseda.visualization), [1] (in module tseda.visualization.anomaly_plots), [1], [2] plot_anomaly_heatmap() (in module tseda.visualization), [1] (in module tseda.visualization.anomaly_plots), [1], [2] plot_anomaly_scores() (in module tseda.visualization), [1] (in module tseda.visualization.anomaly_plots), [1], [2] plot_calendar_heatmap() (in module tseda.visualization), [1] (in module tseda.visualization.time_plots), [1], [2] plot_changepoints() (in module tseda.visualization), [1] (in module tseda.visualization.changepoint_plots), [1], [2] plot_cusum() (in module tseda.visualization), [1] (in module tseda.visualization.changepoint_plots), [1], [2]

plot_decomposition() (in module tseda.visualization), [1] (in module tseda.visualization.decomposition_plots), [1], [2] plot_density_ridge() (in module tseda.visualization), [1] (in module tseda.visualization.time_plots), [1], [2] plot_distribution() (in module tseda.visualization), [1] (in module tseda.visualization.distribution_plots), [1], [2] plot_lag() (in module tseda.visualization), [1] (in module tseda.visualization.time_plots), [1], [2] plot_missing_heatmap() (in module tseda.visualization), [1] (in module tseda.visualization.quality_plots), [1], [2] plot_monthly_boxplots() (in module tseda.visualization), [1] (in module tseda.visualization.seasonality_plots), [1], [2] plot_outlier_score() (in module tseda.visualization), [1] (in module tseda.visualization.quality_plots), [1], [2] plot_outliers() (in module tseda.visualization), [1] (in module tseda.visualization.quality_plots), [1], [2] plot_periodogram() (in module tseda.visualization), [1] (in module tseda.visualization.seasonality_plots), [1], [2] plot_polar_seasonal() (in module tseda.visualization), [1] (in module tseda.visualization.seasonality_plots), [1], [2] plot_qq() (in module tseda.visualization), [1] (in module tseda.visualization.distribution_plots), [1], [2] plot_residual_diagnostics() (in module tseda.visualization), [1] (in module tseda.visualization.decomposition_plots), [1], [2] plot_rolling_stats() (in module tseda.visualization), [1] (in module tseda.visualization.distribution_plots), [1], [2] plot_season_heatmap() (in module tseda.visualization), [1] (in module tseda.visualization.seasonality_plots), [1], [2] plot_seasonal_subseries() (in module tseda.visualization), [1] (in module tseda.visualization.time_plots), [1], [2] plot_segment_means() (in module tseda.visualization), [1] (in module tseda.visualization.changepoint_plots), [1], [2] plot_series() (in module tseda.visualization), [1] (in module tseda.visualization.time_plots), [1], [2] plot_strength_radar() (in module tseda.visualization), [1] (in module tseda.visualization.decomposition_plots), [1], [2] pp() (tseda.statistics.stationarity.StationarityTester method), [1], [2], [3] (tseda.statistics.StationarityTester method), [1], [2], [3]

Q

quantiles (tseda.statistics.descriptive.DescriptiveStats attribute), [1], [2], [3] (tseda.statistics.DescriptiveStats attribute), [1], [2], [3] QUARTERLY_END (tseda.core.Frequency attribute), [1] (tseda.core.types.Frequency attribute) (tseda.Frequency attribute)

QUARTERLY_START (tseda.core.Frequency attribute), [1] (tseda.core.types.Frequency attribute) (tseda.Frequency attribute)

R

range (tseda.statistics.descriptive.DescriptiveStats attribute), [1], [2], [3] (tseda.statistics.DescriptiveStats attribute), [1], [2], [3] recommended_diff (tseda.forecastability.ForecastabilityReport attribute), [1], [2], [3] (tseda.forecastability.scorer.ForecastabilityReport attribute), [1], [2], [3] recommended_model (tseda.forecastability.ForecastabilityReport attribute), [1], [2], [3] (tseda.forecastability.scorer.ForecastabilityReport attribute), [1], [2], [3] recommended_period (tseda.forecastability.ForecastabilityReport attribute), [1], [2], [3] (tseda.forecastability.scorer.ForecastabilityReport attribute), [1], [2], [3] regression (tseda.statistics.stationarity.StationarityResult attribute), [1], [2], [3] (tseda.statistics.StationarityResult attribute), [1], [2], [3] remove() (tseda.anomaly.AnomalyDetector method), [1], [2], [3] (tseda.anomaly.detector.AnomalyDetector method), [1], [2], [3] (tseda.quality.OutlierDetector method), [1], [2], [3] (tseda.quality.outliers.OutlierDetector method), [1], [2], [3] remove_flatlines() (tseda.quality.DuplicateDetector method), [1], [2], [3] (tseda.quality.duplicates.DuplicateDetector method), [1], [2], [3]

resample() (tseda.core.TimeSeries method), [1] (tseda.core.timeseries.TimeSeries method), [1] (tseda.TimeSeries method) residual (tseda.decomposition.classical.DecompositionResult attribute), [1], [2], [3] (tseda.decomposition.DecompositionResult attribute), [1], [2], [3] rolling() (tseda.core.TimeSeries method), [1] (tseda.core.timeseries.TimeSeries method), [1] (tseda.TimeSeries method) rolling_iqr() (tseda.anomaly.AnomalyDetector method), [1], [2], [3] (tseda.anomaly.detector.AnomalyDetector method), [1], [2], [3] rolling_z() (tseda.anomaly.AnomalyDetector method), [1], [2], [3] (tseda.anomaly.detector.AnomalyDetector method), [1], [2], [3] runs (tseda.quality.duplicates.FlatlineReport attribute), [1], [2], [3] (tseda.quality.FlatlineReport attribute), [1], [2], [3]

S

score (tseda.forecastability.ForecastabilityReport attribute), [1], [2], [3] (tseda.forecastability.scorer.ForecastabilityReport attribute), [1], [2], [3] score() (tseda.forecastability.ForecastabilityScorer method), [1], [2], [3] (tseda.forecastability.scorer.ForecastabilityScorer method), [1], [2], [3] scores (tseda.anomaly.AnomalyReport attribute), [1], [2], [3] (tseda.anomaly.detector.AnomalyReport attribute), [1], [2], [3] (tseda.changepoint.ChangepointReport attribute), [1] (tseda.changepoint.detector.ChangepointReport attribute), [1] seasonal (tseda.decomposition.classical.DecompositionResult attribute), [1], [2], [3] (tseda.decomposition.DecompositionResult attribute), [1], [2], [3] SeasonalityDetector (class in tseda.seasonality), [1] (class in tseda.seasonality.detector), [1] SeasonalityReport (class in tseda.seasonality), [1] (class in tseda.seasonality.detector), [1] SECONDLY (tseda.core.Frequency attribute), [1] (tseda.core.types.Frequency attribute) (tseda.Frequency attribute) segment() (tseda.changepoint.ChangepointDetector method), [1] (tseda.changepoint.detector.ChangepointDetector method), [1] segment_labels() (tseda.changepoint.ChangepointReport method) (tseda.changepoint.detector.ChangepointReport method) set_style() (in module tseda.visualization), [1] (in module tseda.visualization.base), [1], [2] significant_lags() (tseda.statistics.autocorrelation.AutocorrelationAnalyzer method), [1], [2], [3] (tseda.statistics.AutocorrelationAnalyzer method), [1], [2], [3] SIMPLE (tseda.core.DiffMethod attribute), [1], [2], [3] (tseda.core.types.DiffMethod attribute), [1] (tseda.DiffMethod attribute), [1] skewness (tseda.statistics.descriptive.DescriptiveStats attribute), [1], [2], [3] (tseda.statistics.DescriptiveStats attribute), [1], [2], [3] slice() (tseda.core.TimeSeries method), [1] (tseda.core.timeseries.TimeSeries method), [1] (tseda.TimeSeries method) SpectralFeatureExtractor (class in tseda.features), [1] (class in tseda.features.spectral), [1] standardize() (tseda.core.TimeSeries method), [1] (tseda.core.timeseries.TimeSeries method), [1] (tseda.TimeSeries method)

start (tseda.core.TimeSeries property), [1] (tseda.core.timeseries.TimeSeries property), [1] (tseda.TimeSeries property) StationarityResult (class in tseda.statistics), [1] (class in tseda.statistics.stationarity), [1] StationarityTester (class in tseda.statistics), [1] (class in tseda.statistics.stationarity), [1] statistic (tseda.statistics.stationarity.StationarityResult attribute), [1], [2], [3] (tseda.statistics.StationarityResult attribute), [1], [2], [3] StatisticalFeatureExtractor (class in tseda.features), [1] (class in tseda.features.statistical), [1] STD (tseda.AggMethod attribute) (tseda.core.AggMethod attribute), [1] (tseda.core.types.AggMethod attribute) std (tseda.statistics.descriptive.DescriptiveStats attribute), [1], [2], [3] (tseda.statistics.DescriptiveStats attribute), [1], [2], [3] stl_residual() (tseda.anomaly.AnomalyDetector method), [1], [2], [3] (tseda.anomaly.detector.AnomalyDetector method), [1], [2], [3] STLDecomposer (class in tseda.decomposition), [1] (class in tseda.decomposition.stl), [1] strength_scores (tseda.seasonality.detector.SeasonalityReport attribute), [1], [2], [3] (tseda.seasonality.SeasonalityReport attribute), [1], [2], [3] strength_seasonal (tseda.decomposition.classical.DecompositionResult attribute), [1], [2], [3] (tseda.decomposition.DecompositionResult attribute), [1], [2], [3] strength_trend (tseda.decomposition.classical.DecompositionResult attribute), [1], [2], [3] (tseda.decomposition.DecompositionResult attribute), [1], [2], [3] sub_scores (tseda.forecastability.ForecastabilityReport attribute), [1], [2], [3] (tseda.forecastability.scorer.ForecastabilityReport attribute), [1], [2], [3] SUM (tseda.AggMethod attribute) (tseda.core.AggMethod attribute), [1] (tseda.core.types.AggMethod attribute) summary() (tseda.decomposition.classical.DecompositionResult method), [1] (tseda.decomposition.DecompositionResult method), [1] (tseda.seasonality.detector.SeasonalityReport method), [1] (tseda.seasonality.SeasonalityReport method), [1] (tseda.statistics.stationarity.StationarityTester method), [1], [2], [3] (tseda.statistics.StationarityTester method), [1], [2], [3]

T

target_leakage_columns (tseda.forecastability.leakage.LeakageReport attribute), [1], [2], [3] (tseda.forecastability.LeakageReport attribute), [1], [2], [3] target_leakage_correlations (tseda.forecastability.leakage.LeakageReport attribute), [1], [2], [3] (tseda.forecastability.LeakageReport attribute), [1], [2], [3] temporal_leakage_columns (tseda.forecastability.leakage.LeakageReport attribute), [1], [2], [3] (tseda.forecastability.LeakageReport attribute), [1], [2], [3] temporal_peak_lags (tseda.forecastability.leakage.LeakageReport attribute), [1], [2], [3] (tseda.forecastability.LeakageReport attribute), [1], [2], [3] TemporalFeatureExtractor (class in tseda.features), [1] (class in tseda.features.temporal), [1] test_name (tseda.statistics.stationarity.StationarityResult attribute), [1], [2], [3] (tseda.statistics.StationarityResult attribute), [1], [2], [3] test_period() (tseda.seasonality.detector.SeasonalityDetector method), [1], [2], [3] (tseda.seasonality.SeasonalityDetector method), [1], [2], [3] TimeSeries (class in tseda) (class in tseda.core), [1] (class in tseda.core.timeseries), [1] timestamps (tseda.anomaly.AnomalyReport attribute), [1], [2], [3] (tseda.anomaly.detector.AnomalyReport attribute), [1], [2], [3] (tseda.changepoint.ChangepointReport attribute), [1] (tseda.changepoint.detector.ChangepointReport attribute), [1] (tseda.quality.OutlierReport attribute), [1], [2], [3] (tseda.quality.outliers.OutlierReport attribute), [1], [2], [3] to_dataframe() (tseda.decomposition.classical.DecompositionResult method), [1] (tseda.decomposition.DecompositionResult method), [1] to_frame() (tseda.core.TimeSeries method), [1] (tseda.core.timeseries.TimeSeries method), [1] (tseda.TimeSeries method) to_numpy() (tseda.core.TimeSeries method), [1] (tseda.core.timeseries.TimeSeries method), [1] (tseda.TimeSeries method) to_series() (tseda.core.TimeSeries method), [1] (tseda.core.timeseries.TimeSeries method), [1] (tseda.TimeSeries method) to_string() (tseda.report.console_report.ConsoleReport method), [1], [2], [3] (tseda.report.ConsoleReport method), [1], [2], [3] total_flatline_points (tseda.quality.duplicates.FlatlineReport attribute), [1], [2], [3] (tseda.quality.FlatlineReport attribute), [1], [2], [3] trend (tseda.decomposition.classical.DecompositionResult attribute), [1], [2], [3] (tseda.decomposition.DecompositionResult attribute), [1], [2], [3] trimmed_mean (tseda.statistics.descriptive.DescriptiveStats attribute), [1], [2], [3] (tseda.statistics.DescriptiveStats attribute), [1], [2], [3] tseda module tseda.anomaly module, [1] tseda.anomaly.detector module tseda.changepoint module tseda.core module, [1]

tseda.core.timeseries module tseda.core.validator module tseda.decomposition module, [1] tseda.decomposition.classical module tseda.decomposition.stl module tseda.features module, [1] tseda.features.spectral module tseda.features.statistical module tseda.features.temporal module tseda.forecastability module, [1] tseda.forecastability.leakage module tseda.forecastability.scorer module tseda.quality module, [1] tseda.quality.duplicates module tseda.quality.missing module tseda.quality.outliers module tseda.report module, [1] tseda.report.console_report module tseda.report.html_report module tseda.seasonality module, [1] tseda.seasonality.detector module tseda.statistics module, [1] tseda.statistics.autocorrelation module tseda.statistics.descriptive module tseda.statistics.stationarity module tseda.visualization module, [1]

U

unit (tseda.core.TimeSeries property), [1] (tseda.core.timeseries.TimeSeries property), [1] (tseda.TimeSeries property)

upper_bound (tseda.quality.OutlierReport attribute), [1], [2], [3] (tseda.quality.outliers.OutlierReport attribute), [1], [2], [3]

V

validate_data_array() (in module tseda.core), [1] (in module tseda.core.validator) validate_datetime_index() (in module tseda.core), [1] (in module tseda.core.validator) validate_freq_string() (in module tseda.core), [1] (in module tseda.core.validator) validate_lags() (in module tseda.core), [1] (in module tseda.core.validator) validate_positive_int() (in module tseda.core), [1] (in module tseda.core.validator) values (tseda.anomaly.AnomalyReport attribute), [1], [2], [3] (tseda.anomaly.detector.AnomalyReport attribute), [1], [2], [3] (tseda.core.TimeSeries property), [1] (tseda.core.timeseries.TimeSeries property), [1] (tseda.quality.OutlierReport attribute), [1], [2], [3] (tseda.quality.outliers.OutlierReport attribute), [1], [2], [3] (tseda.TimeSeries property)

VAR (tseda.AggMethod attribute) (tseda.core.AggMethod attribute), [1] (tseda.core.types.AggMethod attribute) var (tseda.statistics.descriptive.DescriptiveStats attribute), [1], [2], [3] (tseda.statistics.DescriptiveStats attribute), [1], [2], [3] variance_ratio() (tseda.changepoint.ChangepointDetector method), [1] (tseda.changepoint.detector.ChangepointDetector method), [1]

W

warnings (tseda.forecastability.leakage.LeakageReport attribute), [1], [2], [3] (tseda.forecastability.LeakageReport attribute), [1], [2], [3]

WEEKLY (tseda.core.Frequency attribute), [1] (tseda.core.types.Frequency attribute) (tseda.Frequency attribute)

Z

zscore() (tseda.quality.OutlierDetector method), [1], [2], [3] (tseda.quality.outliers.OutlierDetector method), [1], [2], [3]