abacusai.eda_forecasting_analysis
Classes
Eda Forecasting Analysis of the latest version of the data. |
Module Contents
- class abacusai.eda_forecasting_analysis.EdaForecastingAnalysis(client, primaryKeys=None, forecastingTargetFeature=None, timestampFeature=None, forecastFrequency=None, salesAcrossTime={}, cummulativeContribution={}, missingValueDistribution={}, historyLength={}, numRowsHistogram={}, productMaturity={}, seasonalityYear={}, seasonalityMonth={}, seasonalityWeekOfYear={}, seasonalityDayOfYear={}, seasonalityDayOfMonth={}, seasonalityDayOfWeek={}, seasonalityQuarter={}, seasonalityHour={}, seasonalityMinute={}, seasonalitySecond={}, autocorrelation={}, partialAutocorrelation={})
Bases:
abacusai.return_class.AbstractApiClassEda Forecasting Analysis of the latest version of the data.
- Parameters:
client (ApiClient) – An authenticated API Client instance
primaryKeys (list) – Name of the primary keys in the data
forecastingTargetFeature (str) – Feature in the data that represents the target.
timestampFeature (str) – Feature in the data that represents the timestamp column.
forecastFrequency (str) – Frequency of data, could be hourly, daily, weekly, monthly, quarterly or yearly.
salesAcrossTime (ForecastingAnalysisGraphData) – Data showing average, p10, p90, median sales across time
cummulativeContribution (ForecastingAnalysisGraphData) – Data showing what percent of items contribute to what amount of sales.
missingValueDistribution (ForecastingAnalysisGraphData) – Data showing missing or null value distribution
historyLength (ForecastingAnalysisGraphData) – Data showing length of history distribution
numRowsHistogram (ForecastingAnalysisGraphData) – Data showing number of rows for an item distribution
productMaturity (ForecastingAnalysisGraphData) – Data showing length of how long a product has been alive with average, p10, p90 and median
seasonalityYear (ForecastingAnalysisGraphData) – Data showing average, p10, p90, median sales across grouped years
seasonalityMonth (ForecastingAnalysisGraphData) – Data showing average, p10, p90, median sales across grouped months
seasonalityWeekOfYear (ForecastingAnalysisGraphData) – Data showing average, p10, p90, median sales across week of year seasonality
seasonalityDayOfYear (ForecastingAnalysisGraphData) – Data showing average, p10, p90, median sales across day of year seasonality
seasonalityDayOfMonth (ForecastingAnalysisGraphData) – Data showing average, p10, p90, median sales across day of month seasonality
seasonalityDayOfWeek (ForecastingAnalysisGraphData) – Data showing average, p10, p90, median sales across day of week seasonality
seasonalityQuarter (ForecastingAnalysisGraphData) – Data showing average, p10, p90, median sales across grouped quarters
seasonalityHour (ForecastingAnalysisGraphData) – Data showing average, p10, p90, median sales across grouped hours
seasonalityMinute (ForecastingAnalysisGraphData) – Data showing average, p10, p90, median sales across grouped minutes
seasonalitySecond (ForecastingAnalysisGraphData) – Data showing average, p10, p90, median sales across grouped seconds
autocorrelation (ForecastingAnalysisGraphData) – Data showing the correlation of the forecasting target and its lagged values at different time lags.
partialAutocorrelation (ForecastingAnalysisGraphData) – Data showing the correlation of the forecasting target and its lagged values, controlling for the effects of intervening lags.
- primary_keys = None
- forecasting_target_feature = None
- timestamp_feature = None
- forecast_frequency = None
- sales_across_time
- cummulative_contribution
- missing_value_distribution
- history_length
- num_rows_histogram
- product_maturity
- seasonality_year
- seasonality_month
- seasonality_week_of_year
- seasonality_day_of_year
- seasonality_day_of_month
- seasonality_day_of_week
- seasonality_quarter
- seasonality_hour
- seasonality_minute
- seasonality_second
- autocorrelation
- partial_autocorrelation
- deprecated_keys
- __repr__()