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01_​Accessing_​Transforming_​and_​Modeling_​Time_​Series

Accessing, Transforming and Modeling Time Series
Visual Exploration - Line Plot, Seasonal Plot, Conditional Box Plot, Lag Plot Inspecting and Transforming Time Series Modeling Time Series Steps from accessing to preprocessing, transforming, andmodeling time series Deploying Time Series added condaenv propRead Sample - Superstore dataAscending by timeOriginal daily datamonthYearly seasonalityIntroduce missing daysSales is 0 wheremissingOnly 2017One value perdayyearTurning point, TrendYear, month, weekas seasonal cyclesSeasonal plotMonthly distributions 2017 for testingdeployment.tableNumber rowsMean(Sales)Seasonality lagslags.tabletraining.tableResidualtrend.pmmlOutliers in residualDecomposed time seriesfromhttps://community.tableau.com/s/question/0D54T00000CWeX8SAL/sample-superstore-sales-excelxls Decompose Signal Excel Reader (XLS)(deprecated) Sorter Line Plot AggregationGranularity Line Plot Timestamp Alignment Missing Value Date&Time-basedRow Filter GroupBy AggregationGranularity Line Plot Extract Date&TimeFields (deprecated) Line Plot Pivoting ConditionalBox Plot Number To String Rule-basedRow Splitter Table Writer(deprecated) Extract TableDimension Column Filter Variable to TableRow (deprecated) Table Writer(deprecated) Table Writer(deprecated) Column Filter PMML Writer(deprecated) ARIMA Predictor Line Plot Numeric Scorer Joiner (deprecated) Numeric Outliers Line Plot Line color Line color Line color Line color Excel Reader Auto ARIMA Learner Visual Exploration - Line Plot, Seasonal Plot, Conditional Box Plot, Lag Plot Inspecting and Transforming Time Series Modeling Time Series Steps from accessing to preprocessing, transforming, andmodeling time series Deploying Time Series added condaenv propRead Sample - Superstore dataAscending by timeOriginal daily datamonthYearly seasonalityIntroduce missing daysSales is 0 wheremissingOnly 2017One value perdayyearTurning point, TrendYear, month, weekas seasonal cyclesSeasonal plotMonthly distributions 2017 for testingdeployment.tableNumber rowsMean(Sales)Seasonality lagslags.tabletraining.tableResidualtrend.pmmlOutliers in residualDecomposed time seriesfromhttps://community.tableau.com/s/question/0D54T00000CWeX8SAL/sample-superstore-sales-excelxls Decompose Signal Excel Reader (XLS)(deprecated) Sorter Line Plot AggregationGranularity Line Plot Timestamp Alignment Missing Value Date&Time-basedRow Filter GroupBy AggregationGranularity Line Plot Extract Date&TimeFields (deprecated) Line Plot Pivoting ConditionalBox Plot Number To String Rule-basedRow Splitter Table Writer(deprecated) Extract TableDimension Column Filter Variable to TableRow (deprecated) Table Writer(deprecated) Table Writer(deprecated) Column Filter PMML Writer(deprecated) ARIMA Predictor Line Plot Numeric Scorer Joiner (deprecated) Numeric Outliers Line Plot Line color Line color Line color Line color Excel Reader Auto ARIMA Learner

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: Maarit Laukkanen
Created at: 2020-06-09
On NodePit since: 2022-02-25
Last update: 2024-11-17
Created with KNIME version: v4.5.1
Tags: time seriesARIMAgranularitytrendseasonalityclassical decompositionseasonal plotlag plot

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