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01_​Load_​Clean_​and_​Explore

Exercise 1: Loading and Exploring Data

This workflow accesses, preprocesses, and visualizes time series (energy consumption) data by
- converting time values from String to Date&Time
- aligning the time series by linear interpolation where gaps
- showing the hourly, daily, and monthly total values in a line plot

URL: String to Date&Time Node https://youtu.be/uNgaEGzetkU

Data Loading
Data Preparation
Line Plot by hour Notice the daily and weekly seasonality
Line Plot by month Notice the yearly seasonality
Line Plot by day Notice the weekly and yearly seasonality
How to configure the Line Plot and Line Plot (Plotly) nodes? - Select the x-axis column, in our case the "aggregatedTimestamp" column in the drop down menu - Include y-axis column, in our case the "Sum(cluster_26)" column in the Include/Exclude framework - Open the General Plot Options tab and write the view title and axis labels in the corresponding fields
Time Series Analysis 01. Loading and Exploring Data Summary: In this exercise we will load the data file for cleaning, filtering, aggregating, and for some early visualizations. Instructions:1) Execute the File Reader node to load in the Energy Usage Data 2) Use a String to Date&Time node to convert the Row ID column to the correct format. The digits in the string pattern are converted correctly, if you write "yyyy-MM-dd_HH" in the date format field, or press the "Guess data type and format button". 3) Use a Column Filter node to remove all columns except the Row ID and Cluster 26, this is what we will analyze 4) Use the Time Stamp Alignment component to check for missing time stamps in the data 5) Connect a Missing Value node next to replace the missing values discovered in the previous step. Try the linear interpolation setting. 6) Use separate Aggregation Granularity components to aggregate the Time series into Hourly, Daily, and Monthly series 7) Use Line Plot nodes to visualize the outputs. Do you see any patterns? 8) Open the 01_Additional_Visualizations workflow in the Supplementary Workflows folder and inspect the season plot, confidence bounds, and lag plot of the Time series.
Date&Time Part Extractor
Missing Value
GroupBy
GroupBy
GroupBy
Line Plot
Line Plot
Energy usage data
File Reader (deprecated)
Line Plot
Column Filter
String to Date&Time

Nodes

Extensions

Links

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

Download Workflow
On NodePit since: 2026-03-31
Last update: 2026-03-31
Created with KNIME version: v5.11.0
Tags: Time SeriesEnergy UsageEducationSeasonalityTrend

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