Hub
  • Software
  • Blog
  • Forum
  • Events
  • Documentation
  • About KNIME
  • KNIME Hub
  • Nodes
  • Moving Aggregation
NodeNode / Manipulator

Moving Aggregation

Other Data Types Time Series Smoothing
Drag & drop
Like
Copy short link

This node calculates aggregation values for a moving window. The aggregation values are displayed in new columns appended at the end of the table.

The columns to aggregate can be either defined by selecting the columns directly, by name based on a search pattern or based on the data type. Input columns are handled in this order and only considered once e.g. columns that are added directly on the "Manual Aggregation" tab are ignored even if their name matches a search pattern on the "Pattern Based Aggregation" tab or their type matches a defined type on the "Type Based Aggregation" tab. The same holds for columns that are added based on a search pattern. They are ignored even if they match a criterion that has been defined in the "Type Based Aggregation" tab.

The "Manual Aggregation" tab allows you to change the aggregation method of more than one column. In order to do so select the columns to change, open the context menu with a right mouse click and select the aggregation method to use.

In the "Pattern Based Aggregation" tab you can assign aggregation methods to columns based on a search pattern. The pattern can be either a string with wildcards or a regular expression . Columns where the name matches the pattern but where the data type is not compatible with the selected aggregation method are ignored. Only columns that have not been selected as aggregation column on the "Manual Aggregation" tab are considered.

The "Type Based Aggregation" tab allows to select an aggregation method for all columns of a certain data type e.g. to compute the mean for all decimal columns (DoubleCell). Only columns that have not been handled by the other tabs e.g. column based and pattern based are considered. The data type list to choose from contains basic types e.g String, Double, etc. and all data types the current input table contains.

A detailed description of the available aggregation methods can be found on the 'Description' tab in the node dialog.

Node details

Input ports
  1. Type: Table
    Input column
    Table containing time series.
Output ports
  1. Type: Table
    Moving average values
    Table with columns holding aggregation values.

Extension

The Moving Aggregation node is part of this extension:

  1. Go to item

Related workflows & nodes

  1. Go to item
    2019_07_15_Forum_calculate_next
    iris > Public > 2019_07_15_Forum_calculate_next
  2. Go to item
    Ratio Calculation
    Ratio Data Calculation
    This workflow calculates ratio between two subsequant rows.
    ipazin > Public > 2019_10_09_Ratio_Calculation
  3. Go to item
    Z_025_unpivot
    tommy > Public > Z_025_unpivot
  4. Go to item
    Data Splitting
    Data Manipulation Cumulative Sum
    This workflow divides input table based on data from another table where it is specified …
    ipazin > Public > 2019_10_04_Data_Splitting
  5. Go to item
    justknimeit-14
    Moving aggregation Row filter Just KNIME it
    Description: You are working with audio recognition data tables such that each table’s in…
    hanss > Public > just_knime_it > justknimeit-14
  6. Go to item
    KNIME_challenge14_solution
    Justknimeit-14 Justknimeit
    You are working with audio recognition data tables such that each table’s initial and fin…
    martinmunch > Public > KNIME_challenge14_solution
  7. Go to item
    Challenge 14 Removing Noise from Data
    Justknimeit-14
    Using the fact that "noise" is zero, we can do a cumulative sum on the column and all ini…
    vexatious_outlier > Public > Just KNIME It Challenges > Challenge 14 Removing Noise from Data
  8. Go to item
    Date and Time Analysis - Solution
    Date&Time Time series Moving average
    +3
    Solution to the exercise 8 for KNIME User Training - Constructing a timestamp from String…
    lilipertiwi > Public > KNIMEUserTraining > solutions > 07. Date and Time Analysis - solution
  9. Go to item
    DateTime_Manipulation_Example
    lada > Public > Examples > DateTime_Manipulation_Example
  10. Go to item
    Date and Time Analysis - Solution
    Date&Time Time series Moving average
    +3
    Solution to the exercise 8 for KNIME User Training - Constructing a timestamp from String…
    kzhqtt > Public > WA_Fn-UseC_-IT-Help-Desk > Date and Time Analysis
  1. Go to item
  2. Go to item
  3. Go to item
  4. Go to item
  5. Go to item
  6. Go to item

KNIME
Open for Innovation

KNIME AG
Hardturmstrasse 66
8005 Zurich, Switzerland
  • Software
  • Getting started
  • Documentation
  • E-Learning course
  • Solutions
  • KNIME Hub
  • KNIME Forum
  • Blog
  • Events
  • Partner
  • Developers
  • KNIME Home
  • KNIME Open Source Story
  • Careers
  • Contact us
Download KNIME Analytics Platform Read more on KNIME Server
© 2022 KNIME AG. All rights reserved.
  • Trademarks
  • Imprint
  • Privacy
  • Terms & Conditions
  • Credits