Cell Replacer

Manipulator

Replaces cells in a column according to dictionary table (2nd input). The node has two inputs: The first input contains a target column whose values are to be replaced using the dictionary table (2nd input). From the dictionary table, choose one column (or the rowID column) that is used as lookup criterion. Any occurrence in the target column (1st input) that matches the lookup value is replaced by the corresponding value of the output column, which is another column in the dictionary table.

Missing values are treated as ordinary values, that is, they are valid as lookup and replacement value. If there are duplicates in the lookup column in the dictionary table, the last occurrence (bottom most row) defines the replacement pair.

If the input/lookup column is a collection type, each of the contained values in the collection is a search element.

Input Ports

  1. Type: Data
    Table containing column whose values are to be replaced.
  2. Type: Data
    Dictionary table containing two columns: one lookup column and one replacement column.

Output Ports

  1. Type: Data
    Input table with replaced target column.

  1. Semi Supervised Clustering

    t-SNE Clustering Dimensionality Reduction k-Means meta-clustering semi-supervised learning
    Visualize a table with t-SNE and cluster using k-means and hierarchical clustering.
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  2. Generate Mountain Namesn (Deployment)

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    The workflow generates 200 new, fictive mountain names. It reads the previously trained TensorFlow network and predicts …
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  3. Generate Mountain Namesn (Deployment)

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    The workflow generates 200 new, fictive mountain names. It reads the previously trained TensorFlow network and predicts …
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  4. Network Analytics meets Text Processing

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    This workflow combines two pre-processing techniques: network analytics and text processing.The goal of the text process…
    Users > knime > Examples > 08_Other_Analytics_Types > 04_Social_Media

  5. KNIME Server Log Parsing

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    This workflow parses logfiles created during the operation of KNIME Server. The workflow was developed using KNIME Serve…
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  6. Interactive Big Data Exploration and Visualization

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    Users > knime > Examples > 50_Applications > 49_NYC_Taxi_Visualization

  7. Generate Mountain Namesn (Deployment)

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    The workflow generates 200 new, fictive mountain names. It reads the previously trained TensorFlow network and predicts …
    Users > knime > Examples > 04_Analytics > 14_Deep_Learning > 02_Keras > 10_Generate_Product_Names_With_LSTM

  8. Generate Text Using a Many-To-One LSTM Network (Training)

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    The workflow builds, trains, and saves an RNN with an LSTM layer to generate new fictive fairy tales. The brown nodes de…
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  9. Generate Mountain Namesn (Training)

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    The workflow builds, trains, and saves an RNN with an LSTM layer to generate new fictive mountain names. The brown nodes…
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  10. Init

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Extension

This node is part of the extension

KNIME Core

 v4.0.0

Short Link

Drag node into KNIME Analytics Platform