NodeExtract Table Dimension

Other

The number of rows and columns of the input table are extracted and written to the output table. The output table consists of two rows and one column. The first row contains the number of rows and the second row contains the number of columns of the input table. Additionally the two numbers are pushed out as flow variables.

Input ports
  1. Input table with dimensions to extract Type: Data
    The input table for which dimensions are extracted.
Output ports
  1. Table containing dimensions Type: Data
    The output table containing the dimensions of the input table.
  1. Sentiment Analysis (Classification) of Documents with NGram Features
    NLP Natural Language Processing
    This workflow shows how to import text from a csv file, convert it to documents, preprocess the documents and transform …
    iopsych > Public > 07_Sentiment_Classification_with_NGrams
  2. Example workflow for Fourier Analysis Component
    Example Server Components Fast Fourier Transform Frequency Transformation Python IoT Internet of Things
    This example workflow shows how to use the Fast Fourier Transform (FFT) Component.
    ana_ved > Public > Fourier_Analysis_use_case
  3. Equally distribute work package minutes by number of employees via statistics
    mw > Public > Knime Forum Support > Equally distribute work package minutes by number of employees via statistics
  4. Importing, preprocessing, and clustering of textual data
    NLP Natural Language Processing
    This workflow shows how to import textual data, preprocess documents by filtering and stemming, transform documents into…
    knime > Examples > 08_Other_Analytics_Types > 01_Text_Processing > 01_Document_clustering
  5. Time Series Prediction
    Time Series Prediction Energy Usage Linear Regression
    Time Series Analysis 07. LSTM Network Summary: In this exercise we'll define an LSTM Network Architechure to train and d…
    corey > Public > 08_LSTM_Network
  6. Guided Labeling for Document Classification (Legacy)
    active learning human-in-the-loop guided analytics document classification sentiment analysis topic detection tag cloud topic active learning uncertainty entropy sampling uncertainty sampling movie reviews highliting legacy human-in-the-loop
    Updated workflow with 4.1 nodes available. Check references below. This old legacy workflow defines a fully automated we…
    knime > Examples > 50_Applications > 57_Guided_Labeling > 00_Guided_Labeling_for_Document_Classification_(legacy)
  7. Weak Supervision for Document Classification
    human-in-the-loop guided analytics document classification sentiment analysis movie reviews weak supervision weak model gradient boosted tree probabilistic output compare models binary classification
    This workflow defines a fully automated web based application that will label your data using weak supervision. The work…
    knime > Examples > 50_Applications > 57_Guided_Labeling > 03_Weak_Supervision_for_Document_Classification
  8. h2o_gbm
    knime > Examples > 50_Applications > 36_Guided_Analytics_for_ML_Automation > 01_Guided_Analytics_for_ML_Automation > Models > classification > h2o_gbm
  9. h2o_rndfor
    knime > Examples > 50_Applications > 36_Guided_Analytics_for_ML_Automation > 01_Guided_Analytics_for_ML_Automation > Models > classification > h2o_rndfor
  10. h2o_naive
    knime > Examples > 50_Applications > 36_Guided_Analytics_for_ML_Automation > 01_Guided_Analytics_for_ML_Automation > Models > classification > h2o_naive