This node takes a list of user-defined rules and tries to match them
to each row in the input table. If the first matching rule has a
TRUE outcome, the row will be
selected for inclusion. Otherwise (i.e. if the first matching rule yields FALSE) it will be
excluded. If no rule matches the row will be excluded.
Inclusion and exclusion may be inverted, see the options below.
Each rule is represented by a line.
To add comments, start a line with
//
(comments can not be placed in the same line as a rule). Anything after // will not be interpreted as a rule.
Rules consist of a condition part (antecedent), which must
evaluate to
true
or
false
, and an outcome (consequent, after the => symbol) which is either
TRUE
or
FALSE
.
If no rule matches, the outcome is treated as if it were
FALSE
.
Columns are given by their name surrounded by $, numbers are given
in the usual decimal representation. Note that strings must not
contain (double-)quotes (for those cases use the following syntax: /Oscar Wilde's wisdom: "Experience is simply the name we give our mistakes."/). The flow variables are
represented by
$${
TypeCharacterAndFlowVarName
}$$
.
The TypeCharacter should be 'D' for double (real) values, 'I' for
integer values and 'S' for strings.
The logical expressions can be grouped with parentheses. The
precedence rules for them are the following: NOT binds most, AND,
XOR and finally OR the least.
Comparison operators always take
precedence over logical connectives.
All operators (and their names)
are case-sensitive.
The
ROWID
represents the row key string, the
ROWINDEX
is a the index of the row (first row has
0
value), while
ROWCOUNT
stands for the number of rows in the table.
Some example rules (each should be in one line):
// This is a comment $Col0$ > 0 => TRUEWhen the values in Col0 are greater than 0, we select the row (if no previous rule matched with FALSE outcome).
$Col0$ = "Active" AND $Col1$ <= 5 => TRUEYou can combine conditions.
$Col0$ LIKE "Market Street*" AND
($Col1$ IN ("married", "divorced")
OR $Col2$ > 40) => FALSE
With parentheses you can combine multiple conditions.
$Col0$ MATCHES $${SFlowVar0}$$ OR $$ROWINDEX$$ < $${IFlowVar1}$$ =>
FALSE
The flow variables, table constants can also appear in conditions.
You can use either Ctrl+Space to insert predefined parts, or select them from the upper controls.
The following comparisons result true (other values are neither less, nor greater or equal to missing and NaN values):
- ? =,<=,>= ?
- NaN =,<=,>= NaN
Options
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Binary Objects to Files< 1 %- Binary Objects to Strings< 1 %
- FTP Connection (legacy)< 1 %
- Strings to Binary Objects< 1 %
Table Column to Variable< 1 %Database SQL Executor< 1 %File Reader< 1 %- Silhouette Coefficient< 1 %
- Hierarchical Cluster View< 1 %
Decision Tree Learner< 1 %- MDS (DistMatrix)< 1 %
- MDS Projection (DistMatrix)< 1 %
- OPTICS Cluster Compute< 1 %
Tree Ensemble Predictor< 1 %Gradient Boosted Trees Predictor< 1 %- PMML Gradient Boosted Trees Predictor (Regression)< 1 %
- Tree Ensemble Predictor< 1 %
String To Number (PMML)< 1 %- Kruskal-Wallis Test< 1 %
- HiLite Table (legacy)< 1 %
- Size Manager< 1 %
- SDF Extractor< 1 %
- Smiles Directory Writer< 1 %
- Amazon Comprehend (Key Phrases)< 1 %
DB Loader< 1 %- Java Distance< 1 %
- Radar Plot (Plotly)< 1 %
- Stacked Area Chart (JavaScript)< 1 %
- Prediction Fusion< 1 %
- Cell to PMML< 1 %
- MoSS< 1 %
- Ruby Script< 1 %
- JPython Script 2:1 (Legacy)< 1 %
TIBCO File Writer< 1 %Word Vector Learner (legacy)< 1 %- Word2Vec Learner (legacy)< 1 %
- IDF< 1 %
- Tika Language Detector< 1 %
- Dictionary Replacer< 1 %
- Kuhlen Stemmer< 1 %
- OpenNLP NE Tagger< 1 %
- StanfordNLP NE Tagger< 1 %
- Document Data Assigner< 1 %
- Document Vector Hashing< 1 %
Meta Info Extractor< 1 %- Term Neighborhood Extractor< 1 %
- Slider Input (legacy)< 1 %
- Container Input (Table)< 1 %
- JSON Path (Dictionary)< 1 %
JSON Writer< 1 %- Median Filter< 1 %
- Quantile Filter< 1 %
- Image Properties< 1 %
- Global Thresholder< 1 %
- Multi Feature Inserter< 1 %
Python Script (1⇒1)< 1 %Python Script (2⇒1)< 1 %XGBoost Linear Ensemble Learner< 1 %XPath< 1 %Binary Scorer< 1 %- Lipinski's Rule-of-Five< 1 %
- SMARTS Query< 1 %
- RDKit Aromatizer< 1 %
- RDKit Molecule Highlighting< 1 %
- RDKit SDF Difference Checker< 1 %
- Text Classifier Predictor< 1 %
- Google Address Geocoder< 1 %
Location Extractor< 1 %- URL Extractor< 1 %
- Trim Image Whitespace< 1 %
- HTTP Result Data Extractor< 1 %
- Feed Discovery< 1 %
Web Searcher< 1 %Click< 1 %- Wait< 1 %
- Fast Fourier Transform (FFT)< 1 %
- Window Slider< 1 %
- Network Component Splitter< 1 %
- XLS Control Table Merger< 1 %
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- File Cells to Port< 1 %
- Tautomer Generator< 1 %
- Duplicate Remover< 1 %
- Templated Conformer Generation (RDKit)< 1 %
- Speedy SMILES Remove d-Block Metal-containing Molecules Filter< 1 %
- Speedy SMILES Remove s-Block Metal-containing Molecules Filter< 1 %
- Speedy SMILES Remove Multicomponent Molecules Filter< 1 %
- Length< 1 %
- Total Count< 1 %
IF Switch (Flow Variable Value)< 1 %Loop End (Upto 4 ports)< 1 %- Chunk Loop Run-for-time Loop Start< 1 %
- Timed Loop End (1 port)< 1 %
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- Fragments to MMPs< 1 %
- Uniquify IDs< 1 %
- Benchmark Start (Memory Monitoring)< 1 %
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- URL Decode< 1 %
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Open in Python< 1 %Python Plot< 1 %- Python Plot< 1 %
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- Desirability Ranking< 1 %
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Element Selector< 1 %- List Remote Files (legacy)< 1 %
- URI to Port< 1 %
- URL to File Path (Variable)< 1 %
- Zip Files (legacy)< 1 %
Variable to Table column< 1 %Table Column to Variable< 1 %Variable to Table Row< 1 %Image Writer (Table Column)< 1 %- Table to Image< 1 %
Interval Loop Start< 1 %Variable Loop End< 1 %- Hierarchical Cluster Assigner (local)< 1 %
- MDS< 1 %
PCA Inversion< 1 %Logistic Regression Learner< 1 %Scorer< 1 %Numeric Scorer< 1 %- SVM Predictor< 1 %
- PCA Compute< 1 %
- PCA Inversion< 1 %
Tree Ensemble Learner< 1 %Tree Ensemble Predictor (Regression)< 1 %Random Forest Learner (Regression)< 1 %Random Forest Predictor< 1 %Simple Regression Tree Learner< 1 %- Tree Ensemble Learner< 1 %
Tree Ensemble Predictor< 1 %- PMML Simple Regression Tree Predictor< 1 %
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- String to SVG< 1 %
Linear Correlation< 1 %- CAIM Applier< 1 %
Domain Calculator< 1 %- Edit Nominal Domain (Dictionary)< 1 %
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Normalizer< 1 %- Denormalizer (PMML)< 1 %
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- Rule Engine Variable (Dictionary)< 1 %
Rank Correlation< 1 %- Linear Discriminant Analysis Compute< 1 %
CASE Switch Variable (End)< 1 %CASE Switch Variable (Start)< 1 %- Create Temp Dir (legacy)< 1 %
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- Amazon Comprehend (Sentiment)< 1 %
Microsoft SQL Server Connector< 1 %- Oracle Connector< 1 %
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- Random Number Assigner (Apache)< 1 %
- TimeDelay Loop End< 1 %
Distance Matrix Calculate< 1 %- Matrix Distance< 1 %
K Nearest Neighbor (Distance Function)< 1 %- Keras Network Executor< 1 %
- DL Python Network Creator< 1 %
- TensorFlow Network Executor< 1 %
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- Stacked Area Chart (Plotly)< 1 %
- Boosting Learner Loop Start< 1 %
Delegating Loop End (deprecated)< 1 %PMML Predictor< 1 %- PMML Predictor< 1 %
- Voting Loop End< 1 %
- Explorer Writer< 1 %
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- DL4J Feedforward Predictor (Layer) (legacy)< 1 %
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- HeatMap (JFreeChart)< 1 %
- Bubble Chart (JFreeChart)< 1 %
- Index Query< 1 %
- Rule Viewer (local) (Legacy)< 1 %
Excel Reader (XLS)< 1 %Excel Reader (XLS)< 1 %Send to Power BI< 1 %- Java Edit Variable (simple)< 1 %
Send to Tableau Server (TDE)< 1 %Tableau Writer (TDE)< 1 %Word Vector Apply (legacy)< 1 %- Word Vector Apply (legacy)< 1 %
- Doc2Vec Learner (legacy)< 1 %
- Term Co-Occurrence Counter< 1 %
- DF< 1 %
- Term Document Entropy< 1 %
- StanfordNLP Open Information Extractor< 1 %
- Chi-Square Keyword Extractor< 1 %
- Dictionary Filter< 1 %
- Porter Stemmer< 1 %
Punctuation Erasure< 1 %Stop Word Filter< 1 %- Tag Stripper< 1 %
- Wildcard Tagger< 1 %
- POS Tagger< 1 %
Stanford tagger< 1 %- Stanford Tagger< 1 %
Bag of Words Creator< 1 %Document Data Extractor< 1 %- Document Vector< 1 %
Meta Info Inserter< 1 %Column Filter Configuration< 1 %- Integer Slider Configuration< 1 %
- Text Output (legacy)< 1 %
- Integer Input (legacy)< 1 %
- Value Selection (legacy)< 1 %
- Decision Tree View (JavaScript)< 1 %
- Date&Time Widget< 1 %
- Column Selection Widget< 1 %
- JSON Column Combiner< 1 %
- XML to JSON< 1 %
- JSON to XML< 1 %
- Average Filter< 1 %
- Gaussian Convolution< 1 %
- Labeling to RGB Img< 1 %
- Image Converter< 1 %
- Image Cropper< 1 %
- Inverter< 1 %
- Image Resizer< 1 %
- Connected Component Analysis< 1 %
- Labeling to Image< 1 %
- Apply Color Settings To Labels< 1 %
- Local Thresholding< 1 %
- SHAP Loop End< 1 %
- Partial Dependence/ICE Plot< 1 %
MongoDB Writer< 1 %- Hierarchy Extractor< 1 %
- Row to Network< 1 %
- SubGraph Extractor< 1 %
- Object ID Filter< 1 %
- Node Name Filter< 1 %
- Network Viewer< 1 %
- Parameter Optimization Loop End< 1 %
Python Learner< 1 %Python Script (2⇒1)< 1 %- Python Edit Variable (legacy)< 1 %
Column Selection QuickForm (legacy)< 1 %Value Filter QuickForm (legacy)< 1 %- Add Table to R< 1 %
- Git Pull< 1 %
- Duration to Number< 1 %
- Time to String (legacy)< 1 %
- Twitter Followers Search< 1 %
- Twitter Retweet Search< 1 %
- Byte Converter< 1 %
XGBoost Tree Ensemble Learner (Regression)< 1 %- Binned Performance< 1 %
Table to HTML String< 1 %- CDK to Molecule< 1 %
- 3D Coordinates< 1 %
- 3D D-Similarity< 1 %
- XLogP< 1 %
- Element Filter< 1 %
- Substructure Search< 1 %
- 3D Viewer< 1 %
- RDKit Add Hs< 1 %
- RDKit Calculate Charges< 1 %
- RDKit Interactive Table< 1 %
- RDKit Optimize Geometry< 1 %
- RDKit Count-Based Fingerprint< 1 %
- Information Gain Calculator< 1 %
- Text Classifier Learner< 1 %
Hash Calculator< 1 %- URL Domain Extractor< 1 %
- URL Normalizer< 1 %
- URL Resolver< 1 %
HTTP Retriever< 1 %- Feed Parser< 1 %
FreeGeoIP< 1 %
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Workflows
_01_PMR_AnalysisKNIME Hub- (Optional)_Linear_RegressionKNIME Hub
- [01.CX] Combining Siloed Legacy Data with Running App's Back-End DatabaseKNIME Hub
- [03.CX] Extracting and Transforming Viber Broadcast Data from InfobipKNIME Hub
- 0. Lubes_Sales_Pred-ModelNodePit Space
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Links
- Delete Rowby qqilihq on 2018-06-01forum.knime.com/p/43552
- Filter blank rows outby izaychik63 on 2019-02-14forum.knime.com/p/54508
- Removing rows which contains less than or equal to three wordsby armingrudd on 2019-09-03forum.knime.com/p/69158
- Selection of Product using various rulesby izaychik63 on 2020-04-15forum.knime.com/p/87652
- Find similar rowsby armingrudd on 2018-12-25forum.knime.com/p/52077
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