Metadata-Version: 2.1
Name: spark-nlp-display
Version: 1.8
Summary: Visualization package for Spark NLP
Home-page: http://nlp.johnsnowlabs.com
Author: John Snow Labs
Author-email: john@johnsnowlabs.com
License: UNKNOWN
Description: # spark-nlp-display
        A library for the simple visualization of different types of Spark NLP annotations. 
        
        ## Supported Visualizations:
        - Dependency Parser
        - Named Entity Recognition
        - Entity Resolution
        - Relation Extraction
        - Assertion Status
        
        ## Complete Tutorial
        [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-display/blob/main/tutorials/Spark_NLP_Display.ipynb)
        
        https://github.com/JohnSnowLabs/spark-nlp-display/blob/main/tutorials/Spark_NLP_Display.ipynb
        
        ### Requirements
        - spark-nlp
        - ipython
        - svgwrite
        - pandas
        - numpy
        
        ### Installation
        ```bash
        pip install spark-nlp-display
        ```
        
        ### How to use
        
        ### Databricks
        #### For all modules, pass in the additional parameter "return_html=True" in the display function and use Databrick's function displayHTML() to render visualization as explained below:
        ```python
        from sparknlp_display import NerVisualizer
        
        ner_vis = NerVisualizer()
        
        ## To set custom label colors:
        ner_vis.set_label_colors({'LOC':'#800080', 'PER':'#77b5fe'}) #set label colors by specifying hex codes
        
        pipeline_result = ner_light_pipeline.fullAnnotate(text) ##light pipeline
        #pipeline_result = ner_full_pipeline.transform(df).collect()##full pipeline
        
        vis_html = ner_vis.display(pipeline_result[0], #should be the results of a single example, not the complete dataframe
                            label_col='entities', #specify the entity column
                            document_col='document', #specify the document column (default: 'document')
                            labels=['PER'], #only allow these labels to be displayed. (default: [] - all labels will be displayed)
                            return_html=True)
        
        displayHTML(vis_html)
        ```
        ![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/ner_viz.png)
        
        ### Jupyter
        
        #### Dependency Parser
        ```python
        from sparknlp_display import DependencyParserVisualizer
        
        dependency_vis = DependencyParserVisualizer()
        
        pipeline_result = dp_pipeline.fullAnnotate(text)
        #pipeline_result = dp_full_pipeline.transform(df).collect()##full pipeline
        
        dependency_vis.display(pipeline_result[0], #should be the results of a single example, not the complete dataframe.
                               pos_col = 'pos', #specify the pos column
                               dependency_col = 'dependency', #specify the dependency column
                               dependency_type_col = 'dependency_type' #specify the dependency type column
                               )
        ```
        
        ![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/dp_viz.png)
        
        #### Named Entity Recognition
        
        ```python
        from sparknlp_display import NerVisualizer
        
        ner_vis = NerVisualizer()
        
        pipeline_result = ner_light_pipeline.fullAnnotate(text)
        #pipeline_result = ner_full_pipeline.transform(df).collect()##full pipeline
        
        ner_vis.display(pipeline_result[0], #should be the results of a single example, not the complete dataframe
                            label_col='entities', #specify the entity column
                            document_col='document' #specify the document column (default: 'document')
                            labels=['PER'] #only allow these labels to be displayed. (default: [] - all labels will be displayed)
                            )
        
        ## To set custom label colors:
        ner_vis.set_label_colors({'LOC':'#800080', 'PER':'#77b5fe'}) #set label colors by specifying hex codes
        
        ```
        
        ![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/ner_viz.png)
        
        #### Entity Resolution
        
        ```python
        from sparknlp_display import EntityResolverVisualizer
        
        er_vis = EntityResolverVisualizer()
        
        pipeline_result = er_light_pipeline.fullAnnotate(text)
        
        er_vis.display(pipeline_result[0], #should be the results of a single example, not the complete dataframe
                       label_col='entities', #specify the ner result column
                       resolution_col = 'resolution'
                       document_col='document' #specify the document column (default: 'document')
                       )
        
        ## To set custom label colors:
        er_vis.set_label_colors({'TREATMENT':'#800080', 'PROBLEM':'#77b5fe'}) #set label colors by specifying hex codes
        
        ```
        
        ![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/er_viz.png)
        
        #### Relation Extraction
        ```python
        from sparknlp_display import RelationExtractionVisualizer
        
        re_vis = RelationExtractionVisualizer()
        
        pipeline_result = re_light_pipeline.fullAnnotate(text)
        
        re_vis.display(pipeline_result[0], #should be the results of a single example, not the complete dataframe
                       relation_col = 'relations', #specify relations column
                       document_col = 'document', #specify document column
                       show_relations=True #display relation names on arrows (default: True)
                       )
        
        ```
        
        ![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/re_viz.png)
        
        #### Assertion Status
        ```python
        from sparknlp_display import AssertionVisualizer
        
        assertion_vis = AssertionVisualizer()
        
        pipeline_result = ner_assertion_light_pipeline.fullAnnotate(text)
        
        assertion_vis.display(pipeline_result[0], 
                              label_col = 'entities', #specify the ner result column
                              assertion_col = 'assertion' #specify assertion column
                              document_col = 'document' #specify the document column (default: 'document')
                              )
                              
        ## To set custom label colors:
        assertion_vis.set_label_colors({'TREATMENT':'#008080', 'problem':'#800080'}) #set label colors by specifying hex codes
        
        ```
        
        ![title](https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-display/main/assets/assertion_viz.png)
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 2
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Requires-Python: >=2.7
Description-Content-Type: text/markdown
