Visualization package for Spark NLP
Project 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
https://github.com/JohnSnowLabs/spark-nlp-display/blob/main/tutorials/Spark_NLP_Display.ipynb
Requirements
- spark-nlp
- ipython
- svgwrite
- pandas
- numpy
Installation
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:
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
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)
Jupyter
Dependency Parser
from sparknlp_display import DependencyParserVisualizer
dependency_vis = DependencyParserVisualizer()
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
)
Named Entity Recognition
from sparknlp_display import NerVisualizer
ner_vis = NerVisualizer()
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
Entity Resolution
from sparknlp_display import EntityResolverVisualizer
er_vis = EntityResolverVisualizer()
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
Relation Extraction
from sparknlp_display import RelationExtractionVisualizer
re_vis = RelationExtractionVisualizer()
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)
)
Assertion Status
from sparknlp_display import AssertionVisualizer
assertion_vis = AssertionVisualizer()
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
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
spark-nlp-display-1.7.tar.gz
(83.8 kB
view hashes)
Built Distribution
Close
Hashes for spark_nlp_display-1.7-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b2dcb12355101c51651dc6dc1c335c7eb0a433401be23fb5daa008829d185023 |
|
MD5 | cbfd14661df3b2bab5a8586dc9d037e7 |
|
BLAKE2b-256 | 8d25f1c588b36f910cd555b344f83c4ce3e8eb1845a6e0c7fc1266e9e502cba5 |