Maruta and Kato. Intent-aware Visualization Recommendation for Tabular Data. WISE 2021.
Clone our repository
git clone https://github.com/kasys-lab/intent-viz.git
cd intent-viz
Our model requires word embedding model and trained model
To get word embedding model, please download glove.6B.zip
.
And put glove.6B.100d.txt
file in unzipped glove.6B.zip
file to data/
.
wget http://downloads.cs.stanford.edu/nlp/data/glove.6B.zip
unzip glove.6B.zip
mv glove.6B.100d.txt ./data/
rm glove*
To get trained model, please access https://drive.google.com/drive/folders/1G2WTiNGCOzu2W4E3IFB6WT62RJXJkFeZ?usp=sharing and download predict_vis_columns.pt
.
And put predict_vis_columns.pt
to saved_models/
$ curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python
$ source ~/.bash_profile
$ poetry install
Predict a visualization type and visualized column percents
$ poetry run python demo.py <data path>
$ poetry run python demo.py "./data/input_data.json"
Json format pair data of a visualization intent and tabular data.
{ "visualization_intent": "Population trends in Italy",
"data":
[
{
"Year": 2015,
"population": 100,
"GDP": 2.3
},{
"Year": 2016,
"population": 110,
"GDP": 2.4
},{
"Year": 2017,
"population": 130,
"GDP": 2.9
},{
"Year": 2018,
"population": 170,
"GDP": 3.0
},{
"Year": 2019,
"population": 200,
"GDP": 3.1
},{
"Year": 2020,
"population": 220,
"GDP": 3.6
}
]
}
Output visualuzation type and visualized column percent
predict visualization type : Line chart
predict visualized columns percent
header : percent
Year : 1.0
population : 0.9150764707515349
GDP : 0.0