Streamlit WordCloud

This component will allow you to build beautiful and interactive Wordcloud visualizations in Streamlit. This project is a wrapper on React Wordcloud with some minor modifications.

Overview

You can use this Streamlit component to create beautiful and interactive WordCloud visualization as shown in the image below.

Quickstart

1. Clone this repo.
2. Create a new Python virtual environment for the package to be install (Optional):

$ python3 -m venv .venv  # create venv
$ .venv/bin/activate   # activate venv

3. Install the package from PyPi

$ pip install streamlit-wordcloud # install streamlit wordcloud package

4 Run the example provided in this repo in usage-example.py:

$ streamlit run usage-example.py

5 Open localhost:8501 in your browser.

6 If everything goes well you should be able to see a page similar to this:

Examples

import streamlit as st 
import streamlit_wordcloud as wordcloud

words = [
    dict(text="Robinhood", value=16000, color="#b5de2b", country="US", industry="Cryptocurrency"),
    dict(text="Personio", value=8500, color="#b5de2b", country="DE", industry="Human Resources"),
    dict(text="Boohoo", value=6700, color="#b5de2b", country="UK", industry="Beauty"),
    dict(text="Deliveroo", value=13400, color="#b5de2b", country="UK", industry="Delivery"),
    dict(text="SumUp", value=8300, color="#b5de2b", country="UK", industry="Credit Cards"),
    dict(text="CureVac", value=12400, color="#b5de2b", country="DE", industry="BioPharma"),
    dict(text="Deezer", value=10300, color="#b5de2b", country="FR", industry="Music Streaming"),
    dict(text="Eurazeo", value=31, color="#b5de2b", country="FR", industry="Asset Management"),
    dict(text="Drift", value=6000, color="#b5de2b", country="US", industry="Marketing Automation"),
    dict(text="Twitch", value=4500, color="#b5de2b", country="US", industry="Social Media"),
    dict(text="Plaid", value=5600, color="#b5de2b", country="US", industry="FinTech"),
]
return_obj = wordcloud.visualize(words, tooltip_data_fields={
    'text':'Company', 'value':'Mentions', 'country':'Country of Origin', 'industry':'Industry'
}, per_word_coloring=False)

.visualize() Method Options

Prop	Default	Type	Description
words	None	list[dict]	List of word dictionaries to be used for wordcloud visualiztion. Required keys: 'text', 'value'. Optional keys: 'color', <-Any Additional Meta Key->
width	'100%'	str	Width of wordcloud
height	None	str	Height of wordcloud
font_min	None	int	Smallest font size of words in wordcloud
font_max	None	int	Largest font size of words in wordcloud
font_scale	None	float	The scaling factor which will be multiplied by the default font sizes. font_scale will only have an effect if no font_min or font_max has been passed.
max_words	None	int	Maximum number of words to be displayed on wordcloud.
palette	'viridis'	str	Color palette to be used for the words in the wordcloud. This will only have an effect if per_word_coloring is set to False. Available Options: Matplotlib Colormaps
per_word_coloring	False	bool	If True, the color key in the words objects will be used to fill the words in wordcloud.
padding	1	int	Padding between words in word cloud.
layout	'rectangular'	str	Wordcloud layout. Available options: ['rectangular', 'archimedean']
enable_tooltip	True	bool	Whether to show tooltip popover once hover on a word.
tooltip_data_fields	{'text':'Word', 'value':'Count'}	dict	A dictionary containing keys and their displayed values to be used in tooltip. The keys in this dictionary can only be selected from the ones passed in the words dictionaries.
key	None	str	An optional key that uniquely identifies this Streamlit component.

Development

• Ensure you have Python 3.6+, Node.js, and npm installed.

• Clone this repo.

• Create a new Python virtual environment for the template:

$ python3 -m venv .venv  # create venv
$ .venv/bin/activate   # activate venv
$ pip install streamlit # install streamlit

• Initialize and run the component template frontend:

$ cd streamlit_wordcloud/frontend
$ npm install    # Install npm dependencies
$ npm run start  # Start the Webpack dev server

• First open streamlit_wordcloud/streamlit_wordcloud.py in an editor of your choice and change _RELEASE to False.

• From a separate terminal, run the Streamlit Wordcloud app:

$ .venv/bin/activate  # activate the venv you created earlier
$ streamlit run streamlit_wordcloud/streamlit_wordcloud.py  # run the wordcloud app