Analytics Vidhya
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Analytics Vidhya

Predicting Cryptocurrency Prices using Facebook Prophet

Or how to deploy a Forecasting Web Application using Python, Streamlit & Heroku

Photo by Nick Chong on Unsplash

Building the Streamlit Crypto Forecaster

$pip install pandas 
$pip install streamlit
$pip install plotly
$pip install cryptocmd
$pip install pystan
$pip install fbprophet

The Data

The Graphs

Streamlit app overview with current price data & time series plot

Facebook Prophet

Deployment on Heroku

Required Files

mkdir -p ~/.streamlit/echo “\
port = $PORT\n\
enableCORS = false\n\
headless = true\n\
“ > ~/.streamlit/config.toml
web: sh && streamlit run


Heroku deployment overview, connect with Github as deployment method
Connect with your Github repository path & deploy your app!
Prediction for the next 365 days using Facebook Prophet

Final Note



Analytics Vidhya is a community of Analytics and Data Science professionals. We are building the next-gen data science ecosystem

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Michael Tuijp

I’m a Data Scientist and enthusiast of leveraging the latest tools in Data Science, Engineering & DevOps to improve processes, businesses & our lives overall!