README.md

Streamlit Application Overview & Docuementation

Repository for Data Science 460 from BYU-Idaho, helping them set up an machine learning app with Docker.

What is streamlit

• importable package designed for creating webpages from simple scripts
• uses basic commands to deploy a local webpage with interactive components and other elements from your python code
• this allows us to create our ML model using Python scripts and then deploy it to a shareable webpage

App Deployment

Open your terminal

• Run to install streamlit:

pip install streamlit

Import streamlit

import streamlit as st

Lets put a simple title

st.title("I know what I'm doing")

• Save the file

In terminal:

streamlit run [yourFile].py

You're doing GREAT! Lets add more stuff!

Charts in Streamlit

Streamlit documentation and programming examples can be found here

Line Charts Line Chart Documentation

import streamlit as st
import pandas as pd
import numpy as np

chart_data = pd.DataFrame(
    np.random.randn(20, 3),
    columns=['a', 'b', 'c'])

st.line_chart(chart_data)

Bar Charts Bar Chart Documentation

import streamlit as st
import pandas as pd
import numpy as np

chart_data = pd.DataFrame(
    np.random.randn(50, 3),
    columns=["a", "b", "c"])

st.bar_chart(chart_data)

Maps Map Documentation

import streamlit as st
import pandas as pd
import numpy as np

df = pd.DataFrame(
    np.random.randn(1000, 2) / [50, 50] + [37.76, -122.4],
    columns=['lat', 'lon'])

st.map(df)

ML Deployment with Streamlit

App development Example

• https://www.youtube.com/watch?v=Klqn--Mu2pE&t=211s
• Example here

Links

1. https://docs.streamlit.io/
2. https://docs.streamlit.io/library/api-reference/charts
3. https://docs.streamlit.io/library/api-reference/data
4. https://docs.streamlit.io/library/api-reference/widgets
5. https://docs.streamlit.io/library/api-reference/status