Dashboards with Streamlit

Streamlit is an open-source Python framework that turns data scripts into shareable web applications in minutes — with no front-end experience required. It is widely used for building data dashboards, machine learning demos, and interactive reports.

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Installation

pip install streamlit

Run a Streamlit app:

streamlit run app.py

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Why Streamlit?

Feature	Description
Pure Python	No HTML, CSS, or JavaScript required
Reactive	The app re-runs from top to bottom on every interaction
Fast prototyping	Go from script to web app in minutes
Built-in widgets	Sliders, dropdowns, text inputs, file uploaders
Chart support	Native support for Matplotlib, Seaborn, Plotly, Altair, and more
Deployment	Free deployment via Streamlit Community Cloud

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Hello World

Create a file called app.py:

import streamlit as st

st.title("Hello, Streamlit!")
st.write("This is my first Streamlit app.")

Run it:

streamlit run app.py

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Displaying Text

import streamlit as st

st.title("Main Title")
st.header("Section Header")
st.subheader("Sub-section")
st.write("General text — supports **Markdown**.")
st.markdown("Use `st.markdown()` for rich formatting.")
st.caption("Small caption text")
st.code("print('Hello')", language="python")
st.latex(r"E = mc^2")

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Displaying Data

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

df = pd.DataFrame(
    np.random.randn(10, 3),
    columns=["A", "B", "C"]
)

st.dataframe(df)              # Interactive table
st.table(df.head())           # Static table
st.metric("Revenue", "£1.2M", "+12%")
st.json({"name": "Alice", "score": 95})

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Charts in Streamlit

Built-in Charts

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

df = pd.DataFrame(
    np.random.randn(20, 3),
    columns=["A", "B", "C"]
)

st.line_chart(df)
st.bar_chart(df)
st.area_chart(df)

Matplotlib and Seaborn

import streamlit as st
import matplotlib.pyplot as plt
import seaborn as sns

tips = sns.load_dataset("tips")

fig, ax = plt.subplots()
sns.histplot(data=tips, x="total_bill", bins=20, ax=ax)
ax.set_title("Distribution of Total Bill")

st.pyplot(fig)

Plotly

import streamlit as st
import plotly.express as px

df = px.data.gapminder()
df_2007 = df[df["year"] == 2007]

fig = px.scatter(df_2007, x="gdpPercap", y="lifeExp",
                 size="pop", color="continent",
                 hover_name="country", log_x=True,
                 title="Gapminder 2007")
st.plotly_chart(fig, use_container_width=True)

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Interactive Widgets