Day 4: Dashboards with Dash and Streamlit

$ pip install streamlit plotly pandas

import streamlit as st
import plotly.express as px
import pandas as pd

st.title("Sales Dashboard")

# KPI metrics in columns
col1, col2, col3 = st.columns(3)
col1.metric("Total Revenue", "$342,000", "+12%")
col2.metric("New Customers", "148", "+8")
col3.metric("Avg Deal Size", "$2,310", "-3%")

# Filter
df = px.data.gapminder()
continent = st.selectbox("Continent", df["continent"].unique())
filtered = df[df["continent"] == continent]

# Chart updates automatically when filter changes
fig = px.line(filtered, x="year", y="lifeExp",
                   color="country", title=f"{continent}: Life Expectancy")
st.plotly_chart(fig, use_container_width=True)

import streamlit as st
import pandas as pd

# Sidebar filters
with st.sidebar:
    st.header("Filters")
    year_range = st.slider("Year Range", 2020, 2025, (2022, 2025))
    show_table = st.checkbox("Show raw data")

# File upload
uploaded = st.file_uploader("Upload CSV", type=["csv"])
if uploaded:
    df = pd.read_csv(uploaded)
    st.success(ff"Loaded {len(df)} rows")
    if show_table:
        st.dataframe(df)