Code Editor for app.py

import streamlit as st
import pandas as pd
import altair as alt

st.title("FDA Recalls Analysis Dashboard")

# Load data
@st.cache_data
def load_data():
    # NOTE: Using corsproxy.io because we're in a WASM environment. If running locally,
    # you can remove the corsproxy.io prefix.
    url = "https://corsproxy.io/?https://raw.githubusercontent.com/FDA/open.fda.gov/master/examples/recalls/recalls_sample.json"
    df = pd.read_json(url)
    df['recall_initiation_date'] = pd.to_datetime(df['recall_initiation_date'])
    return df

try:
    df = load_data()
    
    # Show data overview
    st.subheader("Data Overview")
    st.write(f"Total number of recalls: {len(df)}")
    
    # Time series analysis
    st.subheader("Recalls Over Time")
    recalls_by_date = df.groupby('recall_initiation_date').size().reset_index(name='count')
    
    chart = alt.Chart(recalls_by_date).mark_line().encode(
        x='recall_initiation_date:T',
        y='count:Q',
        tooltip=['recall_initiation_date', 'count']
    ).properties(
        width=700,
        height=400
    )
    st.altair_chart(chart, use_container_width=True)
    
    # Classification Analysis
    st.subheader("Recalls by Classification")
    classification_counts = df['classification'].value_counts()
    
    class_chart = alt.Chart(classification_counts.reset_index()).mark_bar().encode(
        x='index:N',
        y='classification:Q',
        color='index:N',
        tooltip=['index', 'classification']
    ).properties(
        width=500,
        height=300
    )
    st.altair_chart(class_chart, use_container_width=True)
    
    # State Analysis
    st.subheader("Recalls by State")
    state_counts = df['state'].value_counts().head(10)
    
    state_chart = alt.Chart(state_counts.reset_index()).mark_bar().encode(
        x='index:N',
        y='state:Q',
        color='index:N',
        tooltip=['index', 'state']
    ).properties(
        width=500,
        height=300
    )
    st.altair_chart(state_chart, use_container_width=True)
    
    # Show raw data
    st.subheader("Raw Data")
    if st.checkbox("Show raw data"):
        st.write(df)

except Exception as e:
    st.error("Error loading or processing data. Please check if the data source is available.")
    st.error(f"Error details: {str(e)}")