Code Editor for app.py

import streamlit as st
import pandas as pd
import requests

st.title("Pokemon Data Plotter")

# NOTE: Using corsproxy.io because we're in a WASM environment. If running locally,
# you can remove the corsproxy.io prefix.
@st.cache_data
def load_pokemon_data():
    url = "https://corsproxy.io/?https://raw.githubusercontent.com/fanzeyi/pokemon.json/master/pokedex.json"
    response = requests.get(url)
    data = response.json()
    
    # Convert to DataFrame
    df = pd.DataFrame(data)
    
    # Explode the stats list into separate columns
    stats_df = pd.DataFrame([{stat['name']: stat['base_stat'] for stat in pokemon['stats']} 
                           for pokemon in data])
    
    # Combine basic info with stats
    df = pd.DataFrame({
        'name': [p['name']['english'] for p in data],
        'type': [p['type'][0] for p in data],  # Using first type only
        'HP': stats_df['HP'],
        'Attack': stats_df['Attack'],
        'Defense': stats_df['Defense'],
        'Sp. Attack': stats_df['Sp. Attack'],
        'Sp. Defense': stats_df['Sp. Defense'],
        'Speed': stats_df['Speed']
    })
    return df

# Load data
df = load_pokemon_data()

# Sidebar controls
st.sidebar.header("Plot Controls")

# Select attributes to plot
x_axis = st.sidebar.selectbox(
    "Choose X-axis", 
    ['HP', 'Attack', 'Defense', 'Sp. Attack', 'Sp. Defense', 'Speed']
)

y_axis = st.sidebar.selectbox(
    "Choose Y-axis",
    ['HP', 'Attack', 'Defense', 'Sp. Attack', 'Sp. Defense', 'Speed'],
    index=1
)

# Create scatter plot
st.subheader(f"{x_axis} vs {y_axis} for Pokemon")
st.scatter_chart(
    data=df,
    x=x_axis,
    y=y_axis,
    color='type',
    size=None,
    use_container_width=True
)

# Display raw data
if st.checkbox("Show raw data"):
    st.write(df)