Code Editor for app.py

import streamlit as st
import requests
import pandas as pd
import matplotlib.pyplot as plt

st.title("Crypto Price Tracker")

# Fetch price and volume data for top 10 cryptocurrencies from CoinGecko API
url = "https://api.coingecko.com/api/v3/coins/markets?vs_currency=usd&order=market_cap_desc&per_page=10&page=1&sparkline=false"
response = requests.get(url)
crypto_data = response.json()

# Create a DataFrame from the API data
df = pd.DataFrame(crypto_data)

# Check if data was retrieved successfully
if not df.empty:
    # Filter for columns we need and rename them
    df = df[['id', 'name', 'current_price', 'market_cap', 'total_volume']]
    df.columns = ['ID', 'Cryptocurrency', 'Price (USD)', 'Market Cap (USD)', 'Volume (24h)']

    # Display a dropdown for cryptocurrency selection
    crypto_names = df['Cryptocurrency'].tolist()
    selected_crypto = st.selectbox("Select a Cryptocurrency from Top 10", crypto_names)

    # Allow user to enter a custom cryptocurrency name
    user_input = st.text_input("Or enter a cryptocurrency name")

    # Determine the cryptocurrency to search for
    if user_input.strip():
        search_crypto = user_input.strip()
        # Fetch the ID for the custom cryptocurrency
        search_url = f"https://api.coingecko.com/api/v3/coins/{search_crypto.lower()}"
        search_response = requests.get(search_url)
        if search_response.status_code == 200:
            search_data = search_response.json()
            crypto_id = search_data['id']
            selected_crypto_name = search_data['name']
            selected_data = {
                "Cryptocurrency": selected_crypto_name,
                "Price (USD)": search_data['market_data']['current_price']['usd'],
                "Market Cap (USD)": search_data['market_data']['market_cap']['usd'],
                "Volume (24h)": search_data['market_data']['total_volume']['usd']
            }
            custom_search = True
        else:
            st.error("Cryptocurrency not found. Please enter a valid name.")
            custom_search = False
    else:
        # Use the dropdown selection if no custom input is provided
        crypto_id = df[df['Cryptocurrency'] == selected_crypto]['ID'].values[0]
        selected_data = df[df['Cryptocurrency'] == selected_crypto].to_dict(orient="records")[0]
        custom_search = False

    # Display the selected cryptocurrency's details
    if selected_data:
        st.write("### Current Data")
        st.write(pd.DataFrame([selected_data]).set_index('Cryptocurrency'))

        # Fetch historical data for the selected cryptocurrency
        history_url = f"https://api.coingecko.com/api/v3/coins/{crypto_id}/market_chart?vs_currency=usd&days=7"
        history_response = requests.get(history_url)
        history_data = history_response.json()

        # Process historical price data if available
        if 'prices' in history_data:
            prices = history_data['prices']
            dates = [pd.to_datetime(price[0], unit='ms') for price in prices]
            price_values = [price[1] for price in prices]

            # Create a DataFrame for plotting
            history_df = pd.DataFrame({
                'Date': dates,
                'Price (USD)': price_values
            })

            # Display the slider to select the date range
            min_date, max_date = history_df['Date'].min(), history_df['Date'].max()
            date_range = st.slider(
                "Select Date Range",
                min_value=min_date,
                max_value=max_date,
                value=(min_date, max_date),
                format="MM/DD"
            )

            # Filter the DataFrame based on the selected date range
            filtered_history_df = history_df[(history_df['Date'] >= date_range[0]) & (history_df['Date'] <= date_range[1])]

            # Plot the historical prices within the selected date range
            st.write("### Price History (Last 7 Days)")
            fig, ax = plt.subplots()
            ax.plot(filtered_history_df['Date'], filtered_history_df['Price (USD)'], color='blue')
            ax.set_title(f"{selected_data['Cryptocurrency']} Price Over the Selected Range")
            ax.set_xlabel("Date")
            ax.set_ylabel("Price (USD)")
            st.pyplot(fig)

        else:
            st.write("Historical price data not available for this cryptocurrency.")
else:
    st.write("Could not retrieve crypto data. Please try again.")