Create app.py

app.py

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+import streamlit as st
+import yfinance as yf
+import matplotlib.pyplot as plt
+import matplotlib.colors as mcolors
+import numpy as np
+import imageio
+from datetime import datetime
+from tempfile import TemporaryDirectory
+import os
+
+st.set_page_config(page_title="Bubble Market Cap Animation", layout="wide")
+st.title("📊 Market Cap Bubble Animation")
+
+tickers_input = st.text_input("Enter Tickers (comma-separated):", "AAPL,MSFT,GOOG,NVDA,AMZN")
+start_date = st.date_input("Start Date", datetime(2021, 1, 1))
+end_date = st.date_input("End Date", datetime.today())
+
+if st.button("Generate Bubble Animation"):
+    tickers = [ticker.strip().upper() for ticker in tickers_input.split(",")]
+    data = {}
+    market_caps = {}
+    colors = {}
+
+    st.info("Fetching data...")
+    for ticker in tickers:
+        try:
+            t = yf.Ticker(ticker)
+            hist = t.history(start=start_date, end=end_date)
+            shares = t.info.get("sharesOutstanding", None)
+            if shares is None:
+                continue
+            hist["Market Cap"] = hist["Close"] * shares
+            data[ticker] = hist
+            market_caps[ticker] = hist["Market Cap"]
+            colors[ticker] = np.random.rand(3,)  # RGB color
+        except Exception as e:
+            st.warning(f"Failed to load {ticker}: {e}")
+
+    if not data:
+        st.error("No valid data found.")
+        st.stop()
+
+    all_dates = sorted(set(date for series in market_caps.values() for date in series.index))
+    st.info(f"Rendering {len(all_dates)} frames...")
+
+    with TemporaryDirectory() as tmpdir:
+        filenames = []
+
+        for i, date in enumerate(all_dates[::max(1, len(all_dates)//30)]):  # Max 30 frames
+            fig, ax = plt.subplots(figsize=(10, 6))
+            ax.set_xlim(0, 1)
+            ax.set_ylim(0, 1)
+            ax.axis('off')
+            ax.set_title(f"Market Cap on {date.date()}", fontsize=16)
+
+            for j, ticker in enumerate(data):
+                try:
+                    cap = market_caps[ticker].get(date, 0)
+                    if cap == 0 or np.isnan(cap):
+                        continue
+                    size = cap / 1e11  # normalize
+                    ax.scatter(
+                        x=0.1 + 0.8 * np.random.rand(), 
+                        y=0.1 + 0.8 * np.random.rand(),
+                        s=1000 * size,
+                        alpha=0.7,
+                        color=colors[ticker],
+                        label=ticker,
+                        edgecolors='black'
+                    )
+                    ax.text(0.1 + 0.8 * np.random.rand(), 0.1 + 0.8 * np.random.rand(), ticker, fontsize=8)
+                except:
+                    continue
+
+            filepath = os.path.join(tmpdir, f"frame_{i:03}.png")
+            plt.savefig(filepath, bbox_inches="tight")
+            filenames.append(filepath)
+            plt.close()
+
+        gif_path = os.path.join(tmpdir, "bubbles.gif")
+        with imageio.get_writer(gif_path, mode='I', duration=0.4) as writer:
+            for filename in filenames:
+                image = imageio.imread(filename)
+                writer.append_data(image)
+
+        st.image(gif_path, caption="Market Cap Bubble Animation", use_column_width=True)
+        with open(gif_path, "rb") as f:
+            st.download_button("Download GIF", f, "market_cap_bubbles.gif", "image/gif")