|
|
import streamlit as st |
|
|
import yfinance as yf |
|
|
import pandas as pd |
|
|
import matplotlib.pyplot as plt |
|
|
import imageio |
|
|
from io import BytesIO |
|
|
import tempfile |
|
|
import math |
|
|
|
|
|
st.set_page_config(layout="wide") |
|
|
st.title("Market Cap Animation") |
|
|
|
|
|
tickers_input = st.text_input("Tickers", "AAPL,MSFT,NVDA,GOOG,AMZN,META") |
|
|
start_date_str = st.text_input("Start Date", "2021-01-01") |
|
|
end_date_str = st.text_input("End Date", "2025-04-01") |
|
|
|
|
|
def fetch_market_caps(tickers, start, end): |
|
|
data = yf.download(tickers, start=start, end=end)["Close"] |
|
|
if isinstance(data, pd.Series): |
|
|
data = data.to_frame() |
|
|
mcap = pd.DataFrame(index=data.index) |
|
|
failed = [] |
|
|
for t in tickers: |
|
|
try: |
|
|
shares = yf.Ticker(t).info.get("sharesOutstanding", None) |
|
|
if not shares or shares <= 0: |
|
|
failed.append(t) |
|
|
continue |
|
|
mcap[t] = data[t] * shares / 1e6 |
|
|
except: |
|
|
failed.append(t) |
|
|
mcap.dropna(how="any", inplace=True) |
|
|
return mcap.iloc[::5], failed |
|
|
|
|
|
if st.button("Generate"): |
|
|
tickers = [t.strip().upper() for t in tickers_input.split(",")] |
|
|
start = pd.to_datetime(start_date_str) |
|
|
end = pd.to_datetime(end_date_str) |
|
|
mcap, failed = fetch_market_caps(tickers, start, end) |
|
|
|
|
|
if mcap.empty: |
|
|
st.error("No data.") |
|
|
else: |
|
|
frames = [] |
|
|
fig, ax = plt.subplots(figsize=(12, 6)) |
|
|
|
|
|
ordered = list(mcap.columns) |
|
|
colors = {t: plt.cm.tab10(i % 10) for i, t in enumerate(ordered)} |
|
|
|
|
|
|
|
|
n = len(ordered) |
|
|
cols = math.ceil(math.sqrt(n)) |
|
|
rows = math.ceil(n / cols) |
|
|
|
|
|
|
|
|
grid_positions = {} |
|
|
for i, t in enumerate(ordered): |
|
|
row = i // cols |
|
|
col = i % cols |
|
|
x = col + 1 |
|
|
y = rows - row |
|
|
grid_positions[t] = (x, y) |
|
|
|
|
|
for date, row in mcap.iterrows(): |
|
|
ax.clear() |
|
|
ax.axis("off") |
|
|
ax.set_xlim(0, cols + 2) |
|
|
ax.set_ylim(0, rows + 2) |
|
|
ax.set_title(str(date.date()), fontsize=14) |
|
|
|
|
|
for t in ordered: |
|
|
val = row[t] |
|
|
x, y = grid_positions[t] |
|
|
ax.text(x, y, f"{t}\n{val:,.0f}M", fontsize=10, |
|
|
ha='center', va='center', |
|
|
bbox=dict(boxstyle="circle,pad=0.6", fc=colors[t], ec="black")) |
|
|
|
|
|
buf = BytesIO() |
|
|
plt.savefig(buf, format="png", bbox_inches="tight") |
|
|
buf.seek(0) |
|
|
frames.append(imageio.v2.imread(buf)) |
|
|
buf.close() |
|
|
|
|
|
with tempfile.NamedTemporaryFile(delete=False, suffix=".gif") as tmp: |
|
|
imageio.mimsave(tmp.name, frames, duration=2.5) |
|
|
st.image(frames[-1]) |
|
|
st.download_button("Download GIF", open(tmp.name, "rb").read(), |
|
|
file_name="market_cap.gif", mime="image/gif") |
