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import requests
import pandas as pd
def fetch_crypto_data(symbol):
"""Fetch crypto market data from Binance."""
url = f"https://api.binance.com/api/v3/klines"
params = {"symbol": symbol, "interval": "1h", "limit": 100}
response = requests.get(url, params=params)
if response.status_code == 200:
data = response.json()
df = pd.DataFrame(data, columns=["timestamp", "open", "high", "low", "close", "volume"])
df["close"] = df["close"].astype(float)
return df.dropna()
else:
raise Exception("Error fetching crypto data.")
def fetch_stock_data(symbol):
"""Fetch stock market data from Alpha Vantage."""
url = f"https://www.alphavantage.co/query"
params = {"function": "TIME_SERIES_INTRADAY", "symbol": symbol, "interval": "60min",
"apikey": ALPHA_VANTAGE_API_KEY}
response = requests.get(url, params=params)
if response.status_code == 200:
data = response.json()["Time Series (60min)"]
df = pd.DataFrame(data).T.astype(float).reset_index()
df.columns = ["timestamp", "open", "high", "low", "close", "volume"]
return df.dropna()
else:
raise Exception("Error fetching stock data.")
def fetch_sentiment_data(keyword):
"""Analyze sentiment from social media."""
tweets = [
f"{keyword} is going to moon!",
f"I hate {keyword}, it's trash!",
f"{keyword} is amazing!"
]
sentiments = [TextBlob(tweet).sentiment.polarity for tweet in tweets]
return sum(sentiments) / len(sentiments)
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