Example code for Predictive modeling 

Here's an example code that retrieves real-time Bitcoin prices for the BTC/USD trading pair for the past 24 hours and performs a simple linear regression model to predict the future price:

```python

import requests

import pandas as pd

import numpy as np

from sklearn.linear_model import LinearRegression from datetime import datetime, timedelta

# Function to convert timestamp to datetime def timestamp_to_datetime(timestamp):

    return datetime.utcfromtimestamp(timestamp).strftime('%Y-%m-%d %H:%M:%S')

# Retrieve Bitcoin prices for the past 24 hours url = "https://www.binance.com/en/terms."

params = {

    "symbol": "BTCUSDT",

    "interval": "1m",

    "limit": 1440,

    "endTime": int(datetime.now().timestamp() * 1000),  # Current timestamp

    "startTime": int((datetime.now() - timedelta(days=1)).timestamp() * 1000)  # 24 hours ago } response = requests.get(url, params=params) data = response.json()

# Extract relevant data

df = pd.DataFrame(data, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume', 'close_time', 'quote_asset_volume', 'trades', 'taker_buy_base', 'taker_buy_quote', 'ignore']) df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms') df['close'] = df['close'].astype(float)

# Calculate features and target variable df['time_index'] = (df['timestamp'] - df['timestamp'].min()).dt.total_seconds() / 60  # Convert timestamp to minutes df['target'] = df['close'].shift(-1)  # Shift the closing price upward by 1 row

# Drop NaN rows

df.dropna(inplace=True)

# Train a linear regression model

X = df[['time_index']]

y = df['target']

model = LinearRegression()

model.fit(X, y)

# Predict tomorrow's closing price

next_time_index = df['time_index'].max() + 1 predicted_price = model.predict([[next_time_index]])

# Print the predicted price

print("Predicted BTC/USD price in 24 hours:", predicted_price[0]) ```

Please note that this code uses the Binance API to fetch the data. Make sure you have the necessary libraries installed (`requests`, `pandas`, `numpy`, and `scikit-learn`) before running the code. You may also need to sign up for a Binance account and replace the `symbol` parameter with the correct trading pair if you want to use a different exchange.

Sent from my iPhone