Recognizing Patterns

import numpy as np 
import pandas as pd from sklearn.cluster 
import KMeans

def detect_bot_patterns(orders): """Detects repeating patterns in orders, characteristic for bots.

  Args: orders: Order data in the form of DataFrame.

  Returns: Dictionary with clusters of bot patterns. """" # Convert the DataFrame to a NumPy array X = orders.drop(["timestamp"], axis=1).values

  # Perform KMeans clustering to identify patterns kmeans = KMeans(n_clusters=3) kmeans.fit(X)

  # Get cluster labels labels = kmeans.labels_

  # Analyze the cluster labels and identify potential bot patterns patterns = {} for i in range(kmeans.n_clusters): cluster_orders = orders[labels == i] patterns[f "Cluster {i+1}"] = cluster_orders.describe()

  return patterns

# Example usage: orders = pd.read_csv("orders.csv") patterns = detect_bot_patterns(orders)

# Print the detected patterns for pattern_name, pattern_info in patterns.items(): print(f"{pattern_name}:\n{pattern_info}")