import sqlite3 import pandas as pd def execute(query, database_path='dataset/database.sqlite'): connection = sqlite3.connect(database_path) result = connection.execute(query).fetchall() column_names = [description[0] for description in connection.execute(query).description] df = pd.DataFrame(result, columns=column_names) connection.close() return df def get_table_names(database_path='dataset/database.sqlite'): connection = sqlite3.connect(database_path) query = "SELECT name FROM sqlite_master WHERE type='table';" result = connection.execute(query).fetchall() table_names = [row[0] for row in result] connection.close() return table_names # Get and print all table names in the database tables = get_table_names() print("Tables in the database:", tables) from pandasql import sqldf # Create helper function for easier query execution execute_df = lambda q: sqldf(q, globals())import pandas as pd import sqlite3 con = sqlite3.connect('/Users/mac/Desktop/Python/Baye_stat/productiondisruption/PCI_meat.sqlite') df = pd.read_sql(<your query here>, con)