<jupyter_start><jupyter_text>Python and SQL Alchemy MySQL Sakila Database - Querying For Answers ---<jupyter_code># Import Dependencies:
import os
import csv
import json
import numpy as np
import pandas as pd
from datetime import datetime
import simplejson
import sys
import string
from sqlalchemy import create_engine
#rds_connection_string = "<inser user name>:<insert password>@127.0.0.1/customer_db"
rds_connection_string = "root:###@127.0.0.1/sakila"
engine = create_engine(f'mysql://{rds_connection_string}')
# CHECK FOR TABLES in Sakila Database
engine.table_names()
# Querying for all First and Last Name of Actors
pd.read_sql_query(
    'SELECT first_name, last_name FROM actor ORDER BY 2, 1;'
                , con=engine).head()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.09102730819245773, 'fraction_numerical': 0.018205461638491547, 'mean_word_length': 5.363636363636363, 'pattern_counts': {'":': 0, '<': 7, '<?xml version=': 0, '>': 7, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 2, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '17298', 'license': 'MIT', 'n_tokens_mistral': 260, 'n_tokens_neox': 245, 'n_words': 77, 'path': '.ipynb_checkpoints/mysql_sql_alchemy_project-checkpoint.ipynb', 'repo_name': 'jhustles/mysql_sql_alchemy_sakila_db', 'size': '769'}