Скачать с ютуб 7. Efficiently Uploading Large Datasets (20x Faster) to MySQL Using Python в хорошем качестве

7. Efficiently Uploading Large Datasets (20x Faster) to MySQL Using Python

GitHub Link: https://github.com/DataThinkers Code : import warnings warnings.filterwarnings('ignore') from sqlalchemy import create_engine import pandas as pd engine = create_engine("mysql+mysqldb://root:[email protected]:3306/data_mysql") # {root}:{password}@host:port/{database name} Establish a connection conn = engine.connect() Read data from CSV into a Pandas DataFrame data = pd.read_csv("Salaries.csv") Write DataFrame to a SQL table data.to_sql('test1', engine, index=False, if_exists='replace') Close Connection conn.close() If you enjoy these tutorials, like the video, give it a thumbs-up, and share these videos with your friends and families if you think they would help him. Please consider clicking the SUBSCRIBE button to be notified of future videos. Disclaimer --- Video is for educational purposes only. Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for "fair use" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is permitted by copyright statute that might otherwise be infringing. Non-profit, educational, or personal use tips the balance in favor of fair use. - Thanks for watching -