Pandas to_sql

Warning

If you are using M series SOC, please read following note

• Install pymssql in M Series macOS (Recommended)
• Install pyodbc in M Series macOS

Create Database Engine

Config database credentials in .env file

# .env
DB_DRIVER_NAME = "mssql+pymssql"
DB_HOST = "xx.xx.xx.xx"
DB_PORT = "1433"
DB_NAME = ""
DB_USERNAME = ""
DB_PASSWORD = ""
DB_DRIVER = "ODBC Driver 18 for SQL Server"

Load Environment Variables

There are two ways to load env

1. Jupyter Notebook

%load_ext dotenv
%dotenv

2. Python

from dotenv import load_dotenv
 
load_dotenv()

from sqlalchemy import URL, create_engine
 
db_url_object = URL.create(
    drivername=os.getenv("DB_DRIVER_NAME", "mssql+pymssql"),
    username=os.getenv("DB_USERNAME"),
    password=os.getenv("DB_PASSWORD"),
    host=os.getenv("DB_HOST"),
    port=int(os.getenv("DB_PORT", 1433)),
    database=os.getenv("DB_NAME"),
)
engine = create_engine(db_url_object)

Dataframe

CSV to Dataframe

data = pd.read_csv("C:\\Temp\\Sample.CSV", encoding="utf-8")
df = pd.DataFrame(data)

Dataframe to SQL

with engine.connect() as conn, conn.begin():
	df.to_sql("TableName", db, if_exists="replace", index=False)
data

From SQL to dataframe

with engine.connect() as conn, conn.begin():
    data = pd.read_sql_table("TableName", con=conn, schema="dbo")
data