CODEWITHSUNDEEP
sql-serverpandaspyodbc
akerr
akerr

Reputation: 11

How to Save a Data Frame as a table in SQL

I have a SQL Server on which I have databases that I want to use pandas to alter that data. I know how to get the data using pyodbc into a DataFrame, but then I have no clue how to get that DataFrame back into my SQL Server.

I have tried to create an engine with sqlalchemy and use the to_sql command, but I can not get that to work because my engine is never able to connect correctly to my database.

import pyodbc
import pandas
server = "server"
db = "db"
conn = pyodbc.connect('DRIVER={SQL Server};SERVER='+server+';DATABASE='+db+';Trusted_Connection=yes')
cursor = conn.cursor()
df = cursor.fetchall()
data = pandas.DataFrame(df)
conn.commit()

Upvotes: 1

Views: 8328

Answers (1)

rzskhr
rzskhr

Reputation: 991

You can use pandas.DataFrame.to_sql to insert your dataframe into SQL server. Databases supported by SQLAlchemy are supported by this method.

Here is a example how you can achieve this:

from sqlalchemy import create_engine, event
from urllib.parse import quote_plus
import logging
import sys
import numpy as np
from datetime import datetime, timedelta

# setup logging
logging.basicConfig(stream=sys.stdout, 
                filemode='a', 
                format='%(asctime)s.%(msecs)3d %(levelname)s:%(name)s: %(message)s', 
                datefmt='%m-%d-%Y %H:%M:%S', 
                level=logging.DEBUG)
logger = logging.getLogger(__name__)    # get the name of the module

def write_to_db(df, database_name, table_name):
    """
    Creates a sqlalchemy engine and write the dataframe to database
    """
    # replacing infinity by nan
    df = df.replace([np.inf, -np.inf], np.nan)

    user_name = 'USERNAME'
    pwd = 'PASSWORD' 
    db_addr = '10.00.000.10'
    chunk_size = 40 

    conn =  "DRIVER={SQL     Server};SERVER="+db_addr+";DATABASE="+database_name+";UID="+user_name+";PWD="+pwd+""
    quoted = quote_plus(conn)
    new_con = 'mssql+pyodbc:///?odbc_connect={}'.format(quoted)

    # create sqlalchemy engine
    engine = create_engine(new_con)

    # Write to DB
    logger.info("Writing to database ...")
    st = datetime.now() # start time
    # WARNING!! -- overwrites the table using if_exists='replace'
    df.to_sql(table_name, engine, if_exists='replace', index=False, chunksize=chunk_size)
    logger.info("Database updated...")
    logger.info("Data written to '{}' databsae into '{}' table ...".format(database_name, table_name))
    logger.info("Time taken to write to DB: {}".format((datetime.now()-st).total_seconds()))

Calling this method should write your dataframe to the database, note that it will replace the table if there is already a table in the database with the same name.

Upvotes: 2

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