Python And Mssql: Filtering Techniques While Retrieving Data From Sql

I have a MS SQL Table as follows Device ID Timestamp Avg_PF THDV_Sum 863071010842661 2014-01-01 22:05:57 4.0 7.0 865733020495321 2016-08-19 17:20:

Solution 1:

I would go about it like this:

from sqlalchemy import create_engine
%%time -- just to measure

# Parameters
ServerName = "SQLSRV01" -- your input
Database = "Database"
Driver = "driver=SQL Server Native Client 11.0"# Create the connection
engine = create_engine('mssql+pyodbc://' + ServerName + '/' + Database + "?" + Driver)

df = pd.read_sql_query ("SELECT Device ID, Timestamp, Avg_PF, THDV_Sum 
                         FROM mytable
                         WHERE Timestamp >= '2018-10-01'"
                       , engine)

Solution 2:

Use the parse_dates argument of the read_sql_query function like so:

df_select = pd.read_sql_query(sql, conn, parse_dates=['Timestamp'])