The Pandas read_sql function allows you to execute SQL queries and retrieve data from a database. One of its features is the ability to pass parameters to the query.
Params can be passed as a list, tuple, or dict. The exact syntax depends on the database driver being used. Here are some common examples:
One option for passing parameters is to use a dictionary. This is supported by most drivers, including PostgreSQL with the psycopg2 driver. The key-value pairs in the dictionary correspond to the named placeholders in the query.
To demonstrate the named argument approach, let's consider the following SQL query:
<code class="sql">select "Timestamp", "Value" from "MyTable" where "Timestamp" BETWEEN :dstart AND :dfinish</code>
Here's how you would pass parameters to this query using a dictionary:
<code class="python">params = {"dstart": datetime(2014, 6, 24, 16, 0), "dfinish": datetime(2014, 6, 24, 17, 0)} df = psql.read_sql( "select \"Timestamp\",\"Value\" from \"MyTable\" where \"Timestamp\" BETWEEN %(dstart)s AND %(dfinish)s", db, params=params, index_col=["Timestamp"], )</code>
In this example, the params dictionary provides values for the named placeholders :dstart and :dfinish. The %(name)s syntax ensures that the values are inserted correctly into the query.
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