How to Export Python data frame to SQL file [Update 2025]

In this blog post, we will explore how to export Python data frame to SQL file, which is a commonly used format for storing structured data, so let’s dive in without further delay.

How to export Python Dataframe to SQL file

Exporting a Pandas DataFrame Exporting to an SQL file is a common task in data science and development, allowing you to efficiently store and retrieve data from databases such as SQLite, MySQL, or PostgreSQL using Python.

To export a Pandas DataFrame to an SQL file using Python, you’ll need to follow these steps:

Steps to Export DataFrame to SQL:

1. Install Required Libraries: You need to have the pandas and SQLAlchemy libraries installed. You can install them using:

pip install sqlalchemy

2. Create a Connection to the SQL Database: Use SQLAlchemy to create a connection to your SQL database. You can connect to various databases like SQLite, MySQL, or PostgreSQL. For example, to connect to an SQLite database:

from sqlalchemy import create_engine

# Create an SQLite database (or connect to an existing one)
engine = create_engine('sqlite:///my_database.db')

3. Export DataFrame to SQL: Now, you can use the to_sql() method to export the DataFrame to your SQL database.

import pandas as pd

# Sample DataFrame
data = {'name': ['John', 'Jane', 'Tom'],
        'age': [28, 34, 29]}

df = pd.DataFrame(data)

# Export DataFrame to SQL table
df.to_sql('my_table', con=engine, if_exists='replace', index=False)

• my_table: This is the name of the table where the DataFrame will be stored.
• if_exists='replace': This will replace the table if it already exists. You can also use append to add data to an existing table.
• index=False: This prevents Pandas from writing the DataFrame index as a column in the SQL table.

4. Saving to a SQL file: If you are using SQLite, the SQL commands are stored in a .db file. If you need to extract the SQL queries, you can export the schema or data using the SQL commands within SQLite. However, there is no direct way to export a DataFrame to a raw .sql file with SQL commands.

To create a raw .sql file manually with data and schema, you can:

• Export your database schema and data with sqlite3 command-line tools or
• Write your custom SQL commands using Python and open() to save them as .sql.

Pandas Dataframe to SQL example

These are examples of pandas data frame to SQL database.

Getting the name column from SQL employee data

# acccesing only a particular 
# column from the database
df3 = pd.read_sql('Employee_Data',
				con = engine,
				columns = ["Names"])
# show the data
print(df3)

OUTPUT

Names
0  Sama
1  Alishba

Retrieving name column as a list from SQL employee data

# get a particular column
# from a database in the
# form of list
df4 = pd.read_sql('Employee_Data',
				con=engine,
				index_col='Names',
				columns=["Names"])
# show the data
print(df4)

OUTPUT

Empty DataFrame
Columns: []
Index: [Sama, Alishba]

FAQ:- Export DataFrame to SQL