read_sql() to crate DataFrame from SQLite database table in google Colab platform

read_sql(): Data from SQLite database table to Pandas DataFrame #B06

Inside Colab platform (left side ) use the session drive and upload the sample student excel file.
Colab file upload during Runtime

Create the DataFrame using read_excel() and the student Excel file.

import pandas as pd
df=pd.read_excel('student.xlsx',index_col='id') # DataFrame created using student file

read_excel() to create DataFrame from Excel at Colab

Create the SQlite database and store the same in session drive.
Check the table list from SQLite database

from sqlalchemy import create_engine,text
from sqlalchemy.exc import SQLAlchemyError
path="sqlite:///my_data.db" # create a SQLite database in google colab session storage
my_conn = create_engine(path)
my_conn=my_conn.connect() # connection is established 
try:    
    result = my_conn.execute(text("select name from sqlite_master where type = 'table'"))
    for row in result:
      print(row) # Display all tables in SQLite database 
except SQLAlchemyError as e:
        error = str(e.__dict__['orig'])
        print(error)

Creating SQlite database in Colab Platform

Transfer the DataFrame data to SQLite Database student table by using to_sql().

df.to_sql(con=my_conn,name='student',if_exists='replace') # create student table in sqlite database

Check the list of tables available inside the SQLite database.

try:    
    result = my_conn.execute(text("SELECT name FROM sqlite_master WHERE  type = 'table'"))
    for row in result:
      print(row) # List all tables in our SQLite database 
except SQLAlchemyError as e:
        error = str(e.__dict__['orig'])
        print(error)

('student',)

From student table, display records.

result = my_conn.execute(text("SELECT *  FROM student"))
for row in result:
  print(row) # display row from student table.

read_sql()

Once our SQLite database is available with the student table ( 35 records ) , we can create our DataFrame using different queries and options.

Here we are using all the records of student table and using id column as index.

df=pd.read_sql('SELECT * FROM student',my_conn,index_col='id')
print(df) # all rows of data

We can add conditions to our query and include only class = 'Five' while creating the DataFrame

df=pd.read_sql('SELECT * FROM student WHERE class="Five"',my_conn,index_col='id')
print(df) # All rows of class = 'Five'

Same code using Query part as string.

q="SELECT * FROM student WHERE class='Five'"
df=pd.read_sql(q,my_conn,index_col='id')
print(df)

params

We can pass parameters to the query string separately ( not as a part of the SQL ) by using params option. This is required when inputs are taken from unsecured sources and to prevent injection attack.

Here we have declared a place holder inside the query and passing single parameter ( class=Five ) as dictionary.

q="SELECT * FROM student WHERE class=:my_class"
df=pd.read_sql(q,my_conn,index_col='id',params={'my_class':'Five'})

We can pass multiple parameters as input to our query. Here we are creating the DataFrame by restricting the rows to Class =Five and mark is equal to or more than 80.

q="SELECT * FROM student WHERE class=:my_class AND mark >=:my_mark"
my_dict={'my_class':'Five','my_mark':80}
df=pd.read_sql(q,my_conn,index_col='id',params=my_dict)
print(df)

Questions

How do you use the read_sql() function in Pandas to read data from a SQL database?
What are the required parameters for the read_sql() function?
How can you specify a database connection string when using read_sql()?
Can you pass a custom SQL query to the read_sql() function? If so, how?
What is the role of the con parameter in the read_sql() function?
How does read_sql() handle SQL queries that return multiple result sets?
How can you limit the number of rows fetched from a database using read_sql()?
Can you provide an example of using read_sql() with a PostgreSQL database?
What is the default behavior of read_sql() when encountering NULL values in the database?
How does read_sql() handle large datasets and memory usage?

Data input and output from Pandas DataFrame Download sample Excel or CSV file or create DataFrame
Pandas DataFrame read_sql (MySQL) read_sql_table insert data

Pandas DataFrame Python & MySQL Python- Tutorials

Subhendu Mohapatra

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SQLite table to DataFrame at Colab platform using read_sql()

read_sql()

params

Questions

Subhendu Mohapatra