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

00:00 Introduction
01:14 Colab platform to upload sample Excel file and create DataFrame using read_excel().
02:54 Crate SQLite database with sample student table by using to_sql()
05:30 Create DataFrame by using SQLite database student table data by using read_sql()
08:19 params options to pass parameters to the query while using read_sql()
10:28 Multiple parameters to pass to Query using params option

#read_sql() #DataFrameFunctions #SQLiteToDataFrame #IMportData #SQLite #plus2net #Tutorial

Download all Jupiter file ( .ipynb ) with source code

Copy or download Excel file or sample DataFrame of student table

Copy or read all source codes and answer sample questions from here

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Upload Excel or CSV file to Colab platform ( mount drive ) and use with Pandas

Course Details

[usipgwo]

Thanks, very good course, i have 3 python files with database and i couldn't make them work together, than make the exe file for the program, i tried auto-py-to-exe but not work i saw many videos but still not clear i hope when you'll have time to make us an example Thank you in advance i hope U accept....

[philmillington]

can you convert this statement so instead of an 'SQLite' database I want a access database 'my_data.accdb'
my_data.accdb

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)