Using Pandas with the Python PYODBC Package

Pandas is a popular library for transforming and calculating large amounts of data, additionally, it is used heavily as a place to dump data from different data sources. Because of its popularity, many individuals want the flexibility of loading data from a DataFrame to a Database like SQL Server. In this video, we will explore how to use the PYODBC library to bulk insert multiple rows of data from a Pandas DataFrame. Additionally, we will also explore how to take data from A PYODBC cursor object and load it into a Pandas' DataFrame.
Video Resources:
--------------------------------------------------
github.com/are...
Resources:
--------------------------------------------------
Facebook Page: / codingsigma
Facebook Group: / sigmacoding
GitHub Sigma Coding: github.com/are...
Support Sigma Coding:
--------------------------------------------------
Patreon: / sigmacoding
Amazon Associates: amzn.to/3bsTI5P **
Related Topics:
--------------------------------------------------
Title: How to Use PYODBC With Access Databases in Python
Link: • How to Use PYODBC With...
Title: How to Use PYODBC With SQL Servers in Python
Link: • How to Use PYODBC With...
Title: How to Use PYODBC With Excel Workbooks in Python
Link: • How to Use PYODBC With...
**Amazon Associates Disclosure:
--------------------------------------------------
I am a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to Amazon.com. One of the ways I support the channel is by using Amazon Associates to earn fees on purchases you make. That means when you use the link above, it will track any purchases made from that link and give a small portion of it to the Sigma Coding. I love this approach because it allows you to do what you're already doing (shopping) but also helps support the channels you care about. Also, it makes it where I can invest that revenue to help improve and grow the channel.
Tags:
--------------------------------------------------
#PYODBC #Python #Pandas

[@immanuelsuleiman7550]

Very nice I use pyOdbc daily in my job I actually learned how to use it from one of your earlier videos As always I truly appreciate your efforts Ps. Thank god for the pandas library I would be way less functionary in my daily duftites if pandas did not exist

[@SigmaCoding]

Great to hear, and same here Pandas has been a life saver so many times :)

[@theguildedcage]

I find it interesting that your specify variables with their datatypes in Python. Some of the syntax you use in defining variables is unlike the way I learned. It makes me think you are a classically trained developer. I learned everything I know from udemy and youtube. lol. Thanks for sharing.

[@immanuelsuleiman7550]

his way: youtube_df: pd.DataFrame=pd.read_csv(data_file) my way: youtube_df=pd.read_csv(data_file) But his way does not throw an error, so it must work

[@awadelrahman]

Great illustration! Watch at 2X speed!

[@JimnyGirl]

from_records is required otherwise every tuple will be considered as one column and wont be able to convert into dataframe for every element in tuple, nice that you have mentioned about from records, safe while reading from sql/snowflake

[@mariakovalevsky1211]

Hi, thanks for the great video. I have a question- if I have a very large number of columns (say 100+), seemt to me that adding 100 times ? to the sql string is a very innaficient way. Is there another (more elegant) way in adding a larget number of variables? Thanks!

[@minhtrung2179]

Thank you for the new tutorial. Just one little suggestion. Can you increase the video's quality? I really appreciate it.

[@SigmaCoding]

It's still processing at the moment, so if you give it like another 30 minutes you should be able to change it to High Definition.

[@sazan108]

Hi , liked your traditional way of inserting,have you ever tried pushing dataframe into hive table using to_sql, please let me know if you ever tried working on excluded dialect(sql alchemy)?

[@zberteoc]

Why all those NVARCHAR(MAX) for the ID and title columns?

[@mazkaibil9108]

great video! Thank you

[@SigmaCoding]

Glad you liked it!

[@celestialadministration]

Mad cool

[@immanuelsuleiman7550]

As another person stated below, they way you set your df variable is very different from what I have seen. And I have probably seen very pandas tutorial there is. your way: youtube_df: pd.DataFrame=pd.read_csv(data_file) my way: youtube_df=pd.read_csv(data_file) Is there a reason for the difference? Is your way more efficient? I hope this does not come off as snarky. I am just always willing to learn something new. Thanks for the videos.

[@SigmaCoding]

No worries, that's a common question. In this video, I was using Type Hinting to help Intellisense (Autocomplete for VS Code) with the Pandas Module. Anytime, I name a variable and then follow it with a ":" and then the Object Type I'm using type hinting. *youtube_df: pd.DataFrame=pd.read_csv(data_file)* That is saying the "youtube_df" is of type "pandas.DataFrame". Hopefully, that answers your question.

[@immanuelsuleiman7550]

@@SigmaCoding so it's almost like strong typing for Python?

[@saema123]

Please make a video on how to make a trading bot with forex

[@JimnyGirl]

little slow but nice

[@phafid]

my ? as the placeholder didn't work. I am stuck