ETL Using Python, Pandas, and Jupyter Notebook

ETL of large amount of data is always a daily task for data analysts and data scientists. While Excel and Text editors can handle a lot of the initial work, they have limitations. Python, in particular, Pandas library and Jupyter Notebook have becoming the primary choice of data analytics and data wrangling tools for data analysts world wide. In this 60 minute session, I will show you how to set up and get it running on your laptop for a jupyter notebook environment and start improve your ETL workflow.

• Wenbin Zhao

  1 Recording

  Wenbin Zhao is a Sr. Data Analyst and Tableau developer. He graduated from Brigham Young University and worked in the finance and data analytics field for the last 14 years. He loves everything data and business analytics, project management, and teamwork. He has been a Tableau user since 2013 and also participated in Tableau Hackathon in Austin. His team built a prototype embedded Tableau dashboard to track eye-movements by utilizing Tableau API and Python libraries to help ALS patients. His current focus at YETI is to help building consumer insights and predictive capabilities through visualization and data science. He’s also a teaching assistant of Data Analytics and Visualization program at University of Texas at Austin’s McCombs School

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