Gold Ambassador and Microsoft Reactor TelAviv talk on Data Analysis to Student Ambassadors

Real-world data is messy. You will likely need to combine several data sources to get the data you want or sometimes have to deal with incomplete data. In this session, we will tackle how to handle missing or duplicate data, joining and merging different datasets and visual and statistical exploratory of your data.

This is a beginner session where we take you through exploring your data and how to prepare it ready for analysis and modelling.

Data Scientists spend 80 per cent of any project is to prepare the data into a form ready for analysis. You should attend this session to understand the basics of data cleaning to prepare your data set for modelling.

• Notebook Link:- http://bit.ly/clean-data-notebook
• Reference Notebook:- http://bit.ly/clean-data-ref
• Pandas documentation:-  http://bit.ly/clean-data-doc
• Installing libraries:- https://pypi.org/
• Live video link:- https://aka.ms/Cleaning_Data