Retail: Data Preparation and Basic Statistical Analysis
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Learn how to download, prepare, and analyze retail data using statistical methods. Discover techniques for visualizing datasets and transforming big data for convenient reporting. Enhance your machine learning skills with this comprehensive lab.
At a Glance
This lab is dedicated to downloading, preparing and making basic statistical analysis of Retail based on Global Food Prices data from the World Food Programme covering foods such as maize, rice, beans, fish, and sugar for 76 countries and some 1,500 markets.
This lab will teach learners to download preparation and statistical analysis including visualization of a DataSet.
The basic difficulty of statistical analysis of real data is that it is prepared or presented in a form that is not convenient for machine learning methods. Very often real data consists of mixed information in different scales. This data must be found and rescaled or recalculated. This lab shows methods of automatic preparation of real data for such cases. There is also the ability to competently manipulate and transform big data in order to obtain a convenient statistical report both in tabular form and in the form of graphs. This will also be addressed here.
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