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Retail: Data Preparation and Basic Statistical Analysis

BeginnerGuided Project

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.

4.9 (16 Reviews)

Language

  • English

Topic

  • Data Analysis

Industries

  • Retail

Enrollment Count

  • 162

Skills You Will Learn

  • Machine Learning, Artificial Intelligence, Data Science

Offered By

  • IBM

Estimated Effort

  • 1 hour

Platform

  • SkillsNetwork

Last Update

  • April 30, 2024
About This Guided Project

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.


What you will learn

After completing this lab, you will be able to:
  • Download a DataSet from *.csv files
  • Analysis of Data
  • Create new columns and recalculate values of existing ones
  • Transform the table
  • Visualize data with pandas and matplotlib
  • Expect
    • Minimum and maximum value
    • Average
    • Quarters
    • Pivot tables



Instructors

Rav Ahuja

Global Program Director, IBM Skills Network

Rav Ahuja is a Global Program Director at IBM. He leads growth strategy, curriculum creation, and partner programs for the IBM Skills Network. Rav co-founded Cognitive Class, an IBM led initiative to democratize skills for in demand technologies. He is based out of the IBM Canada Lab in Toronto and specializes in instructional solutions for AI, Data, Software Engineering and Cloud. Rav presents at events worldwide and has authored numerous papers, articles, books and courses on subjects in managing and analyzing data. Rav holds B. Eng. from McGill University and MBA from University of Western Ontario.

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Olha Vdovichena

Content Creator

Olha Vdovichena – associate professor Department of Management, Marketing and International logistics Chernivtsi Institute of Trade and Economic of State University of Trade and Economic. She is an author of over 93 scientific works, 17 monographs (sections of the monographs), and books, a member of the Editorial Board of scientific journal "Journal Chernivtsi Institute of Trade and Economic of State University of Trade and Economic. Economic sciences". She defended her doctoral dissertation on the topic "Exhibition and trade fair activity as a factor of socio-economic development of the region" and became an Associate Professor of the Department of Commodity Science and Marketing. Olha’s scientific interests focus on research of development of an exhibition activity as a factor of socio-economic growth of the region; retail, marketing, logistics; improving management processes of international investments, regional economy and tourism sphere; formation of mechanisms regulating macroeconomic imbalances in both national and global economies under the conditions of inclusive development and bio-economic orientation.

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Andrei Moskalev

CEO

Integrated Tech Lab ceo

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Yaroslav Vyklyuk

Full Professor, Doctor of Computer Science, PhD

Dr. Yaroslav Vyklyuk is a full professor at the Lviv Polytechnic National University, Department of Artificial Intelligence Systems. He is an author of over 210 scientific works, 10 monographs, and books, a member of the Editorial Board of 6 international scientific journals, member of the Academic Councils on protection Ph.D. and DrSc thesis in "Mathematical modeling and computational methods". Research Interests: Data Science, Applied System Analysis, Mathematical Modeling, and Decision Making of Complex Dynamic Systems (socio-economic, geographical, tourist, and crisis systems) using Artificial Intelligence Technology, DataMining, Big Data, Parallel Calculations, Statistics, Econometrics, Econophysics and other Advanced Mathematical Methods with implementation into information, WEB, and geographic information systems.

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Kateryna Hazdiuk

PhD of Software Engineering

I am an assistant professor at the Yuriy Fedcovych Chernivtsi National University, Software of Computer Systems Department; an author of over 40 scientific works and 10 training manuals. Research Interests: Mathematical Modeling of Complex Dynamic Systems (bio-like systems, socio-economic, geographical systems), Data Science, Decision Making using Artificial Intelligence Technology, DataMining, Big Data, Parallel Calculations, Statistics, and other methods.

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