Project is to answer three questions:
Q1) Which month is best for selling products? Q2) What time of the day do people order the most goods online? Q3) Which product has the highest demand and why?
Project takes in xlsx file and converts to csv. NaN/Nulls removed from csv. Columns added to answer project questions. Plots created to view answers to questions.
To use: Import xlsx or csv as df. Determine if other changes needed. Run cells to create plots to answer questions.
Credits: Data from UCI Machine Learning Repository https://archive.ics.uci.edu/ml/datasets/online+retail#
Abstract: This is a transnational data set which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail.
Source: Dr Daqing Chen, Director: Public Analytics group. chend '@' lsbu.ac.uk, School of Engineering, London South Bank University, London SE1 0AA, UK.
Citation Request: Daqing Chen, Sai Liang Sain, and Kun Guo, Data mining for the online retail industry: A case study of RFM model-based customer segmentation using data mining, Journal of Database Marketing and Customer Strategy Management, Vol. 19, No. 3, pp. 197–208, 2012 (Published online before print: 27 August 2012. doi: 10.1057/dbm.2012.17).
Thank you!