dataRSM

A collection of scanner data on the sale of rice, sugar and milk products in one of Polish supermarkets in the period from December 2023 to January 2025

datasets

Preparing a scanner data set for price dynamics calculations (data selecting, data classification, data matching, data filtering). Computing bilateral and multilateral indexes. For details on these methods see: Diewert and Fox (2020)
<doi:10.1080/07350015.2020.1816176>, Białek (2019) <doi:10.2478/jos-2019-0014> or Białek (2020) <doi:10.2478/jos-2020-0037>.

Jacek Bia<c5><82>ek

PriceIndices

Calculating Bilateral and Multilateral Price Indexes

dataRSM function

A data frame with 9 columns and 8090 rows. The used variables are as follows:
<code>time</code> - Dates of transactions (Year-Month-Day)
<code>prices</code> - Prices of sold products [PLN]
<code>quantities</code> - Quantities of sold products [items]
<code>retID</code> - Unique codes identifying outlets/retailer sale points (data set contains 4 different retIDs)
<code>description</code> - Descriptions (labels) of sold products (data set contains 152 different descriptions)
<code>retailer_code</code> - Retailer codes for product definition (134 retailer codes)
<code>EAN_code</code> - EAN codes (bar codes) for product definition (138 EAN codes)
<code>category</code> - Product categories at the 6-digit COICOP level (4 categories)
<code>subcategory</code> - Product subcategories from 7-digit COICOP level (11 subcategories)

dataRSM: A real data set on sold rice, sugar and milk products

Description

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