retail-data

There are 75 repositories under retail-data topic.

  • FPGrowth-and-Apriori-algorithm-Association-Rule-Data-Mining

    Implementation of FPTree-Growth and Apriori-Algorithm for finding frequent patterns in Transactional Database.

    Language:Python31
  • rfm-analysis-python

    This repository contains RFM analysis applied to identify customer segments for global retail company and to understand how those groups differ from each other.

    Language:Jupyter Notebook28
  • northwind

    From RDBMS to Graph, using a classic dataset

    Language:Cypher21
  • retailhero-recommender-solution

    3rd place solution for RetailHero.ai/#2

    Language:Python16
  • awesome-retail-technology

    A curated list of awesome retail software, platforms, podcasts, and conferences.

  • MarketBasketAnalysis-Apriori-Algorithm

    A simple Market Basket Analysis that uses the apriori algorithm to find affinities between retail products

    Language:R6
  • Trade_area_analysis

    In the retail industry a trade area, also known as a catchment area, is the geographic area from where you draw your customers. Here I derive trade area from scratch

    Language:Python5
  • Customer-Segmentation

    R-Analysis: Identifying high value customers and low value of customers using RFM modelling

    Language:Jupyter Notebook4
  • CustomerSegmentationAndTargeting

    Customer Segmentation and Targeting for Retail Industry

  • Retail-Sector

    A sales forecasting problem in Retail Sector solved using time series analysis, machine learning and deep learning methodologies.

    Language:Jupyter Notebook3
  • Improving-Consumer-Retailer-Connectivity

    Data mining course project

    Language:Jupyter Notebook3
  • Retail-Analytics

    Walmart sales prediction with Linear Regression and Random Forests + Bayesian Structure Learning

    Language:Jupyter Notebook3
  • NRF_MerchandisingCalendar

    .Net Standard library for working with the National Retail Federation Merchandising Calendar.

    Language:C#3
  • Customer-Segmentation-Unsupervised-Learning

    In this project, I will be performing an unsupervised clustering of customer's records from a Retail Chain.

    Language:HTML2
  • Market-Basket-Analysis-Example

    Exploring Market Basket Analysis

    Language:Jupyter Notebook2
  • ML-Retail-Business

    The target in this case, is to create a model of machine learning to know the behaviour of users. What is required is an end-to-end model such as those seen in practice in the module. In this case, you have to apply three models and choose the best one, but the previous part is common to all three.

    Language:Jupyter Notebook2
  • ARC

    A vision-based Automatic Retail Checkout System

    Language:Python2
  • Retail-Sales-Data-EDA

    Using Pandas, scikit learn, Seaborne libraries for data cleaning and exploratory data analysis on retail data

    Language:Jupyter Notebook2
  • Retail

    A repo containing code for retail sales analyses

    Language:Jupyter Notebook2
  • EDA-on-Retail-Data

    This repository is implementation of Exploratory Data Analysis on Retail data.

    Language:Jupyter Notebook2
  • customer-segmentation-rfm

    This repo contains my customer segmentation project in Python.

    Language:Jupyter Notebook2
  • Data-Warehouse

    Data Warehousing project | Outsourced for Autumn Group | Retail Outlet DW | Melbourne based | Sep - Feb 2018

    Language:Batchfile2
  • DataSpark-Illuminating-Insights-for-Global-Electronics

    DataSpark is a retail analytics project for Global Electronics leveraging Python, SQL, and Power BI. It uncovers customer insights, sales trends, and store performance to optimize marketing, inventory, and operations. Features include clean datasets, SQL-driven analysis, and interactive dashboards, driving data-driven growth and decision-making.

    Language:Jupyter Notebook1
  • ML-Project-Amazon-Big-Mart-Sales-Prediction

    🛒 Big Mart store sales using a trained machine learning model. Web forms for user input and displays sales predictions based on historical data.

    Language:Jupyter Notebook1
  • CODEBASICS_CHALLENGE9

    This repository contains files for my Codebasics Challenge #9: Analyse Promotions and Provide Tangible Insights to Sales Director

  • Retail-Customer-Segmentation-Profile

    Customer Profile & Shopping Behavior Analysis is an R-based project analyzing customer data from retail stores, focusing on segmentation, seasonal trends, and market behaviors.

    Language:R1
  • Descriptive-Data-Mining

    Descriptive Data Mining for UK Retail Dataset

    Language:Python1
  • Powerbi-project

    This data visualization is done with powerbi and it explains the exploratory data analysis on dataset samplesuperstore

  • ds-datasets-sku110k

    Scripts for manipulating the annotation files of the SKU110K dataset

    Language:Jupyter Notebook1
  • DataAnalysis-for-ClothingStoreData

    SAS Data Analysis on Retail Clothing Data Set

    Language:SAS1
  • matthiassp.github.io

    Using Payment Transaction Data to monitor Turnover in Retail Trade and Services in Switzerland

  • GSPN

    Code release for Geometry Supervised Pose Network for Accurate Retail Shelf Pose Estimation (GSPN) (IEEE TII).

    Language:Python1
  • Machine-Learning-For-Retail

    Using the Apriori algorithm of the Arules package throughout this project to get insight into the top 10 and bottom 10 of the products sold, get a list of all product package combinations with strong correlations and get a list of all product package combinations with specific items.

    Language:R1
  • retailSpace

    Web platform where Retail Shop Owners can signup and manage their daily sales, customer analytics, and shop inventories effectively. They can manage potential customers, generated sales, and can view detailed inventory transactions using smart graphs/tables.

    Language:PHP1
  • wrangling-sales-workload

    Raw data of real analytical use cases in a number of industries and companies are frequently provided in an Excel-based form. These files usually cannot be processed directly in machine learning models, but must first be cleaned and preprocessed. In this process, many different types of pitfalls may occur. This makes data preprocessing an essential time factor in the daily work of a data scientist. In this concise project an Excel spreadsheet will be presented which in this form is closely oriented to a real case, but contains only simulated figures for reasons of data and business results protection. However, the form and structure of the file corresponds to a real case and could be encountered by a data scientist in a company in this way.

    Language:Jupyter Notebook1