The current paper examines the factors that influence the increase of the
sales volume of a retailer. The aim of the study is to create an accurate model with high explanatory
power which accounts for the promotional and competitor effects on the quantity sold as well
as to identify the main volume uplift drivers. That information could be useful when designing
marketing strategies in order to gain a competitive advantage over the other market players.
Team members: Ana Popova, @anie Izabella Taskova, @ izabellataskova Kamelia Kosekova, @kameliak Kameliya Lokmadzhieva, @kameliyalokmadzhieva Nikolay Bojurin, @nikolay Mentors: @boryana @alex-efremov @pepe Team name: DAB PANDA Team logo: NB!!!! OUR NOTEBOOKS ARE AVAILABLE HERE: DAB PANDA Rmds Data Understanding and Preparation You may see our code with results and brief comments if you […]
Techonnology and methods used: R – plyr, dplyr, tidyverse, stringr, data.table, geohash, ggmap, maps, robustbase, geosphere, pracma, Hmisc, ggplot2, tidyquant, reshape2, pastecs Python – s3fs, pandas, numpy, matplotlib, plotly, geohash2, folium, geopy OLS Regression, Ridge Regression, Decision Trees Introduction Air pollution beyond the norms is a common problem in many locations. Examining the causes behind and being able to predict […]
Techonnology and methods used: R – tidyverse, lubridate, snakecase, sp, raster, spData, sf, leaflet, mapview, ggplot2, shiny, maps, devtools, geojsonio, rgdal, leaflet.esri, leaflet.extras Python – s3fs, pandas, numpy, matplotlib, plotly 1. Business Understanding Air pollution beyond the norms is a common problem in many locations. Examining the causes behind and being able to predict it would help control and reduce pollution, facilitate solving environmental issues and providing a better life to citizens. Air […]
