https://github.com/krzjoa/m5

Data for M5 Walmart Kaggle Competition
https://github.com/krzjoa/m5

data-science kaggle-competition kaggle-dataset m5-competition m5-forecasting time-series-forecasting walmart walmart-sales-forecasting

Last synced: about 2 months ago
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Data for M5 Walmart Kaggle Competition

• Host: GitHub
• URL: https://github.com/krzjoa/m5
• Owner: krzjoa
• License: other
• Created: 2022-08-31T19:15:39.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2022-09-07T20:54:59.000Z (over 2 years ago)
• Last Synced: 2024-09-23T01:18:55.603Z (3 months ago)
• Topics: data-science, kaggle-competition, kaggle-dataset, m5-competition, m5-forecasting, time-series-forecasting, walmart, walmart-sales-forecasting
• Language: R
• Homepage: https://krzjoa.github.io/m5
• Size: 37 MB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.Rmd
  • License: LICENSE

Awesome Lists containing this project

README

        
---

output: github_document

---

```{r, include = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  warning = FALSE, 

  message = FALSE,

  comment = "#>",

  fig.path = "man/figures/README-",

  out.width = "100%"

)

```

# m5 

[![CRAN status](https://www.r-pkg.org/badges/version/m5)](https://CRAN.R-project.org/package=m5)

[![Buy hex

stciker](https://img.shields.io/badge/buy%20hex-m5-green?style=flat&logo=redbubble)](https://www.redbubble.com/i/sticker/m5-R-package-hex-by-krzjoa/122633859.EJUG5)

[![R-CMD-check](https://github.com/krzjoa/m5/workflows/check-standard/badge.svg)](https://github.com/krzjoa/m5/actions)

> M5 Walmart Challenge Data

## Installation

You can install the development version of m5 from [GitHub](https://github.com/) with:

``` r

# install.packages("devtools")

devtools::install_github("krzjoa/m5")

```

## Usage

```{r}

library(m5)

library(zeallot)

library(ggplot2)

DIR <- 'data'

# Downloading the data

m5_download(DIR)

# Loading the data

c(sales_train,

   sales_test,

   sell_prices,

   calendar,

   weights) %<-% m5_get_raw_evaluation(DIR)

   

# Preparing the data

m5_data  <-

   m5_prepare(sales_train, sales_test, calendar, sell_prices)

# Demand classification

m5_demand <- m5_demand_type(m5_data)

foods_1_demand <- 

  m5_demand[startsWith(as.character(m5_demand$item_id), "FOODS_1")]

plot <-

  ggplot(foods_1_demand) +

  geom_point(aes(log(cv2), log(adi),

                 item_id = item_id, col = demand_type)) +

  geom_hline(yintercept = log(1.32)) +

  geom_vline(xintercept = log(0.49)) +

  theme_minimal()

plot

```