exploring_retail_dataexplorer.Rmd

---
title: "Exploring the Cleaned Online Retail Dataset with DataExplorer"
author: "Mick Cooney <mickcooney@gmail.com>"
date: "Last updated: `r format(Sys.time(), '%B %d, %Y')`"
output:
  rmdformats::readthedown:
    toc_depth: 3
    use_bookdown: TRUE
    code_folding: hide
    fig_caption: TRUE

  html_document:
    fig_caption: yes
    theme: spacelab #sandstone #spacelab #flatly
    highlight: pygments
    number_sections: TRUE
    toc: TRUE
    toc_depth: 2
    toc_float:
      smooth_scroll: FALSE

  pdf_document: default
---


```{r import_libraries, echo=FALSE, message=FALSE}
library(conflicted)
library(tidyverse)
library(scales)
library(cowplot)
library(magrittr)
library(rlang)
library(purrr)
library(vctrs)
library(fs)
library(glue)
library(forcats)
library(snakecase)
library(lubridate)
library(DataExplorer)


source("lib_utils.R")

conflict_lst <- resolve_conflicts(
  c("magrittr", "rlang", "dplyr", "readr", "purrr", "ggplot2")
  )


knitr::opts_chunk$set(
  tidy       = FALSE,
  cache      = FALSE,
  warning    = FALSE,
  message    = FALSE,
  fig.height =     8,
  fig.width  =    11
  )

options(
  width = 80L,
  warn  = 1,
  mc.cores = parallel::detectCores()
  )

theme_set(theme_cowplot())

set.seed(42)
```


# Introduction

We previously performed a comprehensive data exploration of the retail dataset
using the `dataexpks` template, but now that we have removed and otherwise
filtered a number of other entries from the dataset.

As these removed rows may change the visualisation of the exploration, it is
worth doing a quick repeat of this exercise, so we perform those now using the
`DataExplorer` package.


# Load Data

We load up the cleaned dataset.

```{r load_dataset, echo=TRUE}
loaded_data_tbl <- read_rds("data/retail_data_cleaned_tbl.rds")

loaded_data_tbl %>% glimpse()
```

We now remove all excluded rows and run the exploration on the data with the
cleaned rows excluded.

```{r remove_excluded_rows, echo=TRUE}
retail_data_tbl <- loaded_data_tbl %>%
  filter(exclude == FALSE)

retail_data_tbl %>% glimpse()
```

# Use DataExplorer Routines


## Intro Data

```{r plot_intro_data, echo=TRUE}
introduce(retail_data_tbl)

plot_intro(retail_data_tbl)
```


## Missing Values

```{r plot_missing_values, echo=TRUE}
plot_missing(retail_data_tbl)
```


```{r plot_bar, echo=TRUE}
plot_bar(retail_data_tbl)
```


```{r plot_histogram, echo=TRUE}
plot_histogram(retail_data_tbl, ncol = 2)
```






# R Environment

```{r show_session_info, echo=TRUE, message=TRUE}
sessioninfo::session_info()
```