# Dataset Card for Book Tabular Data

<!-- Provide a quick summary of the dataset. -->

This tabular dataset provides measurements on books selected from my bookshelf.

## Dataset Details

### Dataset Description

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For a selection of books on my bookshelf, I collected some tabular data. 
I selected 15 fiction and 15 nonfiction books. 
I then documented how many pages each had, how thick the book was, if I had read it/ started it/ not read it, and if it was a book I would recommend to everyone. 
These variables were collected for the 30 books that make up my original split, and then they were augmented to create 300 additional examples.

- **Curated by:** Jennifer Evans
- **Language(s) (NLP):** English
- **License:** MIT

## Uses

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### Direct Use

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This dataset can be used to evaluate how book length and thickness might correlate with it being read and recommended. 
It can also be used to evaluate if a book is fiction or nonfiction.

### Out-of-Scope Use

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This dataset could be used for other evaluations, like metrics on books people buy or preferences on fiction versus nonfiction.

## Dataset Structure

<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->

- **dataset_info:**

- features:

name: FictionorNonfiction

    dtype: string
    
name: NumPages

    dtype: int64
    
name: ThicknessInches

    dtype: float64
    
name: ReadUnfinishedorUnread

    dtype: string
    
name: RecommendtoEveryone

    dtype: string
    
- splits:
  
name: original

    num_bytes: 1345
    
    num_examples: 30
    
name: augmented

    num_bytes: 13747
    
    num_examples: 300
    
download_size: 9114

dataset_size: 15092

- configs:

config_name: default

- data_files:
  
split: original

    path: data/original-*
    
split: augmented

    path: data/augmented-*

## Dataset Creation

### Curation Rationale

<!-- Motivation for the creation of this dataset. -->

The motivation for this dataset was to review books that I keep on my bookshelf and assess patterns related to if a book is fiction or nonfiction.

### Source Data

<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
The data came from the selected books on my bookshelf, which I measured directly.

#### Data Collection and Processing

<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->

Once the data was collected, it was augmented via jittering.

#### Who are the source data producers?

<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->

Jennifer Evans produced this data.