List price: $17.50

NOW AN EMMY-NOMINATED HULU ORIGINAL SERIES • NEW YORK TIMES BESTSELLER • “A stunning novel about the transformative power of relationships” (People) from the author of Conversations with Friends, “a master of the literary page-turner” (J. Courtney Sullivan).

ONE OF THE TEN BEST NOVELS OF THE DECADE—Entertainment Weekly

TEN BEST BOOKS OF THE YEAR—People, Slate, The New York Public Library, Harvard Crimson

AND BEST BOOKS OF THE YEAR—The New York Times, The New York Times Book Review, O: The Oprah Magazine, Time, NPR, The Washington Post, Vogue, Esquire, Glamour, Elle, Marie Claire, Vox, The Paris Review, Good Housekeeping, Town & Country

Connell and Marianne grew up in the same small town, but the similarities end there. At school, Connell is popular and well liked, while Marianne is a loner. But when the two strike up a conversation—awkward but electrifying—something life changing begins.

A year later, they’re both studying at Trinity College in Dublin. Marianne has found her feet in a new social world while Connell hangs at the sidelines, shy and uncertain. Throughout their years at university, Marianne and Connell circle one another, straying toward other people and possibilities but always magnetically, irresistibly drawn back together. And as she veers into self-destruction and he begins to search for meaning elsewhere, each must confront how far they are willing to go to save the other.

Normal People is the story of mutual fascination, friendship and love. It takes us from that first conversation to the years beyond, in the company of two people who try to stay apart but find that they can’t.

Praise for Normal People

“[A] novel that demands to be read compulsively, in one sitting.”—The Washington Post

“Arguably the buzziest novel of the season, Sally Rooney’s elegant sophomore effort . . . is a worthy successor to Conversations with Friends. Here, again, she unflinchingly explores class dynamics and young love with wit and nuance.”—The Wall Street Journal

“[Rooney] has been hailed as the first great millennial novelist for her stories of love and late capitalism. . . . [She writes] some of the best dialogue I’ve read.”—The New Yorker

ISBN: 9781984843333 Published: April 16, 2019 By: Sally Rooney Read by: Aoife McMahon

The dataset has been collected in the frame of the Prac1 of the subject Tipology and Data Life Cycle of the Master's Degree in Data Science of the Universitat Oberta de Catalunya (UOC).

The dataset contains 25 variables and 52478 records corresponding to books on the GoodReads Best Books Ever list (the larges list on the site).

Original code used to retrieve the dataset can be found on github repository: github.com/scostap/goodreads_bbe_dataset

The data was retrieved in two sets, the first 30000 books and then the remainig 22478. Dates were not parsed and reformated on the second chunk so publishDate and firstPublishDate are representet in a mm/dd/yyyy format for the first 30000 records and Month Day Year for the rest.

Book cover images can be optionally downloaded from the url in the 'coverImg' field. Python code for doing so and an example can be found on the github repo.

The 25 fields of the dataset are:

| Attributes | Definition | Completeness |
| ------------- | ------------- | ------------- | 
| bookId | Book Identifier as in goodreads.com | 100 |
| title | Book title | 100 |
| series | Series Name | 45 |
| author | Book's Author | 100 |
| rating | Global goodreads rating | 100 |
| description | Book's description | 97 |
| language | Book's language | 93 |
| isbn | Book's ISBN | 92 |
| genres | Book's genres | 91 |
| characters | Main characters | 26 |
| bookFormat | Type of binding | 97 |
| edition | Type of edition (ex. Anniversary Edition) | 9 |
| pages | Number of pages | 96 |
| publisher | Editorial | 93 |
| publishDate | publication date | 98 |
| firstPublishDate | Publication date of first edition | 59 |
| awards | List of awards | 20 |
| numRatings | Number of total ratings | 100 |
| ratingsByStars | Number of ratings by stars | 97 |
| likedPercent | Derived field, percent of ratings over 2 starts (as in GoodReads) | 99 |
| setting | Story setting | 22 |
| coverImg | URL to cover image | 99 |
| bbeScore | Score in Best Books Ever list | 100 |
| bbeVotes | Number of votes in Best Books Ever list | 100 |
| price | Book's price (extracted from Iberlibro) | 73 |

This dataset is about books. It has 1 row and is filtered where the book is Reading for meaning. Second series. Book 3 answers. It features 7 columns including author, publication date, language, and book publisher.

List price: $26.99

NAMED A MOST ANTICIPATED BOOK OF 2018 BY Buzzfeed • The Boston Globe • The Millions • InStyle • Southern Living • Vogue • Popsugar • Kirkus • The Washington Post • Library Journal • Real Simple • NPR

“With his unerring eye for nuance and unsparing sense of irony, Rumaan Alam’s second novel is both heartfelt and thought-provoking.” — Celeste Ng, author of Little Fires Everywhere

From the bestselling author of Leave the World Behind, a novel about the families we fight to build and those we fight to keep.

Like many first-time mothers, Rebecca Stone finds herself both deeply in love with her newborn son and deeply overwhelmed. Struggling to juggle the demands of motherhood with her own aspirations and feeling utterly alone in the process, she reaches out to the only person at the hospital who offers her any real help—Priscilla Johnson—and begs her to come home with them as her son’s nanny.

Priscilla’s presence quickly does as much to shake up Rebecca’s perception of the world as it does to stabilize her life. Rebecca is white, and Priscilla is black, and through their relationship, Rebecca finds herself confronting, for the first time, the blind spots of her own privilege. She feels profoundly connected to the woman who essentially taught her what it means to be a mother. When Priscilla dies unexpectedly in childbirth, Rebecca steps forward to adopt the baby. But she is unprepared for what it means to be a white mother with a black son. As she soon learns, navigating motherhood for her is a matter of learning how to raise two children whom she loves with equal ferocity, but whom the world is determined to treat differently.

Written with the warmth and psychological acuity that defined his debut, Rumaan Alam has crafted a remarkable novel about the lives we choose, and the lives that are chosen for us.

ISBN: 9780062847720 Published: May 8, 2018 By: Rumaan Alam Read by: Vanessa Johansson

©2018 Rumaan Alam (P)2018 HarperAudio

Context This dataset holds a list of approx 200 + books in the field of Data science related topics. The list of books was constructed using one of the popular websites Amazon which provide information on book ratings and many details given below.

There are 6 column

1. Book_name / book title

2. Publisher:-- name of the publisher or writer

3. Buyers ():--it means no of customer who purchase the same book

4. Cover_type:-- types of cover use to protect the book

5. stars:--out of 5 * how much rated

6. Price

Inspiration I’d like to call the attention of my fellow Kagglers to use Machine Learning and Data Sciences to help me explore these ideas:

• What is the best-selling book?

• Find any hidden patterns if you can

. EDA of dataset

The online novel reading market was valued at USD 3.88 billion in 2022 and will reach USD 6.91 billion by 2030, registering a CAGR of 7.5% for the forecast period 2023-2030. Driving factor:

Increasing demand for online books is driving the market of the online novel reading market.

Online books are easily available and have the advantage of dictionaries, summaries, and appendices. We can get a variety of books on online websites. They have easy access by only clicking on the unknown word so we can grab more information which will make reading easier. As more information will be provided, the reader will be more interested in reading the book. For example, Walmart has released a new version of Onn tablets which have unexpected features for Android tablets. Therefore, an increase in the availability of a variety of books results in increasing demand for the online novel reading market.

Restraining factor:

Rising piracy issues tend to hinder the growth of the online novel reading market.

There are some crucial parts included in the E-books. This data should be managed and operated in a very precise manner. The lack of books, ignorance of copyright rules, and poverty are some of the factors affecting piracy issues. Therefore, technological and cultural change also have a negative impact due to the adoption of learning and reading experiences.

Impact of the COVID-19 Pandemic on the Online Novel Reading Market: There was a positive impact on the market of online reading as it is easily available on online websites. The online novel reading has many advantages such as being cheaper as compared to hardcover, and also having huge discounts on e-books. This is very attractive for the customers who are buying it for the first time. The online reading market has also decreased the consumption of paper which is used for printing paper books so e-books are eco-friendly in nature. Therefore, downloading online books is a simple process and can be stored on the device. Thus, all these factors increase the market of the online novel reading market. What do you mean by the online novel reading platform? Online reading is advantageous for people who are passionate about reading books or novels. Online books are also called e-books and are used by individuals in order to increase their knowledge. The e-books are available in the format of texts and pictures which makes readers more interested in reading books. They are easily available on electronic devices such as computers, laptops, and smartphones. The availability of reading books on online websites is useful for the environment in order to reduce the use of paper. Elderly people who are retired and are interested in reading books can take advantage of reading books online.

This dataset is about books. It has 2 rows and is filtered where the book is Reading for meaning. Book 4. It features 7 columns including author, publication date, language, and book publisher.

Big Data and Society Abstract & Indexing - ResearchHelpDesk - Big Data & Society (BD&S) is open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities and computing and their intersections with the arts and natural sciences about the implications of Big Data for societies. The Journal's key purpose is to provide a space for connecting debates about the emerging field of Big Data practices and how they are reconfiguring academic, social, industry, business, and government relations, expertise, methods, concepts, and knowledge. BD&S moves beyond usual notions of Big Data and treats it as an emerging field of practice that is not defined by but generative of (sometimes) novel data qualities such as high volume and granularity and complex analytics such as data linking and mining. It thus attends to digital content generated through online and offline practices in social, commercial, scientific, and government domains. This includes, for instance, the content generated on the Internet through social media and search engines but also that which is generated in closed networks (commercial or government transactions) and open networks such as digital archives, open government, and crowdsourced data. Critically, rather than settling on a definition the Journal makes this an object of interdisciplinary inquiries and debates explored through studies of a variety of topics and themes. BD&S seeks contributions that analyze Big Data practices and/or involve empirical engagements and experiments with innovative methods while also reflecting on the consequences for how societies are represented (epistemologies), realized (ontologies) and governed (politics). Article processing charge (APC) The article processing charge (APC) for this journal is currently 1500 USD. Authors who do not have funding for open access publishing can request a waiver from the publisher, SAGE, once their Original Research Article is accepted after peer review. For all other content (Commentaries, Editorials, Demos) and Original Research Articles commissioned by the Editor, the APC will be waived. Abstract & Indexing Clarivate Analytics: Social Sciences Citation Index (SSCI) Directory of Open Access Journals (DOAJ) Google Scholar Scopus

List price: $20.00

NEW YORK TIMES BESTSELLER A GOOD MORNING AMERICA Book Club Pick!

Klara and the Sun is a magnificent new novel from the Nobel laureate Kazuo Ishiguro—author of Never Let Me Go and the Booker Prize-winning The Remains of the Day.

Klara and the Sun, the first novel by Kazuo Ishiguro since he was awarded the Nobel Prize in Literature, tells the story of Klara, an Artificial Friend with outstanding observational qualities, who, from her place in the store, watches carefully the behavior of those who come in to browse, and of those who pass on the street outside. She remains hopeful that a customer will soon choose her.

Klara and the Sun is a thrilling book that offers a look at our changing world through the eyes of an unforgettable narrator, and one that explores the fundamental question: what does it mean to love?

In its award citation in 2017, the Nobel committee described Ishiguro’s books as “novels of great emotional force” and said he has “uncovered the abyss beneath our illusory sense of connection with the world.”

By Kazuo Ishiguro Read by Sura Siu Published March 2, 2021

This dataset is about books. It has 1 row and is filtered where the book is The meaning of McCarthyism. It features 7 columns including author, publication date, language, and book publisher.

There are no early detection biomarkers or prognostic markers for oral squamous cell carcinoma (OSCC) thus many are detected late, with unpredictable disease course. Using systems level analysis on shotgun proteomics with quantitative label-free ultra-definition mass spectrometry, our study aims to find novel proteins involved in both low and high grade OSCC tissue, and to further understand pathways involved in cancer development and progression, using proteomic analysis.

This explanation pertains to the data prepared for Non sola scriptura: Essays on the Qur’an and Islam in Honour of William A. Graham (Routledge), Chapter by Sarah Bowen Savant, “People versus Books.”

We are releasing data that was used to create for the chapter, Graphs 1 and 2 and also Tables 1-3.

Note: All the data files (except the text in number 3) are in TSV format (Tab Separated Values) and any text editor or tabular data editor, such as Excel can deal with it.

1. “IsnadFractions_PeopleversusBooks”. This file represents a filtered version of an output from Ryan Muther’s isnād classifier algorithm. Muther ran the algorithm in July 2020, based on the Version 2020.1.2 release of the corpus, available at: http://doi.org/10.5281/zenodo.3891466. The data file includes:

   • author: the name of the author.

   • died: death date of author. NB: Especially the early dates cannot be relied on.

   • title: the title of the author’s book, from the OpenITI Corpus.

   • length: length of the book, measured in word-tokens.

   • isnad_fraction: the percentage of the book’s word-tokens that are made up of isnāds.

2. “GALTags_PeopleversusBooks”. Books in the OpenITI were mapped by Walid A. Akef in 2018 to:

   Brockelmann, Carl, History of the Arabic Written Traditions, trans. Joep Lameer, 2 vols and 3 supplements, Leiden: Brill, 2016-2018.

   The file includes the following columns:

   • id: book id, from the OpenITI Corpus.

   • gal_tags: the GAL tags, also used in the OpenITI Corpus

3. “0571IbnCasakir.TarikhDimashq.JK000916-ara1.mARkdown”. The Ibn ʿAsākir text file, from the Version 2020.1.2 release of the OpenITI Corpus.

4. “NamedEntities_PeopleversusBooks”. This is a very first effort at working on named entities in Ibn ʿAsākir’s Taʾrīkh Madīnat Dimashq and represents only a tiny fraction of the surface forms of names. Most of the names pertain to persons who transmitted from Ibn Saʿd. There may be some duplicate surface forms (which does not affect the method). We use this list to replace the surface forms with transliterated values. The column description is as below:

   • name: the normalized name.

   • ar_name: the Arabic name, which are the surface forms.

   • status: true (T)/false (F) values to include/exclude the cases in the replacement process. We have used true values.

5. “SplittingTerms_PeopleversusBooks”. We started with a list of transmissive terms that R. Kevin Jaques originated and then added more terms, which include the various normalized forms of the same term. We used this list to split isnāds into names.

6. “IbnSadIsnads_PeopleversusBooks”. This file includes the pieces of texts that the algorithm tags as isnāds in the text. We extracted the tagged pieces and made a list of isnāds. Almost all of the isnāds start with a transmissive term. We use this file to extract the names and clean some rows to generate a data table that we can use for clustering. Below are the brief description of the column:

   • text_ID: this contains the book id from the OpenITI Corpus. This column can be ignored as we are using it for one text in this project. However, it is required in the collection of isnāds from multiple texts.

   • id: a unique identifier assigned to each isnād. The isnād classifier algorithm assigns this id and can be used to identify each isnād in the text when required.

   • isnad_text: the isnād that we extract from the text.

   • length: length of the extracted isnād in tokens

7. “IsnadNames_PeopleversusBooks”. This file is the isnāds list (number 5 on this list) splitted by the transmissive terms (number 4 on this list) in order to extract the names in the isnāds. ‌The column are the same as below:
   • text_ID: this contains the book id from the OpenITI corpus. This column can be ignored as we are using it for one text in this project. However, it is required in the collection of isnāds from multiple texts.
   • isnad_text: this column is the isnād that we extract from the text.
   • ibnSad_cnt: number of times that the name Ibn Saʿd is mentioned in the corresponding isnād.

   • name_at_position_X: the rest of the columns in this table include the pieces of the isnād that we get after splitting the isnāds with a list of terms. Each column contains a name or any string that appears between two transmissive terms. Some cells are empty and it is because we probably miss some transmissive terms.

8. “IbnSadClusters_PeopleversusBooks”. This file includes clusters of isnāds of length six (i.e. isnāds that include six names). We have used the affinity propagation (AP) clustering algorithm based on the Levenstein similarity score of the names. Below is the column description:

   • frequency: the frequency of the isnād in the data

   • cluster_id: the id of the cluster to which the isnād belongs

   • nameX: columns C to H include the names in isnād at position 1 to 6, running back to Muhammad b. Saʿd at position 6.
9. “JK000916-ara1.mARkdown_Shamela0001686-ara1.completed”. This is the passim output from the February 2020 run (which used the same version of the corpus; Version 2020.1.2). For definition of fields in this file, please see number 10.

10. “PassimCol-Definition_PeopleversusBooks”. Description of the columns in passim outputs.

In single-particle cryo-electron microscopy (cryo-EM), K-means clustering algorithm is widely used in unsupervised 2D classification of projection images of biological macromolecules. 3D ab initio reconstruction requires accurate unsupervised classification in order to separate molecular projections of distinct orientations. Due to background noise in single-particle images and uncertainty of molecular orientations, traditional K-means clustering algorithm may classify images into wrong classes and produce classes with a large variation in membership. Overcoming these limitations requires further development on clustering algorithms for cryo-EM data analysis. We propose a novel unsupervised data clustering method building upon the traditional K-means algorithm. By introducing an adaptive constraint term in the objective function, our algorithm not only avoids a large variation in class sizes but also produces more accurate data clustering. Applications of this approach to both simulated and experimental cryo-EM data demonstrate that our algorithm is a significantly improved alterative to the traditional K-means algorithm in single-particle cryo-EM analysis.

Analysis of ‘Goodreads-books’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/jealousleopard/goodreadsbooks on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

The primary reason for creating this dataset is the requirement of a good clean dataset of books. Being a bookie myself (see what I did there?) I had searched for datasets on books in kaggle itself - and I found out that while most of the datasets had a good amount of books listed, there were either a) major columns missing or b) grossly unclean data. I mean, you can't determine how good a book is just from a few text reviews, come on! What I needed were numbers, solid integers and floats that say how many people liked the book or hated it, how much did they like it, and stuff like that. Even the good dataset that I found was well-cleaned, it had a number of interlinked files, which increased the hassle. This prompted me to use the Goodreads API to get a well-cleaned dataset, with the promising features only ( minus the redundant ones ), and the result is the dataset you're at now.

Acknowledgements

This data was entirely scraped via the Goodreads API, so kudos to them for providing such a simple interface to scrape their database.

Inspiration

The reason behind creating this dataset is pretty straightforward, I'm listing the books for all book-lovers out there, irrespective of the language and publication and all of that. So go ahead and use it to your liking, find out what book you should be reading next ( there are very few free content recommendation systems that suggest books last I checked ), what are the details of every book you have read, create a word cloud from the books you want to read - all possible approaches to exploring this dataset are welcome. I started creating this dataset on May 25, 2019, and intend to update it frequently. P.S. If you like this, please don't forget to give an upvote!

V2 notes :

You have the information about the publisher and the publication date now! Also, multiple authors are now delimited by '/'. Enjoy!

--- Original source retains full ownership of the source dataset ---

The collection "Fiction littéraire de Gallica" includes 19,240 public domain documents from the digital platform of the French National Library that were originally classified as novels or, more broadly, as literary fiction in prose. It consists of 372 tables of data in tsv format for each year of publication from 1600 to 1996 (all the missing years are in the 17th and 20th centuries). Each table is structured at the page-level of each novel (5,723,986 pages in all). It contains the complete text with the addition of some metadata. It can be opened in Excel or, preferably, with the new data analysis environments in R or Python (tidyverse, pandas…)

This corpus can be used for large-scale quantitative analyses in computational humanities. The OCR text is presented in a raw format without any correction or enrichment in order to be directly processed for text mining purposes.

The extraction is based on a historical categorization of the novels: the Y2 or Ybis classification. This classification, invented in 1730, is the only one that has been continuously applied to the BNF collections now available in the public domain (mainly before 1950). Consequently, the dataset is based on a definition of "novel" that is generally contemporary of the publication.

A French data paper (in PDF and HTML) presents the construction process of the Y2 category and describes the structuring of the corpus. It also gives several examples of possible uses for computational humanities projects.

Context

The reason for creating this dataset is the requirement of a good clean dataset of computer books. I had searched for datasets on books in Kaggle and I found out that while most of the datasets had a good amount of books listed, there were either major columns missing or grossly unclean data. I mean, you can't determine how good a book is just from a few text reviews. So I collected this data from the Goodreads website from the "Computer" category to help people who are li like this type of book.

Acknowledgements

This data was entirely scraped via the Webdriver

Inspiration

The reason behind creating this dataset is pretty straightforward, I'm listing the books for all who need computer books, irrespective of the language and publication and all of that. So go ahead and use it to your liking, find out what book you should be reading next, all possible approaches to exploring this dataset are welcome. I started creating this dataset on Jan 18, 2021, and intend to update it frequently. P.S. If you like this, please don't forget to give an upvote!

Notes

The missing values are imputed in this data by the creator.

Big Data and Society CiteScore 2024-2025 - ResearchHelpDesk - Big Data & Society (BD&S) is open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities and computing and their intersections with the arts and natural sciences about the implications of Big Data for societies. The Journal's key purpose is to provide a space for connecting debates about the emerging field of Big Data practices and how they are reconfiguring academic, social, industry, business, and government relations, expertise, methods, concepts, and knowledge. BD&S moves beyond usual notions of Big Data and treats it as an emerging field of practice that is not defined by but generative of (sometimes) novel data qualities such as high volume and granularity and complex analytics such as data linking and mining. It thus attends to digital content generated through online and offline practices in social, commercial, scientific, and government domains. This includes, for instance, the content generated on the Internet through social media and search engines but also that which is generated in closed networks (commercial or government transactions) and open networks such as digital archives, open government, and crowdsourced data. Critically, rather than settling on a definition the Journal makes this an object of interdisciplinary inquiries and debates explored through studies of a variety of topics and themes. BD&S seeks contributions that analyze Big Data practices and/or involve empirical engagements and experiments with innovative methods while also reflecting on the consequences for how societies are represented (epistemologies), realized (ontologies) and governed (politics). Article processing charge (APC) The article processing charge (APC) for this journal is currently 1500 USD. Authors who do not have funding for open access publishing can request a waiver from the publisher, SAGE, once their Original Research Article is accepted after peer review. For all other content (Commentaries, Editorials, Demos) and Original Research Articles commissioned by the Editor, the APC will be waived. Abstract & Indexing Clarivate Analytics: Social Sciences Citation Index (SSCI) Directory of Open Access Journals (DOAJ) Google Scholar Scopus

This dataset is about books. It has 2 rows and is filtered where the book is The meaning of Paul for today. It features 7 columns including author, publication date, language, and book publisher.

Guide to how to access NRRI data with an email request to the author. This dataset is not publicly accessible because: The data are private, but available on request. It can be accessed through the following means: Email request to Stephen Kolbe - kolbe023@d.umn.edu. Format: Novel data collected by the lead author, which are kept and curated by National Resources Research Institute (NRRI). This dataset is associated with the following publication: Kolbe, S., G. Niemi, A. Bracey, M. Etterson, and A. Grinde. Incorporating weather in counts and trends of migrating Common Nighthawks. Avian Conservation and Ecology. Society of Canadian Ornithologists and Bird Studies Canada, CANADA, 19(1): 9, (2024).

ABSTRACT This article aims to approach the translations of the novel Beloved (1987), by Toni Morrison, in Brazil, focusing on some of their paratexts. It begins with a theoretical reflection on translation that considers it as a process that goes beyond the linguistic transposition between the source text and the target text, since it involves social, historical, cultural, ideological factors, among others. After that, the theory of paratranslation is presented, according to which the paratexts that make up a translated work are important elements to be examined by the researcher, since they contribute to meaning construction. Subsequently, the article provides a brief overview of Toni Morrison and her literary production, highlighting Beloved, and continues with an analysis of the covers and back covers of the different editions of Amada, title of the referred work in Brazil. Finally, it appears that, in general, Beloved’s Brazilian paratranslations reinforce the images of Morrison as an award-winning writer and of the novel in question as a critically acclaimed book.