Because of the sheer number of products available, the German book market is one of the largest business trading today. In order to display a highly individual profile to customers and, at the same time, keep the effort involved in selecting and ordering as low as possible, the key to success for the bookshop therefore lies in the effective purchasing from a choice of roughly 96,000 new titles each year. The challenge for the bookseller is to buy the right amount of the right books at the right time.

It is with this in mind that this year’s DATA MINING CUP Competition will be held in cooperation with Libri, Germany’s leading book wholesaler. Among Libri’s many successful support measures for booksellers, purchase recommendations give the bookshop a competitive advantage. Accordingly, the DATA MINING CUP 2009 challenge will be to forecast of purchase quantities of a clearly defined title portfolio per location, using simulated data.

The Task

The task of the DATA MINING CUP Competition 2009 is to forecast purchase quantities for 8 titles for 2,418 different locations. In order to create the model, simulated purchase data from an additional 2,394 locations will be supplied. All data refers to a fixed period of time. The object is to forecast the purchase quantities of these 8 different titles for the 2,418 locations as exactly as possible.

The Data

There are two text files available to assist in solving the problem: dmc2009_train.txt (train data file) and dmc2009_forecast.txt (data of 2,418 locations for whom a prediction is to be made).

Acknowledgement

This data is publicly available in the data-mining-website.

This dataset provides a comprehensive overview of online sales transactions across different product categories. Each row represents a single transaction with detailed information such as the order ID, date, category, product name, quantity sold, unit price, total price, region, and payment method.

Columns:

• Order ID: Unique identifier for each sales order.
• Date:Date of the sales transaction.
• Category:Broad category of the product sold (e.g., Electronics, Home Appliances, Clothing, Books, Beauty Products, Sports).
• Product Name:Specific name or model of the product sold.
• Quantity:Number of units of the product sold in the transaction.
• Unit Price:Price of one unit of the product.
• Total Price: Total revenue generated from the sales transaction (Quantity * Unit Price).
• Region:Geographic region where the transaction occurred (e.g., North America, Europe, Asia).
• Payment Method: Method used for payment (e.g., Credit Card, PayPal, Debit Card).

Insights:

• 1. Analyze sales trends over time to identify seasonal patterns or growth opportunities.
• 2. Explore the popularity of different product categories across regions.
• 3. Investigate the impact of payment methods on sales volume or revenue.
• 4. Identify top-selling products within each category to optimize inventory and marketing strategies.
• 5. Evaluate the performance of specific products or categories in different regions to tailor marketing campaigns accordingly.

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 |

In 2024, U.S. book store sales stood at 7.86 billion U.S. dollars according to preliminary estimates, down from 7.9 billion in the previous year. The 2024 figure will be subject to later adjustments, but demonstrated a drop from the figures in more recent years, and sales are yet to return to pre-pandemic levels.

The best-selling book in the United States as of the week ending February 10th, 2024 was "The Women" by Kristin Hannah with ****** thousand units sold. Sarah J. Maas had two titles in the bestseller's list that week, "House of Flame and Shadow" and "A Court of Thorns and Roses". What makes a book a best-seller? Ultimately, there is no secret ingredient to making a book a best-seller, despite numerous online articles offering tips on how to craft a novel or non-fiction piece that will earn millions. However, being an international icon naturally presents an advantage. Michelle Obama’s millions of Instagram followers and her previous position as First Lady of the United States certainly helped thrust her book "Becoming" into the media spotlight. For other writers such as E. L. James (author of the 'Fifty Shades’ series) being part of fan fiction communities and crafting a story based on an existing narrative, notably Stephanie Meyer’s ‘Twilight’, helped to push sales by targeting a particular demographic. Many best-selling books go on to become classics, however not all members of the classical literary canon shot to fame upon publishing a novel. A look at classic literature A survey on readership of selected literary genres showed that classics were one of the most favorable among U.S. adults, and numerous books in this category proved popular among Goodreads users. As of November 2018, almost **** million Goodreads users had marked Harper Lee’s ‘To Kill A Mockingbird’ as ‘to be read’, with other important literary works such as Anne Frank’s ‘The Diary of a Young Girl’ garnering significant interest on the platform, as well as books by George Orwell, F. Scott Fitzgerald and Jane Austen. Anne Frank’s book is an excellent example of one which became a best-seller (and indeed, a classic) unintentionally, however like so many authors Frank sadly never lived to see her diary grow to global success.

About Dataset

This is the Amazon Best Sellers of 2010-2020 (Top 100 Books) Data scraped from the amazon website (https://www.amazon.com/gp/bestsellers/2020/books). It contains 1094 obs (It was originally 1100 obs since it's 11 years of data, but already dropped 6 NA or empty values from raw data) with 7 variables such as Year, Rank(1-100 per each year), Book Title, Author, Rating, Number of customers rated (number of customer reviews), and Book price.

From 2004 to 2024, the net revenue of Amazon e-commerce and service sales has increased tremendously. In the fiscal year ending December 31, the multinational e-commerce company's net revenue was almost *** billion U.S. dollars, up from *** billion U.S. dollars in 2023.Amazon.com, a U.S. e-commerce company originally founded in 1994, is the world’s largest online retailer of books, clothing, electronics, music, and many more goods. As of 2024, the company generates the majority of it's net revenues through online retail product sales, followed by third-party retail seller services, cloud computing services, and retail subscription services including Amazon Prime. From seller to digital environment Through Amazon, consumers are able to purchase goods at a rather discounted price from both small and large companies as well as from other users. Both new and used goods are sold on the website. Due to the wide variety of goods available at prices which often undercut local brick-and-mortar retail offerings, Amazon has dominated the retailer market. As of 2024, Amazon’s brand worth amounts to over *** billion U.S. dollars, topping the likes of companies such as Walmart, Ikea, as well as digital competitors Alibaba and eBay. One of Amazon's first forays into the world of hardware was its e-reader Kindle, one of the most popular e-book readers worldwide. More recently, Amazon has also released several series of own-branded products and a voice-controlled virtual assistant, Alexa. Headquartered in North America Due to its location, Amazon offers more services in North America than worldwide. As a result, the majority of the company’s net revenue in 2023 was actually earned in the United States, Canada, and Mexico. In 2023, approximately *** billion U.S. dollars was earned in North America compared to only roughly *** billion U.S. dollars internationally.

The Child Care and Development Fund (CCDF) provides federal money to states and territories to provide assistance to low-income families, to obtain quality child care so they can work, attend training, or receive education. Within the broad federal parameters, States and Territories set the detailed policies. Those details determine whether a particular family will or will not be eligible for subsidies, how much the family will have to pay for the care, how families apply for and retain subsidies, the maximum amounts that child care providers will be reimbursed, and the administrative procedures that providers must follow. Thus, while CCDF is a single program from the perspective of federal law, it is in practice a different program in every state and territory. The CCDF Policies Database project is a comprehensive, up-to-date database of CCDF policy information that supports the needs of a variety of audiences through (1) analytic data files, (2) a project website and search tool, and (3) an annual report (Book of Tables). These resources are made available to researchers, administrators, and policymakers with the goal of addressing important questions concerning the effects of child care subsidy policies and practices on the children and families served. A description of the data files, project website and search tool, and Book of Tables is provided below: 1. Detailed, longitudinal analytic data files provide CCDF policy information for all 50 states, the District of Columbia, and the United States territories and outlying areas that capture the policies actually in effect at a point in time, rather than proposals or legislation. They capture changes throughout each year, allowing users to access the policies in place at any point in time between October 2009 and the most recent data release. The data are organized into 32 categories with each category of variables separated into its own dataset. The categories span five general areas of policy including: Eligibility Requirements for Families and Children (Datasets 1-5) Family Application, Terms of Authorization, and Redetermination (Datasets 6-13) Family Payments (Datasets 14-18) Policies for Providers, Including Maximum Reimbursement Rates (Datasets 19-27) Overall Administrative and Quality Information Plans (Datasets 28-32) The information in the data files is based primarily on the documents that caseworkers use as they work with families and providers (often termed "caseworker manuals"). The caseworker manuals generally provide much more detailed information on eligibility, family payments, and provider-related policies than the CCDF Plans submitted by states and territories to the federal government. The caseworker manuals also provide ongoing detail for periods in between CCDF Plan dates. Each dataset contains a series of variables designed to capture the intricacies of the rules covered in the category. The variables include a mix of categorical, numeric, and text variables. Most variables have a corresponding notes field to capture additional details related to that particular variable. In addition, each category has an additional notes field to capture any information regarding the rules that is not already outlined in the category's variables. Beginning with the 2020 files, the analytic data files are supplemented by four additional data files containing select policy information featured in the annual reports (prior to 2020, the full detail of the annual reports was reproduced as data files). The supplemental data files are available as 4 datasets (Datasets 33-36) and present key aspects of the differences in CCDF-funded programs across all states and territories as of October 1 of each year (2009-2022). The files include variables that are calculated using several variables from the analytic data files (Datasets 1-32) (such as copayment amounts for example family situations) and information that is part of the annual project reports (the annual Book of Tables) but not stored in the full database (such as summary market rate survey information from the CCDF plans). 2. The project website and search tool provide access to a point-and-click user interface. Users can select from the full set of public data to create custom tables. The website also provides access to the full range of reports and products released under the CCDF Policies Data

The Stock Book is the annual review of Fish Stocks in any given year, the latest being 2016, with management advice for the subsequent year. The Stock Book covers fisheries and fishing activities in the greater North Atlantic Ocean, Celtic Sea, Irish Sea and Saint Georges Channel around Ireland. The Stock Book covers data collected between 2011 and 2016. Fisheries scientific advice data includes information collected from surveys and fisheries models. Its purpose has been to provide the latest impartial scientific advice on the commercially exploited fish stocks of interest to Ireland. The Stock Book 2016 was the principal annual publication of the Marine Institutes (Ireland) Fisheries Ecosystem Advisory Services (FEAS) section. The Stock Book was used by the Department of Agriculture, Marine and Food - (DAFM) at the Total Allowable Catch (TAC) negotiations with the EU in December 2016 and throughout the year at fisheries management meetings. Stock Book complete for year of publication in question.

This dataset contains digitized sales ledgers from Gumpert's bookshop in Gothenburg, one of the most prominent bookshops in Sweden during the nineteenth century. Like most major bookshops at the time, Gumpert’s bookshop primarily sold books on credit, and consequently, the bookshop had to keep a record detailing all the returning customers’ purchases. In most cases each customer was assigned a page in the sales ledgers and the purchases were listed in chronological order. The customers’ name, profession or title, and residence location were scribbled on top of the page. The Gumpert ledgers are comprised of 48 volumes, one volume per year from 1870 to 1917, each containing between 900 and 1,200 pages. They record nearly a million purchases. The present dataset contains material from 1870–1900 and consists of photographs of the original documents (in .jpg format) as well as transcriptions of a 10 % sample of the ledgers from 1879–1890 (in .txt /.pdf /.xlsx format), listing in all over 18,000 purchases. The dataset was created in association with the Scandinavian Moment in World Literature project and formed an important empirical source for my doctoral dissertation «Modern Reading: Swedish Book Consumption during the late nineteenth century» and my article Hansen, H. (2017). Buying and Borrowing Books: Book Consumption In Late Nineteenth-Century Sweden (pp 121-154). Papers of The Bibliographical Society of Canada, 54(1-2). https://doi.org/10.33137/pbsc.v54i1-2.25614.

Datasets for each of the chapters in The Blue Book 2024 including the national accounts at a glance, financial and non-financial corporations, households and non-profit institutions serving households and summary supply and use tables.

Four datasets are included focusing on animal communicators (AC): practitioners of intuitive interspecies communication (IIC).

Dataset #1: International English language websites data set (n = 400). To be included and coded, websites had to meet the following 3 criteria: (1) have an English language version of the website, (2) currently offer private AC consultations, and (3) be identified before website analysis was determined comprehensive enough to represent the international scope of AC (Oct. 30, 2020). CITE AS: Barrett, M. J., Zmud, L., Mathur, A., & Hoessler, C. (2024). Animal communicator website scan [Data set]. Zenodo. DOI 10.5281/zenodo.7750695

Dataset #2: International English language published books. Total books (n = 191): Books were identified through internet searches, including searches on Amazon and used bookstores such as Abe Books, from practicing AC websites, and from the directory: Book Authority Website for “53 Best Animal Communication Books of All Time,” https://bookauthority.org/books/best-animal-communication-books. Dataset includes books’ titles, descriptions, front and back covers and tables of contents where available. Where it was not clear whether the author was an animal communicator who consulted with clients, we did additional online searches to make this determination. All books had an English language printed copy of the book. We excluded books that were available in electronic copy only. We expanded our initial content inclusion criteria used in the website report beyond individuals currently offering consultations as professional animal communicators to include: (1) professional animal communicators who have since retired; (2) individuals who work intensively with animals in other capacities such as healing, but also report instances of IIC; (3) individuals who may not have worked as professional animal communicators, but write about their own lived experience of the phenomena; and (4) books written by individuals who are not ACs but have interviewed ACs. Where a book was written by two authors, or in some cases, an animal communicator with an additional author, we included both authors in our formal citation. Books were written by ACs who offered professional services (182), or authors who were not ACs (9). CITE AS: Barrett, M. J., Mathur, A., & Ghoreishi, Z., Hoessler, C., Kuppenbender, S. (2024). Animal communicator Book Scan [Data set]. Zenodo. DOI 10.5281/zenodo.7750695

Dataset #3: Directory of practicing ACs (1990-2011; n = 80 issues). To provide a snapshot of growth in numbers of practitioners over time, we compiled listings of ACs published in the Animal Communicator Directory from Species Link: The Journal of Interspecies Telepathic Communication. From 1990-2011, the publication included a directory of practicing ACs; after 2011, the directory went fully online, and data from each year is not available. CITE AS: Barrett, M.J. & Hoessler, C. (2022). Animal Communicator Directory. [Data set]. Zenodo. DOI 10.5281/zenodo.7750695

Dataset #4: Reference List of 15 Analyzed Animal Communicator Books with formal or informal “How-To” Sections. Compiled to identify and summarize the ways in which ACs were describing essential processes for conducting a successful intuitive communication session with animals, and thus provide an overview of what happens in an IIC session. Selection criteria: We were seeking succinct summaries from ACs. The intent was not to dig into and analyze processes in detail, but rather to summarize and synthesize the essential processes and steps as the ACs were reporting them. As such, it was beyond the scope of this study to analyze reported example communications or analyze processes in books where the entirety of the book was describing communications with animals. Publication date range: 1998-2019. Close to 300 pages were analyzed. The actual "how-to" excerpts are not included as they are subject to copyright. CITE AS: Barrett, M.J. & Kuppenbender, S. (2022). Reference List of 15 Analyzed Animal Communicator Books [Data set]. Zenodo. DOI 10.5281/zenodo.7750695

For further information on data collection and analysis details contact M.J. Barrett, PhD. mj.barrett@usask.ca

Funded by the Social Sciences and Humanities Research Council of Canada Insight Development Grant: Deepening Connection in Pursuit of Environmental Sustainability: Assessing a Promising Lever for Shifting Assumptions of Separation (Grant # 430-2019-01023).

The SPSS data file (RES-062-23-1831 FBS data for ESRC archive.sav) contains 215 variables entered either directly from Farm Management Survey (FMS) Field Books or derived from calculations using field book data and supplementary information (such as price indices). The file ‘RES-062-23-1831 SPSS data handbook.xlsx’ lists all of the variables (both in alphabetical order and the order they appear in in the SPSS file) and includes additional explanatory notes for each variable. Data cleaning was undertaken by looking for logically inconsistent relationships between various variables, querying and checking of anomalous results during data analysis and double checking a number of entries with the original field books. The data file contains information on 168 farm holdings in Devon, Dorset and Cornwall from 1939 to 1984. The file contains 4,987 cases. Each case in the SPSS file relates to a specific field book for a specific year for a particular farm. The 168 farms selected for inclusion in the SPSS dataset represent a proportion of all of the farms in the University of Exeter FMS archive. Farms were purposively selected, initially on grounds of longevity in the FMS sample and then to achieve coverage of a cross-section of farming situations in the counties of Devon, Dorset and Cornwall. The objectives of this project were to produce a detailed survey of agricultural change, and technical change in particular, over the period 1935 – 1985, and to shed light on how and when changes on individual farms were brought about. These objectives were realised, as detailed in the project end of award report. We should note that there was no requirement at the time of the awarding of the grant to produce a pathways to impact plan, and impact beyond these objectives was not the central focus of the project. As an historical project its impact beyond its contribution to the field of knowledge in this area was always bound to be limited. We did, however, identify groups of beneficiaries and we have worked to engage with these audiences to discuss our findings and to broaden knowledge and cultural understanding, and this work is outlined below. In particular we were keen to discuss our findings with rural historians, focusing on but not restricting ourselves to individuals and groups in the area studied, and to this end we undertook engagement with publics including relevant societies and other organisations, and this engagement conintues. Crucially, the PI and Co-Is lead numerous other funded research projects and the findings and knowledge gained from this project help to set the context for and feed into each of those. The policy work of the PI in particular is informed by broad historical contexts and knowledge about the implementation of and response to technological change provided by work on this project is vital in this regard.limited. We did, however, identify groups of beneficiaries and we have worked to engage with these audiences to discuss our findings and to broaden knowledge and cultural understanding, and this work is outlined below. In particular we were keen to discuss our findings with rural historians, focusing on but not restricting ourselves to individuals and groups in the area studied, and to this end we undertook engagement with publics including relevant societies and other organisations, and this engagement conintues. Crucially, the PI and Co-Is lead numerous other funded research projects and the findings and knowledge gained from this project help to set the context for and feed into each of those. The policy work of the PI in particular is informed by broad historical contexts and knowledge about the implementation of and response to technological change provided by work on this project is vital in this regard. The work on the Exeter archives was concerned with the collection of Farm Management Survey fieldbooks. Data on outputs, inputs and capital items were entered from farms that had remained in the survey for a significant period – generally over 20 years – and these were then processed to provide estimates of changes over time in output in relation to various inputs, the level of specialisation, use of machinery etc. The analysis of the total dataset provided 4,978 individual annual entries of information covering 168 different farm holdings (a mean of 29.6 years per farm) spread over Devon, Cornwall and Dorset. Further information on the annual FMS (now the Farm Business Survey, FBS), the aims and objectives of this research and associated oral history interviews are available via the attached Related resources.

This dataset contains raw, unprocessed data files pertaining to the management tool group focused on 'Customer Experience Management' (CEM) and 'Customer Relationship Management' (CRM), including related concepts like Customer Satisfaction Surveys and Measurement. The data originates from five distinct sources, each reflecting different facets of the tool's prominence and usage over time. Files preserve the original metrics and temporal granularity before any comparative normalization or harmonization. Data Sources & File Details: Google Trends File (Prefix: GT_): Metric: Relative Search Interest (RSI) Index (0-100 scale). Keywords Used: "customer relationship management" + "customer experience management" + "customer satisfaction" Time Period: January 2004 - January 2025 (Native Monthly Resolution). Scope: Global Web Search, broad categorization. Extraction Date: Data extracted January 2025. Notes: Index relative to peak interest within the period for these terms. Reflects public/professional search interest trends. Based on probabilistic sampling. Source URL: Google Trends Query Google Books Ngram Viewer File (Prefix: GB_): Metric: Annual Relative Frequency (% of total n-grams in the corpus). Keywords Used: Customer Relationship Management+Customer Experience Management+Customer Satisfaction Measurement+Customer Satisfaction Time Period: 1950 - 2022 (Annual Resolution). Corpus: English. Parameters: Case Insensitive OFF, Smoothing 0. Extraction Date: Data extracted January 2025. Notes: Reflects term usage frequency in Google's digitized book corpus. Subject to corpus limitations (English bias, coverage). Source URL: Ngram Viewer Query Crossref.org File (Prefix: CR_): Metric: Absolute count of publications per month matching keywords. Keywords Used: ("customer relationship management" OR "customer experience management" OR "customer satisfaction" OR "customer satisfaction measurement" OR CRM) AND ("management" OR "strategy" OR "approach" OR "system" OR "implementation" OR "evaluation") Time Period: 1950 - 2025 (Queried for monthly counts based on publication date metadata). Search Fields: Title, Abstract. Extraction Date: Data extracted January 2025. Notes: Reflects volume of relevant academic publications indexed by Crossref. Deduplicated using DOIs; records without DOIs omitted. Source URL: Crossref Search Query Bain & Co. Survey - Usability File (Prefix: BU_): Metric: Original Percentage (%) of executives reporting tool usage. Tool Names/Years Included: Customer Satisfaction Surveys (1993); Customer Satisfaction (1996); Customer Satisfaction Measurement (1999, 2000); Customer Relationship Management (2002, 2006, 2008, 2010, 2012, 2017); CRM (2004, 2014); Customer Experience Management (2022). Respondent Profile: CEOs, CFOs, COOs, other senior leaders; global, multi-sector. Source: Bain & Company Management Tools & Trends publications (Rigby D., Bilodeau B., Ronan C. et al., various years: 1994, 2001, 2003, 2005, 2007, 2009, 2011, 2013, 2015, 2017, 2023). Data Compilation Period: July 2024 - January 2025. Notes: Data points correspond to specific survey years. Sample sizes: 1993/500; 1996/784; 1999/475; 2000/214; 2002/708; 2004/960; 2006/1221; 2008/1430; 2010/1230; 2012/1208; 2014/1067; 2017/1268; 2022/1068. Bain & Co. Survey - Satisfaction File (Prefix: BS_): Metric: Original Average Satisfaction Score (Scale 0-5). Tool Names/Years Included: Customer Satisfaction Surveys (1993); Customer Satisfaction (1996); Customer Satisfaction Measurement (1999, 2000); Customer Relationship Management (2002, 2006, 2008, 2010, 2012, 2017); CRM (2004, 2014); Customer Experience Management (2022). Respondent Profile: CEOs, CFOs, COOs, other senior leaders; global, multi-sector. Source: Bain & Company Management Tools & Trends publications (Rigby D., Bilodeau B., Ronan C. et al., various years: 1994, 2001, 2003, 2005, 2007, 2009, 2011, 2013, 2015, 2017, 2023). Data Compilation Period: July 2024 - January 2025. Notes: Data points correspond to specific survey years. Sample sizes: 1993/500; 1996/784; 1999/475; 2000/214; 2002/708; 2004/960; 2006/1221; 2008/1430; 2010/1230; 2012/1208; 2014/1067; 2017/1268; 2022/1068. Reflects subjective executive perception of utility. File Naming Convention: Files generally follow the pattern: PREFIX_Tool.csv, where the PREFIX indicates the data source: GT_: Google Trends GB_: Google Books Ngram CR_: Crossref.org (Count Data for this Raw Dataset) BU_: Bain & Company Survey (Usability) BS_: Bain & Company Survey (Satisfaction) The essential identification comes from the PREFIX and the Tool Name segment. This dataset resides within the 'Management Tool Source Data (Raw Extracts)' Dataverse.

Louth data ; The Department is awaiting 2015 Data to be confirmed by LA 12/8/16 Wicklow data; The Department is awaiting 2015 Data to be confirmed by LA 12/8/16 Data prior to 2014 is available on the website The most current data is published on these sheets. Previously published data may be subject to revision. Any change from the originally published data will be highlighted by a comment on the cell in question. These comments will be maintained for at least a year after the date of the value change.

The first Media Barometer was conducted in 1979 and since then the survey has been carried out annually. The purpose is to explore how the Swedish population is using different media during an average day. In 1997 the respondents were asked about their usage of different media equipment such as television, text-television, radio, video recorder, CD-player/record player, and tape recorder, the day before the interview. Respondents using any of these equipments were asked about time spent using the equipment. For equipment not used the day before the respondents were asked when it was last used. Television watchers and radio listeners were asked about which channels they had watched/listened to. Video watchers were asked if they watched a recorded program, a rented movie or a movie they had bought. All respondents were asked if the had been reading any of the following the day before: morning paper, evening paper, weekly magazine, comics or any other magazine, or book. If so, they were asked how many and for how long period. Book readers were also asked what kind of literature they were reading and paper and magazine readers were asked about what kind of paper/magazine they read. Those respondents who answered that they did not read any paper, magazine or book the day before were asked when they last did so. The survey also includes detailed information on at what time the day before the respondent spent time reading morning paper, evening paper, listening to the radio or watching television. There is also more detailed information on which news magazines the respondent watched. The respondents also had to state what kind of advertisments they had been reading/looking to during the last week. A number of questions dealt with computer usage at home, and the usage of Internet. Background variables includes information on age, gender, education, occupation, and household composition. Purpose: Describe the trends and changes in people's use of mass media. Mediebarometern genomfördes första gången 1979 och har sedan dess genomförts varje år. Undersökningen avser att belysa hur stor andel av den svenska befolkningen som en genomsnittlig dag tagit del av ett antal enskilda medier. Syftet är att beskriva tendenser och förändringar i människors utnyttjande av massmedier. Syfte: Beskriva tendenser och förändringar i människors nyttjande av massmedier. Totalt urval från DAFA/Spar omfattande 4200 personer. Icke använt överurval exkluderas från detta samt naturligt bortfall bestående av sjuka, ej kommunicerbara, ej svensktalande, utlandsboende och långvarigt bortresta varefter det egentliga urvalet uppgick till 3050 personer.Totalt urval från DAFA/Spar omfattande 4200 personer. Icke använt överurval exkluderas från detta samt naturligt bortfall bestående av sjuka, ej kommunicerbara, ej svensktalande, utlandsboende och långvarigt bortresta varefter det egentliga urvalet uppgick till 3050 personer.

The first Media Barometer was conducted in 1979 and since then the survey has been carried out annually. The purpose is to explore how the Swedish population is using different media during an average day. In 1992 the respondents were asked if they had been listening to a record player or a tape recorder the day before. If so, they were asked for how long period. Respondents answering that they did not listen to record player or tape recorder the day before were asked when they last did so. All respondents were asked if the had been reading any of the following the day before: morning paper, evening paper, weekly magazine, comics or any other magazine, or book. If so, they were asked how many and for how long period. Book readers were also asked if they were reading the books for their own pleasure or if it was study literature. Those respondents who answered that they did not read any paper, magazine or book the day before were asked when they last did so. Furthermore respondents were asked about their radio listening habits including which channel the respondent listened to and if he/she listened to their local radio station or any foreign radio station. Respondents answering that they did not listen to the radio the day before were asked when they last listened to the radio. There is also information on access to equipment such as remote control, text television, stereo television, video recorder, satellite television, or parabolic aerial. Other information deals with the respondent´s possibility to watch Danish, Finnish and Norvegian television channels as well as TV4, channel 5, or local television. Background variables includes information on age, gender, education, occupation, and household composition. Purpose: Describe the trends and changes in people's use of mass media. Mediebarometern genomfördes första gången 1979 och har sedan dess genomförts varje år. Undersökningen avser att belysa hur stor andel av den svenska befolkningen som en genomsnittlig dag tagit del av ett antal enskilda medier. Syftet är att beskriva tendenser och förändringar i människors utnyttjande av massmedier. Syfte: Beskriva tendenser och förändringar i människors nyttjande av massmedier.

This dataset includes a series of R scripts required to carry out some of the practical exercises in the book “Land Use Cover Datasets and Validation Tools”, available in open access.

The scripts have been designed within the context of the R Processing Provider, a plugin that integrates the R processing environment into QGIS. For all the information about how to use these scripts in QGIS, please refer to Chapter 1 of the book referred to above.

The dataset includes 15 different scripts, which can implement the calculation of different metrics in QGIS:

Change statistics such as absolute change, relative change and annual rate of change (Change_Statistics.rsx)

Areal and spatial agreement metrics, either overall (Overall Areal Inconsistency.rsx, Overall Spatial Agreement.rsx, Overall Spatial Inconsistency.rsx) or per category (Individual Areal Inconsistency.rsx, Individual Spatial Agreement.rsx)

The four components of change (gross gains, gross losses, net change and swap) proposed by Pontius Jr. (2004) (LUCCBudget.rsx)

The intensity analysis proposed by Aldwaik and Pontius (2012) (Intensity_analysis.rsx)

The Flow matrix proposed by Runfola and Pontius (2013) (Stable_change_flow_matrix.rsx, Flow_matrix_graf.rsx)

Pearson and Spearman correlations (Correlation.rsx)

The Receiver Operating Characteristic (ROC) (ROCAnalysis.rsx)

The Goodness of Fit (GOF) calculated using the MapCurves method proposed by Hargrove et al. (2006) (MapCurves_raster.rsx, MapCurves_vector.rsx)

The spatial distribution of overall, user and producer’s accuracies, obtained through Geographical Weighted Regression methods (Local accuracy assessment statistics.rsx).

Descriptions of all these methods can be found in different chapters of the aforementioned book.

The dataset also includes a readme file listing all the scripts provided, detailing their authors and the references on which their methods are based.

Redbook Index in the United States increased by 6.50 percent in the week ending August 23 of 2025 over the same week in the previous year. This dataset provides the latest reported value for - United States Redbook Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Each year, a group of experts gathers to assess the global state of happiness. The result, the World Happiness Report, is released on March 20, the International Day of Happiness.

This sounds like a positive thing, but, since 2005, overall happiness is decreasing while negative feelings like sadness and anger are on the rise. What’s worse is the trend of more young people experiencing mental illness, addictions, and their consequences. To an extent, this is understandable.

It’s tough to stay afloat mentally with everything going on in the world these days. No wonder we can crack at the slightest problem. But then we feel bad for not knowing how to handle it all and slip even deeper into unhappiness.

Dozens of books can help educate ourselves about happiness from a multitude of perspectives. We can take the view of science, of history, of philosophy, mindfulness, and spirituality.

Here is the top 33.