Dataset Summary

Mini(24 MB) Classification dataset for mini projects. Cats, dogs and rabbit are included as pet in this dataset.

  Supported Tasks and Leaderboards

image-classification: Based on a pet image, the goal of this task is to predict the type of pet (i.e., dog or cat or rabbit).

  Languages

English

  Class Label Mappings:

{ "cat": 0, "dog": 1, "rabbit": 2, }

  Load Dataset

from datasets import load_dataset

train_dataset =… See the full description on the dataset page: https://huggingface.co/datasets/rokmr/pets.

Volunteers in the US, UK, Australia, and NZ volunteered to strap GPS sensors on their pet cats. The aforelinked datasets include each cat’s characteristics (such as age, sex, neuter status, and hunting habits) and timestamped GPS pings Related: CatTracker Domestic cats (Felis catus) are a conservation concern because they kill billions of native prey each year, but without spatial context the ecological importance of pets as predators remains uncertain. We worked with citizen scientists to track 925 pet cats from six countries, finding remarkably small home ranges (3.6 ± 5.6 ha). Only three cats ranged > 1 km^2 and we found no relationship between home range size and the presence of larger native predators (i.e. coyotes, Canis latrans). Most (75%) cats used primarily (90%) disturbed habitats. Owners reported that their pets killed an average of 3.5 prey items/month, leading to an estimated ecological impact per cat of 14.2‐38.9 prey ha^−1 yr^−1. This is similar or higher than the per‐animal ecological impact of wild carnivores but the effect is amplified by the high density of cats in neighborhoods. As a result, pet cats around the world have an ecological impact greater than native predators but concentrated within ~100 m of their homes.

Works cited: Kays R, Dunn RR, Parsons AW, Mcdonald B, Perkins T, Powers S, Shell L, McDonald JL, Cole H, Kikillus H, Woods L, Tindle H, Roetman P (2020) The small home ranges and large local ecological impacts of pet cats. Animal Conservation. Roetman P, Tindle H (2020) Data from: The small home ranges and large local ecological impacts of pet cats [Australia]. Movebank Data Repository. doi:10.5441/001/1.289p5s77

Pet Health Symptoms Dataset

  Overview

This dataset contains 2,000 LLM-generated pet health symptoms text samples covering 5 common pet health condition categories, designed to train ML models for automated pet health classification. Each entry is labeled with:

Pet health condition (1 of 5 distinct classes)
Record type (Owner Observation or Clinical Notes)

Owner observations are expressed in everyday language (e.g., "My cat scratches constantly"), whereas clinical… See the full description on the dataset page: https://huggingface.co/datasets/karenwky/pet-health-symptoms-dataset.

PetSmart Inc., the American retail chain, accounted for almost a third of the pet store market, based on revenue in 2023. The pet store market is highly concentrated in the United States, with the two leading players, PetSmart and PETCO Animal Supplies, accounting for almost 40 percent of the total market revenue that year.

PetSmart origins

PetSmart, originally named PetFood Warehouse, was founded in 1986 when two stores were opened in Phoenix, Arizona. The company continued to grow and went public in 1993. In the 2021/22 fiscal year, PetSmart’s revenue reached close to 6.7 billion U.S. dollars.

Online pet retail

With the growth of the e-commerce market, came greater online sales numbers, a shift that is also visible in the household and pet care market. In 2020, around a fifth of all household and pet care sales worldwide were made online, which is double the share seen five years earlier. By 2025, nearly a third of this category’s sales are projected to be e-commerce sales. To buy pet products specifically, the most common e-commerce websites used by U.S. consumers were Amazon.com, Walmart.com, and Chewy.com.

Differential predation patterns of free-ranging cats among continents

https://doi.org/10.5061/dryad.hmgqnk9t4

Description of the data and file structure

Files and variables

File: probability_of_predation_by_species_xgboost.csv

Variables

• Scientific name
• Prediction predation status: mean value of the predicted probability of being depredated from xgboost predictions.
• Empirical record of predation: observed predation 1, no empirical record of predation 0.
• Taxon
• Continent

File: continental_mammal_prey_database.csv

Variables

• binomial: Scientific name
• Habitat: number of habitats found in IUCN data, 5 is 5 or >5.
• ln.Mass: Adult body mass in grams transformed into natural logarithm.
• Main.Diet: The main diet was characterized as the dominant type of food (>50%) consumed by the species: Herbivores, Invertebrates, Vertebrates and Carrions, Mixed carnivores, and omnivores.
• For.Niche: Thi...

Feline leukemia virus (FeLV) is a gammaretrovirus with horizontally transmitted and endogenous forms. Domestic cats are the primary reservoir species, but FeLV outbreaks in endangered Florida panthers and Iberian lynx have resulted in mortalities. To assess prevalence and interspecific/intraspecific transmission, we conducted an extensive survey and phylogenetic analysis of FeLV infection in free-ranging pumas (n=641), bobcats (n=212) and shelter domestic cats (n=304). Samples were collected from coincident habitats across the United States between 1985-2018. FeLV infection was detected in 3.12% puma, 6.25% domestic cat, and 0.47% bobcat samples analyzed. Puma prevalence varied by location, with Florida having the highest rate of infection. FeLV env sequences revealed variation among isolates, and we identified two distinct clades. Both progressive and regressive infections were identified in cats and pumas. Based upon time and location of sampling and phylogenetic analysis, we inferred 3 spillover events between domestic cats and puma; 3 puma-to-puma transmissions were inferred in Florida. An additional 14 infections in pumas likely represented spillover events following contact with reservoir host domestic cat populations. Our data provides evidence that FeLV transmission from domestic cats to pumas occurs widely across the US, and puma-to-puma transmission may occur in genetically and geographically constrained populations.

In summer 2020, SARS-CoV-2 was detected on mink farms in Utah. An interagency One Health response was initiated to assess the extent of the outbreak and included sampling animals from or near affected mink farms and testing them for SARS-CoV-2 and non-SARS coronaviruses. Among the 365 animals sampled, including domestic cats, mink, rodents, raccoons, and skunks, 261 (72%) of the animals harbored at least one coronavirus at the time. Among the samples which could be further characterized, 126 alphacoronaviruses and 88 betacoronaviruses (including 74 detections of SARS-CoV-2) were identified. Moreover, at least 10% (n=27) of the corona-virus-positive animals were found to be co-infected with more than one coronavirus. Our findings indicate an unexpectedly high prevalence of coronavirus among the domestic and wild animals tested on mink farms and raise the possibility that commercial animal husbandry operations could be potential hot spots for future trans-species viral spillover and the emergence of new pandemic coronaviruses. Figure 1. Phylogenetic relationships of the identified coronaviruses from mink and other animals from mink farms in Utah. The four genera of coronaviruses are highlighted in different colors. AlphaCoV, alkphacoronavirus; BetaCoV, betacoronavirus; DeltaCoV, deltacoronaviruses; and GammaCoV, gammacoronavirus. Type species for the currently recognized subgenera are annotated according to the nomenclature scheme used in this manuscript with the addition of the ICTV subgenus. Additional viruses, including the closest GenBank entry as identified by the BLAST tool, were included to help delineate relationship. Red circles are viruses identified in this study. Panel A. Full phylogenetic tree (A full-size image is included in Supplementary Figure 1). Red arrows designate the group of nearly identical Utah mink coronavirus strains collapsed into the colored triangle in Panel B. Table 1. Coronavirus distribution among species tested. The species are listed by their common names; Total, the total number of animals of each species tested; Negative, number of each species with no coronavirus detected among the tissues tested; Positive, number of animals positive for coronavirus in at least one tissue; % Pos, percentage of coronavirus positives in each species. Table 2. Detailed tissue panel tested for SARS-CoV-2. The distribution of SARS-CoV-2 RNA detection in the first 96 animals is listed. Tissue, tissue or tissue pools received; Total, total number tested in each category; Negative, number of N1 RT-PCR negatives; Posi-tives, number of N1 RT-PCR positives; % Pos, percentage of tissues positive for corona-virus. Table 3. Summary of coronaviruses identified. The distribution of coronaviruses detected and characterized according to their host is listed. Species, common name of animal species tested; AlphaCoV, number of alphacoronaviruses identified; BetaCoV, number of betacoronaviruses identified; Sequenced, number of viruses identified by sequencing, Unchar, number of coronavirus-positive samples not further characterized. Table 4. SARS-CoV-2 coinfections identified in Utah mammals. The individual animals that are both SARS-CoV-2 positive and infected with a second coronavirus are listed. Animal ID, Unique animal identification number; Common name, common name of animal; Scientific name, scientific name of animal; Sex, F, female, M, male. Unk, un-known; Age, A adult, J juvenile, Unk, unknown; SARS-CoV-2, Neg-N1 RT-PCR nega-tive, Pos-N1 RT-PCR positive, Second strain, genus and common name of the coronavirus, Pan-CoV RT-PCR Equivocal, sample is PCR positive but not further characterized. Supplementary Figure 1. Phylogenetic relationships of the identified coronaviruses from mink farms in Utah. The four genera of coronaviruses are highlighted in different colors. AlphaCoV, alkphacoronavirus; BetaCoV, betacoronavirus; DeltaCoV, deltacoronaviruses; and GammaCoV, gammacoronavirus. Type species for the currently recognized subgenera are annotated according to the nomenclature scheme used in this manuscript with the addition of the ICTV subgenus. Additional viruses, including the closest GenBank entry as identified by the BLAST tool were included to help delineate relationship. Red circles are viruses identified in this study. Supplementary Table 1. List of animals and tissues sampled and RT-PCR test results. Animal ID, unique identifier for each animal; Specimen ID, unique identifier for each tissue; Common name, common name of the animal species; Scientific name, scientific name of the animal species, Sex, F-female, M-male, UNK-unknown; Age, J-juvenile, A-adult, UNK-unknown; Tissue, organ or organ pools tested; Tissue study, X denotes the animals and tissues used in the tissue distribution sub-study; N1 PCR, Ct values from the CDC N1 assay; Pan-CoV PCR, Neg, negative, Pos, positive, Equiv, equivocal; * wild mink. Supplementary Table 2. Summary of coronavirus test results. Animal ID, unique identifier for each animal; Common name, common name of the animal species; Scientific name, scientific name of the animal species, Sex, F-female, M-male, UNK-unknown; Age, J-juvenile, A-adult, UNK-unknown; CoV, Neg-negative, Pos-positive on either one or both RT-PCR tests; SARS-CoV-2, animals positive in the CDC N1 test; AlphaCoV, the tissues positive for alphacoronavirus for each animal is listed; BetaCoV, the tissues positive for betacoronavirus for each animal is listed; C-colon, C/R-colon/rectum pool, H-heart, L-lung, L/S-live/spleen pool, S int-small intestine; Co-infections, Y-yes; PCR only, Y-yes; Virus identified by sequencing, brief name of virus identified.