Name: Multiple Machine Learning Datasets
Creator: Kaggle
License: https://opensource.org/licenses/MIT

About this Dataset

Multiple Machine Learning Datasets

Trending Public Datasets Overview

These Datasets contain a diverse collection of datasets intended for machine learning research and practice. Each dataset is curated to support different types of machine learning challenges, including classification, regression, and clustering. Below is a detailed list of the datasets available in this repository, along with descriptions and links to their sources.

Available Datasets

Iris Dataset

Description: This classic dataset includes measurements for 150 iris flowers from three different species. It includes four features: sepal length, sepal width, petal length, and petal width.
Source: Iris Dataset Source
Files: iris.csv

DHFR Dataset

Description: Contains data for 325 molecules with biological activity against the DHFR enzyme, relevant in anti-malarial drug research. It includes 228 molecular descriptors as features.
Source: DHFR Dataset Source
Files: dhfr.csv

Heart Disease Dataset (Cleveland)

Description: Comprises diagnostic measurements from 303 patients tested for heart disease at the Cleveland Clinic. It features 13 clinical attributes.
Source: UCI Machine Learning Repository
Files: heart-disease-cleveland.csv

HCV Data

Description: Detailed datasets related to Hepatitis C Virus (HCV) progression, with features for classification and regression tasks.
Files: HCV_NS5B_Curated.csv, hcv_classification.csv, hcv_regression.arff

NBA Seasons Stats

Description: Player statistics from the NBA 2020 and 2021 seasons for detailed sports analytics.
Files: NBA_2020.csv, NBA_2021.csv

Boston Housing Dataset

Description: Data concerning housing values in the suburbs of Boston, suitable for regression analysis.
Files: BostonHousing.csv, BostonHousing_train.csv, BostonHousing_test.csv

Acetylcholinesterase Inhibitor Bioactivity

Description: Chemical bioactivity data against acetylcholinesterase, a target relevant to Alzheimer's research. It includes raw and processed formats with chemical fingerprints.
Files: acetylcholinesterase_01_bioactivity_data_raw.csv to acetylcholinesterase_07_bioactivity_data_2class_pIC50_pubchem_fp.csv

California Housing Dataset

Description: Data aimed at predicting median house prices in California districts.
Files: california_housing_train.csv, california_housing_test.csv

Virtual Reality Experiences Data

Description: Data from user experiences with various virtual reality setups to study user engagement and satisfaction.
Files: Virtual Reality Experiences-data.csv

Fast-Food Chains in USA

Description: Overview of various fast-food chains operating in the USA, their locations, and popularity.
Files: Fast-Food Chains in USA.csv

Contributing
We welcome contributions to this dataset repository. If you have a dataset that you believe would be beneficial for the machine learning community, please see our contribution guidelines in CONTRIBUTING.md.

License
This dataset is available under the MIT License.

Tables

Acetylcholinesterase 01 Bioactivity Data Raw

@kaggle.ericamohadjei_trending_public_datasets.acetylcholinesterase_01_bioactivity_data_raw

520.09 kB
7,026 rows
43 columns

CREATE TABLE acetylcholinesterase_01_bioactivity_data_raw (
  "activity_comment" VARCHAR,
  "activity_id" BIGINT,
  "activity_properties" VARCHAR,
  "assay_chembl_id" VARCHAR,
  "assay_description" VARCHAR,
  "assay_type" VARCHAR,
  "bao_endpoint" VARCHAR,
  "bao_format" VARCHAR,
  "bao_label" VARCHAR,
  "canonical_smiles" VARCHAR,
  "data_validity_comment" VARCHAR,
  "data_validity_description" VARCHAR,
  "document_chembl_id" VARCHAR,
  "document_journal" VARCHAR,
  "document_year" DOUBLE,
  "ligand_efficiency" VARCHAR,
  "molecule_chembl_id" VARCHAR,
  "molecule_pref_name" VARCHAR,
  "parent_molecule_chembl_id" VARCHAR,
  "pchembl_value" DOUBLE,
  "potential_duplicate" BOOLEAN,
  "qudt_units" VARCHAR,
  "record_id" BIGINT,
  "relation" VARCHAR,
  "src_id" BIGINT,
  "standard_flag" BOOLEAN,
  "standard_relation" VARCHAR,
  "standard_text_value" VARCHAR,
  "standard_type" VARCHAR,
  "standard_units" VARCHAR,
  "standard_upper_value" VARCHAR,
  "standard_value" DOUBLE,
  "target_chembl_id" VARCHAR,
  "target_organism" VARCHAR,
  "target_pref_name" VARCHAR,
  "target_tax_id" BIGINT,
  "text_value" VARCHAR,
  "toid" VARCHAR,
  "type" VARCHAR,
  "units" VARCHAR,
  "uo_units" VARCHAR,
  "upper_value" DOUBLE,
  "value" DOUBLE
);

Acetylcholinesterase 02 Bioactivity Data Preprocessed

@kaggle.ericamohadjei_trending_public_datasets.acetylcholinesterase_02_bioactivity_data_preprocessed

141.93 kB
4,695 rows
3 columns

CREATE TABLE acetylcholinesterase_02_bioactivity_data_preprocessed (
  "molecule_chembl_id" VARCHAR,
  "canonical_smiles" VARCHAR,
  "standard_value" DOUBLE
);

Acetylcholinesterase 03 Bioactivity Data Curated

@kaggle.ericamohadjei_trending_public_datasets.acetylcholinesterase_03_bioactivity_data_curated

143.65 kB
4,695 rows
4 columns

CREATE TABLE acetylcholinesterase_03_bioactivity_data_curated (
  "molecule_chembl_id" VARCHAR,
  "canonical_smiles" VARCHAR,
  "standard_value" DOUBLE,
  "class" VARCHAR
);

Acetylcholinesterase 04 Bioactivity Data 3class Pic50

@kaggle.ericamohadjei_trending_public_datasets.acetylcholinesterase_04_bioactivity_data_3class_pic50

247.53 kB
4,695 rows
9 columns

CREATE TABLE acetylcholinesterase_04_bioactivity_data_3class_pic50 (
  "unnamed_0" BIGINT  -- Unnamed: 0,
  "molecule_chembl_id" VARCHAR,
  "canonical_smiles" VARCHAR,
  "class" VARCHAR,
  "mw" DOUBLE,
  "logp" DOUBLE,
  "numhdonors" DOUBLE,
  "numhacceptors" DOUBLE,
  "pic50" DOUBLE
);

Acetylcholinesterase 05 Bioactivity Data 2class Pic50

@kaggle.ericamohadjei_trending_public_datasets.acetylcholinesterase_05_bioactivity_data_2class_pic50

191.5 kB
3,549 rows
9 columns

CREATE TABLE acetylcholinesterase_05_bioactivity_data_2class_pic50 (
  "unnamed_0" BIGINT  -- Unnamed: 0,
  "molecule_chembl_id" VARCHAR,
  "canonical_smiles" VARCHAR,
  "class" VARCHAR,
  "mw" DOUBLE,
  "logp" DOUBLE,
  "numhdonors" DOUBLE,
  "numhacceptors" DOUBLE,
  "pic50" DOUBLE
);

Acetylcholinesterase 06 Bioactivity Data 3class Pic50, Ae45a880

@kaggle.ericamohadjei_trending_public_datasets.acetylcholinesterase_06_bioactivity_data_3class_pic50__ae45a880

812.72 kB
4,695 rows
882 columns

CREATE TABLE acetylcholinesterase_06_bioactivity_data_3class_pic50__ae45a880 (
  "pubchemfp0" BIGINT,
  "pubchemfp1" BIGINT,
  "pubchemfp2" BIGINT,
  "pubchemfp3" BIGINT,
  "pubchemfp4" BIGINT,
  "pubchemfp5" BIGINT,
  "pubchemfp6" BIGINT,
  "pubchemfp7" BIGINT,
  "pubchemfp8" BIGINT,
  "pubchemfp9" BIGINT,
  "pubchemfp10" BIGINT,
  "pubchemfp11" BIGINT,
  "pubchemfp12" BIGINT,
  "pubchemfp13" BIGINT,
  "pubchemfp14" BIGINT,
  "pubchemfp15" BIGINT,
  "pubchemfp16" BIGINT,
  "pubchemfp17" BIGINT,
  "pubchemfp18" BIGINT,
  "pubchemfp19" BIGINT,
  "pubchemfp20" BIGINT,
  "pubchemfp21" BIGINT,
  "pubchemfp22" BIGINT,
  "pubchemfp23" BIGINT,
  "pubchemfp24" BIGINT,
  "pubchemfp25" BIGINT,
  "pubchemfp26" BIGINT,
  "pubchemfp27" BIGINT,
  "pubchemfp28" BIGINT,
  "pubchemfp29" BIGINT,
  "pubchemfp30" BIGINT,
  "pubchemfp31" BIGINT,
  "pubchemfp32" BIGINT,
  "pubchemfp33" BIGINT,
  "pubchemfp34" BIGINT,
  "pubchemfp35" BIGINT,
  "pubchemfp36" BIGINT,
  "pubchemfp37" BIGINT,
  "pubchemfp38" BIGINT,
  "pubchemfp39" BIGINT,
  "pubchemfp40" BIGINT,
  "pubchemfp41" BIGINT,
  "pubchemfp42" BIGINT,
  "pubchemfp43" BIGINT,
  "pubchemfp44" BIGINT,
  "pubchemfp45" BIGINT,
  "pubchemfp46" BIGINT,
  "pubchemfp47" BIGINT,
  "pubchemfp48" BIGINT,
  "pubchemfp49" BIGINT,
  "pubchemfp50" BIGINT,
  "pubchemfp51" BIGINT,
  "pubchemfp52" BIGINT,
  "pubchemfp53" BIGINT,
  "pubchemfp54" BIGINT,
  "pubchemfp55" BIGINT,
  "pubchemfp56" BIGINT,
  "pubchemfp57" BIGINT,
  "pubchemfp58" BIGINT,
  "pubchemfp59" BIGINT,
  "pubchemfp60" BIGINT,
  "pubchemfp61" BIGINT,
  "pubchemfp62" BIGINT,
  "pubchemfp63" BIGINT,
  "pubchemfp64" BIGINT,
  "pubchemfp65" BIGINT,
  "pubchemfp66" BIGINT,
  "pubchemfp67" BIGINT,
  "pubchemfp68" BIGINT,
  "pubchemfp69" BIGINT,
  "pubchemfp70" BIGINT,
  "pubchemfp71" BIGINT,
  "pubchemfp72" BIGINT,
  "pubchemfp73" BIGINT,
  "pubchemfp74" BIGINT,
  "pubchemfp75" BIGINT,
  "pubchemfp76" BIGINT,
  "pubchemfp77" BIGINT,
  "pubchemfp78" BIGINT,
  "pubchemfp79" BIGINT,
  "pubchemfp80" BIGINT,
  "pubchemfp81" BIGINT,
  "pubchemfp82" BIGINT,
  "pubchemfp83" BIGINT,
  "pubchemfp84" BIGINT,
  "pubchemfp85" BIGINT,
  "pubchemfp86" BIGINT,
  "pubchemfp87" BIGINT,
  "pubchemfp88" BIGINT,
  "pubchemfp89" BIGINT,
  "pubchemfp90" BIGINT,
  "pubchemfp91" BIGINT,
  "pubchemfp92" BIGINT,
  "pubchemfp93" BIGINT,
  "pubchemfp94" BIGINT,
  "pubchemfp95" BIGINT,
  "pubchemfp96" BIGINT,
  "pubchemfp97" BIGINT,
  "pubchemfp98" BIGINT,
  "pubchemfp99" BIGINT
);

Acetylcholinesterase 07 Bioactivity Data 2class Pic50, E1902878

@kaggle.ericamohadjei_trending_public_datasets.acetylcholinesterase_07_bioactivity_data_2class_pic50__e1902878

775.72 kB
3,549 rows
882 columns

CREATE TABLE acetylcholinesterase_07_bioactivity_data_2class_pic50__e1902878 (
  "pubchemfp0" BIGINT,
  "pubchemfp1" BIGINT,
  "pubchemfp2" BIGINT,
  "pubchemfp3" BIGINT,
  "pubchemfp4" BIGINT,
  "pubchemfp5" BIGINT,
  "pubchemfp6" BIGINT,
  "pubchemfp7" BIGINT,
  "pubchemfp8" BIGINT,
  "pubchemfp9" BIGINT,
  "pubchemfp10" BIGINT,
  "pubchemfp11" BIGINT,
  "pubchemfp12" BIGINT,
  "pubchemfp13" BIGINT,
  "pubchemfp14" BIGINT,
  "pubchemfp15" BIGINT,
  "pubchemfp16" BIGINT,
  "pubchemfp17" BIGINT,
  "pubchemfp18" BIGINT,
  "pubchemfp19" BIGINT,
  "pubchemfp20" BIGINT,
  "pubchemfp21" BIGINT,
  "pubchemfp22" BIGINT,
  "pubchemfp23" BIGINT,
  "pubchemfp24" BIGINT,
  "pubchemfp25" BIGINT,
  "pubchemfp26" BIGINT,
  "pubchemfp27" BIGINT,
  "pubchemfp28" BIGINT,
  "pubchemfp29" BIGINT,
  "pubchemfp30" BIGINT,
  "pubchemfp31" BIGINT,
  "pubchemfp32" BIGINT,
  "pubchemfp33" BIGINT,
  "pubchemfp34" BIGINT,
  "pubchemfp35" BIGINT,
  "pubchemfp36" BIGINT,
  "pubchemfp37" BIGINT,
  "pubchemfp38" BIGINT,
  "pubchemfp39" BIGINT,
  "pubchemfp40" BIGINT,
  "pubchemfp41" BIGINT,
  "pubchemfp42" BIGINT,
  "pubchemfp43" BIGINT,
  "pubchemfp44" BIGINT,
  "pubchemfp45" BIGINT,
  "pubchemfp46" BIGINT,
  "pubchemfp47" BIGINT,
  "pubchemfp48" BIGINT,
  "pubchemfp49" BIGINT,
  "pubchemfp50" BIGINT,
  "pubchemfp51" BIGINT,
  "pubchemfp52" BIGINT,
  "pubchemfp53" BIGINT,
  "pubchemfp54" BIGINT,
  "pubchemfp55" BIGINT,
  "pubchemfp56" BIGINT,
  "pubchemfp57" BIGINT,
  "pubchemfp58" BIGINT,
  "pubchemfp59" BIGINT,
  "pubchemfp60" BIGINT,
  "pubchemfp61" BIGINT,
  "pubchemfp62" BIGINT,
  "pubchemfp63" BIGINT,
  "pubchemfp64" BIGINT,
  "pubchemfp65" BIGINT,
  "pubchemfp66" BIGINT,
  "pubchemfp67" BIGINT,
  "pubchemfp68" BIGINT,
  "pubchemfp69" BIGINT,
  "pubchemfp70" BIGINT,
  "pubchemfp71" BIGINT,
  "pubchemfp72" BIGINT,
  "pubchemfp73" BIGINT,
  "pubchemfp74" BIGINT,
  "pubchemfp75" BIGINT,
  "pubchemfp76" BIGINT,
  "pubchemfp77" BIGINT,
  "pubchemfp78" BIGINT,
  "pubchemfp79" BIGINT,
  "pubchemfp80" BIGINT,
  "pubchemfp81" BIGINT,
  "pubchemfp82" BIGINT,
  "pubchemfp83" BIGINT,
  "pubchemfp84" BIGINT,
  "pubchemfp85" BIGINT,
  "pubchemfp86" BIGINT,
  "pubchemfp87" BIGINT,
  "pubchemfp88" BIGINT,
  "pubchemfp89" BIGINT,
  "pubchemfp90" BIGINT,
  "pubchemfp91" BIGINT,
  "pubchemfp92" BIGINT,
  "pubchemfp93" BIGINT,
  "pubchemfp94" BIGINT,
  "pubchemfp95" BIGINT,
  "pubchemfp96" BIGINT,
  "pubchemfp97" BIGINT,
  "pubchemfp98" BIGINT,
  "pubchemfp99" BIGINT
);

Bostonhousing

@kaggle.ericamohadjei_trending_public_datasets.bostonhousing

32.26 kB
506 rows
14 columns

CREATE TABLE bostonhousing (
  "crim" DOUBLE,
  "zn" DOUBLE,
  "indus" DOUBLE,
  "chas" BIGINT,
  "nox" DOUBLE,
  "rm" DOUBLE,
  "age" DOUBLE,
  "dis" DOUBLE,
  "rad" BIGINT,
  "tax" BIGINT,
  "ptratio" DOUBLE,
  "b" DOUBLE,
  "lstat" DOUBLE,
  "medv" DOUBLE
);

Bostonhousing Test

@kaggle.ericamohadjei_trending_public_datasets.bostonhousing_test

15.57 kB
102 rows
14 columns

CREATE TABLE bostonhousing_test (
  "crim" DOUBLE,
  "zn" DOUBLE,
  "indus" DOUBLE,
  "chas" BIGINT,
  "nox" DOUBLE,
  "rm" DOUBLE,
  "age" DOUBLE,
  "dis" DOUBLE,
  "rad" BIGINT,
  "tax" BIGINT,
  "ptratio" DOUBLE,
  "b" DOUBLE,
  "lstat" DOUBLE,
  "medv" DOUBLE
);

Bostonhousing Train

@kaggle.ericamohadjei_trending_public_datasets.bostonhousing_train

29.18 kB
404 rows
14 columns

CREATE TABLE bostonhousing_train (
  "crim" DOUBLE,
  "zn" DOUBLE,
  "indus" DOUBLE,
  "chas" BIGINT,
  "nox" DOUBLE,
  "rm" DOUBLE,
  "age" DOUBLE,
  "dis" DOUBLE,
  "rad" BIGINT,
  "tax" BIGINT,
  "ptratio" DOUBLE,
  "b" DOUBLE,
  "lstat" DOUBLE,
  "medv" DOUBLE
);

California Housing Test

@kaggle.ericamohadjei_trending_public_datasets.california_housing_test

96.78 kB
3,000 rows
9 columns

CREATE TABLE california_housing_test (
  "longitude" DOUBLE,
  "latitude" DOUBLE,
  "housing_median_age" DOUBLE,
  "total_rooms" DOUBLE,
  "total_bedrooms" DOUBLE,
  "population" DOUBLE,
  "households" DOUBLE,
  "median_income" DOUBLE,
  "median_house_value" DOUBLE
);

California Housing Train

@kaggle.ericamohadjei_trending_public_datasets.california_housing_train

339.13 kB
17,000 rows
9 columns

CREATE TABLE california_housing_train (
  "longitude" DOUBLE,
  "latitude" DOUBLE,
  "housing_median_age" DOUBLE,
  "total_rooms" DOUBLE,
  "total_bedrooms" DOUBLE,
  "population" DOUBLE,
  "households" DOUBLE,
  "median_income" DOUBLE,
  "median_house_value" DOUBLE
);

Delaney

@kaggle.ericamohadjei_trending_public_datasets.delaney

42.01 kB
1,144 rows
4 columns

CREATE TABLE delaney (
  "compound_id" VARCHAR,
  "measured_log_solubility_mol_l" DOUBLE  -- Measured Log(solubility:mol/L),
  "esol_predicted_log_solubility_mol_l" DOUBLE  -- ESOL Predicted Log(solubility:mol/L),
  "smiles" VARCHAR
);

Delaney Solubility With Descriptors

@kaggle.ericamohadjei_trending_public_datasets.delaney_solubility_with_descriptors

26.73 kB
1,144 rows
5 columns

CREATE TABLE delaney_solubility_with_descriptors (
  "mollogp" DOUBLE,
  "molwt" DOUBLE,
  "numrotatablebonds" DOUBLE,
  "aromaticproportion" DOUBLE,
  "logs" DOUBLE
);

Descriptors Output

@kaggle.ericamohadjei_trending_public_datasets.descriptors_output

825.89 kB
4,695 rows
882 columns

CREATE TABLE descriptors_output (
  "name" VARCHAR,
  "pubchemfp0" BIGINT,
  "pubchemfp1" BIGINT,
  "pubchemfp2" BIGINT,
  "pubchemfp3" BIGINT,
  "pubchemfp4" BIGINT,
  "pubchemfp5" BIGINT,
  "pubchemfp6" BIGINT,
  "pubchemfp7" BIGINT,
  "pubchemfp8" BIGINT,
  "pubchemfp9" BIGINT,
  "pubchemfp10" BIGINT,
  "pubchemfp11" BIGINT,
  "pubchemfp12" BIGINT,
  "pubchemfp13" BIGINT,
  "pubchemfp14" BIGINT,
  "pubchemfp15" BIGINT,
  "pubchemfp16" BIGINT,
  "pubchemfp17" BIGINT,
  "pubchemfp18" BIGINT,
  "pubchemfp19" BIGINT,
  "pubchemfp20" BIGINT,
  "pubchemfp21" BIGINT,
  "pubchemfp22" BIGINT,
  "pubchemfp23" BIGINT,
  "pubchemfp24" BIGINT,
  "pubchemfp25" BIGINT,
  "pubchemfp26" BIGINT,
  "pubchemfp27" BIGINT,
  "pubchemfp28" BIGINT,
  "pubchemfp29" BIGINT,
  "pubchemfp30" BIGINT,
  "pubchemfp31" BIGINT,
  "pubchemfp32" BIGINT,
  "pubchemfp33" BIGINT,
  "pubchemfp34" BIGINT,
  "pubchemfp35" BIGINT,
  "pubchemfp36" BIGINT,
  "pubchemfp37" BIGINT,
  "pubchemfp38" BIGINT,
  "pubchemfp39" BIGINT,
  "pubchemfp40" BIGINT,
  "pubchemfp41" BIGINT,
  "pubchemfp42" BIGINT,
  "pubchemfp43" BIGINT,
  "pubchemfp44" BIGINT,
  "pubchemfp45" BIGINT,
  "pubchemfp46" BIGINT,
  "pubchemfp47" BIGINT,
  "pubchemfp48" BIGINT,
  "pubchemfp49" BIGINT,
  "pubchemfp50" BIGINT,
  "pubchemfp51" BIGINT,
  "pubchemfp52" BIGINT,
  "pubchemfp53" BIGINT,
  "pubchemfp54" BIGINT,
  "pubchemfp55" BIGINT,
  "pubchemfp56" BIGINT,
  "pubchemfp57" BIGINT,
  "pubchemfp58" BIGINT,
  "pubchemfp59" BIGINT,
  "pubchemfp60" BIGINT,
  "pubchemfp61" BIGINT,
  "pubchemfp62" BIGINT,
  "pubchemfp63" BIGINT,
  "pubchemfp64" BIGINT,
  "pubchemfp65" BIGINT,
  "pubchemfp66" BIGINT,
  "pubchemfp67" BIGINT,
  "pubchemfp68" BIGINT,
  "pubchemfp69" BIGINT,
  "pubchemfp70" BIGINT,
  "pubchemfp71" BIGINT,
  "pubchemfp72" BIGINT,
  "pubchemfp73" BIGINT,
  "pubchemfp74" BIGINT,
  "pubchemfp75" BIGINT,
  "pubchemfp76" BIGINT,
  "pubchemfp77" BIGINT,
  "pubchemfp78" BIGINT,
  "pubchemfp79" BIGINT,
  "pubchemfp80" BIGINT,
  "pubchemfp81" BIGINT,
  "pubchemfp82" BIGINT,
  "pubchemfp83" BIGINT,
  "pubchemfp84" BIGINT,
  "pubchemfp85" BIGINT,
  "pubchemfp86" BIGINT,
  "pubchemfp87" BIGINT,
  "pubchemfp88" BIGINT,
  "pubchemfp89" BIGINT,
  "pubchemfp90" BIGINT,
  "pubchemfp91" BIGINT,
  "pubchemfp92" BIGINT,
  "pubchemfp93" BIGINT,
  "pubchemfp94" BIGINT,
  "pubchemfp95" BIGINT,
  "pubchemfp96" BIGINT,
  "pubchemfp97" BIGINT,
  "pubchemfp98" BIGINT
);

Dhfr

@kaggle.ericamohadjei_trending_public_datasets.dhfr

437.03 kB
325 rows
229 columns

CREATE TABLE dhfr (
  "y" VARCHAR,
  "moegao_abra_l" DOUBLE,
  "moegao_abra_r" DOUBLE,
  "moegao_abra_acidity" DOUBLE,
  "moegao_abra_basicity" DOUBLE,
  "moegao_abra_pi" DOUBLE,
  "moe2d_bcut_peoe_0" DOUBLE,
  "moe2d_bcut_peoe_1" DOUBLE,
  "moe2d_bcut_peoe_2" DOUBLE,
  "moe2d_bcut_peoe_3" DOUBLE,
  "moe2d_bcut_slogp_0" DOUBLE,
  "moe2d_bcut_slogp_1" DOUBLE,
  "moe2d_bcut_slogp_2" DOUBLE,
  "moe2d_bcut_slogp_3" DOUBLE,
  "moe2d_bcut_smr_0" DOUBLE,
  "moe2d_bcut_smr_1" DOUBLE,
  "moe2d_bcut_smr_2" DOUBLE,
  "moe2d_bcut_smr_3" DOUBLE,
  "moe2d_fcharge" DOUBLE,
  "moe2d_gcut_peoe_0" DOUBLE,
  "moe2d_gcut_peoe_1" DOUBLE,
  "moe2d_gcut_peoe_2" DOUBLE,
  "moe2d_gcut_peoe_3" DOUBLE,
  "moe2d_gcut_slogp_0" DOUBLE,
  "moe2d_gcut_slogp_1" DOUBLE,
  "moe2d_gcut_slogp_2" DOUBLE,
  "moe2d_gcut_slogp_3" DOUBLE,
  "moe2d_gcut_smr_0" DOUBLE,
  "moe2d_gcut_smr_1" DOUBLE,
  "moe2d_gcut_smr_2" DOUBLE,
  "moe2d_gcut_smr_3" DOUBLE,
  "moe2d_kier1" DOUBLE,
  "moe2d_kier2" DOUBLE,
  "moe2d_kier3" DOUBLE,
  "moe2d_kiera1" DOUBLE,
  "moe2d_kiera2" DOUBLE,
  "moe2d_kiera3" DOUBLE,
  "moe2d_kierflex" DOUBLE,
  "moe2d_peoe_pc" DOUBLE  -- Moe2D PEOE PC.,
  "moe2d_peoe_pc_1" DOUBLE  -- Moe2D PEOE PC..1,
  "moe2d_peoe_rpc" DOUBLE  -- Moe2D PEOE RPC.,
  "moe2d_peoe_rpc_1" DOUBLE  -- Moe2D PEOE RPC..1,
  "moe2d_peoe_vsa_0" DOUBLE,
  "moe2d_peoe_vsa_1" DOUBLE,
  "moe2d_peoe_vsa_2" DOUBLE,
  "moe2d_peoe_vsa_3" DOUBLE,
  "moe2d_peoe_vsa_4" DOUBLE,
  "moe2d_peoe_vsa_5" DOUBLE,
  "moe2d_peoe_vsa_6" DOUBLE,
  "moe2d_peoe_vsa_0_1" DOUBLE,
  "moe2d_peoe_vsa_1_1" DOUBLE,
  "moe2d_peoe_vsa_2_1" DOUBLE,
  "moe2d_peoe_vsa_3_1" DOUBLE,
  "moe2d_peoe_vsa_4_1" DOUBLE,
  "moe2d_peoe_vsa_5_1" DOUBLE,
  "moe2d_peoe_vsa_6_1" DOUBLE,
  "moe2d_peoe_vsa_fhyd" DOUBLE,
  "moe2d_peoe_vsa_fneg" DOUBLE,
  "moe2d_peoe_vsa_fpneg" DOUBLE,
  "moe2d_peoe_vsa_fpol" DOUBLE,
  "moe2d_peoe_vsa_fpos" DOUBLE,
  "moe2d_peoe_vsa_fppos" DOUBLE,
  "moe2d_peoe_vsa_hyd" DOUBLE,
  "moe2d_peoe_vsa_neg" DOUBLE,
  "moe2d_peoe_vsa_pneg" DOUBLE,
  "moe2d_peoe_vsa_pol" DOUBLE,
  "moe2d_peoe_vsa_pos" DOUBLE,
  "moe2d_peoe_vsa_ppos" DOUBLE,
  "moe2d_q_pc" DOUBLE  -- Moe2D Q PC.,
  "moe2d_q_pc_1" DOUBLE  -- Moe2D Q PC..1,
  "moe2d_q_rpc" DOUBLE  -- Moe2D Q RPC.,
  "moe2d_q_rpc_1" DOUBLE  -- Moe2D Q RPC..1,
  "moe2d_q_vsa_fhyd" DOUBLE,
  "moe2d_q_vsa_fneg" DOUBLE,
  "moe2d_q_vsa_fpneg" DOUBLE,
  "moe2d_q_vsa_fpol" DOUBLE,
  "moe2d_q_vsa_fpos" DOUBLE,
  "moe2d_q_vsa_fppos" DOUBLE,
  "moe2d_q_vsa_hyd" DOUBLE,
  "moe2d_q_vsa_neg" DOUBLE,
  "moe2d_q_vsa_pneg" DOUBLE,
  "moe2d_q_vsa_pol" DOUBLE,
  "moe2d_q_vsa_pos" DOUBLE,
  "moe2d_q_vsa_ppos" DOUBLE,
  "moe2d_smr" DOUBLE,
  "moe2d_smr_vsa0" DOUBLE,
  "moe2d_smr_vsa1" DOUBLE,
  "moe2d_smr_vsa2" DOUBLE,
  "moe2d_smr_vsa3" DOUBLE,
  "moe2d_smr_vsa4" DOUBLE,
  "moe2d_smr_vsa5" DOUBLE,
  "moe2d_smr_vsa6" DOUBLE,
  "moe2d_smr_vsa7" DOUBLE,
  "moe2d_slogp" DOUBLE,
  "moe2d_slogp_vsa0" DOUBLE,
  "moe2d_slogp_vsa1" DOUBLE,
  "moe2d_slogp_vsa2" DOUBLE,
  "moe2d_slogp_vsa3" DOUBLE,
  "moe2d_slogp_vsa4" DOUBLE,
  "moe2d_slogp_vsa5" DOUBLE
);

Fast Food Chains In Usa

@kaggle.ericamohadjei_trending_public_datasets.fast_food_chains_in_usa

8.83 kB
50 rows
7 columns

CREATE TABLE fast_food_chains_in_usa (
  "fast_food_chains" VARCHAR,
  "u_s_systemwide_sales_millions_u_s_dollars" BIGINT  -- U.S. Systemwide Sales (Millions - U.S Dollars),
  "average_sales_per_unit_thousands_u_s_dollars" BIGINT  -- Average Sales Per Unit (Thousands - U.S Dollars),
  "franchised_stores" BIGINT,
  "company_stores" BIGINT,
  "n_2021_total_units" BIGINT  -- 2021 Total Units,
  "total_change_in_units_from_2020" BIGINT
);

Hcv Classification

@kaggle.ericamohadjei_trending_public_datasets.hcv_classification

652.7 kB
578 rows
882 columns

CREATE TABLE hcv_classification (
  "pubchemfp0" BIGINT,
  "pubchemfp1" BIGINT,
  "pubchemfp2" BIGINT,
  "pubchemfp3" BIGINT,
  "pubchemfp4" BIGINT,
  "pubchemfp5" BIGINT,
  "pubchemfp6" BIGINT,
  "pubchemfp7" BIGINT,
  "pubchemfp8" BIGINT,
  "pubchemfp9" BIGINT,
  "pubchemfp10" BIGINT,
  "pubchemfp11" BIGINT,
  "pubchemfp12" BIGINT,
  "pubchemfp13" BIGINT,
  "pubchemfp14" BIGINT,
  "pubchemfp15" BIGINT,
  "pubchemfp16" BIGINT,
  "pubchemfp17" BIGINT,
  "pubchemfp18" BIGINT,
  "pubchemfp19" BIGINT,
  "pubchemfp20" BIGINT,
  "pubchemfp21" BIGINT,
  "pubchemfp22" BIGINT,
  "pubchemfp23" BIGINT,
  "pubchemfp24" BIGINT,
  "pubchemfp25" BIGINT,
  "pubchemfp26" BIGINT,
  "pubchemfp27" BIGINT,
  "pubchemfp28" BIGINT,
  "pubchemfp29" BIGINT,
  "pubchemfp30" BIGINT,
  "pubchemfp31" BIGINT,
  "pubchemfp32" BIGINT,
  "pubchemfp33" BIGINT,
  "pubchemfp34" BIGINT,
  "pubchemfp35" BIGINT,
  "pubchemfp36" BIGINT,
  "pubchemfp37" BIGINT,
  "pubchemfp38" BIGINT,
  "pubchemfp39" BIGINT,
  "pubchemfp40" BIGINT,
  "pubchemfp41" BIGINT,
  "pubchemfp42" BIGINT,
  "pubchemfp43" BIGINT,
  "pubchemfp44" BIGINT,
  "pubchemfp45" BIGINT,
  "pubchemfp46" BIGINT,
  "pubchemfp47" BIGINT,
  "pubchemfp48" BIGINT,
  "pubchemfp49" BIGINT,
  "pubchemfp50" BIGINT,
  "pubchemfp51" BIGINT,
  "pubchemfp52" BIGINT,
  "pubchemfp53" BIGINT,
  "pubchemfp54" BIGINT,
  "pubchemfp55" BIGINT,
  "pubchemfp56" BIGINT,
  "pubchemfp57" BIGINT,
  "pubchemfp58" BIGINT,
  "pubchemfp59" BIGINT,
  "pubchemfp60" BIGINT,
  "pubchemfp61" BIGINT,
  "pubchemfp62" BIGINT,
  "pubchemfp63" BIGINT,
  "pubchemfp64" BIGINT,
  "pubchemfp65" BIGINT,
  "pubchemfp66" BIGINT,
  "pubchemfp67" BIGINT,
  "pubchemfp68" BIGINT,
  "pubchemfp69" BIGINT,
  "pubchemfp70" BIGINT,
  "pubchemfp71" BIGINT,
  "pubchemfp72" BIGINT,
  "pubchemfp73" BIGINT,
  "pubchemfp74" BIGINT,
  "pubchemfp75" BIGINT,
  "pubchemfp76" BIGINT,
  "pubchemfp77" BIGINT,
  "pubchemfp78" BIGINT,
  "pubchemfp79" BIGINT,
  "pubchemfp80" BIGINT,
  "pubchemfp81" BIGINT,
  "pubchemfp82" BIGINT,
  "pubchemfp83" BIGINT,
  "pubchemfp84" BIGINT,
  "pubchemfp85" BIGINT,
  "pubchemfp86" BIGINT,
  "pubchemfp87" BIGINT,
  "pubchemfp88" BIGINT,
  "pubchemfp89" BIGINT,
  "pubchemfp90" BIGINT,
  "pubchemfp91" BIGINT,
  "pubchemfp92" BIGINT,
  "pubchemfp93" BIGINT,
  "pubchemfp94" BIGINT,
  "pubchemfp95" BIGINT,
  "pubchemfp96" BIGINT,
  "pubchemfp97" BIGINT,
  "pubchemfp98" BIGINT,
  "pubchemfp99" BIGINT
);

Hcv Descriptor

@kaggle.ericamohadjei_trending_public_datasets.hcv_descriptor

657.52 kB
578 rows
882 columns

CREATE TABLE hcv_descriptor (
  "name" VARCHAR,
  "pubchemfp0" BIGINT,
  "pubchemfp1" BIGINT,
  "pubchemfp2" BIGINT,
  "pubchemfp3" BIGINT,
  "pubchemfp4" BIGINT,
  "pubchemfp5" BIGINT,
  "pubchemfp6" BIGINT,
  "pubchemfp7" BIGINT,
  "pubchemfp8" BIGINT,
  "pubchemfp9" BIGINT,
  "pubchemfp10" BIGINT,
  "pubchemfp11" BIGINT,
  "pubchemfp12" BIGINT,
  "pubchemfp13" BIGINT,
  "pubchemfp14" BIGINT,
  "pubchemfp15" BIGINT,
  "pubchemfp16" BIGINT,
  "pubchemfp17" BIGINT,
  "pubchemfp18" BIGINT,
  "pubchemfp19" BIGINT,
  "pubchemfp20" BIGINT,
  "pubchemfp21" BIGINT,
  "pubchemfp22" BIGINT,
  "pubchemfp23" BIGINT,
  "pubchemfp24" BIGINT,
  "pubchemfp25" BIGINT,
  "pubchemfp26" BIGINT,
  "pubchemfp27" BIGINT,
  "pubchemfp28" BIGINT,
  "pubchemfp29" BIGINT,
  "pubchemfp30" BIGINT,
  "pubchemfp31" BIGINT,
  "pubchemfp32" BIGINT,
  "pubchemfp33" BIGINT,
  "pubchemfp34" BIGINT,
  "pubchemfp35" BIGINT,
  "pubchemfp36" BIGINT,
  "pubchemfp37" BIGINT,
  "pubchemfp38" BIGINT,
  "pubchemfp39" BIGINT,
  "pubchemfp40" BIGINT,
  "pubchemfp41" BIGINT,
  "pubchemfp42" BIGINT,
  "pubchemfp43" BIGINT,
  "pubchemfp44" BIGINT,
  "pubchemfp45" BIGINT,
  "pubchemfp46" BIGINT,
  "pubchemfp47" BIGINT,
  "pubchemfp48" BIGINT,
  "pubchemfp49" BIGINT,
  "pubchemfp50" BIGINT,
  "pubchemfp51" BIGINT,
  "pubchemfp52" BIGINT,
  "pubchemfp53" BIGINT,
  "pubchemfp54" BIGINT,
  "pubchemfp55" BIGINT,
  "pubchemfp56" BIGINT,
  "pubchemfp57" BIGINT,
  "pubchemfp58" BIGINT,
  "pubchemfp59" BIGINT,
  "pubchemfp60" BIGINT,
  "pubchemfp61" BIGINT,
  "pubchemfp62" BIGINT,
  "pubchemfp63" BIGINT,
  "pubchemfp64" BIGINT,
  "pubchemfp65" BIGINT,
  "pubchemfp66" BIGINT,
  "pubchemfp67" BIGINT,
  "pubchemfp68" BIGINT,
  "pubchemfp69" BIGINT,
  "pubchemfp70" BIGINT,
  "pubchemfp71" BIGINT,
  "pubchemfp72" BIGINT,
  "pubchemfp73" BIGINT,
  "pubchemfp74" BIGINT,
  "pubchemfp75" BIGINT,
  "pubchemfp76" BIGINT,
  "pubchemfp77" BIGINT,
  "pubchemfp78" BIGINT,
  "pubchemfp79" BIGINT,
  "pubchemfp80" BIGINT,
  "pubchemfp81" BIGINT,
  "pubchemfp82" BIGINT,
  "pubchemfp83" BIGINT,
  "pubchemfp84" BIGINT,
  "pubchemfp85" BIGINT,
  "pubchemfp86" BIGINT,
  "pubchemfp87" BIGINT,
  "pubchemfp88" BIGINT,
  "pubchemfp89" BIGINT,
  "pubchemfp90" BIGINT,
  "pubchemfp91" BIGINT,
  "pubchemfp92" BIGINT,
  "pubchemfp93" BIGINT,
  "pubchemfp94" BIGINT,
  "pubchemfp95" BIGINT,
  "pubchemfp96" BIGINT,
  "pubchemfp97" BIGINT,
  "pubchemfp98" BIGINT
);

Hcv Ns5b Curated

@kaggle.ericamohadjei_trending_public_datasets.hcv_ns5b_curated

48.9 kB
578 rows
23 columns

CREATE TABLE hcv_ns5b_curated (
  "cmpd_chemblid" VARCHAR,
  "canonical_smiles" VARCHAR,
  "standard_type" VARCHAR,
  "relation" VARCHAR,
  "standard_value" DOUBLE,
  "standard_units" VARCHAR,
  "pic50" DOUBLE,
  "protein_accession" VARCHAR,
  "pref_name" VARCHAR,
  "doc_chemblid" VARCHAR,
  "assay_src_description" VARCHAR,
  "description" VARCHAR,
  "pubmed_id" DOUBLE,
  "journal" VARCHAR,
  "year" BIGINT,
  "volume" DOUBLE,
  "issue" DOUBLE,
  "first_page" DOUBLE,
  "molweight" DOUBLE,
  "alogp" DOUBLE,
  "psa" DOUBLE,
  "num_ro5_violations" BIGINT,
  "activity" VARCHAR
);

Heart Disease Cleveland

@kaggle.ericamohadjei_trending_public_datasets.heart_disease_cleveland

13.5 kB
303 rows
14 columns

CREATE TABLE heart_disease_cleveland (
  "age" BIGINT,
  "n__sex" BIGINT  -- Sex,
  "n__cp" BIGINT  -- Cp,
  "n__trestbps" BIGINT  -- Trestbps,
  "n__chol" BIGINT  -- Chol,
  "n__fbs" BIGINT  -- Fbs,
  "n__restecg" BIGINT  -- Restecg,
  "n__thalach" BIGINT  -- Thalach,
  "n__exang" BIGINT  -- Exang,
  "n__oldpeak" DOUBLE  -- Oldpeak,
  "n__slope" BIGINT  -- Slope,
  "n__ca" VARCHAR  -- Ca,
  "n__thal" VARCHAR  -- Thal,
  "n__diagnosis" BIGINT  -- Diagnosis
);

Iris

@kaggle.ericamohadjei_trending_public_datasets.iris

5.26 kB
150 rows
5 columns

CREATE TABLE iris (
  "sepal_length" DOUBLE,
  "sepal_width" DOUBLE,
  "petal_length" DOUBLE,
  "petal_width" DOUBLE,
  "species" VARCHAR
);

Metabolic Syndrome Synthetic Data

@kaggle.ericamohadjei_trending_public_datasets.metabolic_syndrome_synthetic_data

40.29 kB
1,000 rows
7 columns

CREATE TABLE metabolic_syndrome_synthetic_data (
  "wc" DOUBLE,
  "tg" DOUBLE,
  "hdlc" DOUBLE,
  "sbp" DOUBLE,
  "dbp" DOUBLE,
  "fpg" DOUBLE,
  "sex" VARCHAR
);

Mushrooms

@kaggle.ericamohadjei_trending_public_datasets.mushrooms

60.63 kB
8,124 rows
23 columns

CREATE TABLE mushrooms (
  "class" VARCHAR,
  "cap_shape" VARCHAR,
  "cap_surface" VARCHAR,
  "cap_color" VARCHAR,
  "bruises" VARCHAR,
  "odor" VARCHAR,
  "gill_attachment" VARCHAR,
  "gill_spacing" VARCHAR,
  "gill_size" VARCHAR,
  "gill_color" VARCHAR,
  "stalk_shape" VARCHAR,
  "stalk_root" VARCHAR,
  "stalk_surface_above_ring" VARCHAR,
  "stalk_surface_below_ring" VARCHAR,
  "stalk_color_above_ring" VARCHAR,
  "stalk_color_below_ring" VARCHAR,
  "veil_type" VARCHAR,
  "veil_color" VARCHAR,
  "ring_number" VARCHAR,
  "ring_type" VARCHAR,
  "spore_print_color" VARCHAR,
  "population" VARCHAR,
  "habitat" VARCHAR
);

Nba 2020

@kaggle.ericamohadjei_trending_public_datasets.nba_2020

57.11 kB
651 rows
29 columns

CREATE TABLE nba_2020 (
  "player" VARCHAR,
  "pos" VARCHAR,
  "age" BIGINT,
  "tm" VARCHAR,
  "g" BIGINT,
  "gs" BIGINT,
  "mp" DOUBLE,
  "fg" DOUBLE,
  "fga" DOUBLE,
  "fg_51ab2d" DOUBLE  -- FG%,
  "n_3p" DOUBLE  -- 3P,
  "n_3pa" DOUBLE  -- 3PA,
  "n_3p_d87a85" DOUBLE  -- 3P%,
  "n_2p" DOUBLE  -- 2P,
  "n_2pa" DOUBLE  -- 2PA,
  "n_2p_c8658d" DOUBLE  -- 2P%,
  "efg" DOUBLE  -- EFG%,
  "ft" DOUBLE,
  "fta" DOUBLE,
  "ft_ba25d5" DOUBLE  -- FT%,
  "orb" DOUBLE,
  "drb" DOUBLE,
  "trb" DOUBLE,
  "ast" DOUBLE,
  "stl" DOUBLE,
  "blk" DOUBLE,
  "tov" DOUBLE,
  "pf" DOUBLE,
  "pts" DOUBLE
);