Now you can request additional data and/or customized columns!
Try It Now!Files | Size | Format | Created | Updated | License | Source |
---|---|---|---|---|---|---|
3 | 11MB | arff csv zip | 4 years ago | 4 years ago | Open Data Commons Public Domain Dedication and License |
The resources for this dataset can be found at https://www.openml.org/d/1116
Author:
Source: Unknown - Date unknown
Please cite:
Dataset from the MLRR repository: http://axon.cs.byu.edu:5000/
More infos: https://archive.ics.uci.edu/ml/datasets/Musk+(Version+2)
Download files in this dataset
File | Description | Size | Last changed | Download |
---|---|---|---|---|
musk_arff | 4MB | arff (4MB) | ||
musk | 4MB | csv (4MB) , json (16MB) | ||
musk_zip | Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. | 6MB | zip (6MB) |
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This is a preview version. There might be more data in the original version.
Field Name | Order | Type (Format) | Description |
---|---|---|---|
ID | 1 | number (default) | |
molecule_name | 2 | string (default) | |
conformation_name | 3 | string (default) | |
f1 | 4 | number (default) | |
f2 | 5 | number (default) | |
f3 | 6 | number (default) | |
f4 | 7 | number (default) | |
f5 | 8 | number (default) | |
f6 | 9 | number (default) | |
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f92 | 95 | number (default) | |
f93 | 96 | number (default) | |
f94 | 97 | number (default) | |
f95 | 98 | number (default) | |
f96 | 99 | number (default) | |
f97 | 100 | number (default) | |
f98 | 101 | number (default) | |
f99 | 102 | number (default) | |
f100 | 103 | number (default) | |
f101 | 104 | number (default) | |
f102 | 105 | number (default) | |
f103 | 106 | number (default) | |
f104 | 107 | number (default) | |
f105 | 108 | number (default) | |
f106 | 109 | number (default) | |
f107 | 110 | number (default) | |
f108 | 111 | number (default) | |
f109 | 112 | number (default) | |
f110 | 113 | number (default) | |
f111 | 114 | number (default) | |
f112 | 115 | number (default) | |
f113 | 116 | number (default) | |
f114 | 117 | number (default) | |
f115 | 118 | number (default) | |
f116 | 119 | number (default) | |
f117 | 120 | number (default) | |
f118 | 121 | number (default) | |
f119 | 122 | number (default) | |
f120 | 123 | number (default) | |
f121 | 124 | number (default) | |
f122 | 125 | number (default) | |
f123 | 126 | number (default) | |
f124 | 127 | number (default) | |
f125 | 128 | number (default) | |
f126 | 129 | number (default) | |
f127 | 130 | number (default) | |
f128 | 131 | number (default) | |
f129 | 132 | number (default) | |
f130 | 133 | number (default) | |
f131 | 134 | number (default) | |
f132 | 135 | number (default) | |
f133 | 136 | number (default) | |
f134 | 137 | number (default) | |
f135 | 138 | number (default) | |
f136 | 139 | number (default) | |
f137 | 140 | number (default) | |
f138 | 141 | number (default) | |
f139 | 142 | number (default) | |
f140 | 143 | number (default) | |
f141 | 144 | number (default) | |
f142 | 145 | number (default) | |
f143 | 146 | number (default) | |
f144 | 147 | number (default) | |
f145 | 148 | number (default) | |
f146 | 149 | number (default) | |
f147 | 150 | number (default) | |
f148 | 151 | number (default) | |
f149 | 152 | number (default) | |
f150 | 153 | number (default) | |
f151 | 154 | number (default) | |
f152 | 155 | number (default) | |
f153 | 156 | number (default) | |
f154 | 157 | number (default) | |
f155 | 158 | number (default) | |
f156 | 159 | number (default) | |
f157 | 160 | number (default) | |
f158 | 161 | number (default) | |
f159 | 162 | number (default) | |
f160 | 163 | number (default) | |
f161 | 164 | number (default) | |
f162 | 165 | number (default) | |
f163 | 166 | number (default) | |
f164 | 167 | number (default) | |
f165 | 168 | number (default) | |
f166 | 169 | number (default) | |
class | 170 | number (default) |
Use our data-cli tool designed for data wranglers:
data get https://datahub.io/machine-learning/musk
data info machine-learning/musk
tree machine-learning/musk
# Get a list of dataset's resources
curl -L -s https://datahub.io/machine-learning/musk/datapackage.json | grep path
# Get resources
curl -L https://datahub.io/machine-learning/musk/r/0.arff
curl -L https://datahub.io/machine-learning/musk/r/1.csv
curl -L https://datahub.io/machine-learning/musk/r/2.zip
If you are using R here's how to get the data you want quickly loaded:
install.packages("jsonlite", repos="https://cran.rstudio.com/")
library("jsonlite")
json_file <- 'https://datahub.io/machine-learning/musk/datapackage.json'
json_data <- fromJSON(paste(readLines(json_file), collapse=""))
# get list of all resources:
print(json_data$resources$name)
# print all tabular data(if exists any)
for(i in 1:length(json_data$resources$datahub$type)){
if(json_data$resources$datahub$type[i]=='derived/csv'){
path_to_file = json_data$resources$path[i]
data <- read.csv(url(path_to_file))
print(data)
}
}
Note: You might need to run the script with root permissions if you are running on Linux machine
Install the Frictionless Data data package library and the pandas itself:
pip install datapackage
pip install pandas
Now you can use the datapackage in the Pandas:
import datapackage
import pandas as pd
data_url = 'https://datahub.io/machine-learning/musk/datapackage.json'
# to load Data Package into storage
package = datapackage.Package(data_url)
# to load only tabular data
resources = package.resources
for resource in resources:
if resource.tabular:
data = pd.read_csv(resource.descriptor['path'])
print (data)
For Python, first install the `datapackage` library (all the datasets on DataHub are Data Packages):
pip install datapackage
To get Data Package into your Python environment, run following code:
from datapackage import Package
package = Package('https://datahub.io/machine-learning/musk/datapackage.json')
# print list of all resources:
print(package.resource_names)
# print processed tabular data (if exists any)
for resource in package.resources:
if resource.descriptor['datahub']['type'] == 'derived/csv':
print(resource.read())
If you are using JavaScript, please, follow instructions below:
Install data.js
module using npm
:
$ npm install data.js
Once the package is installed, use the following code snippet:
const {Dataset} = require('data.js')
const path = 'https://datahub.io/machine-learning/musk/datapackage.json'
// We're using self-invoking function here as we want to use async-await syntax:
;(async () => {
const dataset = await Dataset.load(path)
// get list of all resources:
for (const id in dataset.resources) {
console.log(dataset.resources[id]._descriptor.name)
}
// get all tabular data(if exists any)
for (const id in dataset.resources) {
if (dataset.resources[id]._descriptor.format === "csv") {
const file = dataset.resources[id]
// Get a raw stream
const stream = await file.stream()
// entire file as a buffer (be careful with large files!)
const buffer = await file.buffer
// print data
stream.pipe(process.stdout)
}
}
})()
The resources for this dataset can be found at https://www.openml.org/d/1116
Author:
Source: Unknown - Date unknown
Please cite:
Dataset from the MLRR repository: http://axon.cs.byu.edu:5000/
More infos: https://archive.ics.uci.edu/ml/datasets/Musk+(Version+2)
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