Accessing datasets with R using the AzureML R package

The AzureML R package enables access to your Azure Machine Learning datasets from a local R session and enables the creation and management of datasets in workspace.

This topic provides instructions on how to:

  • get your authorization codes to access Azure Machine Learning datasets from your notebook
  • access and upload datasets
  • access intermediate datasets from experiments
  • use the AzureML R package to enumerate datasets, access metadata, read the contents of a dataset, create new datasets and delete existing datasets

Use Studio Code snippets to access datasets

The R client library gives you programmatic access to your existing datasets from experiments that have been run.

From the Studio web interface, you can generate code snippets that include all the necessary information to download and deserialize datasets as Pandas DataFrame objects on your location machine.

Security for data access

The code snippets provided by Studio for use with the Python client library includes your workspace id and authorization token. These provide full access to your workspace and must be protected, like a password.

For security reasons, the code snippet functionality is only available to users that have their role set as Owner for the workspace. Your role is displayed in Azure Machine Learning Studio on the USERS page under Settings.

If your role is not set as Owner, you can either request to be re-invited as an owner, or ask the owner of the workspace to provide you with the code snippet.

To obtain the authorization token, you can do one of the following:

  • Ask for a token from an owner. Owners can access their authorization tokens from the Settings page of their workspace in Studio. Select Settings from the left pane and click on AUTHORIZATION TOKENS to see the primary and secondary tokens. Although either the primary or the secondary authorization tokens can be used in the code snippet, it is recommended that owners only share the secondary authorization tokens.

  • Ask to be promoted to role of owner. To do this, a current owner of the workspace needs to first remove you from the workspace then re-invite you to it as an owner.

*Once developers have obtained the workspace id and authorization token, they will be able to access the workspace using the code snippet regardless of their role.

Authorization tokens are managed on the AUTHORIZATION TOKENS page under SETTINGS. You can regenerate them, but this procedure will revoke access to the previous token.

Access datasets from a Notebook

  • In Machine Learning Studio, click on DATASETS in the navigation bar on the left.

  • Select the dataset you would like to access. You can select any of the datasets from the MY DATASETS list or from the SAMPLES list.

  • From the bottom toolbar, click on Generate Data Access Code. Note that this button will be disabled if the data is in a format incompatible with the Python client library.

  • Select the code snippet from the window that appears and copy it to your clipboard.

  • Paste the code into the notebook of your notebook.

In [1]:
library("AzureML")

dataset <- "Breast cancer data"

if(file.exists("~/.azureml/settings.json")){
    ws <- workspace()
} else {
    # workspace_id <- ""
    # authorization_token <- ""
    ws <- workspace(workspace_id, authorization_token)
}
dat <- download.datasets(ws, dataset)


Warning message:
: package 'AzureML' was built under R version 3.2.3

In [2]:
head(dat)


Out[2]:
Classagemenopausetumor-sizeinv-nodesnode-capsdeg-maligbreastbreast-quadirradiat
10511121311
205445710321
30311122311
40688134371
50411321311
61810108710971

Access intermediate datasets from Machine Learning experiments

After an experiment is run in the Machine Learning Studio, it is possible to access the intermediate datasets from the output nodes of modules. Intermediate datasets are data that has been created and used for intermediate steps when a model tool has been run.

Intermediate datasets can be accessed as long as the data format is compatible with the AzureML R package.

The following formats are supported (constants for these are in the azureml.DataTypeIds class):

  • PlainText
  • GenericCSV
  • GenericTSV
  • GenericCSVNoHeader
  • GenericTSVNoHeader

You can determine the format by hovering over a module output node. It is displayed along with the node name, in a tooltip.

Some of the modules, such as the Split module, output to a format named Dataset, which is not supported by the AzureML R package.

You'll need to use a conversion module, such as Convert to CSV, to get an output into a supported format.

The following steps show an example that creates an experiment, runs it and accesses the intermediate dataset.

  1. Create a new experiment.
  2. Insert an Adult Census Income Binary Classification dataset module.
  3. Insert a Split module, and connect its input to the dataset module output.
  4. Insert a Convert to CSV module and connect its input to one of the Split module outputs.
  5. Save the experiment, run it, and wait for it to finish running.
  6. Click on the output node on the Convert to CSV module.
  7. A context menu will appear, select Generate Data Access Code.
  8. A window will appear. Select the code snippet and copy it to your clipboard.
  9. Paste the code in your notebook.

In [3]:
#dat <- download.intermediate.dataset(
#  ws,
#  experiment = "dd01c7e4a424432c9a9f83142d5cfec4.f-id.00191edf9205484abff308cc624f7c24",
#  node_id = "1bc34767-d39e-472a-aea8-9f414dcbd144-79",
#  port_name = "Results dataset",
#  data_type_id = "GenericTSV"
#)

In [4]:
head(dat)


Out[4]:
Classagemenopausetumor-sizeinv-nodesnode-capsdeg-maligbreastbreast-quadirradiat
10511121311
205445710321
30311122311
40688134371
50411321311
61810108710971

You can visualize the data using the hist() function. This displays in a histogram for the age column:


In [5]:
options(repr.plot.width = 5, repr.plot.height = 5)
hist(dat$age, main = "age")


Use the AzureML R package to access, read, create, and manage datasets

Workspace

The workspace object contains your credentials for a specific AzureML environment.


In [6]:
library("AzureML")

dataset <- "Breast cancer data"

if(file.exists("~/.azureml/settings.json")){
    ws <- workspace()
} else {
    # workspace_id <- ""
    # authorization_token <- ""
    ws <- workspace(workspace_id, authorization_token)
}

List datasets

To enumerate all datasets in a given workspace:


In [7]:
datasets(ws)


Out[7]:
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58https://esintussouth001.blob.core.windows.net/?sv=2015-02-21&sr=b&sig=5J0yRdSaSIL4J9Ogf27Cr3rvilTeWMtQ02ZNDpWOJ5U%3D&st=2016-03-13T09%3A18%3A45Z&se=2016-03-14T09%3A23%3A45Z&sp=rhttps://esintussouth001.blob.core.windows.net/experimentoutput/6ccff2b1-f232-4451-9398-3091d69e5690/25afa776-8322-4f5d-8b5e-590fd57c2dba?sv=2015-02-21&sr=b&sig=wvg7I7ZohrEHU4Dr82R3ytDYQSN8CH9rrp33el00HGA%3D&st=2016-03-13T09%3A18%3A45Z&se=2016-03-14T09%3A23%3A45Z&sp=rComplete506153734175476c4f62416c57734963.e5c44c4642eb0e2981cf2778e32a7254.v1-default-460GenericTSVtestDataSource_d0a2ba648c204f9fb9c4ec2fd04791cfdatasourceDescriptione5c44c4642eb0e2981cf2778e32a7254b92deaa2e5e3409a93522003fe96156eFromResourceUpload<8b>NANA0FALSENAhttps://esintussouth001.blob.core.windows.net/uploadedresources/b92deaa2e5e3409a93522003fe96156e.tsv?sv=2015-02-21&sr=b&sig=IdKAkofkis%2B8zAk%2FTQbWemDfbDVRs6N8TRX%2BdqzwdMk%3D&st=2016-03-13T09%3A18%3A45Z&se=2016-03-14T09%3A23%3A45Z&sp=r&rscd=attachment%3B%20filename%3D%22testDataSource_d0a2ba648c204f9fb9c4ec2fd04791cf.tsv%22FALSEdefault4606.357067e+17

To list just the user-created datasets:


In [8]:
datasets(ws, filter = "my datasets")


Out[8]:
VisualizeEndPointSchemaEndPointSchemaStatusIdDataTypeIdNameDescriptionFamilyIdResourceUploadIdSourceOriginellip.hPromotedFromUploadedFromFilenameServiceVersionIsLatestCategoryDownloadLocationIsDeprecatedCultureBatchCreatedDateTicks
1https://esintussouthsus.blob.core.windows.net/?sv=2015-02-21&sr=b&sig=TlQHK0dXH3UY5pjzAActsPraoHkbshM03jwnuRiZZ6Y%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=rhttps://esintussouthsus.blob.core.windows.net/experimentoutput/a47473da-8d46-4c10-8fa5-90f0b1cf49b7/14f2ca51-3260-4889-880d-03f7fd70c9dc?sv=2015-02-21&sr=b&sig=LfV67rmFrR8vgL6iY62oSk0bbdV0FKIFRUKMlsLvFM4%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=rCompletea2aba0dafad8436788401bbc8c22fe36.8374d198487e485b91bd8e87abd6ff8b.v1-default-100GenericTSViris-testsample upload of iris8374d198487e485b91bd8e87abd6ff8b36fc94c1d9a0407bb23de6db7cac1fbbFromResourceUpload<8b>NA0FALSENAhttps://esintussouthsus.blob.core.windows.net/uploadedresources/C7FDC_a2aba0dafad8436788401bbc8c22fe36_36fc94c1d9a0407bb23de6db7cac1fbb.tsv?sv=2015-02-21&sr=b&sig=EGHt1UB%2F7DJD%2BDpK3bOFZkvzJ1GHStIG%2F9ngFuejNgk%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=r&rscd=attachment%3B%20filename%3D%22iris-test.tsv%22FALSEdefault1006.359018e+17
2https://esintussouthsus.blob.core.windows.net/?sv=2015-02-21&sr=b&sig=qY1UEu0uckb3TPppYRtoNxZ1A4nErH7o65eO8cs3Fms%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=rhttps://esintussouthsus.blob.core.windows.net/experimentoutput/b16124e2-36aa-46ac-8f4f-232ad25b964d/1a0c5c98-1467-4e84-a07e-db162057eece?sv=2015-02-21&sr=b&sig=fWbdIJyYHL022i4DZSp6cIkbwTqE%2BAPd6SeUcHY%2Bod0%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=rCompletea2aba0dafad8436788401bbc8c22fe36.3804d259587645c7a7784eea83f567c5.v1-default-101GenericTSViris-test-2sample upload of iris3804d259587645c7a7784eea83f567c56ef948258e3642898ec078ae3ef199ccFromResourceUpload<8b>NA0FALSENAhttps://esintussouthsus.blob.core.windows.net/uploadedresources/C7FDC_a2aba0dafad8436788401bbc8c22fe36_6ef948258e3642898ec078ae3ef199cc.tsv?sv=2015-02-21&sr=b&sig=io2kY6TcuvkmEwO7MMSYarVhaR7dSZW4ZcZ36DcDnDg%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=r&rscd=attachment%3B%20filename%3D%22iris-test-2.tsv%22FALSEdefault1016.359019e+17
3https://esintussouthsus.blob.core.windows.net/?sv=2015-02-21&sr=b&sig=dtunteYfRAx8WcJ7Yznf6wZ%2B%2BWFB9kcFCjDZwrV2nAY%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=rhttps://esintussouthsus.blob.core.windows.net/experimentoutput/aeae20ad-54cd-4845-9a8e-3d055eb801fb/c23a2cad-4251-4298-9fed-66429249e5a0?sv=2015-02-21&sr=b&sig=S1Z3RILzX%2FwB%2BbQjH6mSp%2Bh%2B%2FLR7E7BWqBHM3u%2Bg9O4%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=rCompletea2aba0dafad8436788401bbc8c22fe36.5abe1c7047ec425eb69789295426f25c.v1-default-102GenericTSVBugBash5abe1c7047ec425eb69789295426f25cd6fb128fceab4a82b57187b3b73ad57bFromResourceUpload<8b>NA0FALSENAhttps://esintussouthsus.blob.core.windows.net/uploadedresources/C7FDC_a2aba0dafad8436788401bbc8c22fe36_d6fb128fceab4a82b57187b3b73ad57b.tsv?sv=2015-02-21&sr=b&sig=AB%2BIaMQd9md2ws58dlQ%2BuSAtBDOaAZo1FTWeXhTg8tk%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=r&rscd=attachment%3B%20filename%3D%22BugBash.tsv%22FALSEdefault1026.359021e+17
4https://esintussouthsus.blob.core.windows.net/?sv=2015-02-21&sr=b&sig=pO5JebUbm1dHHSwS7A45xHCowqaoF0kq1XTj2MZRzYU%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=rhttps://esintussouthsus.blob.core.windows.net/experimentoutput/87928616-8487-4ca3-89f4-9bb20746b1bf/762f6e7f-2e35-4959-ac41-7b844b81aab0?sv=2015-02-21&sr=b&sig=H2t%2FeYy4y7qRVg5jmmojrb7Q68IKDK%2Bf1us7kXgwTVs%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=rCompletea2aba0dafad8436788401bbc8c22fe36.2ae2179497824f2b8160c989bb8e7b6c.v1-default-103GenericTSVmissingssample with missing data2ae2179497824f2b8160c989bb8e7b6c45808595b56a47f29c61af9308780012FromResourceUpload<8b>NA0FALSENAhttps://esintussouthsus.blob.core.windows.net/uploadedresources/C7FDC_a2aba0dafad8436788401bbc8c22fe36_45808595b56a47f29c61af9308780012.tsv?sv=2015-02-21&sr=b&sig=qExRsKuNWmd%2B45y3asf1DLnakI62TStT5Ql%2FlL9R6Ik%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=r&rscd=attachment%3B%20filename%3D%22missings.tsv%22FALSEdefault1036.359026e+17

To enumerate just the example datasets:


In [9]:
datasets(ws, filter = "sample")


Out[9]:
VisualizeEndPointSchemaEndPointSchemaStatusIdDataTypeIdNameDescriptionFamilyIdResourceUploadIdSourceOriginellip.hPromotedFromUploadedFromFilenameServiceVersionIsLatestCategoryDownloadLocationIsDeprecatedCultureBatchCreatedDateTicks
5NANANANANANotSupported506153734175476c4f62416c57734963.7bbb260f62084435bc0a39d085242d8a.v1-default-459Ziptext.preprocessing.zipUtility R script for text preprocessing to use with text classification template7bbb260f62084435bc0a39d085242d8a33293495a16a4237ae369ee97e922d9aFromResourceUpload<8b>NANA3TRUENAhttps://esintussouth001.blob.core.windows.net/uploadedresources/33293495a16a4237ae369ee97e922d9a.zip?sv=2015-02-21&sr=b&sig=ZxnuLnsiyEByhLjMk4ZFLrjTqWKJk5LdDdAlAhCeC9U%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=r&rscd=attachment%3B%20filename%3D%22text.preprocessing.zip%22FALSEdefault4596.356938e+17
6NANANANANANotSupported506153734175476c4f62416c57734963.b915384c130f4afbaf980bc414abcd4a.v1-default-458ZipfraudTemplateUtil.zipUtility R script to use with online fraud detection templateb915384c130f4afbaf980bc414abcd4aec235692917748de818f7a1a9e8c6effFromResourceUpload<8b>NANA3TRUENAhttps://esintussouth001.blob.core.windows.net/uploadedresources/ec235692917748de818f7a1a9e8c6eff.zip?sv=2015-02-21&sr=b&sig=53DufB8Drvrxom6ceL02Tt8aznx%2B66CuhocHszbbpOE%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=r&rscd=attachment%3B%20filename%3D%22fraudTemplateUtil.zip%22FALSEdefault4586.356938e+17
7https://esintussouth001.blob.core.windows.net/?sv=2015-02-21&sr=b&sig=1aJtE58qVMh7Cq7IkvYQv4ATGXu86PQk2azw%2BwhSxhw%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=rhttps://esintussouth001.blob.core.windows.net/experimentoutput/0b754310-aa4c-439f-90fc-0651aed47cf1/a4d1f673-4091-46b6-9542-696e5bb0bdfb?sv=2015-02-21&sr=b&sig=AU6qUel1uV6R8c0VbsOnsAl4jOF29tVv0nQzRJmY3eg%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=rComplete506153734175476c4f62416c57734963.f7a7a0f43b7b04d897ecc5e973d1fb98.v1-default-69GenericTSVtestDataSource_a5e9faf817084997981d094ef040389bdatasourceDescriptionf7a7a0f43b7b04d897ecc5e973d1fb989712c9702afe0675b081536050fd1deeFromResourceUpload<8b>NANA0FALSENAhttps://esintussouth001.blob.core.windows.net/uploadedresources/49d3bafa-10e3-4dc7-9073-f3415a8f0635/49d3bafa-10e3-4dc7-9073-f3415a8f0635.tsv?sv=2015-02-21&sr=b&sig=RIpCNHtE%2BL1X%2Be1pd8a0YHXvG%2FpRAPyWuBtfA9W4M4A%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=r&rscd=attachment%3B%20filename%3D%22testDataSource_a5e9faf817084997981d094ef040389b.tsv%22FALSEdefault696.355073e+17
8https://esintussouth001.blob.core.windows.net/?sv=2015-02-21&sr=b&sig=71Oq%2BQNEd0sp5tHIfkjR7UNuc6BmYzWB5FVNb2xRT%2BU%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=rhttps://esintussouth001.blob.core.windows.net/experimentoutput/28c94894-ce9f-48b2-bb7e-9629028d2c82/56ba3726-ce26-4ace-bd9e-1fa312df9f97?sv=2015-02-21&sr=b&sig=BokWldS2grBIkMtrSiviB6t9idru3MIPPe6sCA%2BtdJk%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=rComplete506153734175476c4f62416c57734963.6f71bb7d80d6017ab9d1a9c500675299.v1-default-70GenericTSVMetaAnalytics.Test.GlobalDataset.IntegerTSVFileGlobal TSV test file6f71bb7d80d6017ab9d1a9c500675299b567075a9d1905cc9d82a3f16db827eaFromResourceUpload<8b>NANA0FALSENAhttps://esintussouth001.blob.core.windows.net/uploadedresources/55e91c8c-4201-4195-baad-d3b151d49cb4/55e91c8c-4201-4195-baad-d3b151d49cb4.tsv?sv=2015-02-21&sr=b&sig=QiZcPqTBWlP0acwpUD6vMKeFV8g0spxFSOKmciiAlkA%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=r&rscd=attachment%3B%20filename%3D%22MetaAnalytics.Test.GlobalDataset.IntegerTSVFile.tsv%22FALSEdefault706.355079e+17
9https://esintussouth001.blob.core.windows.net/?sv=2015-02-21&sr=b&sig=6GEOQAd8yMBQ8zQoaYCWBa%2B%2Fo%2BS1Bbfa8gGQPpkHnwc%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=rhttps://esintussouth001.blob.core.windows.net/experimentoutput/38bbf6dd-5c83-490b-95ee-6e3b2fcd4b08/aa7de936-fe52-45ce-99e6-1fbd0a1c8919?sv=2015-02-21&sr=b&sig=jGmAGu65Vr0rxqlj7mtKUlaYl5rgVuhngvI3dh%2FKgcs%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=rComplete506153734175476c4f62416c57734963.416ede55ec48040a80973784c6c76d76.v1-default-71GenericCSVMetaAnalytics.Test.GlobalDataset.IntegerCSVFileGlobal CSV test file416ede55ec48040a80973784c6c76d763a2f9ea4fc730b809e00a2e0fd6afb78FromResourceUpload<8b>NANA0FALSENAhttps://esintussouth001.blob.core.windows.net/uploadedresources/7f0ecd0b-cd82-4979-80a0-a38ef4bc5fcd/7f0ecd0b-cd82-4979-80a0-a38ef4bc5fcd.csv?sv=2015-02-21&sr=b&sig=DDmFTqgqI7FM2ETy5XAi8COWtkcnS4vodBuIcFz2MWs%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=r&rscd=attachment%3B%20filename%3D%22MetaAnalytics.Test.GlobalDataset.IntegerCSVFile.csv%22FALSEdefault716.355079e+17
10https://esintussouth001.blob.core.windows.net/?sv=2015-02-21&sr=b&sig=%2BcJkarnbdXLNWIK8PozSI1Z8VMOKJZFm1JTV2xaBg7U%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=rhttps://esintussouth001.blob.core.windows.net/experimentoutput/445375dc-af52-4e40-a8d6-696ef5036cd4/a2c63723-bf7c-4a46-804b-93a49d857604?sv=2015-02-21&sr=b&sig=TIV%2BQjgzTIT8O5lkydoSNWfUxeKeWBaDQTmb%2ByUo6PM%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=rComplete506153734175476c4f62416c57734963.208d213c5cf2065687874d8133f93a4e.v1-default-76GenericTSVtestDataSource_65885ed31a854d70962a02d5641d3c92datasourceDescription208d213c5cf2065687874d8133f93a4e55fcf4ef2d6b04479a47a8c45ab8db92FromResourceUpload<8b>NANA0FALSENAhttps://esintussouth001.blob.core.windows.net/uploadedresources/b27fddab-a102-4943-9856-3927e75d87e5/b27fddab-a102-4943-9856-3927e75d87e5.tsv?sv=2015-02-21&sr=b&sig=JJYYGGrN4SHiJgSOow1OxqM3tI5EuDkQhORYfhNgpU0%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=r&rscd=attachment%3B%20filename%3D%22testDataSource_65885ed31a854d70962a02d5641d3c92.tsv%22FALSEdefault766.355079e+17
11https://esintussouth001.blob.core.windows.net/?sv=2015-02-21&sr=b&sig=yhIahRSLAK88q357ftg8VhYZvuaXdj%2BBdxc0427op6M%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=rhttps://esintussouth001.blob.core.windows.net/experimentoutput/11ceddd7-ec0f-4e94-8bd6-3e4c6fed4352/f59d2497-5dd7-40ae-9422-abae999a2d22?sv=2015-02-21&sr=b&sig=N3UXuI4FzckpknUXYJNTSmdKY9%2F03FlQQa1QUQA0Cbs%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=rComplete506153734175476c4f62416c57734963.f2e09c6e4d8f03eab27acbfcae942abc.v1-default-81GenericTSVtestDataSource_b9934ad1356e4f1d969565bfc24ee01bdatasourceDescriptionf2e09c6e4d8f03eab27acbfcae942abc51891688fa060a188ced78d3db9ae2aeFromResourceUpload<8b>NANA0FALSENAhttps://esintussouth001.blob.core.windows.net/uploadedresources/6d7cc85a-6655-4835-993d-b5b61cd3e7c4/6d7cc85a-6655-4835-993d-b5b61cd3e7c4.tsv?sv=2015-02-21&sr=b&sig=gyfh%2FVjGHk%2B83vSmH5iDbtdnKlcLaCGkQMLFazFEqFg%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=r&rscd=attachment%3B%20filename%3D%22testDataSource_b9934ad1356e4f1d969565bfc24ee01b.tsv%22FALSEdefault816.355089e+17
12https://esintussouth001.blob.core.windows.net/?sv=2015-02-21&sr=b&sig=3Og%2FxdeX89AwBMjQJT%2B7TKNntG%2BaFIMcAdGjI29yX68%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=rhttps://esintussouth001.blob.core.windows.net/experimentoutput/9c49a011-51c9-47a4-be62-ea44aa9ef059/1a8c4671-c968-4e9f-9e30-de31651f61b1?sv=2015-02-21&sr=b&sig=wj2yp5LnJUt9q3YAe90x0suwe9qbCzclP%2BOM%2FI%2Fvkok%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=rComplete506153734175476c4f62416c57734963.3d9e998d77aa08d8a9a86cff2225e67e.v1-default-86GenericTSVtestDataSource_dc2c925cb44147b0a5e98a6c44a369fedatasourceDescription3d9e998d77aa08d8a9a86cff2225e67e1bae69b6e03a0edc807fc04414319e69FromResourceUpload<8b>NANA0FALSENAhttps://esintussouth001.blob.core.windows.net/uploadedresources/2b2a626c-6df8-4eed-98a7-65c6966fc09c/2b2a626c-6df8-4eed-98a7-65c6966fc09c.tsv?sv=2015-02-21&sr=b&sig=rjlGi8lrmIBH7gKODd1f0Htcqyr54erf8JjOu1sN9CQ%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=r&rscd=attachment%3B%20filename%3D%22testDataSource_dc2c925cb44147b0a5e98a6c44a369fe.tsv%22FALSEdefault866.35509e+17
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54https://esintussouth001.blob.core.windows.net/?sv=2015-02-21&sr=b&sig=e4%2FljbnhpQHbaUQKUIQCJvtOSKglTZqQFWCL%2FFZRW7M%3D&st=2016-03-13T09%3A18%3A45Z&se=2016-03-14T09%3A23%3A45Z&sp=rhttps://esintussouth001.blob.core.windows.net/experimentoutput/28bebf5b-0936-4926-812c-86f4dc30e93a/b4d93812-3276-4967-8e81-526b2c4dd685?sv=2015-02-21&sr=b&sig=wpyJIzcqvRcP3BLvw5GnkzJ7PN4XZrMh%2FbTvcolT75M%3D&st=2016-03-13T09%3A18%3A45Z&se=2016-03-14T09%3A23%3A45Z&sp=rComplete506153734175476c4f62416c57734963.6dee1fc8d44141c9ad41e46ad94b85b3.v1-default-454GenericTSVNoHeaderNamed Entity Recognition Sample ArticlesNamed Entity Recognition Sample Articles6dee1fc8d44141c9ad41e46ad94b85b36de7f795fb3a48fdbd4c34efb9c01037FromResourceUpload<8b>NANA9FALSENAhttps://esintussouth001.blob.core.windows.net/uploadedresources/6de7f795fb3a48fdbd4c34efb9c01037.nh.tsv?sv=2015-02-21&sr=b&sig=3n8Xt99I%2FdFIqPWApfdkrv%2BRlSo4BdxFfEcmuAoE8Y8%3D&st=2016-03-13T09%3A18%3A45Z&se=2016-03-14T09%3A23%3A45Z&sp=r&rscd=attachment%3B%20filename%3D%22Named%20Entity%20Recognition%20Sample%20Articles.tsv%22FALSEdefault4546.356938e+17
55https://esintussouth001.blob.core.windows.net/?sv=2015-02-21&sr=b&sig=HhmbS1SQJCwUdnw10T94yGTFACxgc6BmInGUmQJpl2A%3D&st=2016-03-13T09%3A18%3A45Z&se=2016-03-14T09%3A23%3A45Z&sp=rhttps://esintussouth001.blob.core.windows.net/experimentoutput/e197c93d-174c-4cfa-850f-191237fc592d/ba18a730-cfd4-4355-af39-1ea2c5a6c725?sv=2015-02-21&sr=b&sig=pMT5qDGB8L4RIX%2BZGw0Fgs5%2F%2F9IsM3zfPN%2B%2Fmexv6TM%3D&st=2016-03-13T09%3A18%3A45Z&se=2016-03-14T09%3A23%3A45Z&sp=rComplete506153734175476c4f62416c57734963.0c5234182a844ce4a201bb9ad6739cf6.v1-default-455GenericTSVNoHeaderBook Reviews from AmazonBook Reviews from Amazon0c5234182a844ce4a201bb9ad6739cf60106630011c6446aafde512514e4f21fFromResourceUpload<8b>NANA9FALSENAhttps://esintussouth001.blob.core.windows.net/uploadedresources/0106630011c6446aafde512514e4f21f.nh.tsv?sv=2015-02-21&sr=b&sig=8b2glWOLnEFWsufRp2Z%2BeG%2BORLG9W8Q4W0Mxwok8T2Q%3D&st=2016-03-13T09%3A18%3A45Z&se=2016-03-14T09%3A23%3A45Z&sp=r&rscd=attachment%3B%20filename%3D%22Book%20Reviews%20from%20Amazon.tsv%22FALSEdefault4556.356938e+17
56https://esintussouth001.blob.core.windows.net/?sv=2015-02-21&sr=b&sig=8ZeOzwAuZ1kq5j5BA9aTkfcWJtdLikH3YvjxbYKDSiw%3D&st=2016-03-13T09%3A18%3A45Z&se=2016-03-14T09%3A23%3A45Z&sp=rhttps://esintussouth001.blob.core.windows.net/experimentoutput/05b498ec-3e0e-456b-aa11-3c7d3d1957bc/a96498cf-6ef1-4006-9d40-77e7dece8676?sv=2015-02-21&sr=b&sig=CB5c8rvGzHAeCvnnblnGVZK6DZJSeYUkIYbgtRjS7c0%3D&st=2016-03-13T09%3A18%3A45Z&se=2016-03-14T09%3A23%3A45Z&sp=rComplete506153734175476c4f62416c57734963.896db14734324ce084481451363389f8.v1-default-456GenericTSVMNIST Test 10k 28x28 denseMNIST Test data896db14734324ce084481451363389f8cb63b5ce35374b54ba11bbbe5d696996FromResourceUpload<8b>NANA6FALSENAhttps://esintussouth001.blob.core.windows.net/uploadedresources/cb63b5ce35374b54ba11bbbe5d696996.tsv?sv=2015-02-21&sr=b&sig=Rju1%2BmLXsmFo2%2FZupfNHceKsd2ErPs75FnZsz9GoxVI%3D&st=2016-03-13T09%3A18%3A45Z&se=2016-03-14T09%3A23%3A45Z&sp=r&rscd=attachment%3B%20filename%3D%22MNIST%20Test%2010k%2028x28%20dense.tsv%22FALSEdefault4566.356938e+17
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A dataset object is a data.frame, where each row contains the metadata for a specific dataset inside AzureML.


In [10]:
ds <- datasets(ws)
ds[ds$Name == "Blood donation data", ]


Out[10]:
VisualizeEndPointSchemaEndPointSchemaStatusIdDataTypeIdNameDescriptionFamilyIdResourceUploadIdSourceOriginellip.hPromotedFromUploadedFromFilenameServiceVersionIsLatestCategoryDownloadLocationIsDeprecatedCultureBatchCreatedDateTicks
29https://esintussouth001.blob.core.windows.net/?sv=2015-02-21&sr=b&sig=TBdq3%2BCaOymu%2BJptkFpV97whg0tDRPlUX2YhVYhITu0%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=rhttps://esintussouth001.blob.core.windows.net/experimentoutput/abb189b0-6226-4a78-b88b-60f2d81ad9e9/cacaa16d-9464-4a66-8428-d1184130fd5c?sv=2015-02-21&sr=b&sig=mhOd81V1y9ZFtzfbuIFnGMsVvTlmsar6HmamHqzWd2k%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=rComplete506153734175476c4f62416c57734963.7e3ffd95222a0c3698ec559ec9e596eb.v1-default-429GenericCSVBlood donation dataBlood donor data taken from the Blood Transfusion Service Center7e3ffd95222a0c3698ec559ec9e596eb58e87a776266491ab0a29e663c4ebc1aFromResourceUpload<8b>NANA9FALSENAhttps://esintussouth001.blob.core.windows.net/uploadedresources/58e87a776266491ab0a29e663c4ebc1a.csv?sv=2015-02-21&sr=b&sig=d6GAftrcmN8PNlZd2OPFvIZUo%2F3SF9dzDZi1%2FUrZe8g%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=r&rscd=attachment%3B%20filename%3D%22Blood%20donation%20data.csv%22FALSEdefault4296.356938e+17

Or you can access it by index:


In [11]:
ds[5, ]


Out[11]:
VisualizeEndPointSchemaEndPointSchemaStatusIdDataTypeIdNameDescriptionFamilyIdResourceUploadIdSourceOriginellip.hPromotedFromUploadedFromFilenameServiceVersionIsLatestCategoryDownloadLocationIsDeprecatedCultureBatchCreatedDateTicks
5NANANANANANotSupported506153734175476c4f62416c57734963.7bbb260f62084435bc0a39d085242d8a.v1-default-459Ziptext.preprocessing.zipUtility R script for text preprocessing to use with text classification template7bbb260f62084435bc0a39d085242d8a33293495a16a4237ae369ee97e922d9aFromResourceUpload<8b>NANA3TRUENAhttps://esintussouth001.blob.core.windows.net/uploadedresources/33293495a16a4237ae369ee97e922d9a.zip?sv=2015-02-21&sr=b&sig=ZxnuLnsiyEByhLjMk4ZFLrjTqWKJk5LdDdAlAhCeC9U%3D&st=2016-03-13T09%3A18%3A44Z&se=2016-03-14T09%3A23%3A44Z&sp=r&rscd=attachment%3B%20filename%3D%22text.preprocessing.zip%22FALSEdefault4596.356938e+17

Metadata

Datasets have metadata, in addition to content. (Intermediate datasets are an exception to this rule and do not have any metadata.)

The datasets object contains all of this data as a data frame


In [12]:
names(ds)


Out[12]:
  1. "VisualizeEndPoint"
  2. "SchemaEndPoint"
  3. "SchemaStatus"
  4. "Id"
  5. "DataTypeId"
  6. "Name"
  7. "Description"
  8. "FamilyId"
  9. "ResourceUploadId"
  10. "SourceOrigin"
  11. "Size"
  12. "CreatedDate"
  13. "Owner"
  14. "ExperimentId"
  15. "ClientVersion"
  16. "PromotedFrom"
  17. "UploadedFromFilename"
  18. "ServiceVersion"
  19. "IsLatest"
  20. "Category"
  21. "DownloadLocation"
  22. "IsDeprecated"
  23. "Culture"
  24. "Batch"
  25. "CreatedDateTicks"

In [13]:
ds$Name


Out[13]:
  1. "iris-test"
  2. "iris-test-2"
  3. "BugBash"
  4. "missings"
  5. "text.preprocessing.zip"
  6. "fraudTemplateUtil.zip"
  7. "testDataSource_a5e9faf817084997981d094ef040389b"
  8. "MetaAnalytics.Test.GlobalDataset.IntegerTSVFile"
  9. "MetaAnalytics.Test.GlobalDataset.IntegerCSVFile"
  10. "testDataSource_65885ed31a854d70962a02d5641d3c92"
  11. "testDataSource_b9934ad1356e4f1d969565bfc24ee01b"
  12. "testDataSource_dc2c925cb44147b0a5e98a6c44a369fe"
  13. "Adult Census Income Binary Classification dataset 100KB dataset for perf testing"
  14. "Adult Census Income Binary Classification dataset 500KB dataset for perf testing"
  15. "Adult Census Income Binary Classification dataset 1MB dataset for perf testing"
  16. "Adult Census Income Binary Classification dataset 5MB dataset for perf testing"
  17. "Adult Census Income Binary Classification dataset 10MB dataset for perf testing"
  18. "Adult Census Income Binary Classification dataset 50MB dataset for perf testing"
  19. "Adult Census Income Binary Classification dataset 100MB dataset for perf testing"
  20. "Adult Census Income Binary Classification dataset 200MB dataset for perf testing"
  21. "Adult Census Income Binary Classification dataset 500MB dataset for perf testing"
  22. "Breast cancer data"
  23. "Forest fires data"
  24. "Iris Two Class Data"
  25. "Adult Census Income Binary Classification dataset"
  26. "Steel Annealing multi-class dataset"
  27. "Automobile price data (Raw)"
  28. "MPG data for various automobiles"
  29. "Blood donation data"
  30. "Energy Efficiency Regression data"
  31. "Flight on-time performance (Raw)"
  32. "Pima Indians Diabetes Binary Classification dataset"
  33. "Telescope data"
  34. "Restaurant customer data"
  35. "Restaurant feature data"
  36. "Restaurant ratings"
  37. "Bike Rental UCI dataset"
  38. "Weather Dataset"
  39. "Airport Codes Dataset"
  40. "Flight Delays Data"
  41. "German Credit Card UCI dataset"
  42. "Bill Gates RGB Image"
  43. "Wikipedia SP 500 Dataset"
  44. "IMDB Movie Titles"
  45. "Movie Tweets"
  46. "Movie Ratings"
  47. "Time Series Dataset"
  48. "CRM Appetency Labels Shared"
  49. "CRM Churn Labels Shared"
  50. "CRM Upselling Labels Shared"
  51. "CRM Dataset Shared"
  52. "Breast Cancer Info"
  53. "Breast Cancer Features"
  54. "Named Entity Recognition Sample Articles"
  55. "Book Reviews from Amazon"
  56. "MNIST Test 10k 28x28 dense"
  57. "MNIST Train 60k 28x28 dense"
  58. "testDataSource_d0a2ba648c204f9fb9c4ec2fd04791cf"

Read contents

The code snippets provided by Machine Learning Studio automatically download and deserialize the dataset to a data.frame.

You can do this using the function download.datasets()


In [14]:
dat <- download.datasets(ws, "Breast cancer data")
head(dat)


Out[14]:
Classagemenopausetumor-sizeinv-nodesnode-capsdeg-maligbreastbreast-quadirradiat
10511121311
205445710321
30311122311
40688134371
50411321311
61810108710971

Create a new dataset

The AzureML package allows you to upload datasets directly from R to the Azure ML Studio. These datasets will be available for use in your workspace.


In [15]:
# Upload the R airquality data.frame to the workspace.
upload.dataset(airquality, ws, "temp-airquality-for-demo")

# Now see if this is in fact available
datasets(ws, filter = "my datasets")


Out[15]:
VisualizeEndPointSchemaEndPointSchemaStatusIdDataTypeIdNameDescriptionFamilyIdResourceUploadIdSourceOriginellip.hPromotedFromUploadedFromFilenameServiceVersionIsLatestCategoryDownloadLocationIsDeprecatedCultureBatchCreatedDateTicks
1NANANANANAPendinga2aba0dafad8436788401bbc8c22fe36.c088e101813e47b2a7e68e6d33c58655.v1-default-105GenericTSVtemp-airquality-for-democ088e101813e47b2a7e68e6d33c58655682ed28402f34435a076208cdb09be25FromResourceUpload<8b>NA0TRUENAhttps://esintussouthsus.blob.core.windows.net/uploadedresources/C7FDC_a2aba0dafad8436788401bbc8c22fe36_682ed28402f34435a076208cdb09be25.tsv?sv=2015-02-21&sr=b&sig=IjiKAdlIleKH3ZsHoZijXr8v7grYU6BO%2FAuaM4KEyAw%3D&st=2016-03-13T09%3A18%3A57Z&se=2016-03-14T09%3A23%3A57Z&sp=r&rscd=attachment%3B%20filename%3D%22temp-airquality-for-demo.tsv%22FALSEdefault1056.359346e+17
Out[15]:
VisualizeEndPointSchemaEndPointSchemaStatusIdDataTypeIdNameDescriptionFamilyIdResourceUploadIdSourceOriginellip.hPromotedFromUploadedFromFilenameServiceVersionIsLatestCategoryDownloadLocationIsDeprecatedCultureBatchCreatedDateTicks
1NANANANANAPendinga2aba0dafad8436788401bbc8c22fe36.c088e101813e47b2a7e68e6d33c58655.v1-default-105GenericTSVtemp-airquality-for-democ088e101813e47b2a7e68e6d33c58655682ed28402f34435a076208cdb09be25FromResourceUpload<8b>NA0TRUENAhttps://esintussouthsus.blob.core.windows.net/uploadedresources/C7FDC_a2aba0dafad8436788401bbc8c22fe36_682ed28402f34435a076208cdb09be25.tsv?sv=2015-02-21&sr=b&sig=IjiKAdlIleKH3ZsHoZijXr8v7grYU6BO%2FAuaM4KEyAw%3D&st=2016-03-13T09%3A18%3A57Z&se=2016-03-14T09%3A23%3A57Z&sp=r&rscd=attachment%3B%20filename%3D%22temp-airquality-for-demo.tsv%22FALSEdefault1056.359346e+17
2https://esintussouthsus.blob.core.windows.net/?sv=2015-02-21&sr=b&sig=JsceEoc%2BL%2BPt5X3WiB81om8cTEqfMoympz0FMzAgdNY%3D&st=2016-03-13T09%3A18%3A57Z&se=2016-03-14T09%3A23%3A57Z&sp=rhttps://esintussouthsus.blob.core.windows.net/experimentoutput/a47473da-8d46-4c10-8fa5-90f0b1cf49b7/14f2ca51-3260-4889-880d-03f7fd70c9dc?sv=2015-02-21&sr=b&sig=yO4PbWkjp5nrT%2BtQi5H4h%2Ba8TbJy0QfLwT%2FvtDplMG4%3D&st=2016-03-13T09%3A18%3A57Z&se=2016-03-14T09%3A23%3A57Z&sp=rCompletea2aba0dafad8436788401bbc8c22fe36.8374d198487e485b91bd8e87abd6ff8b.v1-default-100GenericTSViris-testsample upload of iris8374d198487e485b91bd8e87abd6ff8b36fc94c1d9a0407bb23de6db7cac1fbbFromResourceUpload<8b>NA0FALSENAhttps://esintussouthsus.blob.core.windows.net/uploadedresources/C7FDC_a2aba0dafad8436788401bbc8c22fe36_36fc94c1d9a0407bb23de6db7cac1fbb.tsv?sv=2015-02-21&sr=b&sig=0LDKkbpqQv3qeVgGtOa5rmc0Y2%2FKvhrkDfWVAqQ9AFE%3D&st=2016-03-13T09%3A18%3A57Z&se=2016-03-14T09%3A23%3A57Z&sp=r&rscd=attachment%3B%20filename%3D%22iris-test.tsv%22FALSEdefault1006.359018e+17
3https://esintussouthsus.blob.core.windows.net/?sv=2015-02-21&sr=b&sig=P4R6L4A2Bqope6g24s3LiHAVcbB7lcraN2uDgfFluE8%3D&st=2016-03-13T09%3A18%3A57Z&se=2016-03-14T09%3A23%3A57Z&sp=rhttps://esintussouthsus.blob.core.windows.net/experimentoutput/b16124e2-36aa-46ac-8f4f-232ad25b964d/1a0c5c98-1467-4e84-a07e-db162057eece?sv=2015-02-21&sr=b&sig=wR7Zupli0dsjtObGL0IMUAHbJA0jW5fXmFaQ2%2F2dlN0%3D&st=2016-03-13T09%3A18%3A57Z&se=2016-03-14T09%3A23%3A57Z&sp=rCompletea2aba0dafad8436788401bbc8c22fe36.3804d259587645c7a7784eea83f567c5.v1-default-101GenericTSViris-test-2sample upload of iris3804d259587645c7a7784eea83f567c56ef948258e3642898ec078ae3ef199ccFromResourceUpload<8b>NA0FALSENAhttps://esintussouthsus.blob.core.windows.net/uploadedresources/C7FDC_a2aba0dafad8436788401bbc8c22fe36_6ef948258e3642898ec078ae3ef199cc.tsv?sv=2015-02-21&sr=b&sig=4ztQt2hiOEexUi818p%2FPdhNT3FD%2FsMiouj4WmQKdVKw%3D&st=2016-03-13T09%3A18%3A57Z&se=2016-03-14T09%3A23%3A57Z&sp=r&rscd=attachment%3B%20filename%3D%22iris-test-2.tsv%22FALSEdefault1016.359019e+17
4https://esintussouthsus.blob.core.windows.net/?sv=2015-02-21&sr=b&sig=7FPpRIBz4JuDT0qPJN%2BHJoV%2B4eFyPwkXeRpMQFAgCcA%3D&st=2016-03-13T09%3A18%3A57Z&se=2016-03-14T09%3A23%3A57Z&sp=rhttps://esintussouthsus.blob.core.windows.net/experimentoutput/aeae20ad-54cd-4845-9a8e-3d055eb801fb/c23a2cad-4251-4298-9fed-66429249e5a0?sv=2015-02-21&sr=b&sig=yR4DDmunAwY4S2RNLVRDDXt9%2F5cPZoDI%2BKg2W4l6WKI%3D&st=2016-03-13T09%3A18%3A57Z&se=2016-03-14T09%3A23%3A57Z&sp=rCompletea2aba0dafad8436788401bbc8c22fe36.5abe1c7047ec425eb69789295426f25c.v1-default-102GenericTSVBugBash5abe1c7047ec425eb69789295426f25cd6fb128fceab4a82b57187b3b73ad57bFromResourceUpload<8b>NA0FALSENAhttps://esintussouthsus.blob.core.windows.net/uploadedresources/C7FDC_a2aba0dafad8436788401bbc8c22fe36_d6fb128fceab4a82b57187b3b73ad57b.tsv?sv=2015-02-21&sr=b&sig=4ztzwp%2BR0l8qWg6QhoBZ6OIGkcUAzZSaMiuv8watBbI%3D&st=2016-03-13T09%3A18%3A57Z&se=2016-03-14T09%3A23%3A57Z&sp=r&rscd=attachment%3B%20filename%3D%22BugBash.tsv%22FALSEdefault1026.359021e+17
5https://esintussouthsus.blob.core.windows.net/?sv=2015-02-21&sr=b&sig=xOOIK9kPYKEgYRvhDgpUUGl100t1kcNlEaaWhjb3Gc4%3D&st=2016-03-13T09%3A18%3A57Z&se=2016-03-14T09%3A23%3A57Z&sp=rhttps://esintussouthsus.blob.core.windows.net/experimentoutput/87928616-8487-4ca3-89f4-9bb20746b1bf/762f6e7f-2e35-4959-ac41-7b844b81aab0?sv=2015-02-21&sr=b&sig=ym7MgYq%2FzP%2Bo4dmlEHzCfP2krvEdYTe0o3JIBPXPVM4%3D&st=2016-03-13T09%3A18%3A57Z&se=2016-03-14T09%3A23%3A57Z&sp=rCompletea2aba0dafad8436788401bbc8c22fe36.2ae2179497824f2b8160c989bb8e7b6c.v1-default-103GenericTSVmissingssample with missing data2ae2179497824f2b8160c989bb8e7b6c45808595b56a47f29c61af9308780012FromResourceUpload<8b>NA0FALSENAhttps://esintussouthsus.blob.core.windows.net/uploadedresources/C7FDC_a2aba0dafad8436788401bbc8c22fe36_45808595b56a47f29c61af9308780012.tsv?sv=2015-02-21&sr=b&sig=3R70RU39PL0WV3Ss36i0q1%2F1zykQNbNYJfpAik4SNXw%3D&st=2016-03-13T09%3A18%3A57Z&se=2016-03-14T09%3A23%3A57Z&sp=r&rscd=attachment%3B%20filename%3D%22missings.tsv%22FALSEdefault1036.359026e+17

Deleting a dataset

You can delete a dataset using delete.datasets()


In [16]:
delete.datasets(ws, "temp-airquality-for-demo")


Out[16]:
NameDeletedstatus_code
1temp-airquality-for-demoTRUE204

Resources

The following links provide further info about Jupyter and AzureML:

Jupyter

AzureML R package

R Tools for Visual Studio

Help!

  • If you have any questions, issues, bugs (repro appreciated!), ... please send us an email
  • If you have examples, not ebooks, etc. that you'd like to add to our gallery, please let us know!

Thanks & enjoy!


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