# Dataset ## *class* Dataset Datasets on Redivis are the entity where data is stored. Datasets are made up of tables, non-tabular files, and various metadata. Datasets can be owned by a user or organization, and are version controlled. ## Constructors

Method	Description
`Organization.dataset`(dataset_reference)	Construct a new dataset instance that references a dataset owned by an organization.
`Organization.list_datasets`([max_results])	Returns a list of Datasets owned by an organization.
`User.dataset`(dataset_reference)	Construct a new dataset instance that references a dataset owned by a user.
`User.list_datasets`([max_results])	Returns a list of Datasets owned by a user.

## Examples {% tabs %} {% tab title="Basics" %} ```python dataset = redivis.organization("Demo").dataset("US Fires") # Will throw an error if the dataset doesn't exists # Can first call dataset.exists() to check for existence dataset.get() print(dataset.properties) ``` {% endtab %} {% tab title="Create" %} ```python dataset = redivis.user("my_username").dataset("My dataset") dataset.create(public_access_level="overview") print(dataset.properties) ``` {% endtab %} {% tab title="New version" %} ```python dataset = redivis.user("my_username").dataset("My dataset") dataset = dataset.create_next_version() # We can upload new data to existing tables once we have a "next" version with open("data.csv", "rb") as file: dataset.table("My table").upload("data.csv").upload_file(file) dataset.release() ``` {% endtab %} {% tab title="Query" %} ```python dataset = redivis.organization("Demo").dataset("CMS 2014 Medicare Data") # The home_health_agencies table is assumed to be within the dataset, # since it isn't otherwise qualified query = dataset.query(""" SELECT * FROM home_health_agencies WHERE state = 'CA' """) print(query.to_dataframe()) ``` {% endtab %} {% endtabs %} ## Attributes | **`organization`** | A reference to the [Organization](/api/client-libraries/redivis-python/reference/organization.md) instance that constructed this dataset. Will be `None` if the dataset belongs to a user. | | ------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **`properties`** |

A dict containing the API resource representation of the dataset. This will be fully populated after calling get(), create\_next\_version(), and release(), otherwise will be None.

This will also be partially populated for datasets returned via the Organization.list\_datasets and User.list\_datasets methods

| | **`qualified_reference`** | The [fully qualified reference](/api/referencing-resources.md) for the dataset, which can be used in SQL queries or the REST API. E.g., `demo.ghcn_daily_weather_data:v1_1:7br5` | | **`scoped_reference`** | The canonical reference for the dataset, without the username qualifier. E.g.,: `ghcn_daily_weather_data:v1_1:7br5` | | **`user`** | A reference to the [User](/api/client-libraries/redivis-python/reference/user.md) instance that constructed this dataset. Will be `None` if the dataset belongs to an organization. | ## Methods


`Dataset.add_labels`(labels)	Add labels to a dataset.
`Dataset.create`([*, public_access_level, ...])	Create a new dataset.
`Dataset.create_next_version`([*, if_not_exists])	Create a "next" (unreleased) version on the dataset. Data can only be uploaded to unreleased versions.
`Dataset.delete`()	Delete the dataset.
`Dataset.exists`()	Check whether the dataset exists.
`Dataset.get`()	Get the dataset, populating the `properties` attribute on the current instance.
`Dataset.list_tables`([max_results])	List all tables in the dataset.
`Dataset.list_versions`([max_results])	List all versions for the dataset.
`Dataset.next_version`()	Return a reference to the dataset at the version subsequent to the currently referenced version.
`Dataset.previous_version`()	Return a reference to the dataset at the version prior to the currently referenced version.
`Dataset.query`(query_string)	Create a query scoped to the dataset.
`Dataset.release`()	Release the `next` version of the dataset.
`Dataset.remove_labels`()	Remove labels from a dataset.
`Dataset.table`(table_reference)	Create a reference to a specific table within the dataset.
`Dataset.unrelease`()	Unrelease the current version of the dataset, moving it back to an unreleased, "next" version.
`Dataset.update`([*, name, public_access_level, ...])	Update certain attributes on the dataset.
`Dataset.update_variables`(variables)	Batch update variable metadata across tables in a dataset.
`Dataset.version`([tag])	Create a reference to a version instance at a particular tag.

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