Table
Work with tables on Redivis
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Work with tables on Redivis
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Tables are the fundamental data-containing entity in Redivis. Tables belong to either a dataset or workflow, and are made up of rows and variables (columns). Various methods allow you to read table data, as well as to create / update / delete tables belonging to an unreleased version of a dataset.
Certain tables may be , which represent a collection of non-tabular files, where each row corresponds to a file. There are additional methods available on file index tables that allow for you to interface with these files.
Returns a list of Tables within a dataset
Returns a list of Tables within a workflow
dataset
workflow
properties
qualified_reference
For example,
scoped_reference
The canonical reference for the table, without any qualifiers. E.g., posts:7q4m
Reading data and metadata
Export a table in a particular format and download it to disk.
Download all files represented in a file index table to a local directory.
Check whether the table exists
Fetch table metadata. Once called, the properties
attribute on the table will be fully populated.
Deprecated. Please use to_[geo]pandas_dataframe instead.
Uploading and modifying data
Upload non-tabular files to an unreleased file index table.
Create a table within a dataset if it doesn't already exist. Table must belong to an unreleased version of the dataset.
Delete a table belonging to an unreleased version of a dataset.
Return a list of uploads on a table
Update properties on the table (name, description).
(table_reference)
Return a Table within the (either a dataset or workflow). In a Redivis notebook, the default scope will always be the notebook's workflow. If no default scope is specified, the table_reference must be fully qualified (see below).
table_reference
is a string that identifies the unique table. In some cases this may be the table name, though in others you'll want to include additional information to identify the table and to ensure reproducibility if the table name changes. Consult the documentation to learn more.
If you are operating within a Redivis notebook, you can specify "_source_"
as the table reference to automatically refer to the notebook's source table.
(table_reference)
Return a Table within a specific . The table_reference does not need to be fully qualified, since the table lookup is already scoped to a dataset. Consult the documentation to learn more.
(table_reference)
Return a Table within a specific . The table_reference does not need to be fully qualified, since the table lookup is already scoped to a workflow.
()
()
A reference to the instance that constructed this table. Will be None
if the table belongs to a workflow.
A reference to the instance that constructed this table. Will be None
if the table belongs to a dataset.
A dict containing the . This will only be populated after certain methods are called, particularly the get
method, and will otherwise be None
.
The to this table, for use (e.g.) in a SQL query.
([path, *, format, ...])
([path, *, overwrite, ...])
()
()
([max_results, *, ...])
Return a list of instances in a file index table.
([max_results, *, variables, ...])
Deprecated. Return a list of named tuples referencing the rows of the table. Use to_pydict() instead.
([max_results])
Return a list of instances associated with this table.
([...])
Return an iterator that yields , for processing the table's data in a memory-efficient streaming manner.
([max_results, ...])
Return a for the table. Data is backed by disk, allowing for larger-than-memory analysis.
([max_results, ...])
Return a with the table's data.
([max_results, ...])
([...])
Return a . For working with tables that contain a geography variable.
([max_results, ...])
Return a . Data is backed by disk, allowing for larger-than-memory analysis.
([max_results, ...])
Return a with the table's data.
([max_results])
Return a . Data is backed by disk, allowing for larger-than-memory analysis.
(name)
Reference a within the table.
(*, [files, directory])
([description, ...])
()
([max_results])
()
()
Create a reference to an on the table, which can subsequently be used to upload tabular data.