Table

(columns=None, data=None, rows=None, dataframe=None, dtype=None, optional=True, allow_mixed_types=False,
log_mode: "Literal['IMMUTABLE', 'MUTABLE', 'INCREMENTAL'] | None" = 'IMMUTABLE')

Description

The Table class used to display and analyze tabular data.

Unlike traditional spreadsheets, Tables support numerous types of data: scalar values, strings, numpy arrays, and most subclasses of wandb.data_types.Media. This means you can embed Images, Video, Audio, and other sorts of rich, annotated media directly in Tables, alongside other traditional scalar values.

This class is the primary class used to generate W&B Tables https://docs.wandb.ai/models/tables

Args

• columns:
• data:
• rows:
• dataframe:
• dtype:
• optional:
• allow_mixed_types:
• log_mode:

Methods

method add_column

(self, name, data, optional=False)

Adds a column of data to the table.

Arguments

• name: (str) - the unique name of the column
• data: (list | np.array) - a column of homogeneous data
• optional: (bool) - if null-like values are permitted

method add_computed_columns

(self, fn)

Adds one or more computed columns based on existing data.

Arguments

• fn: A function which accepts one or two parameters, ndx (int) and row (dict), which is expected to return a dict representing new columns for that row, keyed by the new column names. - ndx is an integer representing the index of the row. Only included if include_ndx is set to True. - row is a dictionary keyed by existing columns

method add_data

(self, *data)

Adds a new row of data to the table.

The maximum amount ofrows in a table is determined by wandb.Table.MAX_ARTIFACT_ROWS.

The length of the data should match the length of the table column.

Arguments

• data:

method add_row

(self, *row)

Deprecated. Use Table.add_data method instead.

Arguments

• row:

method captions

media_items: 'Sequence[Media]'

Arguments

• media_items:

method cast

(self, col_name, dtype, optional=False)

Casts a column to a specific data type.

This can be one of the normal python classes, an internal W&B type, or an example object, like an instance of wandb.Image or wandb.Classes.

Arguments

• col_name: The name of the column to cast.
• dtype: The target dtype.
• optional: If the column should allow Nones.

method file_is_set

self

method get_column

(self, name, convert_to=None)

Retrieves a column from the table and optionally converts it to a NumPy object.

Arguments

• name: (str) - the name of the column
• convert_to: (str, optional)

method get_dataframe

(self)

Returns a pandas.DataFrame of the table.

method get_index

(self)

Returns an array of row indexes for use in other tables to create links.

method init_from_json

json_obj: 'dict',
source_artifact: 'Artifact'

Initialize a WBValue from a JSON blob based on the class that created it.

Looks through all subclasses and tries to match the json obj with the class which created it. It will then call that subclass’ from_json method. Importantly, this function will set the return object’s source_artifact attribute to the passed in source artifact. This is critical for artifact bookkeeping. If you choose to create a wandb.Value via it’s from_json method, make sure to properly set this artifact_source to avoid data duplication.

Arguments

• json_obj: A JSON dictionary to deserialize. It must contain a _type key. This is used to lookup the correct subclass to use.
• source_artifact: An artifact which will hold any additional resources which were stored during the to_json function.

method is_bound

self

method path_is_reference

path: 'str | pathlib.Path | None'

Arguments

• path:

method to_data_array

self

Convert the object to a list of primitives representing the underlying data.

method type_mapping

Return a map from _log_type to subclass. Used to lookup correct types for deserialization.

method with_suffix

name: 'str',
filetype: 'str' = 'json'

Get the name with the appropriate suffix.

Arguments

• name: the name of the file
• filetype: the filetype to use. Defaults to “json”.