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class Table

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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

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Args

  • columns: (List[str]) Names of the columns in the table. Defaults to [“Input”, “Output”, “Expected”].
  • data: (List[List[any]]) 2D row-oriented array of values.
  • rows: (List[List[any]]) 2D row-oriented array of values.
  • dataframe: (pandas.DataFrame) DataFrame object used to create the table. When set, data and columns arguments are ignored.
  • dtype:
  • optional: (Union[bool,List[bool]]) Determines if None values are allowed. Default to True
    • If a singular bool value, then the optionality is enforced for all columns specified at construction time
    • If a list of bool values, then the optionality is applied to each column - should be the same length as columns applies to all columns. A list of bool values applies to each respective column.
  • allow_mixed_types: (bool) Determines if columns are allowed to have mixed types (disables type validation). Defaults to False
  • log_mode: Optional[str] Controls how the Table is logged when mutations occur. Options:
    • “IMMUTABLE” (default): Table can only be logged once; subsequent logging attempts after the table has been mutated will be no-ops.
    • “MUTABLE”: Table can be re-logged after mutations, creating a new artifact version each time it’s logged.
    • “INCREMENTAL”: Table data is logged incrementally, with each log creating a new artifact entry containing the new data since the last log.

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Methods

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method Table.add_column()

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

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method Table.add_computed_columns()

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

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method Table.add_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:

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method Table.add_row()

Deprecated. Use Table.add_data method instead.
Arguments
  • row:

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method Table.cast()

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.

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method Table.get_column()

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)
    • “numpy”: will convert the underlying data to numpy object

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method Table.get_dataframe()

Returns a pandas.DataFrame of the table.

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method Table.get_index()

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