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Try in Colab

Try in W&B

Use W&B Tables to visualize and query tabular data. For example:
  • Compare how different models perform on the same test set
  • Identify patterns in your data
  • Look at sample model predictions visually
  • Query to find commonly misclassified examples
Semantic segmentation predictions table
The above image shows a table with semantic segmentation and custom metrics. View this table here in this sample project from the W&B ML Course.

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How it works

A Table is a two-dimensional grid of data where each column has a single type of data. Tables support primitive and numeric types, as well as nested lists, dictionaries, and rich media types.

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Log a Table

Log a table with a few lines of code:
  • wandb.init(): Create a run to track results.
  • wandb.Table(): Create a new table object.
    • columns: Set the column names.
    • data: Set the contents of the table.
  • run.log(): Log the table to save it to W&B.
import wandb

run = wandb.init(project="table-test")
my_table = wandb.Table(columns=["a", "b"], data=[["a1", "b1"], ["a2", "b2"]])
run.log({"Table Name": my_table})

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How to get started

  • Quickstart: Learn to log data tables, visualize data, and query data.
  • Tables Gallery: See example use cases for Tables.
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