Tutorial: Log tables, visualize and query data ↗

wandb tutorial beginner models
no
Summary: Explore how to use W&B Tables with this 5 minute Quickstart.

Original Documentation

Documentation Index#

Fetch the complete documentation index at: https://docs.wandb.ai/llms.txt Use this file to discover all available pages before exploring further.

Explore how to use W&B Tables with this 5 minute Quickstart.

The following Quickstart demonstrates how to log data tables, visualize data, and query data.

Select the button below to try a PyTorch Quickstart example project on MNIST data.

1. Log a table#

Log a table with W&B. You can either construct a new table or pass a Pandas Dataframe.

To construct and log a new Table, you will use:

Here’s an example:

    import wandb

    with wandb.init(project="table-test") as run:
        # Create and log a new table.
        my_table = wandb.Table(columns=["a", "b"], data=[["a1", "b1"], ["a2", "b2"]])
        run.log({"Table Name": my_table})
    ```
  <span class="tab-end"></span>

  <span class="tab-start" data-tab-title="Pandas Dataframe"></span>
Pass a Pandas Dataframe to `wandb.Table()` to create a new table.

```python
    import wandb
    import pandas as pd

    df = pd.read_csv("my_data.csv")

    with wandb.init(project="df-table") as run:
        # Create a new table from the DataFrame
        # and log it to W&B.
      my_table = wandb.Table(dataframe=df)
      run.log({"Table Name": my_table})
    ```

For more information on supported data types, see the [`wandb.Table`](/models/ref/python/data-types/table) in the W\&B API Reference Guide.
  <span class="tab-end"></span>
<span class="tab-group-end"></span>

## 2. Visualize tables in your project workspace

View the resulting table in your workspace.

1. Navigate to your project in the W\&B App.
2. Select the name of your run in your project workspace. A new panel is added for each unique table key.


  <img src="https://mintcdn.com/wb-21fd5541/88iR80mZ8tuFCZUU/images/data_vis/wandb_demo_logged_sample_table.png?fit=max&auto=format&n=88iR80mZ8tuFCZUU&q=85&s=ea6c316c96db26caeba464622a9a7b0c" alt="Sample table logged" data-og-width="1762" width="1762" data-og-height="880" height="880" data-path="images/data_vis/wandb_demo_logged_sample_table.png" data-optimize="true" data-opv="3" srcset="https://mintcdn.com/wb-21fd5541/88iR80mZ8tuFCZUU/images/data_vis/wandb_demo_logged_sample_table.png?w=280&fit=max&auto=format&n=88iR80mZ8tuFCZUU&q=85&s=6e3e049a56e7712ad89a65305be0ab0f 280w, https://mintcdn.com/wb-21fd5541/88iR80mZ8tuFCZUU/images/data_vis/wandb_demo_logged_sample_table.png?w=560&fit=max&auto=format&n=88iR80mZ8tuFCZUU&q=85&s=2dd1b4d24a1b16e9bbea7297bf462e6c 560w, https://mintcdn.com/wb-21fd5541/88iR80mZ8tuFCZUU/images/data_vis/wandb_demo_logged_sample_table.png?w=840&fit=max&auto=format&n=88iR80mZ8tuFCZUU&q=85&s=0ee855e6c8bff7c8322ae3d349614441 840w, https://mintcdn.com/wb-21fd5541/88iR80mZ8tuFCZUU/images/data_vis/wandb_demo_logged_sample_table.png?w=1100&fit=max&auto=format&n=88iR80mZ8tuFCZUU&q=85&s=727d86bdde50e67f58b587de8ddd9208 1100w, https://mintcdn.com/wb-21fd5541/88iR80mZ8tuFCZUU/images/data_vis/wandb_demo_logged_sample_table.png?w=1650&fit=max&auto=format&n=88iR80mZ8tuFCZUU&q=85&s=de72f69bfea4698271dba47f58c5fede 1650w, https://mintcdn.com/wb-21fd5541/88iR80mZ8tuFCZUU/images/data_vis/wandb_demo_logged_sample_table.png?w=2500&fit=max&auto=format&n=88iR80mZ8tuFCZUU&q=85&s=9c5c7152615a39131c5ecca1d5a895b0 2500w" />


In this example, `my_table`, is logged under the key `"Table Name"`.

## 3. Compare across model versions

Log sample tables from multiple W\&B Runs and compare results in the project workspace. In this [example workspace](https://wandb.ai/carey/table-test?workspace=user-carey), we show how to combine rows from multiple different versions in the same table.


  <img src="https://mintcdn.com/wb-21fd5541/88iR80mZ8tuFCZUU/images/data_vis/wandb_demo_toggle_on_and_off_cross_run_comparisons_in_tables.gif?s=a1da4671329b7d038cda71c91c56045e" alt="Cross-run table comparison" data-og-width="1754" width="1754" data-og-height="1026" height="1026" data-path="images/data_vis/wandb_demo_toggle_on_and_off_cross_run_comparisons_in_tables.gif" data-optimize="true" data-opv="3" />


Use the table filter, sort, and grouping features to explore and evaluate model results.


  <img src="https://mintcdn.com/wb-21fd5541/88iR80mZ8tuFCZUU/images/data_vis/wandb_demo_filter_on_a_table.png?fit=max&auto=format&n=88iR80mZ8tuFCZUU&q=85&s=21ac42731b4da719d0baef5bcfc03ad2" alt="Table filtering" data-og-width="1602" width="1602" data-og-height="606" height="606" data-path="images/data_vis/wandb_demo_filter_on_a_table.png" data-optimize="true" data-opv="3" srcset="https://mintcdn.com/wb-21fd5541/88iR80mZ8tuFCZUU/images/data_vis/wandb_demo_filter_on_a_table.png?w=280&fit=max&auto=format&n=88iR80mZ8tuFCZUU&q=85&s=14392ffcb05d24ccb61203c9b95d8059 280w, https://mintcdn.com/wb-21fd5541/88iR80mZ8tuFCZUU/images/data_vis/wandb_demo_filter_on_a_table.png?w=560&fit=max&auto=format&n=88iR80mZ8tuFCZUU&q=85&s=a86913bd2bc400660073944a4bfb16b8 560w, https://mintcdn.com/wb-21fd5541/88iR80mZ8tuFCZUU/images/data_vis/wandb_demo_filter_on_a_table.png?w=840&fit=max&auto=format&n=88iR80mZ8tuFCZUU&q=85&s=a9542f0e788ad8ebc73903aa471b8946 840w, https://mintcdn.com/wb-21fd5541/88iR80mZ8tuFCZUU/images/data_vis/wandb_demo_filter_on_a_table.png?w=1100&fit=max&auto=format&n=88iR80mZ8tuFCZUU&q=85&s=5ea31ac4abb8739ae4547b7373373884 1100w, https://mintcdn.com/wb-21fd5541/88iR80mZ8tuFCZUU/images/data_vis/wandb_demo_filter_on_a_table.png?w=1650&fit=max&auto=format&n=88iR80mZ8tuFCZUU&q=85&s=cdecc55885be948ffa0f78cbdf15fb14 1650w, https://mintcdn.com/wb-21fd5541/88iR80mZ8tuFCZUU/images/data_vis/wandb_demo_filter_on_a_table.png?w=2500&fit=max&auto=format&n=88iR80mZ8tuFCZUU&q=85&s=7ab5afa341b79efb4f809f8d400ac12c 2500w" />
Link last verified June 7, 2026. View original ↗
Source: Weights & Biases Docs
Link last verified: 2026-03-04