Tutorial: Log tables, visualize, and query data

Learn how to log data tables to W&B, visualize them in your project workspace, and compare results across runs. By the end, you’ll have a logged table that you can explore and compare in W&B. Select the button below to try a PyTorch Quickstart example project on MNIST data.

Log a table

In this step, you create a table and log it to W&B so that it’s available for visualization later in the walkthrough. You can either construct a new table or pass a pandas DataFrame.

Construct a table
Pandas DataFrame

To construct and log a new table, use the following:

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 each row.
wandb.Run.log(): Log the table to save it to W&B.

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})

Pass a pandas DataFrame to wandb.Table() to create a new table.

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 in the W&B API Reference Guide.

Visualize tables in your project workspace

After logging a table, you can view it in W&B.

Navigate to your project in W&B.
Select the name of your run in your project workspace. W&B adds a new panel for each unique table key.

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

Compare across model versions

After you have logged tables from more than one run, you can use the project workspace to compare results side by side and evaluate how model versions differ. After you log tables from multiple W&B runs, compare results side by side in the project workspace to evaluate differences between model versions. This example workspace shows how to combine rows from multiple versions in the same table.

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

Guides

Integrations

Reference

Log a table

Visualize tables in your project workspace

Compare across model versions

​Log a table

​Visualize tables in your project workspace

​Compare across model versions

Log a table

Visualize tables in your project workspace

Compare across model versions