---
metadata:
  - name: generator
    content: Diplodoc Platform v5.50.3
alternate:
  - https://catboost.ai/docs/en/features/visualization.md
---
> **Documentation Index:** Fetch the complete configuration index at https://catboost.ai/docs/en/llms.txt

# Data visualization

CatBoost provides tools for the [Python package](https://catboost.ai/docs/en/concepts/python-installation.md) that allow plotting charts with different training statistics. This information can be accessed both during and after the training procedure. [Additional packages](https://catboost.ai/docs/en/installation/python-installation-additional-data-visualization-packages.md) must be installed to support the visualization tools.

The following information is reflected on the charts:
- [metric](https://catboost.ai/docs/en/concepts/loss-functions.md) values
- best metric values on the validation dataset
- elapsed time of training
- remaining time of training
- current metric value
- metric value on the best iteration

The table below lists the [Python training parameters](https://catboost.ai/docs/en/references/training-parameters/index.md) that affect visualization.

**Parameter** | **Usage tips**
:-------- | :---------
`plot` | Set to <q>true</q>
`--name` | The given value is used for signing the charts of the corresponding experiment. This parameter is useful when viewing results of different experiments on one chart.
`custom_metric`, `--loss-function`, `--eval-metric` | All the metrics specified in these parameters are output.


The following applications can be used for viewing the charts:
- [Jupyter Notebook](https://catboost.ai/docs/en/features/visualization_jupyter-notebook.md)
- [TensorBoard](https://catboost.ai/docs/en/features/visualization_tensorboard.md)