How to use Neptune with Seaborn#

Seaborn is a library for making statistical graphics in Python. With Neptune, you can log and display Seaborn figures as PNG images.

Seaborn figure in Neptune

See in Neptune Example script

Before you start#

Sign up at neptune.ai/register.
Create a project for storing your metadata.

Have Seaborn and Neptune installed:

pipconda

pip install -U seaborn neptune

conda install -c conda-forge seaborn neptune

Tip

To follow the guide without any setup, run the example notebook in Colab

Seaborn logging example#

Import Neptune and start a run:

import neptune

run = neptune.init_run() # (1)!

If you haven't set up your credentials, you can log anonymously:

neptune.init_run(
    api_token=neptune.ANONYMOUS_API_TOKEN,
    project="common/plotting",
)

Create a sample figure:

import seaborn as sns

figure = sns.relplot(...)

Log the figure to the run:

run["seaborn_fig"] = figure

If using neptune <1.9.x

Seaborn figure support was added in version 1.9.0 of the Neptune client library.

On older versions, you need to access the .figure property of the Seaborn figure:

import seaborn as sns

seaborn_fig = ...

# Convert Seaborn object to Matplotlib format (matplotlib.Figure)
figure = seaborn_fig.figure

# Log figure to run
run["seaborn-img"].upload(figure)

To stop the connection to Neptune and sync all data, call the stop() method:
```
run.stop()
```
Run your script as you normally would.

To open the run, click the Neptune link that appears in the console output.

[neptune] [info ] Neptune initialized. Open in the app: https://app.neptune.ai/workspace/project/e/RUN-1

Result

You can find the resulting figure in the Images tab of the run details.

Logging a series of Seaborn images#

To log a series of Seaborn figures, use append() inside a loop:

for epoch in range(params["iterations"]):
    seaborn_fig = ...
    run["train/distribution"].append(seaborn_fig)

If using neptune <1.9.x

Seaborn figure support was added in version 1.9.0 of the Neptune client library.

On older versions, you need to access the .figure property of the Seaborn figure:

for epoch in range(params["iterations"]):
    seaborn_fig = ...
    figure = seaborn_fig.figure
    run["train/distribution"].append(figure)