What will you get with this integration?

​Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. This integration lets you log charts generated in matplotlib to Neptune for easy reference and collaboration.

Introduction

This guide will show you how to:

• Initialize Neptune and create a run,

• Log matplotlib charts to Neptune.

Step 0: Before you start

Install neptune-client and matplotlib:

pip install --upgrade --quiet neptune-client matplotlib

Step 1: Import and initialize Neptune

import neptune.new as neptune
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run = neptune.init(api_token='<your_api_token>',
                   project='<your_project_name>')

Executing this cell will give you a link looking like: https://app.neptune.ai/common/matplotlib-support/e/MAT-1 with common/matplotlib-support replaced by your project, and MAT-1 replaced by your run.

Click on the link to open the run in Neptune. For now, it is empty but keep the tab with the run open to see what happens next.

Step 2: Log Matplotlib figures to Neptune

Create a sample figure

import matplotlib.pyplot as plt
import numpy as np
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np.random.seed(42)
data = np.random.randn(2, 100)
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figure, ax = plt.subplots(2, 2, figsize=(5, 5))
ax[0, 0].hist(data[0])
ax[1, 0].scatter(data[0], data[1])
ax[0, 1].plot(data[0], data[1])

Log as static image

run['static-img'] = neptune.types.File.as_image(figure)

Log as interactive chart

run['interactive-img'] = neptune.types.File.as_html(figure)

Step 3: Explore the charts in Neptune

The images can be found in the All metadata section:

Step 4: Stop logging

run.stop()

Conclusion

You’ve learned how to:

• Initialize Neptune and create a run,

• Log matplotlib charts to Neptune.

What's next

Now that you know how to log charts to Neptune, you can learn:

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