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Python•Data Science and Scientific Python

Matplotlib Pyplot

Pyplot

Most of the Matplotlib utilities lies under the pyplot submodule, and are usually imported under the plt alias:

import matplotlib.pyplot as plt

Now the Pyplot package can be referred to as plt .

Example

import matplotlib.pyplot as plt

import numpy as np

xpoints = np.array([0, 6])
ypoints = np.array([0, 250])
plt.plot(xpoints,
ypoints)

plt.show()

You will learn more about drawing (plotting) in the next chapters.

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This chapter

Overview
38

Lessons

159m

Read time

1. NumPy Tutorial2. Matplotlib Tutorial3. Machine Learning4. Pandas Tutorial5. Matplotlib Getting Started6. Machine Learning - Mean Median Mode7. Matplotlib Pyplot8. Machine Learning - Standard Deviation9. Matplotlib Plotting10. Machine Learning - Percentiles11. Matplotlib Markers12. Machine Learning - Data Distribution13. Matplotlib Line14. Machine Learning - Normal Data Distribution15. Matplotlib Labels and Title16. Machine Learning - Scatter Plot17. Matplotlib Adding Grid Lines18. Machine Learning - Linear Regression19. Matplotlib Subplot20. Machine Learning - Polynomial Regression21. Matplotlib Scatter22. Machine Learning - Multiple Regression23. Matplotlib Bars24. Machine Learning - Scale25. Matplotlib Histograms26. Machine Learning - Train/Test27. Matplotlib Pie Charts28. Machine Learning - Decision Tree29. Machine Learning - Confusion Matrix30. Machine Learning - Hierarchical Clustering31. Machine Learning - Logistic Regression32. Machine Learning - Grid Search33. Preprocessing - Categorical Data34. Machine Learning - K-means35. Machine Learning - Bootstrap Aggregation (Bagging)36. Machine Learning - Cross Validation37. Machine Learning - AUC - ROC Curve38. Machine Learning - K-nearest neighbors (KNN)