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Python•Data Science and Scientific Python

NumPy Tutorial

Learn NumPy

NumPy is a Python library.

NumPy is used for working with arrays.

NumPy is short for "Numerical Python".

Learning by Reading

We have created 43 tutorial pages for you to learn more about NumPy.

Starting with a basic introduction and ends up with creating and plotting random data sets, and working with NumPy functions:

ufunc

Example

import numpy as np

arr = np.array([1, 2, 3, 4, 5])
print(arr)

print(type(arr))

Chapter

Back to Data Science and Scientific Python

Next

Matplotlib Tutorial

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)

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