Data Science Essentials in Python by Zinoviev, Dmitry -- Read -- Imperial Library of Trantor

Index

 Acknowledgments  Preface

About This Book About the Audience About the Software Notes on Quotes The Book Forum Your Turn

1. What Is Data Science?

Unit 1. Data Analysis Sequence Unit 2. Data Acquisition Pipeline Unit 3. Report Structure Your Turn

2. Core Python for Data Science

Unit 4. Understanding Basic String Functions Unit 5. Choosing the Right Data Structure Unit 6. Comprehending Lists Through List Comprehension Unit 7. Counting with Counters Unit 8. Working with Files Unit 9. Reaching the Web Unit 10. Pattern Matching with Regular Expressions Unit 11. Globbing File Names and Other Strings Unit 12. Pickling and Unpickling Data Your Turn

3. Working with Text Data

Unit 13. Processing HTML Files Unit 14. Handling CSV Files Unit 15. Reading JSON Files Unit 16. Processing Texts in Natural Languages Your Turn

4. Working with Databases

Unit 17. Setting Up a MySQL Database Unit 18. Using a MySQL Database: Command Line Unit 19. Using a MySQL Database: pymysql Unit 20. Taming Document Stores: MongoDB Your Turn

5. Working with Tabular Numeric Data

Unit 21. Creating Arrays Unit 22. Transposing and Reshaping Unit 23. Indexing and Slicing Unit 24. Broadcasting Unit 25. Demystifying Universal Functions Unit 26. Understanding Conditional Functions Unit 27. Aggregating and Ordering Arrays Unit 28. Treating Arrays as Sets Unit 29. Saving and Reading Arrays Unit 30. Generating a Synthetic Sine Wave Your Turn

6. Working with Data Series and Frames

Unit 31. Getting Used to Pandas Data Structures Unit 32. Reshaping Data Unit 33. Handling Missing Data Unit 34. Combining Data Unit 35. Ordering and Describing Data Unit 36. Transforming Data Unit 37. Taming Pandas File I/O Your Turn

7. Working with Network Data

Unit 38. Dissecting Graphs Unit 39. Network Analysis Sequence Unit 40. Harnessing Networkx Your Turn

8. Plotting

Unit 41. Basic Plotting with PyPlot Unit 42. Getting to Know Other Plot Types Unit 43. Mastering Embellishments Unit 44. Plotting with Pandas Your Turn

9. Probability and Statistics

Unit 45. Reviewing Probability Distributions Unit 46. Recollecting Statistical Measures Unit 47. Doing Stats the Python Way Your Turn

10. Machine Learning

Unit 48. Designing a Predictive Experiment Unit 49. Fitting a Linear Regression Unit 50. Grouping Data with K-Means Clustering Unit 51. Surviving in Random Decision Forests Your Turn

A1. Further Reading A2. Solutions to Single-Star Projects  Bibliography