Suggestions for a reading list in Statistics and intro to machine learning

Question

I have built a reading list based on recommendations and suggestions found on several posts from this community. My intention is to use this reading list to acquire a good understanding about statistics and also about some topics on machine learning. Being my final goal to start a PhD in Statistics (in around 2 years).

I'm familiar with basic calculus and basic Linear Algebra (almost all the concepts covered by Gilbert Strang books, even though in a practical level). Furthermore, I'm familiar with basic concepts of probability and statistics. Additionally, I'm highly proficient in R and Python (and I have some experience using numpy, matplotlib, pandas and scikit-learn).

For this reason, I would appreciate further suggestions and recommendations, in order to improve this reading list.

The books on this reading list range from introductory to more advanced level, being the following:

1. Gilbert Strang - Calculus
2. Daniel J. Velleman - How to Prove It: A Structured Approach
3. Gilbert Strang - Linear Algebra and Its Applications
4. Larry Wasserman - All of Statistics
5. James, Witten, Hastie and Tibshirani - An Introduction to Statistical Learning
6. Kreyszig - Introductory Functional Analysis with Applications [chapters 1 to 3]
7. Golub and Van Loan - Matrix Computations
8. Stein and Shakarchi - Real Analysis: Measure Theory, Integration, and Hilbert Spaces
9. Jan R. Magnus - Matrix Differential Calculus with Applications in Statistics and Econometrics
10. Fitzpatrick - Advanced Calculus
11. Wakerly, Mendenhall and Scheaffer - Mathematical Statistics with Applications
12. Casella and Berger - Statistical Inference
13. Boyd and Vandenberghe - Convex Optimization
14. Hastie, Tibshirani and Friedman - The Elements of Statistical Learning: Data Mining, Inference, and Prediction
15. Gelman et al. - Bayesian Data Analysis
16. Kevin Murphy - Machine Learning: A Probabilistic Perspective

Click this link to see a visual representation of the previous reading list

Thanks in advance!

Edit 1: Added Hans Engler Feedback

Edit 2: Added All of Statistics as suggested by Wanshan

Edit 3: Added paf feedback

Answer 1

I recommend you the book Practical Econometrics with Python. The book links theory with practical examples in Python from most basic topics like OLS to advanced topics like VARMA.