Introduction

Hello. Last time, ** Important unit seen from Python lecture materials of Kyoto University ** I posted an article called. This time, I would like to take a look at that ** column edition **. I felt that mainly ** "It is omitted in classes and lectures, but it is important" ** is well organized. Someone who uses Python somehow may not know it.

To be honest, it is easy to read, so it is recommended that you read it quickly, unlike the lecture materials. I just thought that I should write the column edition as an article, so if you want to refer to it, please laugh.

If you want to review the basics of Python, please read the previous article and lecture materials.

Relation: Lecture Material Repository Introduction article-Qiita Introduction article-CodeZine

Reference site summary: How to write comments Summary of Python implementation know-how and tips that AI engineers want to be careful about

What to do in this article

In this article, I would like to rank from my personal opinion from the lecture materials (column edition) of Kyoto University. I am also a beginner, so please comment if you have any opinions.

Article target

I can use Python somehow, but I want to know one step ahead! People

Ranking

It is relatively appropriate, but it is ranked. Please for reference

Example: ** 1. Computer and programming (☆☆☆) **

Rank	meaning
☆☆☆	Essential knowledge
☆☆	Trivia
☆	The part that you don't need to know

0. Column 0 Beginning (☆☆)

About subscripts starting from 0. I think it's known, but let's read it.

1. What is Column Float? (☆☆)

chapter	title	Rank	Overview
1.1	Floating point	☆☆	It's a common sense part, but it's okay to be light.
1.2	The bad thing about working with floating point numbers in binary	☆☆	Let's know.

2. Column Newton's method (☆☆)

chapter	title	Rank	Overview
2.1	Newton's method	☆☆	Let's reproduce the last formula programmatically.
2.2	Find the nth root	☆☆	Same as above.
2.3	Equal temperament	☆	You don't have to read it.

3. Column relative accuracy (☆)

** You can skip it. ** **

chapter	title	Rank	Overview
3.1	Numerical accuracy	☆
3.2	Absolute accuracy and relative accuracy	☆

4. Column Formal and actual arguments (☆☆☆)

It is a word that often appears. Let's know the term.

5. Column Variable scope (☆☆☆)

The content is important, but honestly it's hard to understand. If you understand variables and functions, you should look them up yourself.

chapter	title	Rank	Overview
5.1	Local variables=Variables to discard	☆☆
5.2	Variable scope in Python	☆☆☆

6. Column Random numbers (☆☆☆)

I think it's a good idea to check the usage example and try it yourself.

chapter	title	Rank	Overview
6.1	Computer and random numbers	☆	You don't have to read it.
6.2	Random number you want to use	☆☆☆	This is an assumption of a situation where you want to use random numbers. Let's read while imagining.
6.3	Use Random module	☆☆☆	The method using the standard module is introduced. If possible, try it out.
6.4	Execute with a certain probability	☆☆	Use unexpectedly
6.5	Random number generation with Numpy	☆☆☆	Numpy is useful. Let's run it.

7. Column recursion (☆☆)

You can skip it if it is difficult.

chapter	title	Rank	Overview
7.1	Processing mathematical formulas	☆
7.2	Relative pronoun	☆
7.3	Revival	☆☆	I feel like I can do that. If you are interested.

8. Column GUI

chapter	title	Rank	Overview
8.1	What is GUI?	☆☆☆	It's a common sense term
8.2	Difficulty in software development	☆☆☆	Let's know.
8.3	Exclusion and inclusion	☆☆	I think you should read it.

9. Column Program and Japanese (☆☆☆)

chapter	title	Rank	Overview
9.1	UTF in Python-8	☆☆☆	It's common sense. windwos shift-jis。
9.2	Character code on source code Apologize	☆☆☆	Let's watch out
9.3	Pay attention to the \ symbol	☆☆☆	About \ n. I walk without knowing it.

10. Column namespace (☆☆☆)

chapter	title	Rank	Overview
10.1	Name confusion	☆☆	An easy-to-understand analogy
10.2	Computer namespace	☆☆☆	It's common sense. Let's not use it somehow.

11. Column Program documentation (☆☆☆)

This is especially good to read. I have not written in detail, so I will post a reference page. ・ How to write comments ・ Summary of Python implementation know-how and tips that AI engineers want to be careful about

chapter	title	Rank	Overview
11.1	The program quickly disappears	☆☆☆	I don't even know who wrote the program.
11.2	Program documentation	☆☆☆	Write comments frequently.
11.3	docstring	☆☆	You don't have to know.

12. Column trigonometric function (☆☆)

You can skip it.

chapter	title	Rank
12.1	Manufacturing and trigonometric functions	☆☆
12.2	Trigonometric function as a wave	☆☆☆
12.3	Listen to the difference in waveform as sound	☆

13. Column reference and duplication (☆☆☆)

Be sure to read it. I think you should also check passing by value and passing by reference.

chapter	title	Rank	Overview
13.1	Reference and replication of information, its loss	☆☆☆	It's a parable.
13.2	Mutable and immutable	☆☆☆	It's a complicated story, but it's important. Let's read.

in conclusion

Thank you for watching until the end. That's all for the column edition. The volume is less than the lecture materials, but there are some parts that take some time to understand.

If you are self-taught in Python, the contents that will make you stumbled are organized properly. However, since it is only basic, it is best to learn according to what you want to do. It is also recommended to challenge the past questions of the competition professionals.

As I wrote at the beginning, this teaching material has ** Lecture Materials ** that summarizes the basics of Python. I highly recommend reading it. ** Important unit from the Python lecture materials of Kyoto University **

** This article is over. If you have any questions, please leave a comment and we will respond. Thank you very much. ** **

Kyoto University Python Lecture Material: Introduction of Columns