Question

Разберите 6 любых словосочетаний

Answer 1

1.Красивый(прил., волнистой линией, определение) мячик( сущ.____,, подлежащие, определяемое слово)Можно задать вопрос:

Мячик( какой?) красивый

2.Разговаривать(глагол, ===, определяемое слово) по телефону(сущ., _ _ _, дополнение)

Можно задать вопрос:

Разговаривать ( по чему?) по телефону

3.Выглядеть( глагол, ==, определяемое слово) красиво( наречие, _._._)

Можно задать вопрос:

Выглядеть ( как?) красиво

4.Говорить( глагол,==, определяемое слово) с вежливостью( сущ. _ _ _, дополнение)

Можно задать вопрос:

Говорить (как?) с вежливостью

5. Красивый(прил., врлнистой линией, определение) закат( сущ.,____, подлежащее, определяемое слово

Можно задать вопрос:

Закат (какой?) красивый6. 6.Увидеть( глагол,==, определяемое слово) картину( сущ. _ _ _, дополнение)

Можно задать вопрос:

Увидеть (что?) картину

Надеюсь, помогла

Answer 2

1. Python: `re.split()`

The `re.split()` function in Python is used to split a string into a list of substrings based on a specified pattern. It takes two arguments: the pattern to split on and the string to split. Here are a couple of examples:

Example 1: ```python import re print(re.split(r'(\s*)([+*/-])(\s*)', r'12 + 13*15 - 6')) # Output: ['12', ' ', '+', ' ', '13', '', '*', '', '15', ' ', '-', ' ', '6'] ``` In this example, the string `'12 + 13*15 - 6'` is split based on the pattern `r'(\s*)([+*/-])(\s*)'`, which matches any whitespace characters followed by a mathematical operator (`+`, `-`, `*`, or `/`) and any subsequent whitespace characters. The resulting list contains the individual substrings.

Example 2: ```python import re print(re.split(r'\s*([+*/-])\s*', r'12 + 13*15 - 6')) # Output: ['12', '+', '13', '*', '15', '-', '6'] ``` In this example, the string `'12 + 13*15 - 6'` is split based on the pattern `r'\s*([+*/-])\s*'`, which matches any whitespace characters surrounding a mathematical operator. The resulting list contains the individual substrings without any whitespace.

These examples demonstrate how `re.split()` can be used to split strings based on specific patterns [[1]](https://habr.com/ru/articles/349860/).

2. Python: `re.sub()`

The `re.sub()` function in Python is used to replace substrings in a string that match a specified pattern with a replacement string. It takes three arguments: the pattern to search for, the replacement string, and the input string. Here's an example:

```python import re text = "We arrive on 03/25/2018. So you are welcome after 04/01/2018." print(re.sub(r'(\d\d)/(\d\d)/(\d{4})', r'\2.\1.\3', text)) # Output: "We arrive on 25.03.2018. So you are welcome after 01.04.2018." ``` In this example, the pattern `r'(\d\d)/(\d\d)/(\d{4})'` matches dates in the format `dd/mm/yyyy`. The `re.sub()` function replaces each matched date with the corresponding parts rearranged using the replacement string `r'\2.\1.\3'`, which swaps the day and month and separates them with dots.

The `re.sub()` function is a powerful tool for performing string substitutions based on patterns in Python [[1]](https://habr.com/ru/articles/349860/).

3. Cryptology: Caesar Ciphers

Caesar ciphers are a type of substitution cipher where each letter in the plaintext is shifted a certain number of positions down the alphabet. For example, with a shift of 3, the letter 'A' would be encrypted as 'D', 'B' as 'E', and so on. The name "Caesar" comes from Julius Caesar, who is said to have used this type of cipher.

Caesar ciphers are relatively easy to break, especially with the help of computers, as there are only 25 possible shifts. The most common method of breaking a Caesar cipher is by using frequency analysis, where the frequency of letters in the ciphertext is compared to the expected frequency of letters in the language being used.

While Caesar ciphers are not secure for modern cryptographic purposes, they serve as a good introduction to the concept of encryption and decryption.

4. DataFrame

A DataFrame is a two-dimensional labeled data structure in pandas, a popular data manipulation library in Python. It is similar to a table in a relational database or a spreadsheet, where data is organized in rows and columns.

DataFrames provide a convenient way to store and analyze structured data. They can be created from various data sources, such as CSV files, Excel spreadsheets, or even from scratch using Python lists or dictionaries.

Once a DataFrame is created, you can perform various operations on it, such as filtering rows, selecting columns, aggregating data, and applying functions to specific columns or rows.

DataFrames are a fundamental data structure in pandas and are widely used in data analysis and data science tasks.

5. Phortran

Phortran is a port of the Fortran programming language to the Java Virtual Machine (JVM). It allows Fortran code to be compiled and executed on the JVM, which provides platform independence and access to the Java ecosystem.

Phortran aims to provide a seamless integration between Fortran and Java, allowing Fortran code to interact with Java libraries and vice versa. It provides a set of tools and libraries for developing, testing, and optimizing Fortran programs on the JVM.

Phortran is designed to be compatible with existing Fortran codebases, making it easier to migrate Fortran applications to the JVM and take advantage of the Java ecosystem.

6. Astrology

Astrology is a belief system that suggests a connection between the positions of celestial bodies and events or characteristics of individuals or societies. It is based on the idea that the positions and movements of celestial bodies, such as the sun, moon, planets, and stars, can influence human behavior and personality traits.

Astrology is often associated with horoscopes, which are predictions or interpretations based on the positions of celestial bodies at the time of a person's birth. Horoscopes are commonly used to provide insights into a person's personality, relationships, and future events.

While astrology has a long history and is still practiced by many people, it is not considered a scientific discipline. The scientific consensus is that there is no evidence to support the claims made by astrology, and any perceived correlations are likely due to coincidence or psychological factors.

I hope this breakdown helps! Let me know if you have any further questions.