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feat: add solutions to lc problem: No.3374 #3831

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6 changes: 4 additions & 2 deletions solution/0200-0299/0277.Find the Celebrity/README.md
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Expand Up @@ -22,9 +22,11 @@ tags:

<p>现在你想要确认这个 “名人” 是谁，或者确定这里没有&nbsp;“名人”。而你唯一能做的就是问诸如 “A&nbsp;你好呀，请问你认不认识&nbsp;B呀？”&nbsp;的问题，以确定 A 是否认识 B。你需要在（渐近意义上）尽可能少的问题内来确定这位 “名人” 是谁（或者确定这里没有 “名人”）。</p>

<p>在本题中，你可以使用辅助函数&nbsp;<code>bool knows(a, b)</code>&nbsp;获取到 A&nbsp;是否认识 B。请你来实现一个函数&nbsp;<code>int findCelebrity(n)</code>。</p>
<p>给定整数&nbsp;<code>n</code>&nbsp;和一个辅助函数&nbsp;<code>bool knows(a, b)</code>&nbsp;用来获取&nbsp;<code>a</code> 是否认识&nbsp;<code>b</code>。实现一个函数&nbsp;<code>int findCelebrity(n)</code>。派对最多只会有一个 “名人” 参加。</p>

<p>派对最多只会有一个 “名人” 参加。若&nbsp;“名人” 存在，请返回他/她的编号；若&nbsp;“名人”&nbsp;不存在，请返回&nbsp;<code>-1</code>。</p>
<p>若&nbsp;“名人” 存在，请返回他/她的编号；若&nbsp;“名人”&nbsp;不存在，请返回&nbsp;<code>-1</code>。</p>

<p><strong>注意</strong>&nbsp;<code>n x n</code>&nbsp;的二维数组&nbsp;<code>graph</code>&nbsp;给定的输入并不是&nbsp;<strong>直接</strong>&nbsp;提供给你的，而是&nbsp;<strong>只能</strong>&nbsp;通过辅助函数 <code>knows</code>&nbsp;获取。<code>graph[i][j] == 1</code>&nbsp;表示&nbsp;<code>i</code> 认识 <code>j</code>，而&nbsp;<code>graph[i][j] == 0</code>&nbsp;表示&nbsp;<code>j</code>&nbsp;不认识&nbsp;<code>i</code>。</p>

<p>&nbsp;</p>

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6 changes: 3 additions & 3 deletions solution/3300-3399/3368.First Letter Capitalization/README.md
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Expand Up @@ -56,7 +56,7 @@ content_id 是这张表的唯一主键。
+------------+-----------------------------------+
| content_id | content_text |
+------------+-----------------------------------+
| 1 | hello world of SQL |
| 1 | hello world of Sql |
| 2 | the QUICK brown fox |
| 3 | data science AND machine learning |
| 4 | TOP rated programming BOOKS |
Expand All @@ -69,7 +69,7 @@ content_id 是这张表的唯一主键。
+------------+-----------------------------------+-----------------------------------+
| content_id | original_text | converted_text |
+------------+-----------------------------------+-----------------------------------+
| 1 | hello world of SQL | Hello World Of SQL |
| 1 | hello world of Sql | Hello World Of Sql |
| 2 | the QUICK brown fox | The Quick Brown Fox |
| 3 | data science AND machine learning | Data Science And Machine Learning |
| 4 | TOP rated programming BOOKS | Top Rated Programming Books |
Expand All @@ -81,7 +81,7 @@ content_id 是这张表的唯一主键。
<ul>
<li>对于 content_id = 1:
<ul>
<li>每个单词的首字母都已经大写：Hello World Of SQL</li>
<li>每个单词的首字母都已经大写：Hello World Of Sql</li>
</ul>
</li>
<li>对于 content_id = 2:
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147 changes: 147 additions & 0 deletions solution/3300-3399/3374.First Letter Capitalization II/README.md
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---
comments: true
difficulty: 困难
edit_url: https://github.com/doocs/leetcode/edit/main/solution/3300-3399/3374.First%20Letter%20Capitalization%20II/README.md
tags:
- 数据库
---

<!-- problem:start -->

# [3374. 首字母大写 II](https://leetcode.cn/problems/first-letter-capitalization-ii)

[English Version](/solution/3300-3399/3374.First%20Letter%20Capitalization%20II/README_EN.md)

## 题目描述

<!-- description:start -->

<p>表：<code>user_content</code></p>

<pre>
+-------------+---------+
| Column Name | Type |
+-------------+---------+
| content_id | int |
| content_text| varchar |
+-------------+---------+
content_id 是这张表的唯一主键。
每一行包含一个不同的 ID 以及对应的文本内容。
</pre>

<p>编写一个解决方案来根据下面的规则来转换&nbsp;<code>content_text</code>&nbsp;列中的文本：</p>

<ul>
<li>将每个单词的 <strong>第一个字母</strong>&nbsp;转换为 <strong>大写</strong>，其余字母 <strong>保持小写</strong>。</li>
<li>特殊处理包含特殊字符的单词：
<ul>
<li>对于用短横&nbsp;<code>-</code>&nbsp;连接的词语，<strong>两个部份</strong>&nbsp;都应该&nbsp;<strong>大写</strong>（<strong>例如</strong>，top-rated&nbsp;→ Top-Rated）</li>
</ul>
</li>
<li>所有其他 <strong>格式</strong> 和 <strong>空格</strong> 应保持 <strong>不变</strong></li>
</ul>

<p>返回结果表同时包含原始的&nbsp;<code>content_text</code> 以及根据上述规则修改后的文本。</p>

<p>结果格式如下例所示。</p>

<p>&nbsp;</p>

<p><strong class="example">示例：</strong></p>

<div class="example-block">
<p><strong>输入：</strong></p>

<p>user_content 表：</p>

<pre class="example-io">
+------------+---------------------------------+
| content_id | content_text |
+------------+---------------------------------+
| 1 | hello world of SQL |
| 2 | the QUICK-brown fox |
| 3 | modern-day DATA science |
| 4 | web-based FRONT-end development |
+------------+---------------------------------+
</pre>

<p><strong>输出：</strong></p>

<pre class="example-io">
+------------+---------------------------------+---------------------------------+
| content_id | original_text | converted_text |
+------------+---------------------------------+---------------------------------+
| 1 | hello world of SQL | Hello World Of Sql |
| 2 | the QUICK-brown fox | The Quick-Brown Fox |
| 3 | modern-day DATA science | Modern-Day Data Science |
| 4 | web-based FRONT-end development | Web-Based Front-End Development |
+------------+---------------------------------+---------------------------------+
</pre>

<p><strong>解释：</strong></p>

<ul>
<li>对于 content_id = 1：
<ul>
<li>每个单词的首字母都是大写的："Hello World Of Sql"</li>
</ul>
</li>
<li>对于 content_id = 2：
<ul>
<li>包含的连字符词 "QUICK-brown" 变为 "Quick-Brown"</li>
<li>其它单词遵循普通的首字母大写规则</li>
</ul>
</li>
<li>对于 content_id = 3：
<ul>
<li>连字符词 "modern-day" 变为 "Modern-Day"</li>
<li>"DATA" 转换为 "Data"</li>
</ul>
</li>
<li>对于 content_id = 4：
<ul>
<li>包含两个连字符词："web-based" → "Web-Based"</li>
<li>以及 "FRONT-end" → "Front-End"</li>
</ul>
</li>
</ul>
</div>

<!-- description:end -->

## 解法

<!-- solution:start -->

### 方法一

<!-- tabs:start -->

#### Pandas

```python
import pandas as pd


def capitalize_content(user_content: pd.DataFrame) -> pd.DataFrame:
def convert_text(text: str) -> str:
return " ".join(
(
"-".join([part.capitalize() for part in word.split("-")])
if "-" in word
else word.capitalize()
)
for word in text.split(" ")
)

user_content["converted_text"] = user_content["content_text"].apply(convert_text)
return user_content.rename(columns={"content_text": "original_text"})[
["content_id", "original_text", "converted_text"]
]
```

<!-- tabs:end -->

<!-- solution:end -->

<!-- problem:end -->
146 changes: 146 additions & 0 deletions solution/3300-3399/3374.First Letter Capitalization II/README_EN.md
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---
comments: true
difficulty: Hard
edit_url: https://github.com/doocs/leetcode/edit/main/solution/3300-3399/3374.First%20Letter%20Capitalization%20II/README_EN.md
tags:
- Database
---

<!-- problem:start -->

# [3374. First Letter Capitalization II](https://leetcode.com/problems/first-letter-capitalization-ii)

[中文文档](/solution/3300-3399/3374.First%20Letter%20Capitalization%20II/README.md)

## Description

<!-- description:start -->

<p>Table: <code>user_content</code></p>

<pre>
+-------------+---------+
| Column Name | Type |
+-------------+---------+
| content_id | int |
| content_text| varchar |
+-------------+---------+
content_id is the unique key for this table.
Each row contains a unique ID and the corresponding text content.
</pre>

<p>Write a solution to transform the text in the <code>content_text</code> column by applying the following rules:</p>

<ul>
<li>Convert the <strong>first letter</strong> of each word to <strong>uppercase</strong> and the <strong>remaining</strong> letters to <strong>lowercase</strong></li>
<li>Special handling for words containing special characters:
<ul>
<li>For words connected with a hyphen <code>-</code>, <strong>both parts</strong> should be <strong>capitalized</strong> (<strong>e.g.</strong>, top-rated&nbsp;&rarr; Top-Rated)</li>
</ul>
</li>
<li>All other <strong>formatting</strong> and <strong>spacing</strong> should remain <strong>unchanged</strong></li>
</ul>

<p>Return <em>the result table that includes both the original <code>content_text</code> and the modified text following the above rules</em>.</p>

<p>The result format is in the following example.</p>

<p>&nbsp;</p>
<p><strong class="example">Example:</strong></p>

<div class="example-block">
<p><strong>Input:</strong></p>

<p>user_content table:</p>

<pre class="example-io">
+------------+---------------------------------+
| content_id | content_text |
+------------+---------------------------------+
| 1 | hello world of SQL |
| 2 | the QUICK-brown fox |
| 3 | modern-day DATA science |
| 4 | web-based FRONT-end development |
+------------+---------------------------------+
</pre>

<p><strong>Output:</strong></p>

<pre class="example-io">
+------------+---------------------------------+---------------------------------+
| content_id | original_text | converted_text |
+------------+---------------------------------+---------------------------------+
| 1 | hello world of SQL | Hello World Of Sql |
| 2 | the QUICK-brown fox | The Quick-Brown Fox |
| 3 | modern-day DATA science | Modern-Day Data Science |
| 4 | web-based FRONT-end development | Web-Based Front-End Development |
+------------+---------------------------------+---------------------------------+
</pre>

<p><strong>Explanation:</strong></p>

<ul>
<li>For content_id = 1:
<ul>
<li>Each word&#39;s first letter is capitalized: &quot;Hello World Of Sql&quot;</li>
</ul>
</li>
<li>For content_id = 2:
<ul>
<li>Contains the hyphenated word &quot;QUICK-brown&quot; which becomes &quot;Quick-Brown&quot;</li>
<li>Other words follow normal capitalization rules</li>
</ul>
</li>
<li>For content_id = 3:
<ul>
<li>Hyphenated word &quot;modern-day&quot; becomes &quot;Modern-Day&quot;</li>
<li>&quot;DATA&quot; is converted to &quot;Data&quot;</li>
</ul>
</li>
<li>For content_id = 4:
<ul>
<li>Contains two hyphenated words: &quot;web-based&quot; &rarr; &quot;Web-Based&quot;</li>
<li>And &quot;FRONT-end&quot; &rarr; &quot;Front-End&quot;</li>
</ul>
</li>
</ul>
</div>

<!-- description:end -->

## Solutions

<!-- solution:start -->

### Solution 1

<!-- tabs:start -->

#### Pandas

```python
import pandas as pd


def capitalize_content(user_content: pd.DataFrame) -> pd.DataFrame:
def convert_text(text: str) -> str:
return " ".join(
(
"-".join([part.capitalize() for part in word.split("-")])
if "-" in word
else word.capitalize()
)
for word in text.split(" ")
)

user_content["converted_text"] = user_content["content_text"].apply(convert_text)
return user_content.rename(columns={"content_text": "original_text"})[
["content_id", "original_text", "converted_text"]
]
```

<!-- tabs:end -->

<!-- solution:end -->

<!-- problem:end -->
18 changes: 18 additions & 0 deletions solution/3300-3399/3374.First Letter Capitalization II/Solution.py
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import pandas as pd


def capitalize_content(user_content: pd.DataFrame) -> pd.DataFrame:
def convert_text(text: str) -> str:
return " ".join(
(
"-".join([part.capitalize() for part in word.split("-")])
if "-" in word
else word.capitalize()
)
for word in text.split(" ")
)

user_content["converted_text"] = user_content["content_text"].apply(convert_text)
return user_content.rename(columns={"content_text": "original_text"})[
["content_id", "original_text", "converted_text"]
]
1 change: 1 addition & 0 deletions solution/DATABASE_README.md
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Expand Up @@ -302,6 +302,7 @@
| 3338 | [第二高的薪水 II](/solution/3300-3399/3338.Second%20Highest%20Salary%20II/README.md) | `数据库` | 中等 | 🔒 |
| 3358 | [评分为 NULL 的图书](/solution/3300-3399/3358.Books%20with%20NULL%20Ratings/README.md) | `数据库` | 简单 | 🔒 |
| 3368 | [首字母大写](/solution/3300-3399/3368.First%20Letter%20Capitalization/README.md) | | 困难 | 🔒 |
| 3374 | [首字母大写 II](/solution/3300-3399/3374.First%20Letter%20Capitalization%20II/README.md) | | 困难 | |

## 版权

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Expand Up @@ -300,6 +300,7 @@ Press <kbd>Control</kbd> + <kbd>F</kbd>(or <kbd>Command</kbd> + <kbd>F</kbd> on
| 3338 | [Second Highest Salary II](/solution/3300-3399/3338.Second%20Highest%20Salary%20II/README_EN.md) | `Database` | Medium | 🔒 |
| 3358 | [Books with NULL Ratings](/solution/3300-3399/3358.Books%20with%20NULL%20Ratings/README_EN.md) | `Database` | Easy | 🔒 |
| 3368 | [First Letter Capitalization](/solution/3300-3399/3368.First%20Letter%20Capitalization/README_EN.md) | | Hard | 🔒 |
| 3374 | [First Letter Capitalization II](/solution/3300-3399/3374.First%20Letter%20Capitalization%20II/README_EN.md) | | Hard | |

## Copyright

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1 change: 1 addition & 0 deletions solution/README.md
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Expand Up @@ -3383,6 +3383,7 @@
| 3371 | [识别数组中的最大异常值](/solution/3300-3399/3371.Identify%20the%20Largest%20Outlier%20in%20an%20Array/README.md) | | 中等 | 第 426 场周赛 |
| 3372 | [连接两棵树后最大目标节点数目 I](/solution/3300-3399/3372.Maximize%20the%20Number%20of%20Target%20Nodes%20After%20Connecting%20Trees%20I/README.md) | | 中等 | 第 426 场周赛 |
| 3373 | [连接两棵树后最大目标节点数目 II](/solution/3300-3399/3373.Maximize%20the%20Number%20of%20Target%20Nodes%20After%20Connecting%20Trees%20II/README.md) | | 困难 | 第 426 场周赛 |
| 3374 | [首字母大写 II](/solution/3300-3399/3374.First%20Letter%20Capitalization%20II/README.md) | | 困难 | |

## 版权

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| 3371 | [Identify the Largest Outlier in an Array](/solution/3300-3399/3371.Identify%20the%20Largest%20Outlier%20in%20an%20Array/README_EN.md) | | Medium | Weekly Contest 426 |
| 3372 | [Maximize the Number of Target Nodes After Connecting Trees I](/solution/3300-3399/3372.Maximize%20the%20Number%20of%20Target%20Nodes%20After%20Connecting%20Trees%20I/README_EN.md) | | Medium | Weekly Contest 426 |
| 3373 | [Maximize the Number of Target Nodes After Connecting Trees II](/solution/3300-3399/3373.Maximize%20the%20Number%20of%20Target%20Nodes%20After%20Connecting%20Trees%20II/README_EN.md) | | Hard | Weekly Contest 426 |
| 3374 | [First Letter Capitalization II](/solution/3300-3399/3374.First%20Letter%20Capitalization%20II/README_EN.md) | | Hard | |

## Copyright

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