diff --git a/translations/zh-HK/.co-op-translator.json b/translations/zh-HK/.co-op-translator.json
index 62fdbeb8..258c457f 100644
--- a/translations/zh-HK/.co-op-translator.json
+++ b/translations/zh-HK/.co-op-translator.json
@@ -12,8 +12,8 @@
"language_code": "zh-HK"
},
"1-Introduction/01-defining-data-science/notebook.ipynb": {
- "original_hash": "8f5eb7b3f7cc89e6d98fb32e1de65dec",
- "translation_date": "2026-02-28T09:00:47+00:00",
+ "original_hash": "8eb07e3d899aaba7ea9c9ec9b5aa2850",
+ "translation_date": "2026-07-17T21:36:53+00:00",
"source_file": "1-Introduction/01-defining-data-science/notebook.ipynb",
"language_code": "zh-HK"
},
@@ -42,8 +42,8 @@
"language_code": "zh-HK"
},
"1-Introduction/03-defining-data/README.md": {
- "original_hash": "12339119c0165da569a93ddba05f9339",
- "translation_date": "2025-09-05T12:13:46+00:00",
+ "original_hash": "7217c6f9eb464d4ff4bae6c036ab53cb",
+ "translation_date": "2026-07-17T21:41:39+00:00",
"source_file": "1-Introduction/03-defining-data/README.md",
"language_code": "zh-HK"
},
@@ -65,6 +65,12 @@
"source_file": "1-Introduction/04-stats-and-probability/assignment.md",
"language_code": "zh-HK"
},
+ "1-Introduction/04-stats-and-probability/notebook.ipynb": {
+ "original_hash": "0c77e104b29c723287bf11b773fcc5d5",
+ "translation_date": "2026-07-17T21:38:04+00:00",
+ "source_file": "1-Introduction/04-stats-and-probability/notebook.ipynb",
+ "language_code": "zh-HK"
+ },
"1-Introduction/README.md": {
"original_hash": "696a8474a01054281704cbfb09148949",
"translation_date": "2025-08-25T16:38:14+00:00",
@@ -108,8 +114,8 @@
"language_code": "zh-HK"
},
"2-Working-With-Data/07-python/notebook-covidspread.ipynb": {
- "original_hash": "6335cccba01dc6ad7b15aba7a8c73f38",
- "translation_date": "2026-02-28T09:02:48+00:00",
+ "original_hash": "da97f98781c7cd271063f605fe8d71d0",
+ "translation_date": "2026-07-17T21:36:22+00:00",
"source_file": "2-Working-With-Data/07-python/notebook-covidspread.ipynb",
"language_code": "zh-HK"
},
@@ -192,14 +198,14 @@
"language_code": "zh-HK"
},
"3-Data-Visualization/13-meaningful-visualizations/solution/README.md": {
- "original_hash": "5c51a54dd89075a7a362890117b7ed9e",
- "translation_date": "2025-08-25T18:04:12+00:00",
+ "original_hash": "2b3b2632bb02af608ca60be828e8097d",
+ "translation_date": "2026-07-17T21:41:48+00:00",
"source_file": "3-Data-Visualization/13-meaningful-visualizations/solution/README.md",
"language_code": "zh-HK"
},
"3-Data-Visualization/13-meaningful-visualizations/starter/README.md": {
- "original_hash": "5c51a54dd89075a7a362890117b7ed9e",
- "translation_date": "2025-08-25T18:03:33+00:00",
+ "original_hash": "2b3b2632bb02af608ca60be828e8097d",
+ "translation_date": "2026-07-17T21:41:44+00:00",
"source_file": "3-Data-Visualization/13-meaningful-visualizations/starter/README.md",
"language_code": "zh-HK"
},
diff --git a/translations/zh-HK/1-Introduction/01-defining-data-science/notebook.ipynb b/translations/zh-HK/1-Introduction/01-defining-data-science/notebook.ipynb
index aae72fed..c88f6482 100644
--- a/translations/zh-HK/1-Introduction/01-defining-data-science/notebook.ipynb
+++ b/translations/zh-HK/1-Introduction/01-defining-data-science/notebook.ipynb
@@ -2,421 +2,319 @@
"cells": [
{
"cell_type": "markdown",
+ "metadata": {},
"source": [
- "# 挑戰：分析有關數據科學的文本\n",
+ "# 挑戰：分析關於數據科學的文本\n",
"\n",
- "在這個範例中，讓我們做一個涵蓋傳統數據科學流程所有步驟的簡單練習。你不必寫任何程式碼，只需點擊以下儲存格以執行它們並觀察結果。作為挑戰，你可以嘗試用不同的資料來執行這段代碼。\n",
+ "在這個例子中，我們做一個涵蓋傳統數據科學流程所有步驟的簡單練習。你不需要寫任何代碼，只需點擊下面的單元格執行它們並觀察結果。作為挑戰，鼓勵你使用不同的數據嘗試這段代碼。\n",
"\n",
"## 目標\n",
"\n",
- "在本課程中，我們一直在討論與數據科學相關的不同概念。讓我們透過進行一些**文本探勘**，嘗試發現更多相關概念。我們將從一篇關於數據科學的文本開始，從中提取關鍵詞，然後嘗試視覺化結果。\n",
+ "在本課程中，我們討論了與數據科學相關的不同概念。讓我們透過做一些文本挖掘來嘗試發現更多相關概念。我們將從一段關於數據科學的文本開始，從中提取關鍵字，然後嘗試將結果視覺化。\n",
"\n",
- "作為文本，我將使用維基百科上有關數據科學的頁面：\n"
- ],
- "metadata": {}
+ "我將使用維基百科上關於數據科學的頁面作為文本：\n"
+ ]
},
{
"cell_type": "markdown",
- "source": [],
- "metadata": {}
+ "metadata": {},
+ "source": []
},
{
"cell_type": "code",
- "execution_count": 62,
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
"source": [
"url = 'https://en.wikipedia.org/wiki/Data_science'"
- ],
- "outputs": [],
- "metadata": {}
+ ]
},
{
"cell_type": "markdown",
+ "metadata": {},
"source": [
- "## Step 1: 獲取數據\n",
+ "## 第一步：取得數據\n",
"\n",
- "每個數據科學流程的第一步都是獲取數據。我們將使用 `requests` 庫來完成這個工作：\n"
- ],
- "metadata": {}
+ "每個數據科學流程的第一步都是取得數據。我們將使用 `requests` 函式庫來完成這個步驟：\n"
+ ]
},
{
"cell_type": "code",
- "execution_count": 63,
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
"source": [
- "import requests\r\n",
- "\r\n",
- "text = requests.get(url).content.decode('utf-8')\r\n",
- "print(text[:1000])"
- ],
- "outputs": [
- {
- "output_type": "stream",
- "name": "stdout",
- "text": [
- "\n",
- "\n",
- "\n",
- "\n",
- "Data science - Wikipedia\n",
- "