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  • LeetCode SQL 50 Solution/1484. Group Sold Products By The Date

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Here’s a well-structured `README.md` for **LeetCode 1484 - Group Sold Products By The Date**, formatted for a GitHub repository:
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```md
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# 🛍️ Group Sold Products By The Date - LeetCode 1484
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## 📌 Problem Statement
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You are given a table **Activities** that contains records of products sold on different dates.
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Your task is to return:
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- The **number of distinct products** sold on each date.
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- A **comma-separated string** of the product names, sorted **lexicographically**.
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The result should be **ordered by `sell_date`**.
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---
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## 📊 Table Structure
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### **Activities Table**
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| Column Name | Type |
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| ----------- | ------- |
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| sell_date | date |
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| product | varchar |
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- This table **does not** have a **primary key**.
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- It may **contain duplicate entries**.
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---
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## 📊 Example 1:
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### **Input:**
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#### **Activities Table**
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| sell_date | product |
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| ---------- | ---------- |
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| 2020年05月30日 | Headphone |
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| 2020年06月01日 | Pencil |
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| 2020年06月02日 | Mask |
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| 2020年05月30日 | Basketball |
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| 2020年06月01日 | Bible |
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| 2020年06月02日 | Mask |
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| 2020年05月30日 | T-Shirt |
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### **Output:**
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| sell_date | num_sold | products |
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| ---------- | -------- | ---------------------------- |
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| 2020年05月30日 | 3 | Basketball,Headphone,T-Shirt |
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| 2020年06月01日 | 2 | Bible,Pencil |
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| 2020年06月02日 | 1 | Mask |
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### **Explanation:**
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- `2020年05月30日`: Sold items → _(Headphone, Basketball, T-Shirt)_
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- Sorted → **"Basketball, Headphone, T-Shirt"**
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- `2020年06月01日`: Sold items → _(Pencil, Bible)_
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- Sorted → **"Bible, Pencil"**
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- `2020年06月02日`: Sold item → _(Mask)_
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- **"Mask"** (only one item)
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---
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## 🖥 SQL Solution
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### ✅ **Using `GROUP_CONCAT` with `DISTINCT`**
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#### **Explanation:**
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- Use `COUNT(DISTINCT product)` to get the **number of distinct products**.
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- Use `GROUP_CONCAT(DISTINCT product ORDER BY product ASC)` to **join product names in alphabetical order**.
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- Group by `sell_date`, then order the result by `sell_date`.
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```sql
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SELECT
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sell_date,
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COUNT(DISTINCT product) AS num_sold,
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GROUP_CONCAT(DISTINCT product ORDER BY product ASC SEPARATOR ',') AS products
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FROM Activities
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GROUP BY sell_date
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ORDER BY sell_date ASC;
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```
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---
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## 🐍 Pandas Solution (Python)
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#### **Explanation:**
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- **Group by `sell_date`**.
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- Use `.nunique()` to count distinct products.
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- Use `', '.join(sorted(set(products)))` to sort and concatenate product names.
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```python
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import pandas as pd
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def group_sold_products(activities: pd.DataFrame) -> pd.DataFrame:
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grouped_df = (
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activities.groupby("sell_date")["product"]
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.agg(lambda x: ", ".join(sorted(set(x))))
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.reset_index()
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)
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grouped_df["num_sold"] = grouped_df["product"].apply(lambda x: len(x.split(",")))
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return grouped_df.rename(columns={"product": "products"})
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```
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---
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## 📁 File Structure
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```
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📂 Group-Sold-Products
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│── 📜 README.md
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│── 📜 solution.sql
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│── 📜 solution_pandas.py
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│── 📜 test_cases.sql
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```
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---
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## 🔗 Useful Links
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- 📖 [LeetCode Problem](https://leetcode.com/problems/group-sold-products-by-the-date/)
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- 📚 [SQL `GROUP BY`](https://www.w3schools.com/sql/sql_groupby.asp)
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- 🐍 [Pandas `groupby()` Documentation](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.groupby.html)
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```
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### Features of this `README.md`:
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✅ **Clear problem statement with tables**
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✅ **Example with step-by-step explanation**
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✅ **SQL and Pandas solutions with detailed breakdowns**
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✅ **File structure for easy organization**
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✅ **Helpful references for further learning**
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Would you like any modifications? 🚀

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