feat: add solutions to lc problem: No.3673

solution/3000-3099/3005.Count Elements With Maximum Frequency/README.md

@@ -169,6 +169,30 @@ function maxFrequencyElements(nums: number[]): number {
 }
 ```
 
+#### Rust
+
+```rust
+impl Solution {
+    pub fn max_frequency_elements(nums: Vec<i32>) -> i32 {
+        let mut cnt = [0; 101];
+        for &x in &nums {
+            cnt[x as usize] += 1;
+        }
+        let mut ans = 0;
+        let mut mx = -1;
+        for &x in &cnt {
+            if mx < x {
+                mx = x;
+                ans = x;
+            } else if mx == x {
+                ans += x;
+            }
+        }
+        ans
+    }
+}
+```
+
 <!-- tabs:end -->
 
 <!-- solution:end -->

solution/3000-3099/3005.Count Elements With Maximum Frequency/README_EN.md

@@ -167,6 +167,30 @@ function maxFrequencyElements(nums: number[]): number {
 }
 ```
 
+#### Rust
+
+```rust
+impl Solution {
+    pub fn max_frequency_elements(nums: Vec<i32>) -> i32 {
+        let mut cnt = [0; 101];
+        for &x in &nums {
+            cnt[x as usize] += 1;
+        }
+        let mut ans = 0;
+        let mut mx = -1;
+        for &x in &cnt {
+            if mx < x {
+                mx = x;
+                ans = x;
+            } else if mx == x {
+                ans += x;
+            }
+        }
+        ans
+    }
+}
+```
+
 <!-- tabs:end -->
 
 <!-- solution:end -->

solution/3000-3099/3005.Count Elements With Maximum Frequency/Solution.rs

@@ -0,0 +1,19 @@
+impl Solution {
+    pub fn max_frequency_elements(nums: Vec<i32>) -> i32 {
+        let mut cnt = [0; 101];
+        for &x in &nums {
+            cnt[x as usize] += 1;
+        }
+        let mut ans = 0;
+        let mut mx = -1;
+        for &x in &cnt {
+            if mx < x {
+                mx = x;
+                ans = x;
+            } else if mx == x {
+                ans += x;
+            }
+        }
+        ans
+    }
+}

solution/3600-3699/3673.Find Zombie Sessions/README.md

@@ -20,7 +20,7 @@ tags:
 
 <pre>
 +------------------+----------+
-| Column Name      | Type     | 
+| Column Name      | Type     |
 +------------------+----------+
 | event_id         | int      |
 | user_id          | int      |
@@ -151,14 +151,65 @@ event_value represents: for purchase - amount in dollars, for scroll - pixels sc
 
 <!-- solution:start -->
 
-### 方法一
+### 方法一：分组统计
+
+我们可以将会话按照 `session_id` 进行分组，统计每个会话的持续时间、滚动事件数、点击事件数和购买事件数，然后根据题目中的条件进行筛选，最后按照滚动事件数降序、会话 ID 升序排序。
 
 <!-- tabs:start -->
 
 #### MySQL
 
 ```sql
+# Write your MySQL query statement below
+SELECT
+    session_id,
+    user_id,
+    TIMESTAMPDIFF(MINUTE, MIN(event_timestamp), MAX(event_timestamp)) session_duration_minutes,
+    SUM(event_type = 'scroll') scroll_count
+FROM app_events
+GROUP BY session_id
+HAVING
+    session_duration_minutes >= 30
+    AND SUM(event_type = 'click') / SUM(event_type = 'scroll') < 0.2
+    AND SUM(event_type = 'purchase') = 0
+    AND SUM(event_type = 'scroll') >= 5
+ORDER BY scroll_count DESC, session_id;
+```
+
+#### Pandas
+
+```python
+import pandas as pd
+
+
+def find_zombie_sessions(app_events: pd.DataFrame) -> pd.DataFrame:
+    if not pd.api.types.is_datetime64_any_dtype(app_events["event_timestamp"]):
+        app_events["event_timestamp"] = pd.to_datetime(app_events["event_timestamp"])
+
+    grouped = app_events.groupby(["session_id", "user_id"])
+
+    result = grouped.agg(
+        session_duration_minutes=(
+            "event_timestamp",
+            lambda x: (x.max() - x.min()).total_seconds() // 60,
+        ),
+        scroll_count=("event_type", lambda x: (x == "scroll").sum()),
+        click_count=("event_type", lambda x: (x == "click").sum()),
+        purchase_count=("event_type", lambda x: (x == "purchase").sum()),
+    ).reset_index()
+
+    result = result[
+        (result["session_duration_minutes"] >= 30)
+        & (result["click_count"] / result["scroll_count"] < 0.2)
+        & (result["purchase_count"] == 0)
+        & (result["scroll_count"] >= 5)
+    ]
+
+    result = result.sort_values(
+        by=["scroll_count", "session_id"], ascending=[False, True]
+    ).reset_index(drop=True)
 
+    return result[["session_id", "user_id", "session_duration_minutes", "scroll_count"]]
 ```
 
 <!-- tabs:end -->

solution/3600-3699/3673.Find Zombie Sessions/README_EN.md

@@ -20,7 +20,7 @@ tags:
 
 <pre>
 +------------------+----------+
-| Column Name      | Type     | 
+| Column Name      | Type     |
 +------------------+----------+
 | event_id         | int      |
 | user_id          | int      |
@@ -151,14 +151,65 @@ event_value represents: for purchase - amount in dollars, for scroll - pixels sc
 
 <!-- solution:start -->
 
-### Solution 1
+### Solution 1: Grouped Aggregation
+
+We can group the sessions by session_id, calculate the session duration, the number of scroll events, click events, and purchase events for each session, then filter according to the conditions given in the problem. Finally, we sort by the number of scroll events in descending order and by session ID in ascending order.
 
 <!-- tabs:start -->
 
 #### MySQL
 
 ```sql
+# Write your MySQL query statement below
+SELECT
+    session_id,
+    user_id,
+    TIMESTAMPDIFF(MINUTE, MIN(event_timestamp), MAX(event_timestamp)) session_duration_minutes,
+    SUM(event_type = 'scroll') scroll_count
+FROM app_events
+GROUP BY session_id
+HAVING
+    session_duration_minutes >= 30
+    AND SUM(event_type = 'click') / SUM(event_type = 'scroll') < 0.2
+    AND SUM(event_type = 'purchase') = 0
+    AND SUM(event_type = 'scroll') >= 5
+ORDER BY scroll_count DESC, session_id;
+```
+
+#### Pandas
+
+```python
+import pandas as pd
+
+
+def find_zombie_sessions(app_events: pd.DataFrame) -> pd.DataFrame:
+    if not pd.api.types.is_datetime64_any_dtype(app_events["event_timestamp"]):
+        app_events["event_timestamp"] = pd.to_datetime(app_events["event_timestamp"])
+
+    grouped = app_events.groupby(["session_id", "user_id"])
+
+    result = grouped.agg(
+        session_duration_minutes=(
+            "event_timestamp",
+            lambda x: (x.max() - x.min()).total_seconds() // 60,
+        ),
+        scroll_count=("event_type", lambda x: (x == "scroll").sum()),
+        click_count=("event_type", lambda x: (x == "click").sum()),
+        purchase_count=("event_type", lambda x: (x == "purchase").sum()),
+    ).reset_index()
+
+    result = result[
+        (result["session_duration_minutes"] >= 30)
+        & (result["click_count"] / result["scroll_count"] < 0.2)
+        & (result["purchase_count"] == 0)
+        & (result["scroll_count"] >= 5)
+    ]
+
+    result = result.sort_values(
+        by=["scroll_count", "session_id"], ascending=[False, True]
+    ).reset_index(drop=True)
 
+    return result[["session_id", "user_id", "session_duration_minutes", "scroll_count"]]
 ```
 
 <!-- tabs:end -->

solution/3600-3699/3673.Find Zombie Sessions/Solution.py

@@ -0,0 +1,31 @@
+import pandas as pd
+
+
+def find_zombie_sessions(app_events: pd.DataFrame) -> pd.DataFrame:
+    if not pd.api.types.is_datetime64_any_dtype(app_events["event_timestamp"]):
+        app_events["event_timestamp"] = pd.to_datetime(app_events["event_timestamp"])
+
+    grouped = app_events.groupby(["session_id", "user_id"])
+
+    result = grouped.agg(
+        session_duration_minutes=(
+            "event_timestamp",
+            lambda x: (x.max() - x.min()).total_seconds() // 60,
+        ),
+        scroll_count=("event_type", lambda x: (x == "scroll").sum()),
+        click_count=("event_type", lambda x: (x == "click").sum()),
+        purchase_count=("event_type", lambda x: (x == "purchase").sum()),
+    ).reset_index()
+
+    result = result[
+        (result["session_duration_minutes"] >= 30)
+        & (result["click_count"] / result["scroll_count"] < 0.2)
+        & (result["purchase_count"] == 0)
+        & (result["scroll_count"] >= 5)
+    ]
+
+    result = result.sort_values(
+        by=["scroll_count", "session_id"], ascending=[False, True]
+    ).reset_index(drop=True)
+
+    return result[["session_id", "user_id", "session_duration_minutes", "scroll_count"]]

solution/3600-3699/3673.Find Zombie Sessions/Solution.sql

@@ -0,0 +1,14 @@
+# Write your MySQL query statement below
+SELECT
+    session_id,
+    user_id,
+    TIMESTAMPDIFF(MINUTE, MIN(event_timestamp), MAX(event_timestamp)) session_duration_minutes,
+    SUM(event_type = 'scroll') scroll_count
+FROM app_events
+GROUP BY session_id
+HAVING
+    session_duration_minutes >= 30
+    AND SUM(event_type = 'click') / SUM(event_type = 'scroll') < 0.2
+    AND SUM(event_type = 'purchase') = 0
+    AND SUM(event_type = 'scroll') >= 5
+ORDER BY scroll_count DESC, session_id;