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feat: add sql solutions to lc problems: No.2984+ (doocs#2172)
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‎solution/2900-2999/2984.Find Peak Calling Hours for Each City/README.md

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@@ -69,7 +69,29 @@ Output table is ordered by peak_calling_hour and city in descending order.</pre>
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<!-- 这里可写当前语言的特殊实现逻辑 -->
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```sql
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# Write your MySQL query statement below
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WITH
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T AS (
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SELECT
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*,
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RANK() OVER (
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PARTITION BY city
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ORDER BY cnt DESC
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) AS rk
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FROM
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(
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SELECT
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city,
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HOUR(call_time) AS h,
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COUNT(1) AS cnt
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FROM Calls
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GROUP BY 1, 2
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) AS t
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)
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SELECT city, h AS peak_calling_hour, cnt AS number_of_calls
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FROM T
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WHERE rk = 1
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ORDER BY 2 DESC, 1 DESC;
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```
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<!-- tabs:end -->

‎solution/2900-2999/2984.Find Peak Calling Hours for Each City/README_EN.md

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@@ -63,7 +63,29 @@ Output table is ordered by peak_calling_hour and city in descending order.</pre>
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### **SQL**
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```sql
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# Write your MySQL query statement below
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WITH
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T AS (
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SELECT
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*,
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RANK() OVER (
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PARTITION BY city
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ORDER BY cnt DESC
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) AS rk
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FROM
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(
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SELECT
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city,
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HOUR(call_time) AS h,
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COUNT(1) AS cnt
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FROM Calls
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GROUP BY 1, 2
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) AS t
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)
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SELECT city, h AS peak_calling_hour, cnt AS number_of_calls
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FROM T
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WHERE rk = 1
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ORDER BY 2 DESC, 1 DESC;
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```
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<!-- tabs:end -->

‎solution/2900-2999/2984.Find Peak Calling Hours for Each City/Solution.sql

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# Write your MySQL query statement below
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WITH
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T AS (
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SELECT
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*,
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RANK() OVER (
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PARTITION BY city
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ORDER BY cnt DESC
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) AS rk
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FROM
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(
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SELECT
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city,
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HOUR(call_time) AS h,
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COUNT(1) AS cnt
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FROM Calls
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GROUP BY 1, 2
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) AS t
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)
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SELECT city, h AS peak_calling_hour, cnt AS number_of_calls
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FROM T
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WHERE rk = 1
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ORDER BY 2 DESC, 1 DESC;

‎solution/2900-2999/2985.Calculate Compressed Mean/README.md

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Original file line numberDiff line numberDiff line change
@@ -63,7 +63,13 @@ The calculation is as follows:
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<!-- 这里可写当前语言的特殊实现逻辑 -->
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```sql
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# Write your MySQL query statement below
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SELECT
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ROUND(
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SUM(item_count * order_occurrences) / SUM(order_occurrences),
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2
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) AS average_items_per_order
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FROM Orders;
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```
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<!-- tabs:end -->

‎solution/2900-2999/2985.Calculate Compressed Mean/README_EN.md

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Original file line numberDiff line numberDiff line change
@@ -57,7 +57,13 @@ The calculation is as follows:
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### **SQL**
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```sql
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# Write your MySQL query statement below
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SELECT
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ROUND(
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SUM(item_count * order_occurrences) / SUM(order_occurrences),
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2
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) AS average_items_per_order
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FROM Orders;
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```
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<!-- tabs:end -->

‎solution/2900-2999/2985.Calculate Compressed Mean/Solution.sql

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# Write your MySQL query statement below
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SELECT
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ROUND(
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SUM(item_count * order_occurrences) / SUM(order_occurrences),
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2
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) AS average_items_per_order
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FROM Orders;

‎solution/2900-2999/2986.Find Third Transaction/README.md

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Original file line numberDiff line numberDiff line change
@@ -70,7 +70,32 @@ Output table is ordered by user_id in ascending order.
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<!-- 这里可写当前语言的特殊实现逻辑 -->
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```sql
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# Write your MySQL query statement below
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WITH
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T AS (
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SELECT
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*,
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RANK() OVER (
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PARTITION BY user_id
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ORDER BY transaction_date
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) AS rk,
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spend > (
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LAG(spend) OVER (
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PARTITION BY user_id
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ORDER BY transaction_date
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)
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)
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AND spend > (
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LAG(spend, 2) OVER (
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PARTITION BY user_id
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ORDER BY transaction_date
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)
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) AS st
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FROM Transactions
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)
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SELECT user_id, spend AS third_transaction_spend, transaction_date AS third_transaction_date
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FROM T
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WHERE rk = 3 AND st = 1;
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```
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<!-- tabs:end -->

‎solution/2900-2999/2986.Find Third Transaction/README_EN.md

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Original file line numberDiff line numberDiff line change
@@ -64,7 +64,32 @@ Output table is ordered by user_id in ascending order.
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### **SQL**
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```sql
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# Write your MySQL query statement below
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WITH
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T AS (
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SELECT
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*,
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RANK() OVER (
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PARTITION BY user_id
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ORDER BY transaction_date
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) AS rk,
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spend > (
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LAG(spend) OVER (
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PARTITION BY user_id
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ORDER BY transaction_date
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)
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)
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AND spend > (
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LAG(spend, 2) OVER (
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PARTITION BY user_id
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ORDER BY transaction_date
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)
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) AS st
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FROM Transactions
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)
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SELECT user_id, spend AS third_transaction_spend, transaction_date AS third_transaction_date
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FROM T
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WHERE rk = 3 AND st = 1;
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```
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<!-- tabs:end -->

‎solution/2900-2999/2986.Find Third Transaction/Solution.sql

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# Write your MySQL query statement below
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WITH
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T AS (
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SELECT
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*,
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RANK() OVER (
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PARTITION BY user_id
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ORDER BY transaction_date
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) AS rk,
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spend > (
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LAG(spend) OVER (
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PARTITION BY user_id
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ORDER BY transaction_date
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)
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)
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AND spend > (
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LAG(spend, 2) OVER (
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PARTITION BY user_id
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ORDER BY transaction_date
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)
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) AS st
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FROM Transactions
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)
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SELECT user_id, spend AS third_transaction_spend, transaction_date AS third_transaction_date
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FROM T
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WHERE rk = 3 AND st = 1;

‎solution/2900-2999/2987.Find Expensive Cities/README.md

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@@ -75,7 +75,12 @@ Only Chicago and Los Angeles have average home prices exceeding the national ave
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<!-- 这里可写当前语言的特殊实现逻辑 -->
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```sql
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# Write your MySQL query statement below
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SELECT city
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FROM Listings
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GROUP BY city
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HAVING AVG(price) > (SELECT AVG(price) FROM Listings)
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ORDER BY 1;
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```
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<!-- tabs:end -->

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