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Commit 9d11a79

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feat: add pandas solutions to lc problem: No.0175,0176 (#1858)
1 parent 29d4633 commit 9d11a79

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‎solution/0100-0199/0175.Combine Two Tables/README.md‎

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LEFT JOIN Address USING (personId);
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```
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```pandas
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import pandas as pd
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def combine_two_tables(person: pd.DataFrame, address: pd.DataFrame) -> pd.DataFrame:
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return pd.merge(left=person, right=address, how="left", on="personId")[
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["firstName", "lastName", "city", "state"]
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]
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```
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<!-- tabs:end -->

‎solution/0100-0199/0175.Combine Two Tables/README_EN.md‎

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LEFT JOIN Address USING (personId);
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```
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```pandas
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import pandas as pd
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def combine_two_tables(person: pd.DataFrame, address: pd.DataFrame) -> pd.DataFrame:
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return pd.merge(left=person, right=address, how="left", on="personId")[
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["firstName", "lastName", "city", "state"]
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]
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```
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<!-- tabs:end -->
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import pandas as pd
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def combine_two_tables(person: pd.DataFrame, address: pd.DataFrame) -> pd.DataFrame:
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return pd.merge(left=person, right=address, how="left", on="personId")[
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["firstName", "lastName", "city", "state"]
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]

‎solution/0100-0199/0176.Second Highest Salary/README.md‎

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@@ -113,4 +113,28 @@ WITH T AS (SELECT salary, DENSE_RANK() OVER (ORDER BY salary DESC) AS rk FROM Em
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SELECT (SELECT DISTINCT salary FROM T WHERE rk = 2) AS SecondHighestSalary;
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```
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```python
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import pandas as pd
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def second_highest_salary(employee: pd.DataFrame) -> pd.DataFrame:
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# Drop any duplicate salary values to avoid counting duplicates as separate salary ranks
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unique_salaries = employee["salary"].drop_duplicates()
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# Sort the unique salaries in descending order and get the second highest salary
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second_highest = (
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unique_salaries.nlargest(2).iloc[-1] if len(unique_salaries) >= 2 else None
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)
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# If the second highest salary doesn't exist (e.g., there are fewer than two unique salaries), return None
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if second_highest is None:
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return pd.DataFrame({"SecondHighestSalary": [None]})
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# Create a DataFrame with the second highest salary
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result_df = pd.DataFrame({"SecondHighestSalary": [second_highest]})
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return result_df
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```
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<!-- tabs:end -->

‎solution/0100-0199/0176.Second Highest Salary/README_EN.md‎

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SELECT (SELECT DISTINCT salary FROM T WHERE rk = 2) AS SecondHighestSalary;
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```
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```python
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import pandas as pd
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def second_highest_salary(employee: pd.DataFrame) -> pd.DataFrame:
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# Drop any duplicate salary values to avoid counting duplicates as separate salary ranks
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unique_salaries = employee["salary"].drop_duplicates()
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# Sort the unique salaries in descending order and get the second highest salary
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second_highest = (
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unique_salaries.nlargest(2).iloc[-1] if len(unique_salaries) >= 2 else None
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)
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# If the second highest salary doesn't exist (e.g., there are fewer than two unique salaries), return None
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if second_highest is None:
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return pd.DataFrame({"SecondHighestSalary": [None]})
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# Create a DataFrame with the second highest salary
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result_df = pd.DataFrame({"SecondHighestSalary": [second_highest]})
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return result_df
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```
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<!-- tabs:end -->
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import pandas as pd
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def second_highest_salary(employee: pd.DataFrame) -> pd.DataFrame:
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# Drop any duplicate salary values to avoid counting duplicates as separate salary ranks
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unique_salaries = employee["salary"].drop_duplicates()
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# Sort the unique salaries in descending order and get the second highest salary
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second_highest = (
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unique_salaries.nlargest(2).iloc[-1] if len(unique_salaries) >= 2 else None
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)
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# If the second highest salary doesn't exist (e.g., there are fewer than two unique salaries), return None
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if second_highest is None:
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return pd.DataFrame({"SecondHighestSalary": [None]})
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# Create a DataFrame with the second highest salary
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result_df = pd.DataFrame({"SecondHighestSalary": [second_highest]})
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return result_df

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