Pandas5 solutions

departmentHighestSalary.py

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+import pandas as pd
+
+def department_highest_salary(employee: pd.DataFrame, department: pd.DataFrame) -> pd.DataFrame:
+
+    merge_df = pd.merge(employee, department, left_on = 'departmentId', right_on = 'id', how = 'left')
+    merge_df = merge_df.rename(columns = {
+        'id_x' : 'Employee_id',
+        'name_x': 'Employee',
+        'name_y': 'Department',
+        'salary': 'Salary'
+    })[['Department', 'Employee', 'Salary']]
+
+    result = merge_df[merge_df['Salary'] == merge_df.groupby('Department')['Salary'].transform(max)]
+    return result

rankScores.py

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+import pandas as pd
+
+def order_scores(scores: pd.DataFrame) -> pd.DataFrame:
+    scores['score_rank'] = scores['score'].rank(method='dense', ascending=False)
+    scores.sort_values(by = 'score_rank', inplace = True)
+    scores.rename(columns = {'score_rank' : 'rank'}, inplace = True)
+    return scores[['score', 'rank']]