PR #137, 138: Radhika

137_department_highest_salary.py

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+# Perform inner join on Employee and Department tables. Get the max salary and return only the rows that
+# have max salary.
+
+import pandas as pd
+
+def department_highest_salary(employee: pd.DataFrame, department: pd.DataFrame) -> pd.DataFrame:
+    df = employee.merge(department, left_on='departmentId', right_on='id', how='inner')
+    max_salary = df.groupby('departmentId')['salary'].transform('max')
+    df = df[df['salary'] == max_salary]
+    return (df[['name_y', 'name_x', 'salary']]
+            .rename(columns= {'name_y': 'Department', 'name_x': 'Employee', 'salary': 'Salary'}))

138_rank_scores.py

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+# Perform Dense Rank on the scores (descending order) and return two columns (scores and rank) in sorted
+# ascending order of rank.
+
+import pandas as pd
+
+def order_scores(scores: pd.DataFrame) -> pd.DataFrame:
+    scores['rank'] = scores['score'].rank(method='dense', ascending=False)
+    return scores[['score', 'rank']].sort_values(by=['rank'])