diff --git a/Problem 1: Nth Highest Salary b/Problem 1: Nth Highest Salary
new file mode 100644
index 0000000..5fc0bfd
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+++ b/Problem 1: Nth Highest Salary	
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+import pandas as pd
+
+def nth_highest_salary(employee: pd.DataFrame, N: int) -> pd.DataFrame:
+    #Using Pandas
+    df = employee[['salary']].drop_duplicates()
+    if N > len(df) or N<=0:
+        return pd.DataFrame({f'getNthHighestSalary({N})' : [None]})
+    return df.sort_values('salary', ascending = False).head(N).tail(1)[['salary']].rename(columns = {'salary': f'getNthHighestSalary({N})'})
+
+    #Using Python
+    result = []
+    for i in range(len(employee)):
+        salary = employee['salary'][i]
+        if salary not in result:
+            result.append(salary)
+    result.sort(reverse = True)
+    if N > len(result) or N <= 0:
+        return pd.DataFrame ({f'getNthHighestSalary({N})' : [None]})
+    return pd.DataFrame({f'getNthHighestSalary({N})' : [result[N-1]]})
+
+    #Using Set
+    result_set = set()
+    for i in range(len(employee)):
+        salary = employee['salary'][i]
+        result_set.add(salary)
+    result = []
+    for element in result_set:
+        result.append(element)
+    result.sort(reverse = True)
+    if N > len(result) or N <= 0:
+        return pd.DataFrame ({f'getNthHighestSalary({N})' : [None]})
+    return pd.DataFrame({f'getNthHighestSalary({N})' : [result[N-1]]})
+
diff --git a/Problem 2: Second Highest Salary b/Problem 2: Second Highest Salary
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index 0000000..ec96f21
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+++ b/Problem 2: Second Highest Salary	
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+import pandas as pd
+
+def second_highest_salary(employee: pd.DataFrame) -> pd.DataFrame:
+    all_salaries = set()
+    for i in range(len(employee)):
+        salary = employee ['salary'][i]
+        all_salaries.add(salary)
+    result = []
+    for salary in all_salaries:
+        result.append(salary)
+    result.sort(reverse = True)
+    if len(result)<2:
+        return pd.DataFrame([None], columns = ['SecondHighestSalary'])
+    return pd.DataFrame([result[1]], columns = ['SecondHighestSalary'])
+
+ #Using Pandas
+     employee = employee.drop_duplicates(['salary'])
+    if len(employee) < 2:
+        return pd.DataFrame({'SecondHighestSalary' : [np.NaN]})
+    employee.sort_values(by=['salary'], ascending = False, inplace= True)
+    employee.drop('id', axis = 1, inplace= True)
+    employee.rename(columns = {'salary': 'SecondHighestSalary'}, inplace= True)
+    return employee.head(2).tail(1)
+    
+