Completed Pandas3

01-CalculateSpecialBonus.py

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+# Problem 1 - Calculate Special Bonus ( https://leetcode.com/problems/calculate-special-bonus/)
+import pandas as pd
+
+def calculate_special_bonus(employees: pd.DataFrame) -> pd.DataFrame:
+    # Approach 1
+    # Condition 1 - Employee ID is odd
+    odd_id = employees['employee_id'] % 2 == 1
+
+    # Condition 2 - Employee's name does not start with 'M'
+    name_start = ~employees['name'].str.startswith('M')
+
+    # Combining both conditions
+    bonus = odd_id & name_start
+
+    # Employee bonus column
+    employees['bonus'] = employees['salary'].where(bonus, 0)
+
+    return employees[['employee_id', 'bonus']].sort_values(by = 'employee_id')
+
+    # Approach 2
+    result = []
+    for i in range(len(employees)):
+        employee_id = employees['employee_id'][i]
+        name = employees['name'][i]
+
+        if (employee_id % 2 != 0) and (name[0] != 'M'):
+            result.append([employee_id, employees['salary'][i]])
+        else:
+            result.append([employee_id, 0])
+
+    df = pd.DataFrame(result, columns = ['employee_id', 'bonus']).sort_values(by = ['employee_id'])
+    return df
+
+    # Approach 3
+    employees['bonus'] = employees.apply(lambda x : x['salary'] if x['employee_id'] % 2 != 0 and not x['name'].startswith('M') else 0, axis = 1)
+
+    return employees[['employee_id', 'bonus']].sort_values(by = ['employee_id'])

02-FixNamesInATable.py

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+# Problem 2 - Fix Names in a Table ( https://leetcode.com/problems/fix-names-in-a-table/ )
+import pandas as pd
+
+def fix_names(users: pd.DataFrame) -> pd.DataFrame:
+    # Approach 1
+    users['name'] = users['name'].str[0].str.upper() + users['name'].str[1:].str.lower()
+    return users.sort_values(by = ['user_id'])
+
+    # Approach 2
+    users['name'] = users['name'].str.capitalize()
+    return users.sort_values(by = ['user_id'])

03-PatientsWithACondition.py

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+# Problem 3 - Patients with a Condition ( https://leetcode.com/problems/patients-with-a-condition/)
+import pandas as pd
+
+def find_patients(patients: pd.DataFrame) -> pd.DataFrame:
+    # Approach 1
+    result = []
+    for i in range(len(patients)):
+        patient_id = patients['patient_id'][i]
+        patient_name = patients['patient_name'][i]
+        conditions = patients['conditions'][i]
+
+        for condition in conditions.split():
+            if condition.startswith('DIAB1'):
+                result.append([patient_id, patient_name, conditions])
+                break
+    return pd.DataFrame(result, columns = ['patient_id', 'patient_name', 'conditions'])
+
+    # Approach 2
+    return patients[patients['conditions'].str.contains(r"(^|\s)DIAB1", regex = True)]