Completed Pandas3

Problem 1.py

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+# Calculate Special Bonus
+
+import pandas as pd
+
+def calculate_special_bonus(employees: pd.DataFrame) -> pd.DataFrame:
+    employees['bonus'] = employees.apply(lambda x : x['salary']
+                                         if x['employee_id'] % 2 and
+                                         not x['name'].startswith('M')
+                                         else 0, axis = 1)
+    df = employees[['employee_id', 'bonus']].sort_values('employee_id')
+    print(df)
+    return df
+
+data = [[2, 'Meir', 3000], [3, 'Michael', 3800], [7, 'Addilyn', 7400], [8, 'Juan', 6100], [9, 'Kannon', 7700]]
+employees = pd.DataFrame(data, columns=['employee_id', 'name', 'salary']).astype({'employee_id':'int64', 'name':'object', 'salary':'int64'})
+calculate_special_bonus(employees)

Problem 2.py

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+# Fix Names in a Table
+
+import pandas as pd
+
+def fix_names(users: pd.DataFrame) -> pd.DataFrame:
+    users['name'] = users['name'].str.capitalize()
+    print(users)
+    return users.sort_values(by = 'user_id')
+
+data = [[1, 'aLice'], [2, 'bOB']]
+users = pd.DataFrame(data, columns=['user_id', 'name']).astype({'user_id':'Int64', 'name':'object'})
+fix_names(users)

Problem 3.py

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+# Patients with a Condition
+
+import pandas as pd
+
+def find_patients(patients: pd.DataFrame) -> pd.DataFrame:
+    patients = patients[patients['conditions'].str.startswith('DIAB1') | patients['conditions'].str.contains(' DIAB1')]
+    print(patients)
+    return patients
+
+data = [[1, 'Daniel', 'YFEV COUGH'], [2, 'Alice', ''], [3, 'Bob', 'DIAB100 MYOP'], [4, 'George', 'ACNE DIAB100'], [5, 'Alain', 'DIAB201']]
+patients = pd.DataFrame(data, columns=['patient_id', 'patient_name', 'conditions']).astype({'patient_id':'int64', 'patient_name':'object', 'conditions':'object'})
+find_patients(patients)