Done

Problem 1 Calculate Special Bonus.py

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+#1873. Calculate Special bonus
+
+#Method 1: Through Python
+import pandas as pd
+
+def calculate_special_bonus(employees: pd.DataFrame) -> pd.DataFrame:
+      result = []
+    for i in range(len(employees)):
+        e_id = employees['employee_id'][i]
+        name = employees['name'][i]
+        if (e_id % 2 !=0) and (name[0])!='M':
+            result.append([e_id,employees['salary'][i]])
+        else:
+            result.append([e_id,0]) 
+    return pd.DataFrame(result,columns = ['employee_id','bonus']).sort_values('employee_id')
+
+
+#Method 2
+
+
+def calculate_special_bonus(employees: pd.DataFrame) -> pd.DataFrame:
+    df = employees.copy()
+    df['bonus'] = df.apply(
+        lambda row: row['salary'] if row['employee_id'] % 2 != 0 and row['name'][0] != 'M' else 0,
+        axis=1
+    )
+    return df[['employee_id','bonus']].sort_values('employee_id')

Problem 2 Fix Names in a Table.py

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+#1667 Fix Names in a table
+
+import pandas as pd
+
+def fix_names(users: pd.DataFrame) -> pd.DataFrame:
+    users['name'] = users['name'].str[0].str.upper()+users['name'].str[1:].str.lower()
+    return users.sort_values(by=['user_id'])

Problem 3 Patients with a condition.py

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+import pandas as pd
+
+def find_patients(patients: pd.DataFrame) -> pd.DataFrame:
+    result = []
+    for i in range(len(patients)):
+        p_id = patients['patient_id'][i]
+        p_name = patients['patient_name'][i]
+        conditions = patients['conditions'][i]
+        for condition in conditions.split():
+            if condition.startswith('DIAB1'):
+                result.append([p_id,p_name,conditions])
+
+    return pd.DataFrame(result, columns =['patient_id','patient_name','conditions'])     
+