diff --git a/Calculate Special Bonus.py b/Calculate Special Bonus.py
new file mode 100644
index 0000000..e9e3132
--- /dev/null
+++ b/Calculate Special Bonus.py	
@@ -0,0 +1,33 @@
+import pandas as pd
+
+def calculate_special_bonus(employees: pd.DataFrame) -> pd.DataFrame:
+    #sol1
+    # 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(by = 'employee_id')
+    
+    #sol2
+    # for i in range(len(employees)):
+    #     e_id = employees['employee_id'][i]
+    #     name = employees['name'][i]
+
+    #     if (e_id % 2 == 0) or (name[0] == 'M'):
+    #         employees['salary'][i] = 0
+    # df = employees[['employee_id', 'salary']]
+    # return df.rename(columns = {'salary':'bonus'}).sort_values(by = 'employee_id')    
+    
+    #sol3
+    employees['bonus'] = employees.apply(lambda x: x['salary'] if x['employee_id']%2 and not x['name'].startswith('M')
+    else 0, axis =1 )
+
+    return employees[['employee_id','bonus']].sort_values(by=['employee_id'])
+    
+    
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diff --git a/Fix Names in a Table.py b/Fix Names in a Table.py
new file mode 100644
index 0000000..2dbd078
--- /dev/null
+++ b/Fix Names in a Table.py	
@@ -0,0 +1,8 @@
+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()
+    users['name'] = users['name'].str.capitalize()
+    return users.sort_values(by =['user_id']) 
+
+    
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diff --git a/Patients With a Condition.py b/Patients With a Condition.py
new file mode 100644
index 0000000..0ed007d
--- /dev/null
+++ b/Patients With a Condition.py	
@@ -0,0 +1,26 @@
+import pandas as pd
+
+def find_patients(patients: pd.DataFrame) -> pd.DataFrame:
+    #sol1
+    # 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']) 
+
+    #sol2
+    # patients = patients[patients['conditions'].str.startswith('DIAB1')|
+    #                     patients['conditions'].str.contains(' DIAB1') ] 
+    # return patients      
+
+    #sol3
+    return patients[patients['conditions'].str.contains( r"(^|\s)DIAB1", regex =True)]                     
+    
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