Pandas3: Problem Solutions_RN32MAY2025DS

CalculateSpecialBonus.py

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+#Method 1:
+import pandas as pd
+
+def calculate_special_bonus(employees: pd.DataFrame) -> pd.DataFrame:
+
+    result = []
+    for i in range(len(employees)):
+        eid = employees['employee_id'][i]
+        ename = employees['name'][i]
+        esal = employees['salary'][i]
+
+        if eid % 2 == 1 and ename[0] != 'M':
+            bonus = esal
+        else:
+            bonus = 0
+        result.append([eid,bonus])
+    return pd.DataFrame(result, columns = ['employee_id','bonus']).sort_values(['employee_id'])
+
+#Method 2:
+
+import pandas as pd
+
+def calculate_special_bonus(employees: pd.DataFrame) -> pd.DataFrame:
+    condition = (employees['employee_id'] % 2 == 1) & (~employees['name'].str.startswith('M'))
+    employees['bonus'] = employees['salary'].where(condition,0)
+    return employees[['employee_id','bonus']].sort_values(by = ['employee_id'])

FixNamesInATable.py

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+# Method 1
+import pandas as pd
+
+def fix_names(users: pd.DataFrame) -> pd.DataFrame:
+    result = []
+    for i in range(len(users)):
+        name = users['name'][i]
+        uid = users['user_id'][i]
+
+        new_name = name[0].upper() + name[1:].lower()
+
+        result.append([uid,new_name])
+    return pd.DataFrame(result, columns = ['user_id','name']).sort_values(['user_id'])
+
+# # Method 2
+
+import pandas as pd
+
+def fix_names(users: pd.DataFrame) -> pd.DataFrame:
+    result = []
+    for i in range(len(users)):
+        name = users['name'][i]
+        uid = users['user_id'][i]
+
+        new_name = name.capitalize()
+        # new_name is taking one string at a time. If we had taken the whole column users['name'] then we would write it as name.str.capitalize()
+
+        result.append([uid,new_name])
+    return pd.DataFrame(result, columns = ['user_id','name']).sort_values(['user_id'])

PatientsWithACondition.py

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+import pandas as pd
+
+def find_patients(patients: pd.DataFrame) -> pd.DataFrame:
+    cond = (patients['conditions'].str.startswith('DIAB1'))|(patients['conditions'].str.contains(' DIAB1'))
+    return patients[cond]