PR #132, 133, 134: Radhika

132_calculate_special_bonus.py

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+# Create new column 'bonus' with if else condition such that 'bonus' == 'salary' if employee_id is even
+# and the 'name' does not start with M. Sort the resulting df and return in ascending order of id.
+
+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)
+    return employees[['employee_id', 'bonus']].sort_values(by=['employee_id'])

133_fix_names_in_table.py

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+# Changed the 'name' by using the function 'str.capitalize()' and return the resulting df in ascending
+# user_id.
+
+import pandas as pd
+
+def fix_names(users: pd.DataFrame) -> pd.DataFrame:
+    users['name'] = users['name'].str.capitalize()
+    return users.sort_values(by=['user_id'])

134_patients_with_condition.py

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+# Since there are multiple conditions, we need to look for two things, conditions that startswith 'DIAB1'
+# and conditions that contain ' DIAB1'. Note the "contain" has a blank space at the start for the spaces
+# between words.
+
+import pandas as pd
+
+def find_patients(patients: pd.DataFrame) -> pd.DataFrame:
+    df = patients[(patients['conditions'].str.startswith('DIAB1')) | \
+        (patients['conditions'].str.contains(' DIAB1'))]
+    return df