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39 changes: 39 additions & 0 deletions README.md
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1 Problem 1 :Calculate Special Bonus ( https://leetcode.com/problems/calculate-special-bonus/)

Write a solution to calculate the bonus of each employee. The bonus of an employee is 100% of their salary if the ID of the employee is an odd number and the employee's name does not start with the character 'M'. The bonus of an employee is 0 otherwise.

Return the result table ordered by employee_id.

The result format is in the following example.


------------------------------------------------
import pandas as pd

def calculate_special_bonus(employees: pd.DataFrame) -> pd.DataFrame:
employees['bonus'] = employees.apply(
lambda row: row['salary'] if row['employee_id'] % 2 == 1 and not row['name'].startswith('M') else 0,
axis=1
)
return employees[['employee_id', 'bonus']].sort_values('employee_id')


2 Problem 2 : Fix Names in a Table ( https://leetcode.com/problems/fix-names-in-a-table/ )

Write a solution to fix the names so that only the first character is uppercase and the rest are lowercase.

Return the result table ordered by user_id.

The result format is in the following example.
------------------------------------------------

import pandas as pd

def fix_names(users: pd.DataFrame) -> pd.DataFrame:
users['name'] = users['name'].str.capitalize()
return users.sort_values('user_id')


3 Problem 3 : Patients with a Condition ( https://leetcode.com/problems/patients-with-a-condition/)

Write a solution to find the patient_id, patient_name, and conditions of the patients who have Type I Diabetes. Type I Diabetes always starts with DIAB1 prefix.

Return the result table in any order.

The result format is in the following example.
------------------------------------------------

import pandas as pd

def patients_with_a_condition(patients: pd.DataFrame) -> pd.DataFrame:
return patients[patients['conditions'].str.contains(r'\bDIAB1', regex=True)]