Kolanut Distribution · Human resources
Analyse attendance, lateness and leave across departments, and what staff turnover looks like.
Kolanut Distribution has six departments, and 80 people have worked there since it started keeping records. The HR manager has noticed more lateness in some teams and has had several resignations, but decisions so far have been based on impressions.
HR has June 2026 attendance, leave records since January 2025, and a list of everyone who has worked at the company.
Prepare an HR review for the management team: where lateness and absence are highest, how leave is used, who is leaving, and how pay compares across levels.
Kolanut Distribution (HR). The distributor's 80 staff, their June 2026 attendance, and leave records since January 2025.
3 files · 1,675 rows in total · 46 kB. Download everything as a ZIP.
1,518 rows · 4 columns · 38 kB
Daily attendance for June 2026, one row per employee per working day.
| Column | Type | Description | Values | Missing |
|---|---|---|---|---|
| date | Date | Working day. | 2026-06-01 to 2026-06-30 | None |
| employee_id | Number | Links to employees.employee_id. | 1,004 to 1,080 | None |
| status | Text | Present, Late, Absent or On leave. | 4 distinct | None |
| hours_worked | Number | Hours worked that day (0 when absent or on leave). | 0 to 9 | None |
80 rows · 8 columns · 5 kB
Everyone who has worked at Kolanut, including people who have left.
| Column | Type | Description | Values | Missing |
|---|---|---|---|---|
| employee_id | Number | Unique employee number. | 1,001 to 1,080 | None |
| full_name | Text | Employee's name. | 76 distinct | None |
| department | Text | Finance, Operations, Customer Service, Human Resources, Sales or IT. | 6 distinct | None |
| job_level | Text | Junior, Mid, Senior or Manager. | 4 distinct | None |
| hire_date | Date | Date they joined. | 2018-01-22 to 2026-03-02 | None |
| exit_date | Date | Date they left. Blank if still employed. | 2019-04-10 to 2026-08-01 | 69 |
| monthly_salary | Number | Monthly salary in naira. | 180,000 to 1,565,000 | None |
| status | Text | Active or Resigned. | 2 distinct | None |
77 rows · 7 columns · 3 kB
Leave requests since January 2025.
| Column | Type | Description | Values | Missing |
|---|---|---|---|---|
| leave_id | Number | Unique leave request number. | 1 to 77 | None |
| employee_id | Number | Links to employees.employee_id. | 1,002 to 1,080 | None |
| leave_type | Text | Annual, Sick or Compassionate. | 3 distinct | None |
| start_date | Date | First day of leave. | 2025-01-05 to 2026-06-25 | None |
| end_date | Date | Last day of leave. | 2025-01-09 to 2026-07-06 | None |
| days | Number | Number of days requested. | 1 to 15 | None |
| approved | Text | Yes or No. | 2 distinct | None |
Starter code to get you going. The Python runs as it is in Google Colab: it loads the data straight from this site. For SQL, import each CSV as a table with the same name as the file.
SQLLateness and absence by department
SELECT e.department,
COUNT(*) AS staff_days,
ROUND(100.0 * SUM(a.status = 'Late') / COUNT(*), 1) AS late_pct,
ROUND(100.0 * SUM(a.status = 'Absent') / COUNT(*), 1) AS absent_pct
FROM attendance a
JOIN employees e ON e.employee_id = a.employee_id
GROUP BY e.department
ORDER BY late_pct DESC;PythonResignation rate by department
import pandas as pd
employees = pd.read_csv("https://academy.cloudtechanalytics.com/datasets/hr/employees.csv")
rate = employees.groupby("department")["status"].apply(lambda s: (s == "Resigned").mean() * 100)
rate.round(1).sort_values(ascending=False)Put your work on GitHub with a short README, add it to your portfolio, and share what you found. The Git & GitHub and Student Portfolio courses show you how.