📣 Hey guys, meet @Ezy007 - Data Analyst Track
I’d love to introduce Oladepo Ezekiel, a surgery resident doctor based in Ilorin, Kwara State, Nigeria.
Ezekiel is currently in his 5th year of residency training at the University of Ilorin Teaching Hospital, with a strong passion for surgical research, global surgery, and health system strengthening.
He’s officially starting his journey into data analysis — with the goal of applying it directly to his medical research work, improving how he collects, interprets, and presents surgical and health system data.
By the end of this program, he’s aiming to have:
A compelling personal/professional profile that reflects both his medical expertise and new data skills.
A clear roadmap for aligning his surgical career with global research and impact opportunities.
Practical strategies to showcase his work and expertise beyond the clinical space, backed by data-driven insights.
@Ezy007 Watch this 16 min tutorial. Then complete the task below.
🧠 Week 1 Task – Excel Practice Project
📊 Project Title: Analyze a Medical Test Dataset
⏰ Deadline: 24 hours
🎯 Goal: Practice key Excel skills - formatting, formulas, filtering, sorting, pivot tables, and charts — while exploring hospital test data.
Scenario:
You have just joined the hospital analytics team. Your manager has given you a dataset of patient tests, including test types, results, departments, costs, and test dates. Your task is to clean, summarize, and visualize key insights to help understand test distributions, costs, and result patterns.
Load the medical_test.csv file in Excel or Google Sheets.
Step 2 – Perform These Tasks
✅ Format the header row: bold, center align, and freeze top row.
✅ Adjust column widths so all content is visible.
✅ Create a new column called Test Month by extracting the month and year from the test_date column (format as MMM-YYYY).
✅ Use a pivot table or formulas to calculate:
• The total number of tests conducted by each test_type.
• The average cost of tests per department.
• The count of each result category (Normal, Critical, Abnormal).
✅ Apply conditional formatting to highlight tests with cost greater than 1000.
✅ Sort the data by test_date in ascending order.
✅ Filter the dataset to show only tests from the Neurology department.
✅ Create a bar chart showing total test counts per test_type.
✅ Create a line chart showing monthly average test costs across all departments.
What to Submit
📤 A screenshot (or short video) showing:
Your dataset with the Test Month column and at least one formula visible.
The pivot tables summarizing test counts by type, average cost by department, and result counts.
The bar chart of test counts per test type.
The line chart of monthly average test costs.
✏️ A short insight summary (1-2 sentences), for example:
"The Blood Test is the most frequent test type, while the Neurology department has the highest average test cost. Critical results occur most often in X-Ray tests.
