Becoming a Data Scientist with a Spreadsheet
Becoming a data scientist might feel like a far-off goal, requiring coding skills, software, and technical training. But here’s the secret...
Here’s the secret: you can start your data science journey with something as simple as a spreadsheet. Today, I’ll talk about how to approach five essential data science techniques using just spreadsheet as a tool.
1. NOVA: Analyzing Cohorts and Predicting Outcomes
Imagine you run a small business and want to track customer retention. With a spreadsheet, you can use basic formulas and charts to analyze how different groups of customers behave over time.
Step 1: Organize Your Data
Group customers by the month they joined and track how many return each subsequent month. For example:
Step 2: Create a Heatmap
Use conditional formatting to color-code the cells. Higher numbers (bright colors) show strong retention, and lower numbers (fading colors) highlight drop-offs.
Questions
What percentage of customers stick around after 3 months?
Which cohort performs best?
2. Mixed Distribution Analysis: Finding Hidden Patterns
Suppose you’re a teacher looking at test scores from your students. Some students perform exceptionally, while others struggle. A spreadsheet can help you identify these groups.
Step 1: Calculate Averages
Find the average score for the entire class using:
Step 2: Identify Clusters
Sort the scores and split them into categories like "High Performers" and "Struggling Students." Use filters or pivot tables to count how many students fall into each group.
Questions
How many students are excelling, and how many need extra help?
Are there patterns based on age, gender, or study habits?
3. Mode Analysis on GPS Data: Understanding Movement
Let’s say you’re tracking locations for a delivery service. A spreadsheet can help you find the busiest areas and optimize routes.
Step 1: Input GPS Coordinates
List all delivery stops as pairs of latitude and longitude in your spreadsheet.
Step 2: Find High-Density Areas
Use a simple counting formula to identify where multiple deliveries occur in the same region. For example, group coordinates into ranges and count how many deliveries fall into each range.
Questions
Which areas have the most deliveries?
Can you consolidate stops to save time and fuel?
4. Image Classification: Organizing Visual Data
You don’t need fancy algorithms to classify images—you just need a plan. Let’s say you’ve scraped product images from websites and want to categorize them.
Step 1: Create a Labeling System
In your spreadsheet, list the image names in one column and add a “Category” column. Classify each image as "Shirt," "Pants," etc using OpenAI or Gemini API endpoints.
Step 2: Analyze Trends
Use pivot tables to count how many images fall into each category.
Questions
Which product categories are most common?
Are there trends that competitors are following?
5. Pathway Cost Optimization: Finding the Best Route
If you’re planning a trip or managing logistics, a spreadsheet can help you minimize costs.
Step 1: Create a Cost Table
List all possible routes, distances, and costs in a table. For example:
Step 2: Use Filters
Filter the table to find the route with the lowest cost or shortest distance.
Questions
What’s the cheapest way to travel or transport goods?
How can you adjust routes to save time and money?
Why Spreadsheets are your best friend
Spreadsheets are the ultimate tool for data science. They let you organize, analyze, and visualize data without requiring advanced technical software skills. More importantly, they teach you to think critically about data—an essential skill.
So, if you’ve ever wondered how to start your data science journey. Open up a spreadsheet and start experimenting.