Tutorial
Hands-on walkthroughs for SQL, Python, Excel and visualisation tools — every example is runnable, not a screenshot.
109 articles in Tutorial · Page 7 of 13
Customer Analytics in Python: Cohort Analysis, RFM Segmentation & LTV
Master customer analytics in Python with Pandas and Seaborn. Calculate RFM scores, build customer segments, run monthly cohort retention heatmaps, and estimate Customer Lifetime Value (LTV).
Relative vs Absolute Cell References in Excel (What $ Does)
Learn the difference between relative and absolute cell references in Excel. Discover what the dollar sign ($) does, when to press F4, and how to stop autofill drift.
Excel Charts for Analysts: Pick the Right Visual and Use Aggregation Intentionally
Choose the right Excel chart for the message. Learn column, line, pie, and combo visuals — and how Excel aggregates values before plotting.
How to Filter & Sort in Excel Without Mixing Data (Safe Guide)
Learn how to filter and sort in Excel without mixing up data or breaking rows. Fix filters stopping at blank rows and avoid the selection trap with Ctrl+T.
Excel for Data Analysts: Interface Tour in 6 Minutes
New to Excel for analytics? Tour the ribbon, grid, formula bar, and file basics that prevent silent errors — and find the right tab in seconds.
Best Free Datasets for Data Analyst Practice
Curated list of free datasets perfect for building your portfolio. From beginner-friendly to advanced real-world data.
Market Basket Analysis in Python: Support, Confidence, Lift & Apriori Explained
Master Market Basket Analysis and Association Rule Mining in Python. Learn the mathematical intuition behind Support, Confidence, and Lift, one-hot encode transaction baskets, and implement Apriori and FP-Growth using Pandas and Mlxtend.
REST APIs for Data Analysts in Python: Authentication, Pagination & JSON Normalization
Master REST API data extraction in Python. Learn how to handle Bearer tokens and API keys, loop through offset and cursor pagination, flatten nested JSON with pd.json_normalize(), and build fault-tolerant pipelines with automatic retries.
Python Exploratory Data Analysis (EDA): The Complete Step-by-Step Workflow
Master the complete 6-stage Python Exploratory Data Analysis (EDA) framework. Learn structured data inspection, missing value imputation, IQR outlier detection, distribution analysis, correlation heatmaps, and feature profiling.