DataLens — Automated Dataset Health Checker 📊 Stop repeating dataset checks. Start understanding...DataLens — Automated Dataset Health Checker 📊 Stop repeating dataset checks. Start understanding...
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Back to feedPost
Salma's avatar
Salma Belaicha
• Sep 19
DataLens — Automated Dataset Health Checker 📊
Stop repeating dataset checks. Start understanding your data.
Every new data project begins with the same routine:
Check missing values. Inspect data types. Find outliers. Explore distributions. Calculate statistics.
You write Python code, run Jupyter Notebook cells, and repeat the process—again and again.
What if you could automate that first step?
Meet DataLens
DataLens is an interactive dataset health-checking platform built to make data inspection faster, simpler, and more actionable.
Instead of manually running the same checks for every dataset, simply upload your file and explore its health report in one place.
🚀 What can you do with DataLens?
📊 Automated Dataset Overview Understand your dataset's dimensions, column types, and key statistics at a glance.
🔎 Detailed Column Profiles Explore individual features and discover patterns that deserve attention.
⚠️ Data Quality Checks Identify potential issues such as missing values and outliers before they affect your analysis or ML workflow.
💡 Actionable Recommendations Get practical suggestions to help guide your data-cleaning and preparation decisions.
📋 Dataset Preparation Checklist Review important steps before moving forward with your analysis or model training.
🗂️ Raw Data Exploration Inspect actual dataset records directly within the platform.
Who is DataLens for?
Data Science students
Machine Learning practitioners
Data analysts
Python and Jupyter Notebook users
Anyone who regularly works with new datasets
Why I built it
I wanted to simplify one of the most repetitive parts of data science: the initial dataset inspection.
DataLens helps turn that routine into a structured workflow, so you can spend less time repeating basic checks and more time understanding your data.
It's not about replacing data scientists or eliminating EDA.
It's about making the first step more efficient, organized, and actionable.
🛠️ Built with
Python · Streamlit · Data Analysis
DataLens: Upload your dataset. Discover potential issues. Get recommendations.
Because better data preparation starts with better data understanding.
StreamlitData Analysismachinelearning
Post image
Post image
Back to feed
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started