App Intel

DataLab - Python Coding & AI

LiveKKLabs4 apps · 145 installsToolsFreeIn-app purchases: $9.99 per itemcom.kklabs.datalab

Analyze data, Data Science, Machine learning, Code in PYthon and Learn AI

Alert me★ WatchOpen in Play ↗
Total installs
80
exact · Play shows 50+
Installs / day
0
since last crawl
Rating
—★
— ratings · — reviews
Released
24 Aug 2026
2mo ago
Last update
17 Sept 2026
v2.0.0 · 25d ago
Countries
—
not checked yet

Install history

exact counter from Google Play
78.183.689.194.510011 Oct12 Oct12 Oct
78.183.689.194.510011 Oct12 Oct12 Oct

Installs per day · last 90 days

Not enough history yet — check back tomorrow

Change timeline

No changes recorded yet. We compare every crawl with the previous one and list title, icon, screenshots, description, version, price and availability changes here.

Country availability

Availability has not been checked for this app yet. “Check all countries” looks the app up in about 140 Google Play storefronts and shows where it is live, listed but not installable, or missing — plus any country-specific (custom) store listings.

Top countries

Country data will be available soon.

We estimate where downloads come from using the app’s position in Google Play’s top charts in about 140 countries. This app is not in any chart we have collected yet; the estimate appears as soon as it is.

Top chart positions

Not in any tracked top chart.

App manifest

Read this app's manifest from Google Play: permissions, declared SDKs, components and AdMob app ID. Saved analysis appears here automatically.

Manifest analysis reads only the required APK ranges. Base APK downloads may need separate device splits to install.

Data safety

declared by the developer on Google Play
  • No data shared with third parties
  • Collects data Personal info and Files and docs
  • Data is encrypted in transit
  • You can ask for your data to be deleted

This is the developer's own declaration, summarised from the Play listing. The permissions below show what the app is technically able to access.

Permissions

4 in 1 group
0 Sensitive1 Notable3 Routine
OtherNotable4

Access to miscellaneous device features that don't fit other categories

  • Keep your phone's processor or screen from going to sleep, which can use more batteryprevent device from sleeping · WAKE_LOCK
  • Check whether you are online and whether you use Wi-Fi or mobile dataview network connections · ACCESS_NETWORK_STATE
  • Connect to the internet to load content and send datafull network access · INTERNET
  • Check with Google Play that you got this app legitimatelyGoogle Play license check · com.android.vending.CHECK_LICENSE

Sensitive = can reach personal data, location, camera/mic or act on your behalf. Notable = changes how your device behaves. Routine = normal for almost every app. Source: Google Play's permission list for all versions of this app.

Store listing

Full description
DataLab is a data science, machine learning and Python app that fits in your pocket. Upload a CSV or Excel file, clean your data, train AI models, write Python code and learn artificial intelligence step by step, all on your Android phone. No account, no sign up, no laptop needed. DATA LAB: DATA ANALYSIS WITHOUT CODE • Upload CSV and Excel (XLSX, XLS) files, or start with free practice datasets • Data overview with statistics, charts, histograms and a correlation heatmap • Explore relationships between two columns with scatter plots and charts • Fix data issues: rename columns, replace values, remove columns • Smart Clean finds problems and fixes them in one tap • Handle missing values, duplicates, outliers, data types, scaling and encoding • Undo any step and see your full cleaning history MACHINE LEARNING MODELS • Predict a column with regression or classification, detected automatically • Get a suggested model for your data • Train Logistic Regression, Linear Regression, Decision Tree, Random Forest, KNN, SVR and XGBoost • Model Leaderboard trains every model at once and ranks them • Accuracy, precision, recall, F1, R², confusion matrix and feature importance • Make predictions on new values and download the trained model • Clustering with K-Means, DBSCAN and Agglomerative to discover hidden groups, with an elbow chart • Export a clustering report as PDF PYTHON ON YOUR PHONE • Real Python 3 with NumPy and pandas that runs offline, right on your device • One-time download of about 21 MB, not bundled into the app • Optional packs: scikit-learn for machine learning, matplotlib for charts • Code editor with syntax highlighting, output console and charts • Ready-made templates for data analysis and machine learning • Export every Data Lab step as Python code and run it in the playground LEARN AI STEP BY STEP • 5 beginner friendly courses: Python for AI, Working with Data, Machine Learning Foundations, Finding Patterns and Neural Networks from Scratch • 30 short interactive lessons with runnable code examples • Quizzes, challenges, XP, levels and daily streaks • Final quiz and a shareable certificate for each course • "Learn why" links explain every Data Lab step as you use it WHO IS DATALAB FOR? Students, beginners, data analysts, data science learners, teachers and anyone curious about artificial intelligence. Use it to practice data analysis, prepare for exams, learn Python programming, understand machine learning algorithms or explore your own spreadsheets. PRIVATE AND SIMPLE No login and no personal account. Your datasets are processed only to run your analysis. Python code runs locally on your phone. FREE WITH ADS DataLab is free and supported by ads. Go ad free anytime with a low monthly subscription. Download DataLab and turn your phone into a data science lab, a Python IDE and an AI classroom.

What's new

• New look: three sections, Data Lab, Code and Learn • Run real Python offline with NumPy, pandas, scikit-learn and matplotlib • 5 interactive AI courses with quizzes, XP and certificates • Smart Clean, undo history and a Model Leaderboard • Regression or classification detected automatically, with a suggested model • No sign in needed, plus export your steps as Python code

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