Loading repository dataβ¦
Loading repository dataβ¦
itsluckysharma01 / repository
πThis repository contains a comprehensive collection of π50+ datasets spanning various domains including healthcare, πentertainment, transportation, demographics, and more.
β¨ A curated collection of 70+ diverse datasets for data science, machine learning, and analytics projects
β¬οΈ Get Started β’ π View All Datasets β’ π― Find Your Dataset
| π¦ Total Files | π Categories | β Beginner Friendly | π₯ Updated |
|---|---|---|---|
| 70+ | 11 | 15+ | Regularly |
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β β
β π¬ Data Science β π€ Machine Learning β
β π Analytics β π Learning & Teaching β
β πΌ Business Projects β π Competitions & Kaggle β
β β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
This repository contains a comprehensive collection of 70+ datasets spanning various domains including healthcare, entertainment, transportation, demographics, finance, and more. Each dataset is carefully organized and ready for analysis!
β¨ 70+ Curated Datasets | π― Well-Organized | π Documented | π Ready to Use | π Quality Verified
| π₯ Healthcare | π¬ Entertainment | π Transport | π Real Estate | π Demographics |
|---|---|---|---|---|
| 8+ Datasets | 8+ Datasets | 3+ Datasets | 2+ Datasets | 2+ Datasets |
| π Explore | π Explore | π Explore | π Explore | π Explore |
| π° Finance | π Education | π¬ Science | π Forecasting | πΎ Environment |
|---|---|---|---|---|
| 5+ Datasets | 3+ Datasets | 5+ Datasets | 4+ Datasets | 3+ Datasets |
| π Explore | π Explore | π Explore | π Explore | π Explore |
Each category includes dataset descriptions, file names, use cases, and difficulty levels!
Medical data for health analytics and prediction models
| Dataset | File | Purpose | Type | Level |
|---|---|---|---|---|
| π Diabetes Prediction | diabetes.csv, diabetes1.csv | Classification for diabetes risk | Classification | π’ Beginner |
| π₯ Health Camp Data | Health_Care_Dataset/ | Multi-camp attendance analysis | Analytics | π‘ Intermediate |
| β€οΈ Heart Disease | gfg_heart.csv, heart_disease_uci.csv | Cardiology prediction | Classification | π’ Beginner |
| π° Medical Costs | medical_cost_gfg.csv | Healthcare expense analysis | Regression | π’ Beginner |
| π Clothing Reviews | RNN_Clothing-Review.csv | NLP sentiment analysis | NLP | π΄ Advanced |
π‘ Quick Start Code:
import pandas as pd
df = pd.read_csv('diabetes.csv')
print(df.shape) # View dimensions
df.describe() # Get statistics
df.isnull().sum() # Check for missing values
Streaming platforms, movies, and content analysis data
| Dataset | File | Purpose | Type | Level |
|---|---|---|---|---|
| π₯ Netflix | Netflix_titles.csv, Netflix_credits.csv | Content analysis & trends | Analysis | π’ Beginner |
| πΊ HBO Content | HBO_titles.csv, HBO_credits.csv | Streaming platform comparison | Comparison | π’ Beginner |
| π¬ IMDB Dataset | IMDB-Dataset.csv | Movie database analysis | Analysis | π’ Beginner |
| π΅ Box Office | gfg_boxoffice.csv | Revenue & performance metrics | Analysis | π’ Beginner |
| π₯ Trending Data | Trending/trending.csv | Social media trends | TimeSeries | π‘ Intermediate |
π‘ Quick Start Code:
netflix = pd.read_csv('Netflix_titles.csv')
netflix['type'].value_counts() # Content distribution
netflix.groupby('country').size() # Country analysis
Vehicle data, traffic, and transportation analytics
| Dataset | File | Purpose | Type | Level |
|---|---|---|---|---|
| π Cars Dataset | Project_2_Cars_Dataset.csv | Vehicle specs & pricing | Regression | π’ Beginner |
| π¨ Police Data | Project_3_Police Data.csv | Traffic & incidents | Analysis | π‘ Intermediate |
| βοΈ Vehicle Failure | vehicle_failure.csv | Maintenance prediction | Classification | π‘ Intermediate |
Housing market and property data
| Dataset | File | Purpose | Type | Level |
|---|---|---|---|---|
| π‘ Housing Data | Project_5_Housing_Data.csv, House_Price_India.csv | Price prediction & analysis | Regression | π’ Beginner |
Population and demographic statistics
| Dataset | File | Purpose | Type | Level |
|---|---|---|---|---|
| π Census 2011 | Project_6_Census_2011.csv | Population statistics | Analysis | π‘ Intermediate |
| π₯ Demographics | demographics.csv, dermographic data.csv | Demographic analysis | Analysis | π’ Beginner |
Financial and business-related datasets
| Dataset | File | Purpose | Type | Level |
|---|---|---|---|---|
| π Loan Datasets | gfg_LoanDataset---LoansDatasest.csv, loan_approval_dataset.csv | Loan approval prediction | Classification | π‘ Intermediate |
| π Churn Modeling | Churn_Modelling_gfg.csv | Customer retention analysis | Classification | π‘ Intermediate |
| π Employee Attrition | MFG10YearTerminationData(EMPLOYEE-ATTRITION).csv | Workforce analytics | Classification | π‘ Intermediate |
| π Stock Data | stock_data.csv | Market analysis | TimeSeries | π‘ Intermediate |
Educational resources and student data
| Dataset | File | Purpose | Type | Level |
|---|---|---|---|---|
| π― Udemy Courses | Project_7_Udemy_Dataset.csv, Udmey Data/ | Course analysis & pricing | Analysis | π’ Beginner |
| π Student Performance | student-pass-fail-data.csv | Academic prediction | Classification | π’ Beginner |
| ποΈ Mall Customers | gfg_Mall_Customers-.csv | Customer segmentation | Clustering | π‘ Intermediate |
Classic datasets perfect for learning and tutorials
| Dataset | File | Purpose | Type | Level |
|---|---|---|---|---|
| πΈ Iris | IRIS.csv | Classic classification | Classification | π’ Beginner |
| β Titanic | Titanic_dataset.csv, GFG_titanic.csv, Titanic_Dataset_SmartED.csv | Survival prediction | Classification | π’ Beginner |
| π· Wine Quality | redwinequality.csv, whitewinequality.csv | Quality |