01Manufacturing15 cols · 200 rows
Manufacturing Quality Control Dataset
| shift | quality_score | defect_type |
|---|---|---|
| afternoon | 99.7 | – |
| morning | 87.4 | – |
| night | 81.1 | scratch |
batch_iddefect_severityrework_required+9 more
1,947 ready-made datasets.
Realistic data for dashboards, models and teaching. Your first download is free.
- No quick match. Search the full library, or make it yourself below.
- 19 industries
- 8 formats, from CSV to Parquet
- Commercial use allowed
Healthcare22 cols · 200 rowsHospital Readmission Prediction
| patient_id | age | primary_diagnosis_code | readmitted |
|---|---|---|---|
| PAT-0001 | 32 | I10 | false |
| PAT-0002 | 71 | I50 | true |
| PAT-0003 | 85 | J18 | false |
| PAT-0004 | 8 | J45 | false |
Finance17 cols · 200 rowsBank Transaction Categorization Sample
| merchant_name | amount | category |
|---|---|---|
| Whole Foods Market | -95.32 | groceries |
| ACME Corp | 2500 | income |
| Netflix | -56.8 | entertainment |
Social Media14 cols · 200 rowsSocial Media Sentiment Dataset
| post_content | post_sentiment_label |
|---|---|
| Happy New Year! Wishing everyone a joyful 2024. | positive |
| Had a tough day at work. Wish things would improve. | negative |
Browse by industry.
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- 248Financee.g. Bank Transaction Categorization Sample
- 221Healthcaree.g. Pharmacy Inventory Sales Forecast
- 205Logisticse.g. Warehouse Inventory Flow Dataset
- 140Energye.g. Smart Grid Fault Detection Dataset
- 101Telecommunicationse.g. Radio Access Network (RAN) Key Performance Indicators (KPIs)
- 90Human Resourcese.g. Employee Attrition Prediction Dataset
- 90Manufacturinge.g. Manufacturing Quality Control Dataset
- 89Educatione.g. Student Performance Tracking
- 89Agriculturee.g. Agtech Crop Yield Prediction
- 88Governmente.g. Smart Bin Sensor Fill Levels
- 83Technologye.g. IT Service Ticket Classification
- 79Gaminge.g. Game User Behavior Dataset
- 78Real Estatee.g. PropTech Rental Listings Dataset
- 78Transportatione.g. Smart Traffic Light Sensor Data
- 68E-commercee.g. Online Retail Product Return Analytics
- 66Insurancee.g. Medical Insurance Fraud Detection
- 63Marketinge.g. Social Media Ad Performance Dataset
- 36Social Mediae.g. Social Media Sentiment Dataset
- 32Othere.g. Retail In-Store Foot Traffic Counts
- Not listed?Describe the dataset you need and preview it.
Most opened this month.
Browse all 1,94702Technology20 cols · 200 rows
IT Service Ticket Classification
| ticket_subject | category | priority |
|---|---|---|
| Laptop battery fails to charge | hardware | medium |
| Cannot print from office printer | hardware | high |
| Server room temperature alert | hardware | critical |
departmentstatusurgency+14 more
03Finance17 cols · 200 rows
Bank Transaction Categorization Sample
| merchant_name | amount | category |
|---|---|---|
| Whole Foods Market | -95.32 | groceries |
| ACME Corp | 2500 | income |
| Netflix | -56.8 | entertainment |
posting_dateis_recurringmerchant_category_code+11 more
04Finance20 cols · 200 rows
Finance Expense Categorization Dataset
| merchant_name | amount | category |
|---|---|---|
| The Grove Bistro | 53.25 | Food |
| Pacific Utilities | 0 | Other |
| Netflix Australia | 19.99 | Entertainment |
currencyis_business_expensereceipt_available+14 more
05Manufacturing9 cols · 200 rows
Manufacturing Line Defect Counts
| shift | defect_type | defect_rate |
|---|---|---|
| Morning | Surface | 0.01 |
| Afternoon | Mechanical | 0 |
| Night | Electrical | 0.12632 |
production_lineproduct_typetotal_units_produced+3 more
06E-commerce22 cols · 200 rows
Online Retail Product Return Analytics
| product_name | return_reason | refund_amount |
|---|---|---|
| UltraHD Smart TV 55in | defective | 449.99 |
| Womens Summer Dress L | size issue | 39.99 |
| Modern Floor Lamp Black | not as described | 125 |
time_to_return_daysreturn_methodcustomer_country+16 more
No. 1 most opened · Manufacturing
Manufacturing Quality Control Dataset
200 inspected batches from 6 factories, across three shifts.
Already in the data: 47 of 52 night batches need rework.
Free account, no card. CSV, Excel, JSON and 5 more formats.
| batch_id | shift | quality_score | defect_type | rework_required |
|---|---|---|---|---|
| A1234-20240601 | afternoon | 99.7 | – | false |
| B0876-20240602 | morning | 87.4 | – | false |
| C4218-20240603 | night | 81.1 | scratch | false |
| F5921-20240605 | afternoon | 61.4 | misalignment | true |
| G7423-20240606 | night | 59.2 | contamination | true |
| K5182-20240609 | night | 3.2 | major_crack | true |
Night-shift rows
Or start from the job.
A date, things to slice by, numbers to sum. Made for Power BI, Tableau and Excel.
- sum(total_amount) by payment_method
- sum(ar_balance) by aging_bucket
- sum(foot_traffic_count) by day_of_week
- rows by academic_standing
A column to predict, shown with its real class balance.
- readmitted = true 31 of 200 rows
- is_fraud = true 26 of 200 rows
- attrition = true 27 of 200 rows
- application_status = declined 56 of 200 rows
Free text with a label to learn from.
- “Had a tough day at work. Wish things would improve.”post_sentiment_label → negative
- “Disappointed with the quality, not what I expected.”star_rating → 2
- “Where can I report illegal dumping in my neighborhood?”query_topic → environment
- “Non-displaced fifth metacarpal fracture.”report_classification → Abnormal
Who stays, who leaves, and the columns that hint why.
- subscription_status = cancelled 12 of 200 rows
- retention_status = churned 10 of 200 rows
- churned = true 45 of 200 rows
- churn_flag = true 28 of 200 rows
Close, but not quite?
Start from a library dataset and say what to change.
From the library200 rows · 15 columns
Manufacturing Quality Control| batch_id | shift | quality_score | factory_location |
|---|---|---|---|
| A1234-20240601 | afternoon | 99.7 | Factory-E1 |
| B0876-20240602 | morning | 87.4 | Factory-Y7 |
| C4218-20240603 | night | 81.1 | Factory-Z3 |
Change
Yours10,000 rows · 15 columns
Your version| batch_id | shift | quality_score | factory_location |
|---|---|---|---|
| A1234-20240601 | afternoon | 99.7 | Sheffield |
| B0876-20240602 | morning | 87.4 | Derby |
| C4218-20240603 | night | 81.1 | Sunderland |
No signup, no card. When it looks right, 10,000 rows cost $12.99, one-off.