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Merge pull request #19 from qalita-io/test/add-testing-cases
make run.sh executables
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**/__pycache__/ | ||
poetry.lock | ||
source_conf.json | ||
target_conf.json | ||
docker-compose.yml | ||
metrics.json | ||
recommendations.json | ||
schemas.json | ||
*.html | ||
*_report.json | ||
*.xlsx | ||
*_metrics.json | ||
*_recommendations.json | ||
*_schemas.json |
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{ | ||
"config": { | ||
"path": "../data/early-stage-diabetes/diabetes_data_upload.xlsx" | ||
}, | ||
"description": "Sign and Symptom Data of Newly Diabetic or would be Diabetic Patient", | ||
"name": "Early Stage Diabetes Risk Prediction Dataset", | ||
"reference": false, | ||
"sensitive": false, | ||
"type": "file", | ||
"visibility": "public" | ||
} |
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{ | ||
"config": { | ||
"path": "../data/heart-failure-prediction-dataset/heart.xlsx" | ||
}, | ||
"description": "11 clinical features for predicting heart disease events.", | ||
"name": "Heart Failure Prediction Dataset", | ||
"reference": false, | ||
"sensitive": false, | ||
"type": "file", | ||
"visibility": "public" | ||
} |
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{ | ||
"config": { | ||
"path": "../data/heart-stroke-prevention/dataset.csv" | ||
}, | ||
"description": "Provides a comprehensive image for cardiovascular diseases & related prevention", | ||
"name": "Heart Disease and Stroke Prevention", | ||
"reference": false, | ||
"sensitive": false, | ||
"type": "file", | ||
"visibility": "public" | ||
} |
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State/UTs,Total Cases,Active,Discharged,Deaths,Active Ratio,Discharge Ratio,Death Ratio,Population | ||
Andaman and Nicobar,10747,0,10618,129,0.0,98.8,1.2,100896618 | ||
Andhra Pradesh,2339078,7,2324338,14733,0.0,99.37,0.63,128500364 | ||
Arunachal Pradesh,66891,0,66595,296,0.0,99.56,0.44,658019 | ||
Assam,746100,0,738065,8035,0.0,98.92,1.08,290492 | ||
Bihar,851404,1,839100,12303,0.0,98.55,1.45,40100376 | ||
Chandigarh,99358,3,98174,1181,0.0,98.81,1.19,30501026 | ||
Chhattisgarh,1177768,8,1163614,14146,0.0,98.8,1.2,28900667 | ||
Dadra and Nagar Haveli and Daman and Diu,11591,0,11587,4,0.0,99.97,0.03,231502578 | ||
Delhi,2007313,10,1980781,26522,0.0,98.68,1.32,773997 | ||
Goa,259110,15,255082,4013,0.01,98.45,1.55,3772103 | ||
Gujarat,1277615,11,1266561,11043,0.0,99.13,0.86,70400153 | ||
Haryana,1056655,38,1045903,10714,0.0,98.98,1.01,7503010 | ||
Himachal Pradesh,312692,14,308465,4213,0.0,98.65,1.35,3436948 | ||
Jammu and Kashmir,479444,10,474649,4785,0.0,99.0,1.0,66001 | ||
Jharkhand,442574,0,437243,5331,0.0,98.8,1.2,124904071 | ||
Karnataka,4072536,123,4032105,40308,0.0,99.01,0.99,1711947 | ||
Kerala,6829249,1300,6756379,71570,0.02,98.93,1.05,91702478 | ||
Ladakh,29417,1,29185,231,0.0,99.21,0.79,4184959 | ||
Lakshadweep,11415,0,11363,52,0.0,99.54,0.46,11700099 | ||
Madhya Pradesh,1054934,2,1044155,10777,0.0,98.98,1.02,14999397 | ||
Maharashtra,8136945,134,7988392,148419,0.0,98.17,1.82,399001 | ||
Manipur,139924,0,137775,2149,0.0,98.46,1.54,47099270 | ||
Meghalaya,96786,1,95161,1624,0.0,98.32,1.68,79502477 | ||
Mizoram,238964,0,238238,726,0.0,99.7,0.3,1308967 | ||
Nagaland,35986,0,35204,782,0.0,97.83,2.17,38157311 | ||
Odisha,1336595,84,1327306,9205,0.01,99.31,0.69,19301096 | ||
Puducherry,175636,73,173588,1975,0.04,98.83,1.12,2073074 | ||
Punjab,784282,29,764964,19289,0.0,97.54,2.46,34698876 | ||
Rajasthan,1315564,5,1305906,9653,0.0,99.27,0.73,1521992 | ||
Sikkim,44321,2,43820,499,0.0,98.87,1.13,83697770 | ||
Tamil Nadu,3594573,58,3556466,38049,0.0,98.94,1.06,35998752 | ||
Telengana,841453,27,837315,4111,0.0,99.51,0.49,69599762 | ||
Tripura,108034,0,107094,940,0.0,99.13,0.87,1646050 | ||
Uttar Pradesh,2128154,18,2104502,23634,0.0,98.89,1.11,1158040 | ||
Uttarakhand,449429,11,441665,7753,0.0,98.27,1.73,85002417 | ||
West Bengal,2118696,50,2097114,21532,0.0,98.98,1.02,32199722 |
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{ | ||
"config": { | ||
"path": "../data/india-covid-19/Latest Covid-19 India Status.csv" | ||
}, | ||
"description": "Covid-19 India Statewise Data as on January 17, 2023", | ||
"name": "Latest Covid-19 India Statewise Data", | ||
"reference": false, | ||
"sensitive": false, | ||
"type": "file", | ||
"visibility": "public" | ||
} |
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{ | ||
"config": { | ||
"path": "../data/life-longevity-factors/LiveLongerData.csv" | ||
}, | ||
"description": "What factors will really increase your average life expectancy and lifespan?", | ||
"name": "Life Longevity Factors", | ||
"reference": false, | ||
"sensitive": false, | ||
"type": "file", | ||
"visibility": "public" | ||
} |
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