updated to datasets 4.*

README.md

@@ -1,19 +1,20 @@
 ---
-language:
-- en
+configs:
+- config_name: death
+  data_files:
+  - path: death/train.csv
+    split: train
+  default: true
+language: en
+license: cc
+pretty_name: Heart failure
+size_categories: 1M<n<10M
 tags:
-- heart failure
 - tabular_classification
 - binary_classification
-- UCI
-pretty_name: Heart failure
-size_categories:
-- n<1K
+- multiclass_classification
 task_categories:
 - tabular-classification
-configs:
-- death
-license: cc
 ---
 # Heart failure
 The [Heart failure dataset](https://www.kaggle.com/datasets/andrewmvd/heart-failure-clinical-data) from Kaggle.

death/train.csv

@@ -0,0 +1,300 @@
+age,has_anaemia,creatinine_phosphokinase_concentration_in_blood,has_diabetes,heart_ejection_fraction,has_high_blood_pressure,platelets_concentration_in_blood,serum_creatinine_concentration_in_blood,serum_sodium_concentration_in_blood,is_male,is_smoker,days_in_study,is_dead
+75,False,582.0,False,20.0,True,265000.0,1.9,130.0,True,False,4,1
+55,False,7861.0,False,38.0,False,263358.03,1.1,136.0,True,False,6,1
+65,False,146.0,False,20.0,False,162000.0,1.3,129.0,True,True,7,1
+50,True,111.0,False,20.0,False,210000.0,1.9,137.0,True,False,7,1
+65,True,160.0,True,20.0,False,327000.0,2.7,116.0,False,False,8,1
+90,True,47.0,False,40.0,True,204000.0,2.1,132.0,True,True,8,1
+75,True,246.0,False,15.0,False,127000.0,1.2,137.0,True,False,10,1
+60,True,315.0,True,60.0,False,454000.0,1.1,131.0,True,True,10,1
+65,False,157.0,False,65.0,False,263358.03,1.5,138.0,False,False,10,1
+80,True,123.0,False,35.0,True,388000.0,9.4,133.0,True,True,10,1
+75,True,81.0,False,38.0,True,368000.0,4.0,131.0,True,True,10,1
+62,False,231.0,False,25.0,True,253000.0,0.9,140.0,True,True,10,1
+45,True,981.0,False,30.0,False,136000.0,1.1,137.0,True,False,11,1
+50,True,168.0,False,38.0,True,276000.0,1.1,137.0,True,False,11,1
+49,True,80.0,False,30.0,True,427000.0,1.0,138.0,False,False,12,0
+82,True,379.0,False,50.0,False,47000.0,1.3,136.0,True,False,13,1
+87,True,149.0,False,38.0,False,262000.0,0.9,140.0,True,False,14,1
+45,False,582.0,False,14.0,False,166000.0,0.8,127.0,True,False,14,1
+70,True,125.0,False,25.0,True,237000.0,1.0,140.0,False,False,15,1
+48,True,582.0,True,55.0,False,87000.0,1.9,121.0,False,False,15,1
+65,True,52.0,False,25.0,True,276000.0,1.3,137.0,False,False,16,0
+65,True,128.0,True,30.0,True,297000.0,1.6,136.0,False,False,20,1
+68,True,220.0,False,35.0,True,289000.0,0.9,140.0,True,True,20,1
+53,False,63.0,True,60.0,False,368000.0,0.8,135.0,True,False,22,0
+75,False,582.0,True,30.0,True,263358.03,1.83,134.0,False,False,23,1
+80,False,148.0,True,38.0,False,149000.0,1.9,144.0,True,True,23,1
+95,True,112.0,False,40.0,True,196000.0,1.0,138.0,False,False,24,1
+70,False,122.0,True,45.0,True,284000.0,1.3,136.0,True,True,26,1
+58,True,60.0,False,38.0,False,153000.0,5.8,134.0,True,False,26,1
+82,False,70.0,True,30.0,False,200000.0,1.2,132.0,True,True,26,1
+94,False,582.0,True,38.0,True,263358.03,1.83,134.0,True,False,27,1
+85,False,23.0,False,45.0,False,360000.0,3.0,132.0,True,False,28,1
+50,True,249.0,True,35.0,True,319000.0,1.0,128.0,False,False,28,1
+50,True,159.0,True,30.0,False,302000.0,1.2,138.0,False,False,29,0
+65,False,94.0,True,50.0,True,188000.0,1.0,140.0,True,False,29,1
+69,False,582.0,True,35.0,False,228000.0,3.5,134.0,True,False,30,1
+90,True,60.0,True,50.0,False,226000.0,1.0,134.0,True,False,30,1
+82,True,855.0,True,50.0,True,321000.0,1.0,145.0,False,False,30,1
+60,False,2656.0,True,30.0,False,305000.0,2.3,137.0,True,False,30,0
+60,False,235.0,True,38.0,False,329000.0,3.0,142.0,False,False,30,1
+70,False,582.0,False,20.0,True,263358.03,1.83,134.0,True,True,31,1
+50,False,124.0,True,30.0,True,153000.0,1.2,136.0,False,True,32,1
+70,False,571.0,True,45.0,True,185000.0,1.2,139.0,True,True,33,1
+72,False,127.0,True,50.0,True,218000.0,1.0,134.0,True,False,33,0
+60,True,588.0,True,60.0,False,194000.0,1.1,142.0,False,False,33,1
+50,False,582.0,True,38.0,False,310000.0,1.9,135.0,True,True,35,1
+51,False,1380.0,False,25.0,True,271000.0,0.9,130.0,True,False,38,1
+60,False,582.0,True,38.0,True,451000.0,0.6,138.0,True,True,40,1
+80,True,553.0,False,20.0,True,140000.0,4.4,133.0,True,False,41,1
+57,True,129.0,False,30.0,False,395000.0,1.0,140.0,False,False,42,1
+68,True,577.0,False,25.0,True,166000.0,1.0,138.0,True,False,43,1
+53,True,91.0,False,20.0,True,418000.0,1.4,139.0,False,False,43,1
+60,False,3964.0,True,62.0,False,263358.03,6.8,146.0,False,False,43,1
+70,True,69.0,True,50.0,True,351000.0,1.0,134.0,False,False,44,1
+60,True,260.0,True,38.0,False,255000.0,2.2,132.0,False,True,45,1
+95,True,371.0,False,30.0,False,461000.0,2.0,132.0,True,False,50,1
+70,True,75.0,False,35.0,False,223000.0,2.7,138.0,True,True,54,0
+60,True,607.0,False,40.0,False,216000.0,0.6,138.0,True,True,54,0
+49,False,789.0,False,20.0,True,319000.0,1.1,136.0,True,True,55,1
+72,False,364.0,True,20.0,True,254000.0,1.3,136.0,True,True,59,1
+45,False,7702.0,True,25.0,True,390000.0,1.0,139.0,True,False,60,1
+50,False,318.0,False,40.0,True,216000.0,2.3,131.0,False,False,60,1
+55,False,109.0,False,35.0,False,254000.0,1.1,139.0,True,True,60,0
+45,False,582.0,False,35.0,False,385000.0,1.0,145.0,True,False,61,1
+45,False,582.0,False,80.0,False,263358.03,1.18,137.0,False,False,63,0
+60,False,68.0,False,20.0,False,119000.0,2.9,127.0,True,True,64,1
+42,True,250.0,True,15.0,False,213000.0,1.3,136.0,False,False,65,1
+72,True,110.0,False,25.0,False,274000.0,1.0,140.0,True,True,65,1
+70,False,161.0,False,25.0,False,244000.0,1.2,142.0,False,False,66,1
+65,False,113.0,True,25.0,False,497000.0,1.83,135.0,True,False,67,1
+41,False,148.0,False,40.0,False,374000.0,0.8,140.0,True,True,68,0
+58,False,582.0,True,35.0,False,122000.0,0.9,139.0,True,True,71,0
+85,False,5882.0,False,35.0,False,243000.0,1.0,132.0,True,True,72,1
+65,False,224.0,True,50.0,False,149000.0,1.3,137.0,True,True,72,0
+69,False,582.0,False,20.0,False,266000.0,1.2,134.0,True,True,73,1
+60,True,47.0,False,20.0,False,204000.0,0.7,139.0,True,True,73,1
+70,False,92.0,False,60.0,True,317000.0,0.8,140.0,False,True,74,0
+42,False,102.0,True,40.0,False,237000.0,1.2,140.0,True,False,74,0
+75,True,203.0,True,38.0,True,283000.0,0.6,131.0,True,True,74,0
+55,False,336.0,False,45.0,True,324000.0,0.9,140.0,False,False,74,0
+70,False,69.0,False,40.0,False,293000.0,1.7,136.0,False,False,75,0
+67,False,582.0,False,50.0,False,263358.03,1.18,137.0,True,True,76,0
+60,True,76.0,True,25.0,False,196000.0,2.5,132.0,False,False,77,1
+79,True,55.0,False,50.0,True,172000.0,1.8,133.0,True,False,78,0
+59,True,280.0,True,25.0,True,302000.0,1.0,141.0,False,False,78,1
+51,False,78.0,False,50.0,False,406000.0,0.7,140.0,True,False,79,0
+55,False,47.0,False,35.0,True,173000.0,1.1,137.0,True,False,79,0
+65,True,68.0,True,60.0,True,304000.0,0.8,140.0,True,False,79,0
+44,False,84.0,True,40.0,True,235000.0,0.7,139.0,True,False,79,0
+57,True,115.0,False,25.0,True,181000.0,1.1,144.0,True,False,79,0
+70,False,66.0,True,45.0,False,249000.0,0.8,136.0,True,True,80,0
+60,False,897.0,True,45.0,False,297000.0,1.0,133.0,True,False,80,0
+42,False,582.0,False,60.0,False,263358.03,1.18,137.0,False,False,82,0
+60,True,154.0,False,25.0,False,210000.0,1.7,135.0,True,False,82,1
+58,False,144.0,True,38.0,True,327000.0,0.7,142.0,False,False,83,0
+58,True,133.0,False,60.0,True,219000.0,1.0,141.0,True,False,83,0
+63,True,514.0,True,25.0,True,254000.0,1.3,134.0,True,False,83,0
+70,True,59.0,False,60.0,False,255000.0,1.1,136.0,False,False,85,0
+60,True,156.0,True,25.0,True,318000.0,1.2,137.0,False,False,85,0
+63,True,61.0,True,40.0,False,221000.0,1.1,140.0,False,False,86,0
+65,True,305.0,False,25.0,False,298000.0,1.1,141.0,True,False,87,0
+75,False,582.0,False,45.0,True,263358.03,1.18,137.0,True,False,87,0
+80,False,898.0,False,25.0,False,149000.0,1.1,144.0,True,True,87,0
+42,False,5209.0,False,30.0,False,226000.0,1.0,140.0,True,True,87,0
+60,False,53.0,False,50.0,True,286000.0,2.3,143.0,False,False,87,0
+72,True,328.0,False,30.0,True,621000.0,1.7,138.0,False,True,88,1
+55,False,748.0,False,45.0,False,263000.0,1.3,137.0,True,False,88,0
+45,True,1876.0,True,35.0,False,226000.0,0.9,138.0,True,False,88,0
+63,False,936.0,False,38.0,False,304000.0,1.1,133.0,True,True,88,0
+45,False,292.0,True,35.0,False,850000.0,1.3,142.0,True,True,88,0
+85,False,129.0,False,60.0,False,306000.0,1.2,132.0,True,True,90,1
+55,False,60.0,False,35.0,False,228000.0,1.2,135.0,True,True,90,0
+50,False,369.0,True,25.0,False,252000.0,1.6,136.0,True,False,90,0
+70,True,143.0,False,60.0,False,351000.0,1.3,137.0,False,False,90,1
+60,True,754.0,True,40.0,True,328000.0,1.2,126.0,True,False,91,0
+58,True,400.0,False,40.0,False,164000.0,1.0,139.0,False,False,91,0
+60,True,96.0,True,60.0,True,271000.0,0.7,136.0,False,False,94,0
+85,True,102.0,False,60.0,False,507000.0,3.2,138.0,False,False,94,0
+65,True,113.0,True,60.0,True,203000.0,0.9,140.0,False,False,94,0
+86,False,582.0,False,38.0,False,263358.03,1.83,134.0,False,False,95,1
+60,True,737.0,False,60.0,True,210000.0,1.5,135.0,True,True,95,0
+66,True,68.0,True,38.0,True,162000.0,1.0,136.0,False,False,95,0
+60,False,96.0,True,38.0,False,228000.0,0.75,140.0,False,False,95,0
+60,True,582.0,False,30.0,True,127000.0,0.9,145.0,False,False,95,0
+60,False,582.0,False,40.0,False,217000.0,3.7,134.0,True,False,96,1
+43,True,358.0,False,50.0,False,237000.0,1.3,135.0,False,False,97,0
+46,False,168.0,True,17.0,True,271000.0,2.1,124.0,False,False,100,1
+58,True,200.0,True,60.0,False,300000.0,0.8,137.0,False,False,104,0
+61,False,248.0,False,30.0,True,267000.0,0.7,136.0,True,True,104,0
+53,True,270.0,True,35.0,False,227000.0,3.4,145.0,True,False,105,0
+53,True,1808.0,False,60.0,True,249000.0,0.7,138.0,True,True,106,0
+60,True,1082.0,True,45.0,False,250000.0,6.1,131.0,True,False,107,0
+46,False,719.0,False,40.0,True,263358.03,1.18,137.0,False,False,107,0
+63,False,193.0,False,60.0,True,295000.0,1.3,145.0,True,True,107,0
+81,False,4540.0,False,35.0,False,231000.0,1.18,137.0,True,True,107,0
+75,False,582.0,False,40.0,False,263358.03,1.18,137.0,True,False,107,0
+65,True,59.0,True,60.0,False,172000.0,0.9,137.0,False,False,107,0
+68,True,646.0,False,25.0,False,305000.0,2.1,130.0,True,False,108,0
+62,False,281.0,True,35.0,False,221000.0,1.0,136.0,False,False,108,0
+50,False,1548.0,False,30.0,True,211000.0,0.8,138.0,True,False,108,0
+80,False,805.0,False,38.0,False,263358.03,1.1,134.0,True,False,109,1
+46,True,291.0,False,35.0,False,348000.0,0.9,140.0,False,False,109,0
+50,False,482.0,True,30.0,False,329000.0,0.9,132.0,False,False,109,0
+61,True,84.0,False,40.0,True,229000.0,0.9,141.0,False,False,110,0
+72,True,943.0,False,25.0,True,338000.0,1.7,139.0,True,True,111,1
+50,False,185.0,False,30.0,False,266000.0,0.7,141.0,True,True,112,0
+52,False,132.0,False,30.0,False,218000.0,0.7,136.0,True,True,112,0
+64,False,1610.0,False,60.0,False,242000.0,1.0,137.0,True,False,113,0
+75,True,582.0,False,30.0,False,225000.0,1.83,134.0,True,False,113,1
+60,False,2261.0,False,35.0,True,228000.0,0.9,136.0,True,False,115,0
+72,False,233.0,False,45.0,True,235000.0,2.5,135.0,False,False,115,1
+62,False,30.0,True,60.0,True,244000.0,0.9,139.0,True,False,117,0
+50,False,115.0,False,45.0,True,184000.0,0.9,134.0,True,True,118,0
+50,False,1846.0,True,35.0,False,263358.03,1.18,137.0,True,True,119,0
+65,True,335.0,False,35.0,True,235000.0,0.8,136.0,False,False,120,0
+60,True,231.0,True,25.0,False,194000.0,1.7,140.0,True,False,120,0
+52,True,58.0,False,35.0,False,277000.0,1.4,136.0,False,False,120,0
+50,False,250.0,False,25.0,False,262000.0,1.0,136.0,True,True,120,0
+85,True,910.0,False,50.0,False,235000.0,1.3,134.0,True,False,121,0
+59,True,129.0,False,45.0,True,362000.0,1.1,139.0,True,True,121,0
+66,True,72.0,False,40.0,True,242000.0,1.2,134.0,True,False,121,0
+45,True,130.0,False,35.0,False,174000.0,0.8,139.0,True,True,121,0
+63,True,582.0,False,40.0,False,448000.0,0.9,137.0,True,True,123,0
+50,True,2334.0,True,35.0,False,75000.0,0.9,142.0,False,False,126,1
+45,False,2442.0,True,30.0,False,334000.0,1.1,139.0,True,False,129,1
+80,False,776.0,True,38.0,True,192000.0,1.3,135.0,False,False,130,1
+53,False,196.0,False,60.0,False,220000.0,0.7,133.0,True,True,134,0
+59,False,66.0,True,20.0,False,70000.0,2.4,134.0,True,False,135,1
+65,False,582.0,True,40.0,False,270000.0,1.0,138.0,False,False,140,0
+70,False,835.0,False,35.0,True,305000.0,0.8,133.0,False,False,145,0
+51,True,582.0,True,35.0,False,263358.03,1.5,136.0,True,True,145,0
+52,False,3966.0,False,40.0,False,325000.0,0.9,140.0,True,True,146,0
+70,True,171.0,False,60.0,True,176000.0,1.1,145.0,True,True,146,0
+50,True,115.0,False,20.0,False,189000.0,0.8,139.0,True,False,146,0
+65,False,198.0,True,35.0,True,281000.0,0.9,137.0,True,True,146,0
+60,True,95.0,False,60.0,False,337000.0,1.0,138.0,True,True,146,0
+69,False,1419.0,False,40.0,False,105000.0,1.0,135.0,True,True,147,0
+49,True,69.0,False,50.0,False,132000.0,1.0,140.0,False,False,147,0
+63,True,122.0,True,60.0,False,267000.0,1.2,145.0,True,False,147,0
+55,False,835.0,False,40.0,False,279000.0,0.7,140.0,True,True,147,0
+40,False,478.0,True,30.0,False,303000.0,0.9,136.0,True,False,148,0
+59,True,176.0,True,25.0,False,221000.0,1.0,136.0,True,True,150,1
+65,False,395.0,True,25.0,False,265000.0,1.2,136.0,True,True,154,1
+75,False,99.0,False,38.0,True,224000.0,2.5,134.0,True,False,162,1
+58,True,145.0,False,25.0,False,219000.0,1.2,137.0,True,True,170,1
+60,True,104.0,True,30.0,False,389000.0,1.5,136.0,True,False,171,1
+50,False,582.0,False,50.0,False,153000.0,0.6,134.0,False,False,172,1
+60,False,1896.0,True,25.0,False,365000.0,2.1,144.0,False,False,172,1
+60,True,151.0,True,40.0,True,201000.0,1.0,136.0,False,False,172,0
+40,False,244.0,False,45.0,True,275000.0,0.9,140.0,False,False,174,0
+80,False,582.0,True,35.0,False,350000.0,2.1,134.0,True,False,174,0
+64,True,62.0,False,60.0,False,309000.0,1.5,135.0,False,False,174,0
+50,True,121.0,True,40.0,False,260000.0,0.7,130.0,True,False,175,0
+73,True,231.0,True,30.0,False,160000.0,1.18,142.0,True,True,180,0
+45,False,582.0,False,20.0,True,126000.0,1.6,135.0,True,False,180,1
+77,True,418.0,False,45.0,False,223000.0,1.8,145.0,True,False,180,1
+45,False,582.0,True,38.0,True,263358.03,1.18,137.0,False,False,185,0
+65,False,167.0,False,30.0,False,259000.0,0.8,138.0,False,False,186,0
+50,True,582.0,True,20.0,True,279000.0,1.0,134.0,False,False,186,0
+60,False,1211.0,True,35.0,False,263358.03,1.8,113.0,True,True,186,0
+63,True,1767.0,False,45.0,False,73000.0,0.7,137.0,True,False,186,0
+45,False,308.0,True,60.0,True,377000.0,1.0,136.0,True,False,186,0
+70,False,97.0,False,60.0,True,220000.0,0.9,138.0,True,False,186,0
+60,False,59.0,False,25.0,True,212000.0,3.5,136.0,True,True,187,0
+78,True,64.0,False,40.0,False,277000.0,0.7,137.0,True,True,187,0
+50,True,167.0,True,45.0,False,362000.0,1.0,136.0,False,False,187,0
+40,True,101.0,False,40.0,False,226000.0,0.8,141.0,False,False,187,0
+85,False,212.0,False,38.0,False,186000.0,0.9,136.0,True,False,187,0
+60,True,2281.0,True,40.0,False,283000.0,1.0,141.0,False,False,187,0
+49,False,972.0,True,35.0,True,268000.0,0.8,130.0,False,False,187,0
+70,False,212.0,True,17.0,True,389000.0,1.0,136.0,True,True,188,0
+50,False,582.0,False,62.0,True,147000.0,0.8,140.0,True,True,192,0
+78,False,224.0,False,50.0,False,481000.0,1.4,138.0,True,True,192,0
+48,True,131.0,True,30.0,True,244000.0,1.6,130.0,False,False,193,1
+65,True,135.0,False,35.0,True,290000.0,0.8,134.0,True,False,194,0
+73,False,582.0,False,35.0,True,203000.0,1.3,134.0,True,False,195,0
+70,False,1202.0,False,50.0,True,358000.0,0.9,141.0,False,False,196,0
+54,True,427.0,False,70.0,True,151000.0,9.0,137.0,False,False,196,1
+68,True,1021.0,True,35.0,False,271000.0,1.1,134.0,True,False,197,0
+55,False,582.0,True,35.0,True,371000.0,0.7,140.0,False,False,197,0
+73,False,582.0,False,20.0,False,263358.03,1.83,134.0,True,False,198,1
+65,False,118.0,False,50.0,False,194000.0,1.1,145.0,True,True,200,0
+42,True,86.0,False,35.0,False,365000.0,1.1,139.0,True,True,201,0
+47,False,582.0,False,25.0,False,130000.0,0.8,134.0,True,False,201,0
+58,False,582.0,True,25.0,False,504000.0,1.0,138.0,True,False,205,0
+75,False,675.0,True,60.0,False,265000.0,1.4,125.0,False,False,205,0
+58,True,57.0,False,25.0,False,189000.0,1.3,132.0,True,True,205,0
+55,True,2794.0,False,35.0,True,141000.0,1.0,140.0,True,False,206,0
+65,False,56.0,False,25.0,False,237000.0,5.0,130.0,False,False,207,0
+72,False,211.0,False,25.0,False,274000.0,1.2,134.0,False,False,207,0
+60,False,166.0,False,30.0,False,62000.0,1.7,127.0,False,False,207,1
+70,False,93.0,False,35.0,False,185000.0,1.1,134.0,True,True,208,0
+40,True,129.0,False,35.0,False,255000.0,0.9,137.0,True,False,209,0
+53,True,707.0,False,38.0,False,330000.0,1.4,137.0,True,True,209,0
+53,True,582.0,False,45.0,False,305000.0,1.1,137.0,True,True,209,0
+77,True,109.0,False,50.0,True,406000.0,1.1,137.0,True,False,209,0
+75,False,119.0,False,50.0,True,248000.0,1.1,148.0,True,False,209,0
+70,False,232.0,False,30.0,False,173000.0,1.2,132.0,True,False,210,0
+65,True,720.0,True,40.0,False,257000.0,1.0,136.0,False,False,210,0
+55,True,180.0,False,45.0,False,263358.03,1.18,137.0,True,True,211,0
+70,False,81.0,True,35.0,True,533000.0,1.3,139.0,False,False,212,0
+65,False,582.0,True,30.0,False,249000.0,1.3,136.0,True,True,212,0
+40,False,90.0,False,35.0,False,255000.0,1.1,136.0,True,True,212,0
+73,True,1185.0,False,40.0,True,220000.0,0.9,141.0,False,False,213,0
+54,False,582.0,True,38.0,False,264000.0,1.8,134.0,True,False,213,0
+61,True,80.0,True,38.0,False,282000.0,1.4,137.0,True,False,213,0
+55,False,2017.0,False,25.0,False,314000.0,1.1,138.0,True,False,214,1
+64,False,143.0,False,25.0,False,246000.0,2.4,135.0,True,False,214,0
+40,False,624.0,False,35.0,False,301000.0,1.0,142.0,True,True,214,0
+53,False,207.0,True,40.0,False,223000.0,1.2,130.0,False,False,214,0
+50,False,2522.0,False,30.0,True,404000.0,0.5,139.0,False,False,214,0
+55,False,572.0,True,35.0,False,231000.0,0.8,143.0,False,False,215,0
+50,False,245.0,False,45.0,True,274000.0,1.0,133.0,True,False,215,0
+70,False,88.0,True,35.0,True,236000.0,1.2,132.0,False,False,215,0
+53,True,446.0,False,60.0,True,263358.03,1.0,139.0,True,False,215,0
+52,True,191.0,True,30.0,True,334000.0,1.0,142.0,True,True,216,0
+65,False,326.0,False,38.0,False,294000.0,1.7,139.0,False,False,220,0
+58,False,132.0,True,38.0,True,253000.0,1.0,139.0,True,False,230,0
+45,True,66.0,True,25.0,False,233000.0,0.8,135.0,True,False,230,0
+53,False,56.0,False,50.0,False,308000.0,0.7,135.0,True,True,231,0
+55,False,66.0,False,40.0,False,203000.0,1.0,138.0,True,False,233,0
+62,True,655.0,False,40.0,False,283000.0,0.7,133.0,False,False,233,0
+65,True,258.0,True,25.0,False,198000.0,1.4,129.0,True,False,235,1
+68,True,157.0,True,60.0,False,208000.0,1.0,140.0,False,False,237,0
+61,False,582.0,True,38.0,False,147000.0,1.2,141.0,True,False,237,0
+50,True,298.0,False,35.0,False,362000.0,0.9,140.0,True,True,240,0
+55,False,1199.0,False,20.0,False,263358.03,1.83,134.0,True,True,241,1
+56,True,135.0,True,38.0,False,133000.0,1.7,140.0,True,False,244,0
+45,False,582.0,True,38.0,False,302000.0,0.9,140.0,False,False,244,0
+40,False,582.0,True,35.0,False,222000.0,1.0,132.0,True,False,244,0
+44,False,582.0,True,30.0,True,263358.03,1.6,130.0,True,True,244,0
+51,False,582.0,True,40.0,False,221000.0,0.9,134.0,False,False,244,0
+67,False,213.0,False,38.0,False,215000.0,1.2,133.0,False,False,245,0
+42,False,64.0,False,40.0,False,189000.0,0.7,140.0,True,False,245,0
+60,True,257.0,True,30.0,False,150000.0,1.0,137.0,True,True,245,0
+45,False,582.0,False,38.0,True,422000.0,0.8,137.0,False,False,245,0
+70,False,618.0,False,35.0,False,327000.0,1.1,142.0,False,False,245,0
+70,False,582.0,True,38.0,False,25100.0,1.1,140.0,True,False,246,0
+50,True,1051.0,True,30.0,False,232000.0,0.7,136.0,False,False,246,0
+55,False,84.0,True,38.0,False,451000.0,1.3,136.0,False,False,246,0
+70,False,2695.0,True,40.0,False,241000.0,1.0,137.0,True,False,247,0
+70,False,582.0,False,40.0,False,51000.0,2.7,136.0,True,True,250,0
+42,False,64.0,False,30.0,False,215000.0,3.8,128.0,True,True,250,0
+65,False,1688.0,False,38.0,False,263358.03,1.1,138.0,True,True,250,0
+50,True,54.0,False,40.0,False,279000.0,0.8,141.0,True,False,250,0
+55,True,170.0,True,40.0,False,336000.0,1.2,135.0,True,False,250,0
+60,False,253.0,False,35.0,False,279000.0,1.7,140.0,True,False,250,0
+45,False,582.0,True,55.0,False,543000.0,1.0,132.0,False,False,250,0
+65,False,892.0,True,35.0,False,263358.03,1.1,142.0,False,False,256,0
+90,True,337.0,False,38.0,False,390000.0,0.9,144.0,False,False,256,0
+45,False,615.0,True,55.0,False,222000.0,0.8,141.0,False,False,257,0
+60,False,320.0,False,35.0,False,133000.0,1.4,139.0,True,False,258,0
+52,False,190.0,True,38.0,False,382000.0,1.0,140.0,True,True,258,0
+63,True,103.0,True,35.0,False,179000.0,0.9,136.0,True,True,270,0
+62,False,61.0,True,38.0,True,155000.0,1.1,143.0,True,True,270,0
+55,False,1820.0,False,38.0,False,270000.0,1.2,139.0,False,False,271,0
+45,False,2060.0,True,60.0,False,742000.0,0.8,138.0,False,False,278,0
+45,False,2413.0,False,38.0,False,140000.0,1.4,140.0,True,True,280,0
+50,False,196.0,False,45.0,False,395000.0,1.6,136.0,True,True,285,0

heart_failure.py

@@ -1,102 +0,0 @@
-"""Heart Failure Dataset"""
-
-from typing import List
-
-import datasets
-
-import pandas
-
-
-VERSION = datasets.Version("1.0.0")
-_BASE_FEATURE_NAMES = [
-    "age",
-    "has_anaemia",
-    "creatinine_phosphokinase_concentration_in_blood",
-    "has_diabetes",
-    "heart_ejection_fraction",
-    "has_high_blood_pressure",
-    "platelets_concentration_in_blood",
-    "serum_creatinine_concentration_in_blood",
-    "serum_sodium_concentration_in_blood",
-    "sex",
-    "is_smoker",
-    "days_in_study",
-    "is_dead"
-]
-
-DESCRIPTION = "Heart Failure dataset."
-_HOMEPAGE = "https://www.kaggle.com/datasets/ulrikthygepedersen/heart_failures"
-_URLS = ("https://www.kaggle.com/datasets/ulrikthygepedersen/heart_failures")
-_CITATION = """"""
-
-# Dataset info
-urls_per_split = {
-    "train": "https://huggingface.co/datasets/mstz/heart_failure/raw/main/heart_failure_clinical_records_dataset.csv",
-}
-features_types_per_config = {
-    "death": {
-        "age": datasets.Value("int8"),
-        "has_anaemia": datasets.Value("bool"),
-        "creatinine_phosphokinase_concentration_in_blood": datasets.Value("float64"),
-        "has_diabetes": datasets.Value("bool"),
-        "heart_ejection_fraction": datasets.Value("float64"),
-        "has_high_blood_pressure": datasets.Value("bool"),
-        "platelets_concentration_in_blood": datasets.Value("float64"),
-        "serum_creatinine_concentration_in_blood": datasets.Value("float64"),
-        "serum_sodium_concentration_in_blood": datasets.Value("float64"),
-        "is_male": datasets.Value("bool"),
-        "is_smoker": datasets.Value("bool"),
-        "days_in_study": datasets.Value("int64"),
-        "is_dead": datasets.ClassLabel(num_classes=2, names=("no", "yes"))
-    }
-}
-features_per_config = {k: datasets.Features(features_types_per_config[k]) for k in features_types_per_config}
-
-
-class HeartFailureConfig(datasets.BuilderConfig):
-    def __init__(self, **kwargs):
-        super(HeartFailureConfig, self).__init__(version=VERSION, **kwargs)
-        self.features = features_per_config[kwargs["name"]]
-
-
-class HeartFailure(datasets.GeneratorBasedBuilder):
-    # dataset versions
-    DEFAULT_CONFIG = "death"
-    BUILDER_CONFIGS = [
-        HeartFailureConfig(name="death",
-                           description="Binary classification, predict if the patient dies.")
-    ]
-
-
-    def _info(self):
-        if self.config.name not in features_per_config:
-            raise ValueError(f"Unknown configuration: {self.config.name}")
-        
-        info = datasets.DatasetInfo(description=DESCRIPTION, citation=_CITATION, homepage=_HOMEPAGE,
-                                    features=features_per_config[self.config.name])
-
-        return info
-    
-    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
-        downloads = dl_manager.download_and_extract(urls_per_split)
-
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloads["train"]}),
-        ]
-    
-    def _generate_examples(self, filepath: str):
-        data = pandas.read_csv(filepath)
-        data = self.preprocess(data, config=self.config.name)
-
-        for row_id, row in data.iterrows():
-            data_row = dict(row)
-
-            yield row_id, data_row
-
-    def preprocess(self, data: pandas.DataFrame, config: str = "death") -> pandas.DataFrame:
-        data.columns = _BASE_FEATURE_NAMES
-        data = data.rename(columns={"sex": "is_male"})
-        data = data.astype({"has_anaemia": "bool", "has_diabetes": "bool", "has_high_blood_pressure": "bool", "is_male": "bool",
-                            "is_smoker": "bool"})
-
-        return data                        

heart_failure_clinical_records_dataset.csv

@@ -1,300 +0,0 @@
-age,anaemia,creatinine_phosphokinase,diabetes,ejection_fraction,high_blood_pressure,platelets,serum_creatinine,serum_sodium,sex,smoking,time,DEATH_EVENT
-75,0,582,0,20,1,265000,1.9,130,1,0,4,1
-55,0,7861,0,38,0,263358.03,1.1,136,1,0,6,1
-65,0,146,0,20,0,162000,1.3,129,1,1,7,1
-50,1,111,0,20,0,210000,1.9,137,1,0,7,1
-65,1,160,1,20,0,327000,2.7,116,0,0,8,1
-90,1,47,0,40,1,204000,2.1,132,1,1,8,1
-75,1,246,0,15,0,127000,1.2,137,1,0,10,1
-60,1,315,1,60,0,454000,1.1,131,1,1,10,1
-65,0,157,0,65,0,263358.03,1.5,138,0,0,10,1
-80,1,123,0,35,1,388000,9.4,133,1,1,10,1
-75,1,81,0,38,1,368000,4,131,1,1,10,1
-62,0,231,0,25,1,253000,0.9,140,1,1,10,1
-45,1,981,0,30,0,136000,1.1,137,1,0,11,1
-50,1,168,0,38,1,276000,1.1,137,1,0,11,1
-49,1,80,0,30,1,427000,1,138,0,0,12,0
-82,1,379,0,50,0,47000,1.3,136,1,0,13,1
-87,1,149,0,38,0,262000,0.9,140,1,0,14,1
-45,0,582,0,14,0,166000,0.8,127,1,0,14,1
-70,1,125,0,25,1,237000,1,140,0,0,15,1
-48,1,582,1,55,0,87000,1.9,121,0,0,15,1
-65,1,52,0,25,1,276000,1.3,137,0,0,16,0
-65,1,128,1,30,1,297000,1.6,136,0,0,20,1
-68,1,220,0,35,1,289000,0.9,140,1,1,20,1
-53,0,63,1,60,0,368000,0.8,135,1,0,22,0
-75,0,582,1,30,1,263358.03,1.83,134,0,0,23,1
-80,0,148,1,38,0,149000,1.9,144,1,1,23,1
-95,1,112,0,40,1,196000,1,138,0,0,24,1
-70,0,122,1,45,1,284000,1.3,136,1,1,26,1
-58,1,60,0,38,0,153000,5.8,134,1,0,26,1
-82,0,70,1,30,0,200000,1.2,132,1,1,26,1
-94,0,582,1,38,1,263358.03,1.83,134,1,0,27,1
-85,0,23,0,45,0,360000,3,132,1,0,28,1
-50,1,249,1,35,1,319000,1,128,0,0,28,1
-50,1,159,1,30,0,302000,1.2,138,0,0,29,0
-65,0,94,1,50,1,188000,1,140,1,0,29,1
-69,0,582,1,35,0,228000,3.5,134,1,0,30,1
-90,1,60,1,50,0,226000,1,134,1,0,30,1
-82,1,855,1,50,1,321000,1,145,0,0,30,1
-60,0,2656,1,30,0,305000,2.3,137,1,0,30,0
-60,0,235,1,38,0,329000,3,142,0,0,30,1
-70,0,582,0,20,1,263358.03,1.83,134,1,1,31,1
-50,0,124,1,30,1,153000,1.2,136,0,1,32,1
-70,0,571,1,45,1,185000,1.2,139,1,1,33,1
-72,0,127,1,50,1,218000,1,134,1,0,33,0
-60,1,588,1,60,0,194000,1.1,142,0,0,33,1
-50,0,582,1,38,0,310000,1.9,135,1,1,35,1
-51,0,1380,0,25,1,271000,0.9,130,1,0,38,1
-60,0,582,1,38,1,451000,0.6,138,1,1,40,1
-80,1,553,0,20,1,140000,4.4,133,1,0,41,1
-57,1,129,0,30,0,395000,1,140,0,0,42,1
-68,1,577,0,25,1,166000,1,138,1,0,43,1
-53,1,91,0,20,1,418000,1.4,139,0,0,43,1
-60,0,3964,1,62,0,263358.03,6.8,146,0,0,43,1
-70,1,69,1,50,1,351000,1,134,0,0,44,1
-60,1,260,1,38,0,255000,2.2,132,0,1,45,1
-95,1,371,0,30,0,461000,2,132,1,0,50,1
-70,1,75,0,35,0,223000,2.7,138,1,1,54,0
-60,1,607,0,40,0,216000,0.6,138,1,1,54,0
-49,0,789,0,20,1,319000,1.1,136,1,1,55,1
-72,0,364,1,20,1,254000,1.3,136,1,1,59,1
-45,0,7702,1,25,1,390000,1,139,1,0,60,1
-50,0,318,0,40,1,216000,2.3,131,0,0,60,1
-55,0,109,0,35,0,254000,1.1,139,1,1,60,0
-45,0,582,0,35,0,385000,1,145,1,0,61,1
-45,0,582,0,80,0,263358.03,1.18,137,0,0,63,0
-60,0,68,0,20,0,119000,2.9,127,1,1,64,1
-42,1,250,1,15,0,213000,1.3,136,0,0,65,1
-72,1,110,0,25,0,274000,1,140,1,1,65,1
-70,0,161,0,25,0,244000,1.2,142,0,0,66,1
-65,0,113,1,25,0,497000,1.83,135,1,0,67,1
-41,0,148,0,40,0,374000,0.8,140,1,1,68,0
-58,0,582,1,35,0,122000,0.9,139,1,1,71,0
-85,0,5882,0,35,0,243000,1,132,1,1,72,1
-65,0,224,1,50,0,149000,1.3,137,1,1,72,0
-69,0,582,0,20,0,266000,1.2,134,1,1,73,1
-60,1,47,0,20,0,204000,0.7,139,1,1,73,1
-70,0,92,0,60,1,317000,0.8,140,0,1,74,0
-42,0,102,1,40,0,237000,1.2,140,1,0,74,0
-75,1,203,1,38,1,283000,0.6,131,1,1,74,0
-55,0,336,0,45,1,324000,0.9,140,0,0,74,0
-70,0,69,0,40,0,293000,1.7,136,0,0,75,0
-67,0,582,0,50,0,263358.03,1.18,137,1,1,76,0
-60,1,76,1,25,0,196000,2.5,132,0,0,77,1
-79,1,55,0,50,1,172000,1.8,133,1,0,78,0
-59,1,280,1,25,1,302000,1,141,0,0,78,1
-51,0,78,0,50,0,406000,0.7,140,1,0,79,0
-55,0,47,0,35,1,173000,1.1,137,1,0,79,0
-65,1,68,1,60,1,304000,0.8,140,1,0,79,0
-44,0,84,1,40,1,235000,0.7,139,1,0,79,0
-57,1,115,0,25,1,181000,1.1,144,1,0,79,0
-70,0,66,1,45,0,249000,0.8,136,1,1,80,0
-60,0,897,1,45,0,297000,1,133,1,0,80,0
-42,0,582,0,60,0,263358.03,1.18,137,0,0,82,0
-60,1,154,0,25,0,210000,1.7,135,1,0,82,1
-58,0,144,1,38,1,327000,0.7,142,0,0,83,0
-58,1,133,0,60,1,219000,1,141,1,0,83,0
-63,1,514,1,25,1,254000,1.3,134,1,0,83,0
-70,1,59,0,60,0,255000,1.1,136,0,0,85,0
-60,1,156,1,25,1,318000,1.2,137,0,0,85,0
-63,1,61,1,40,0,221000,1.1,140,0,0,86,0
-65,1,305,0,25,0,298000,1.1,141,1,0,87,0
-75,0,582,0,45,1,263358.03,1.18,137,1,0,87,0
-80,0,898,0,25,0,149000,1.1,144,1,1,87,0
-42,0,5209,0,30,0,226000,1,140,1,1,87,0
-60,0,53,0,50,1,286000,2.3,143,0,0,87,0
-72,1,328,0,30,1,621000,1.7,138,0,1,88,1
-55,0,748,0,45,0,263000,1.3,137,1,0,88,0
-45,1,1876,1,35,0,226000,0.9,138,1,0,88,0
-63,0,936,0,38,0,304000,1.1,133,1,1,88,0
-45,0,292,1,35,0,850000,1.3,142,1,1,88,0
-85,0,129,0,60,0,306000,1.2,132,1,1,90,1
-55,0,60,0,35,0,228000,1.2,135,1,1,90,0
-50,0,369,1,25,0,252000,1.6,136,1,0,90,0
-70,1,143,0,60,0,351000,1.3,137,0,0,90,1
-60,1,754,1,40,1,328000,1.2,126,1,0,91,0
-58,1,400,0,40,0,164000,1,139,0,0,91,0
-60,1,96,1,60,1,271000,0.7,136,0,0,94,0
-85,1,102,0,60,0,507000,3.2,138,0,0,94,0
-65,1,113,1,60,1,203000,0.9,140,0,0,94,0
-86,0,582,0,38,0,263358.03,1.83,134,0,0,95,1
-60,1,737,0,60,1,210000,1.5,135,1,1,95,0
-66,1,68,1,38,1,162000,1,136,0,0,95,0
-60,0,96,1,38,0,228000,0.75,140,0,0,95,0
-60,1,582,0,30,1,127000,0.9,145,0,0,95,0
-60,0,582,0,40,0,217000,3.7,134,1,0,96,1
-43,1,358,0,50,0,237000,1.3,135,0,0,97,0
-46,0,168,1,17,1,271000,2.1,124,0,0,100,1
-58,1,200,1,60,0,300000,0.8,137,0,0,104,0
-61,0,248,0,30,1,267000,0.7,136,1,1,104,0
-53,1,270,1,35,0,227000,3.4,145,1,0,105,0
-53,1,1808,0,60,1,249000,0.7,138,1,1,106,0
-60,1,1082,1,45,0,250000,6.1,131,1,0,107,0
-46,0,719,0,40,1,263358.03,1.18,137,0,0,107,0
-63,0,193,0,60,1,295000,1.3,145,1,1,107,0
-81,0,4540,0,35,0,231000,1.18,137,1,1,107,0
-75,0,582,0,40,0,263358.03,1.18,137,1,0,107,0
-65,1,59,1,60,0,172000,0.9,137,0,0,107,0
-68,1,646,0,25,0,305000,2.1,130,1,0,108,0
-62,0,281,1,35,0,221000,1,136,0,0,108,0
-50,0,1548,0,30,1,211000,0.8,138,1,0,108,0
-80,0,805,0,38,0,263358.03,1.1,134,1,0,109,1
-46,1,291,0,35,0,348000,0.9,140,0,0,109,0
-50,0,482,1,30,0,329000,0.9,132,0,0,109,0
-61,1,84,0,40,1,229000,0.9,141,0,0,110,0
-72,1,943,0,25,1,338000,1.7,139,1,1,111,1
-50,0,185,0,30,0,266000,0.7,141,1,1,112,0
-52,0,132,0,30,0,218000,0.7,136,1,1,112,0
-64,0,1610,0,60,0,242000,1,137,1,0,113,0
-75,1,582,0,30,0,225000,1.83,134,1,0,113,1
-60,0,2261,0,35,1,228000,0.9,136,1,0,115,0
-72,0,233,0,45,1,235000,2.5,135,0,0,115,1
-62,0,30,1,60,1,244000,0.9,139,1,0,117,0
-50,0,115,0,45,1,184000,0.9,134,1,1,118,0
-50,0,1846,1,35,0,263358.03,1.18,137,1,1,119,0
-65,1,335,0,35,1,235000,0.8,136,0,0,120,0
-60,1,231,1,25,0,194000,1.7,140,1,0,120,0
-52,1,58,0,35,0,277000,1.4,136,0,0,120,0
-50,0,250,0,25,0,262000,1,136,1,1,120,0
-85,1,910,0,50,0,235000,1.3,134,1,0,121,0
-59,1,129,0,45,1,362000,1.1,139,1,1,121,0
-66,1,72,0,40,1,242000,1.2,134,1,0,121,0
-45,1,130,0,35,0,174000,0.8,139,1,1,121,0
-63,1,582,0,40,0,448000,0.9,137,1,1,123,0
-50,1,2334,1,35,0,75000,0.9,142,0,0,126,1
-45,0,2442,1,30,0,334000,1.1,139,1,0,129,1
-80,0,776,1,38,1,192000,1.3,135,0,0,130,1
-53,0,196,0,60,0,220000,0.7,133,1,1,134,0
-59,0,66,1,20,0,70000,2.4,134,1,0,135,1
-65,0,582,1,40,0,270000,1,138,0,0,140,0
-70,0,835,0,35,1,305000,0.8,133,0,0,145,0
-51,1,582,1,35,0,263358.03,1.5,136,1,1,145,0
-52,0,3966,0,40,0,325000,0.9,140,1,1,146,0
-70,1,171,0,60,1,176000,1.1,145,1,1,146,0
-50,1,115,0,20,0,189000,0.8,139,1,0,146,0
-65,0,198,1,35,1,281000,0.9,137,1,1,146,0
-60,1,95,0,60,0,337000,1,138,1,1,146,0
-69,0,1419,0,40,0,105000,1,135,1,1,147,0
-49,1,69,0,50,0,132000,1,140,0,0,147,0
-63,1,122,1,60,0,267000,1.2,145,1,0,147,0
-55,0,835,0,40,0,279000,0.7,140,1,1,147,0
-40,0,478,1,30,0,303000,0.9,136,1,0,148,0
-59,1,176,1,25,0,221000,1,136,1,1,150,1
-65,0,395,1,25,0,265000,1.2,136,1,1,154,1
-75,0,99,0,38,1,224000,2.5,134,1,0,162,1
-58,1,145,0,25,0,219000,1.2,137,1,1,170,1
-60.667,1,104,1,30,0,389000,1.5,136,1,0,171,1
-50,0,582,0,50,0,153000,0.6,134,0,0,172,1
-60,0,1896,1,25,0,365000,2.1,144,0,0,172,1
-60.667,1,151,1,40,1,201000,1,136,0,0,172,0
-40,0,244,0,45,1,275000,0.9,140,0,0,174,0
-80,0,582,1,35,0,350000,2.1,134,1,0,174,0
-64,1,62,0,60,0,309000,1.5,135,0,0,174,0
-50,1,121,1,40,0,260000,0.7,130,1,0,175,0
-73,1,231,1,30,0,160000,1.18,142,1,1,180,0
-45,0,582,0,20,1,126000,1.6,135,1,0,180,1
-77,1,418,0,45,0,223000,1.8,145,1,0,180,1
-45,0,582,1,38,1,263358.03,1.18,137,0,0,185,0
-65,0,167,0,30,0,259000,0.8,138,0,0,186,0
-50,1,582,1,20,1,279000,1,134,0,0,186,0
-60,0,1211,1,35,0,263358.03,1.8,113,1,1,186,0
-63,1,1767,0,45,0,73000,0.7,137,1,0,186,0
-45,0,308,1,60,1,377000,1,136,1,0,186,0
-70,0,97,0,60,1,220000,0.9,138,1,0,186,0
-60,0,59,0,25,1,212000,3.5,136,1,1,187,0
-78,1,64,0,40,0,277000,0.7,137,1,1,187,0
-50,1,167,1,45,0,362000,1,136,0,0,187,0
-40,1,101,0,40,0,226000,0.8,141,0,0,187,0
-85,0,212,0,38,0,186000,0.9,136,1,0,187,0
-60,1,2281,1,40,0,283000,1,141,0,0,187,0
-49,0,972,1,35,1,268000,0.8,130,0,0,187,0
-70,0,212,1,17,1,389000,1,136,1,1,188,0
-50,0,582,0,62,1,147000,0.8,140,1,1,192,0
-78,0,224,0,50,0,481000,1.4,138,1,1,192,0
-48,1,131,1,30,1,244000,1.6,130,0,0,193,1
-65,1,135,0,35,1,290000,0.8,134,1,0,194,0
-73,0,582,0,35,1,203000,1.3,134,1,0,195,0
-70,0,1202,0,50,1,358000,0.9,141,0,0,196,0
-54,1,427,0,70,1,151000,9,137,0,0,196,1
-68,1,1021,1,35,0,271000,1.1,134,1,0,197,0
-55,0,582,1,35,1,371000,0.7,140,0,0,197,0
-73,0,582,0,20,0,263358.03,1.83,134,1,0,198,1
-65,0,118,0,50,0,194000,1.1,145,1,1,200,0
-42,1,86,0,35,0,365000,1.1,139,1,1,201,0
-47,0,582,0,25,0,130000,0.8,134,1,0,201,0
-58,0,582,1,25,0,504000,1,138,1,0,205,0
-75,0,675,1,60,0,265000,1.4,125,0,0,205,0
-58,1,57,0,25,0,189000,1.3,132,1,1,205,0
-55,1,2794,0,35,1,141000,1,140,1,0,206,0
-65,0,56,0,25,0,237000,5,130,0,0,207,0
-72,0,211,0,25,0,274000,1.2,134,0,0,207,0
-60,0,166,0,30,0,62000,1.7,127,0,0,207,1
-70,0,93,0,35,0,185000,1.1,134,1,1,208,0
-40,1,129,0,35,0,255000,0.9,137,1,0,209,0
-53,1,707,0,38,0,330000,1.4,137,1,1,209,0
-53,1,582,0,45,0,305000,1.1,137,1,1,209,0
-77,1,109,0,50,1,406000,1.1,137,1,0,209,0
-75,0,119,0,50,1,248000,1.1,148,1,0,209,0
-70,0,232,0,30,0,173000,1.2,132,1,0,210,0
-65,1,720,1,40,0,257000,1,136,0,0,210,0
-55,1,180,0,45,0,263358.03,1.18,137,1,1,211,0
-70,0,81,1,35,1,533000,1.3,139,0,0,212,0
-65,0,582,1,30,0,249000,1.3,136,1,1,212,0
-40,0,90,0,35,0,255000,1.1,136,1,1,212,0
-73,1,1185,0,40,1,220000,0.9,141,0,0,213,0
-54,0,582,1,38,0,264000,1.8,134,1,0,213,0
-61,1,80,1,38,0,282000,1.4,137,1,0,213,0
-55,0,2017,0,25,0,314000,1.1,138,1,0,214,1
-64,0,143,0,25,0,246000,2.4,135,1,0,214,0
-40,0,624,0,35,0,301000,1,142,1,1,214,0
-53,0,207,1,40,0,223000,1.2,130,0,0,214,0
-50,0,2522,0,30,1,404000,0.5,139,0,0,214,0
-55,0,572,1,35,0,231000,0.8,143,0,0,215,0
-50,0,245,0,45,1,274000,1,133,1,0,215,0
-70,0,88,1,35,1,236000,1.2,132,0,0,215,0
-53,1,446,0,60,1,263358.03,1,139,1,0,215,0
-52,1,191,1,30,1,334000,1,142,1,1,216,0
-65,0,326,0,38,0,294000,1.7,139,0,0,220,0
-58,0,132,1,38,1,253000,1,139,1,0,230,0
-45,1,66,1,25,0,233000,0.8,135,1,0,230,0
-53,0,56,0,50,0,308000,0.7,135,1,1,231,0
-55,0,66,0,40,0,203000,1,138,1,0,233,0
-62,1,655,0,40,0,283000,0.7,133,0,0,233,0
-65,1,258,1,25,0,198000,1.4,129,1,0,235,1
-68,1,157,1,60,0,208000,1,140,0,0,237,0
-61,0,582,1,38,0,147000,1.2,141,1,0,237,0
-50,1,298,0,35,0,362000,0.9,140,1,1,240,0
-55,0,1199,0,20,0,263358.03,1.83,134,1,1,241,1
-56,1,135,1,38,0,133000,1.7,140,1,0,244,0
-45,0,582,1,38,0,302000,0.9,140,0,0,244,0
-40,0,582,1,35,0,222000,1,132,1,0,244,0
-44,0,582,1,30,1,263358.03,1.6,130,1,1,244,0
-51,0,582,1,40,0,221000,0.9,134,0,0,244,0
-67,0,213,0,38,0,215000,1.2,133,0,0,245,0
-42,0,64,0,40,0,189000,0.7,140,1,0,245,0
-60,1,257,1,30,0,150000,1,137,1,1,245,0
-45,0,582,0,38,1,422000,0.8,137,0,0,245,0
-70,0,618,0,35,0,327000,1.1,142,0,0,245,0
-70,0,582,1,38,0,25100,1.1,140,1,0,246,0
-50,1,1051,1,30,0,232000,0.7,136,0,0,246,0
-55,0,84,1,38,0,451000,1.3,136,0,0,246,0
-70,0,2695,1,40,0,241000,1,137,1,0,247,0
-70,0,582,0,40,0,51000,2.7,136,1,1,250,0
-42,0,64,0,30,0,215000,3.8,128,1,1,250,0
-65,0,1688,0,38,0,263358.03,1.1,138,1,1,250,0
-50,1,54,0,40,0,279000,0.8,141,1,0,250,0
-55,1,170,1,40,0,336000,1.2,135,1,0,250,0
-60,0,253,0,35,0,279000,1.7,140,1,0,250,0
-45,0,582,1,55,0,543000,1,132,0,0,250,0
-65,0,892,1,35,0,263358.03,1.1,142,0,0,256,0
-90,1,337,0,38,0,390000,0.9,144,0,0,256,0
-45,0,615,1,55,0,222000,0.8,141,0,0,257,0
-60,0,320,0,35,0,133000,1.4,139,1,0,258,0
-52,0,190,1,38,0,382000,1,140,1,1,258,0
-63,1,103,1,35,0,179000,0.9,136,1,1,270,0
-62,0,61,1,38,1,155000,1.1,143,1,1,270,0
-55,0,1820,0,38,0,270000,1.2,139,0,0,271,0
-45,0,2060,1,60,0,742000,0.8,138,0,0,278,0
-45,0,2413,0,38,0,140000,1.4,140,1,1,280,0
-50,0,196,0,45,0,395000,1.6,136,1,1,285,0