From bd84848bf648e2dcad39014d57c6f5c87186d808 Mon Sep 17 00:00:00 2001 From: Jakub Henyk Date: Tue, 21 Mar 2023 20:42:13 +0100 Subject: [PATCH] Added task 1 (zadanie1) to repository --- Customers.csv | 2001 ++++++++++++++++++++++++++++++++++++++++++++++++ LICENSE | 2 +- README.md | 6 +- zadanie1.ipynb | 186 +++++ 4 files changed, 2191 insertions(+), 4 deletions(-) create mode 100644 Customers.csv create mode 100644 zadanie1.ipynb diff --git a/Customers.csv b/Customers.csv new file mode 100644 index 0000000..6f6d412 --- /dev/null +++ b/Customers.csv @@ -0,0 +1,2001 @@ +CustomerID,Gender,Age,Annual Income ($),Spending Score (1-100),Profession,Work Experience,Family Size +1,Male,19,15000,39,Healthcare,1,4 +2,Male,21,35000,81,Engineer,3,3 +3,Female,20,86000,6,Engineer,1,1 +4,Female,23,59000,77,Lawyer,0,2 +5,Female,31,38000,40,Entertainment,2,6 +6,Female,22,58000,76,Artist,0,2 +7,Female,35,31000,6,Healthcare,1,3 +8,Female,23,84000,94,Healthcare,1,3 +9,Male,64,97000,3,Engineer,0,3 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+526,Female,66,134677,59,Healthcare,15,5 +527,Female,58,180479,74,Healthcare,0,3 +528,Male,97,112783,21,Artist,9,6 +529,Male,13,150258,17,Doctor,0,3 +530,Male,48,115832,92,Artist,2,2 +531,Female,47,104834,44,Artist,0,7 +532,Male,93,152571,66,Doctor,14,5 +533,Female,11,162287,45,Engineer,3,2 +534,Female,68,171761,59,Doctor,1,6 +535,Female,87,77709,73,Artist,0,1 +536,Female,22,95053,17,Entertainment,1,2 +537,Male,89,74820,33,Doctor,1,2 +538,Male,57,152267,92,Engineer,9,5 +539,Male,91,71925,14,Artist,4,2 +540,Female,84,151340,95,Artist,1,7 +541,Male,56,162921,51,Executive,0,4 +542,Female,26,52234,30,Executive,1,2 +543,Female,56,100271,87,Artist,1,5 +544,Female,6,170266,23,Artist,3,2 +545,Female,33,88763,1,Entertainment,1,1 +546,Female,89,107359,26,,10,6 +547,Male,99,164781,83,Engineer,0,2 +548,Female,25,156016,85,Artist,2,1 +549,Female,96,186882,40,Entertainment,1,7 +550,Female,35,99300,88,Homemaker,5,2 +551,Male,16,58127,65,Marketing,0,3 +552,Female,81,89211,12,Doctor,1,7 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+605,Female,94,85265,68,Executive,7,6 +606,Female,3,155864,31,Healthcare,13,3 +607,Female,15,99421,72,Artist,8,7 +608,Female,96,145457,57,Executive,2,1 +609,Male,12,118041,77,Artist,9,2 +610,Female,23,73759,83,Doctor,0,7 +611,Male,94,90082,17,Artist,5,7 +612,Female,7,74928,12,Artist,0,6 +613,Female,74,101352,36,Lawyer,0,5 +614,Female,52,93947,81,Healthcare,9,2 +615,Male,39,134629,23,Engineer,1,6 +616,Male,72,101858,70,Healthcare,8,6 +617,Female,55,165501,47,Artist,10,4 +618,Male,29,135931,74,Lawyer,5,1 +619,Male,38,103356,20,Marketing,1,6 +620,Female,44,75195,79,Artist,1,3 +621,Male,58,123083,44,Entertainment,6,5 +622,Male,77,73884,30,Healthcare,1,2 +623,Female,56,91180,61,Entertainment,1,7 +624,Male,79,86235,52,Artist,0,2 +625,Female,97,96400,4,Doctor,1,7 +626,Male,78,83599,12,Healthcare,1,6 +627,Female,91,82535,50,Healthcare,0,1 +628,Male,35,92227,8,Lawyer,0,5 +629,Female,43,150444,27,Artist,13,4 +630,Female,37,149095,83,Lawyer,1,2 +631,Male,63,113605,42,Artist,3,3 +632,Female,16,93854,82,Healthcare,0,7 +633,Male,32,118280,92,Artist,0,5 +634,Male,91,94576,90,Artist,0,1 +635,Female,33,129257,70,Executive,6,3 +636,Female,57,70373,10,Healthcare,2,6 +637,Female,43,77600,66,Healthcare,0,1 +638,Female,26,113707,97,Entertainment,0,5 +639,Female,59,189672,8,Doctor,0,7 +640,Female,61,143180,58,Artist,0,5 +641,Female,59,174890,14,Marketing,3,4 +642,Male,66,121377,19,,7,7 +643,Male,26,154857,13,Healthcare,0,7 +644,Female,67,160945,51,Healthcare,0,5 +645,Female,85,119557,35,Artist,0,2 +646,Female,76,187141,33,Doctor,0,7 +647,Female,57,97468,22,Artist,0,1 +648,Female,77,160351,77,Lawyer,8,5 +649,Female,66,178627,94,Healthcare,1,2 +650,Female,49,170188,80,Lawyer,1,6 +651,Female,36,166007,40,Doctor,1,4 +652,Male,74,91794,83,Entertainment,0,7 +653,Female,16,189072,86,Artist,6,3 +654,Male,27,152717,15,Executive,1,6 +655,Female,3,158549,98,Executive,0,3 +656,Male,31,134263,94,Marketing,1,3 +657,Female,30,148236,28,Executive,1,1 +658,Male,94,171677,81,Artist,0,6 +659,Female,31,189446,38,Artist,1,6 +660,Male,49,106633,53,Artist,0,3 +661,Male,49,81084,48,Executive,6,5 +662,Male,53,148759,52,Doctor,7,7 +663,Female,3,117638,95,Healthcare,2,7 +664,Female,91,159537,37,Doctor,4,1 +665,Male,26,79526,6,Marketing,9,7 +666,Male,28,101414,64,,8,1 +667,Female,92,109519,72,Entertainment,1,4 +668,Female,59,156880,70,Artist,0,7 +669,Male,15,157278,58,Artist,0,6 +670,Female,23,144916,84,Engineer,1,7 +671,Male,54,59163,100,Marketing,3,3 +672,Female,93,93991,49,Artist,1,3 +673,Female,65,58318,45,Doctor,1,1 +674,Female,13,180786,88,Lawyer,1,5 +675,Male,71,84622,45,Doctor,0,6 +676,Male,1,92674,59,Artist,8,4 +677,Female,57,87553,94,Artist,1,1 +678,Male,14,74174,79,Entertainment,1,2 +679,Female,77,180831,33,Healthcare,1,2 +680,Female,89,137397,33,Doctor,1,7 +681,Male,17,96154,100,Artist,1,4 +682,Male,86,172477,69,Entertainment,1,3 +683,Male,42,59954,37,Executive,4,4 +684,Female,29,112240,95,Entertainment,0,4 +685,Female,54,145679,35,Artist,0,2 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+713,Female,69,153217,83,Healthcare,1,6 +714,Male,62,92768,75,Doctor,1,1 +715,Female,54,132345,10,Artist,0,2 +716,Female,60,186069,49,Marketing,1,2 +717,Female,31,53802,32,Artist,1,7 +718,Female,17,103739,62,Healthcare,6,4 +719,Female,15,50550,34,Healthcare,9,7 +720,Female,37,145648,21,Healthcare,7,6 +721,Male,36,85737,37,Executive,0,3 +722,Female,27,99950,20,Entertainment,0,4 +723,Female,11,83220,21,Engineer,7,4 +724,Male,83,73410,50,Entertainment,8,5 +725,Female,71,64310,43,Marketing,2,1 +726,Female,20,59844,79,Doctor,0,1 +727,Male,3,67787,1,Executive,1,6 +728,Male,52,172841,4,Engineer,0,1 +729,Male,75,145528,61,Healthcare,1,2 +730,Male,36,173807,42,Artist,0,2 +731,Male,60,185794,69,Entertainment,7,1 +732,Male,8,119780,71,Healthcare,1,3 +733,Female,9,158596,86,Artist,1,2 +734,Female,41,118122,52,Entertainment,0,6 +735,Male,38,99964,11,Healthcare,7,4 +736,Female,69,120752,27,Executive,1,6 +737,Female,33,189630,53,Executive,5,5 +738,Male,64,125510,6,Healthcare,3,3 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+1317,Female,33,109396,17,,1,2 +1318,Female,12,149031,96,Artist,10,5 +1319,Female,77,66256,13,Lawyer,1,2 +1320,Female,48,118285,69,Doctor,8,4 +1321,Male,97,128723,58,Artist,4,5 +1322,Female,28,178285,91,Artist,4,7 +1323,Female,99,144176,74,Marketing,7,2 +1324,Male,27,82474,31,Artist,9,3 +1325,Female,95,159010,84,Lawyer,6,2 +1326,Female,6,76164,83,Artist,6,2 +1327,Male,18,77873,49,Executive,6,5 +1328,Male,42,53392,89,Artist,6,4 +1329,Male,50,168898,41,Artist,9,7 +1330,Male,86,128917,7,Homemaker,5,5 +1331,Male,69,185067,49,Lawyer,5,4 +1332,Male,23,132183,76,Artist,10,3 +1333,Female,82,82060,46,Healthcare,7,1 +1334,Female,97,133614,58,Artist,7,4 +1335,Male,42,94844,64,,7,6 +1336,Female,75,76474,5,Doctor,5,5 +1337,Female,14,94655,9,Healthcare,8,1 +1338,Male,3,60933,30,Doctor,8,1 +1339,Male,16,79257,82,Healthcare,6,2 +1340,Female,45,125677,36,Entertainment,5,2 +1341,Female,23,127971,56,Artist,1,5 +1342,Male,38,76103,62,Executive,9,3 +1343,Female,45,114741,96,Artist,0,5 +1344,Female,82,157994,92,Artist,1,1 +1345,Male,73,93786,44,Entertainment,3,1 +1346,Male,36,75178,41,Entertainment,1,7 +1347,Male,13,175267,81,Healthcare,1,4 +1348,Female,96,99263,100,Healthcare,8,1 +1349,Female,83,52590,3,Healthcare,0,4 +1350,Male,33,170959,75,Artist,0,4 +1351,Male,68,135076,60,Engineer,1,5 +1352,Male,88,167112,34,Lawyer,0,1 +1353,Female,87,184639,12,Doctor,1,6 +1354,Female,88,172369,80,Artist,6,6 +1355,Female,43,124256,67,Marketing,1,7 +1356,Female,64,89972,92,Artist,10,6 +1357,Male,96,67799,42,Entertainment,1,6 +1358,Female,72,176074,70,Doctor,1,7 +1359,Male,48,167517,27,Artist,2,7 +1360,Female,64,77914,11,Artist,1,6 +1361,Female,8,57605,81,Doctor,0,2 +1362,Female,52,86365,70,Engineer,1,7 +1363,Male,3,93883,39,Healthcare,1,2 +1364,Female,44,131091,62,Artist,4,1 +1365,Male,14,87222,14,Healthcare,8,4 +1366,Female,50,117076,45,Doctor,1,2 +1367,Male,53,150925,1,Healthcare,1,2 +1368,Female,31,149379,100,Lawyer,0,3 +1369,Female,31,138644,94,Engineer,4,3 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+1397,Female,20,92048,91,Healthcare,1,1 +1398,Male,61,99980,94,Healthcare,10,1 +1399,Male,16,84003,68,Artist,9,6 +1400,Male,2,110889,95,Executive,1,2 +1401,Female,52,82478,95,Executive,10,1 +1402,Male,99,139685,20,Healthcare,1,4 +1403,Female,84,182374,62,Entertainment,0,6 +1404,Female,58,119366,94,Engineer,4,2 +1405,Female,91,53788,57,Doctor,0,2 +1406,Female,1,90341,92,Doctor,0,2 +1407,Female,67,118348,94,Engineer,1,7 +1408,Male,56,137428,87,Artist,0,2 +1409,Female,62,106982,53,Entertainment,1,7 +1410,Female,12,98532,52,Doctor,0,6 +1411,Female,38,120825,24,Executive,9,7 +1412,Female,51,58006,83,Executive,1,5 +1413,Male,20,106941,73,Artist,1,1 +1414,Male,43,129782,31,Entertainment,1,2 +1415,Male,93,121513,90,Engineer,0,6 +1416,Female,54,79925,30,Healthcare,0,3 +1417,Male,23,112089,74,Healthcare,7,7 +1418,Female,1,138656,27,,3,4 +1419,Female,64,146794,90,Healthcare,8,3 +1420,Female,55,75033,30,Engineer,5,5 +1421,Female,85,149969,78,Executive,0,6 +1422,Female,20,124852,39,Healthcare,5,5 +1423,Male,73,154837,42,Executive,8,4 +1424,Female,53,145678,55,Executive,0,1 +1425,Female,7,137354,89,Artist,8,7 +1426,Female,50,136660,48,Entertainment,1,3 +1427,Female,12,63334,99,Artist,0,6 +1428,Male,37,62893,29,Executive,1,5 +1429,Male,78,163514,89,Doctor,9,2 +1430,Male,29,145934,40,Marketing,10,2 +1431,Female,54,119223,58,Lawyer,10,7 +1432,Male,89,127479,18,Doctor,10,2 +1433,Female,25,136146,98,Artist,6,6 +1434,Female,14,76001,46,Artist,7,3 +1435,Female,12,84885,24,Healthcare,6,2 +1436,Female,18,82812,1,Artist,6,2 +1437,Male,74,51260,43,Entertainment,5,5 +1438,Male,21,159572,42,Healthcare,5,5 +1439,Male,9,130186,88,Artist,9,7 +1440,Female,49,176954,57,Artist,5,6 +1441,Male,58,85908,99,Artist,5,4 +1442,Female,16,75831,5,Healthcare,10,7 +1443,Female,55,123045,56,Engineer,7,3 +1444,Female,31,161211,10,Lawyer,9,1 +1445,Female,59,81702,27,Marketing,6,4 +1446,Female,25,173043,3,Artist,8,6 +1447,Male,63,126380,90,Artist,6,1 +1448,Female,60,128205,27,Healthcare,6,5 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+1475,Female,94,183643,51,Artist,5,5 +1476,Male,62,113306,4,Executive,5,6 +1477,Male,20,84008,77,Artist,8,4 +1478,Male,85,85758,35,Lawyer,10,4 +1479,Female,72,63128,45,Engineer,8,7 +1480,Male,95,70174,6,Executive,10,6 +1481,Female,97,170133,42,Engineer,5,5 +1482,Female,25,165978,42,Artist,7,3 +1483,Female,17,149727,78,Artist,7,3 +1484,Female,19,147052,86,,9,4 +1485,Female,59,113389,79,Doctor,4,6 +1486,Male,30,111690,73,Entertainment,10,4 +1487,Female,63,184830,60,Doctor,9,3 +1488,Female,23,91549,23,Artist,4,3 +1489,Female,97,94629,17,Marketing,6,3 +1490,Female,97,167558,99,Artist,4,7 +1491,Male,94,119189,57,Artist,9,3 +1492,Female,28,96207,67,Artist,5,5 +1493,Male,21,85339,6,Doctor,4,7 +1494,Female,25,111942,7,Artist,5,5 +1495,Female,48,157003,45,Engineer,5,4 +1496,Female,53,117123,23,Artist,9,7 +1497,Female,97,172747,76,Artist,7,2 +1498,Male,33,157358,52,Healthcare,7,4 +1499,Male,5,156655,20,Entertainment,4,5 +1500,Male,72,166043,93,Doctor,7,6 +1501,Male,40,67768,15,Doctor,10,6 +1502,Male,34,171353,34,Doctor,8,4 +1503,Female,63,116971,76,Executive,7,5 +1504,Female,85,97822,38,Doctor,5,3 +1505,Female,86,117203,83,Healthcare,10,3 +1506,Female,63,88720,100,Artist,10,1 +1507,Female,9,173233,18,,5,1 +1508,Female,76,139447,36,Artist,8,7 +1509,Male,19,179269,93,Entertainment,6,3 +1510,Female,84,136254,90,Engineer,5,6 +1511,Male,38,174594,56,Executive,8,2 +1512,Female,1,100429,19,Entertainment,9,1 +1513,Female,30,73107,48,Artist,9,1 +1514,Female,86,98344,25,Artist,6,6 +1515,Male,21,163509,21,Healthcare,10,1 +1516,Male,15,116204,16,Engineer,8,2 +1517,Female,87,95853,53,Healthcare,9,1 +1518,Male,40,156411,70,Artist,6,5 +1519,Male,2,72889,36,Homemaker,5,7 +1520,Female,63,106691,79,Healthcare,9,3 +1521,Male,26,144832,42,Artist,5,3 +1522,Male,29,132297,53,Entertainment,8,1 +1523,Female,7,170345,3,Executive,9,5 +1524,Male,28,157383,13,Lawyer,8,2 +1525,Female,99,150782,18,Executive,8,2 +1526,Male,69,143987,87,Healthcare,10,5 +1527,Female,13,129659,59,Entertainment,6,7 +1528,Male,73,104826,36,Healthcare,5,1 +1529,Female,4,181471,59,Healthcare,10,4 +1530,Female,42,152547,56,Artist,7,4 +1531,Male,43,85347,9,Doctor,1,1 +1532,Female,79,122828,32,Executive,0,5 +1533,Male,18,107794,17,Engineer,0,5 +1534,Male,39,152566,11,Entertainment,1,7 +1535,Female,41,91715,99,Entertainment,0,3 +1536,Female,60,99222,48,Artist,1,6 +1537,Female,39,70280,99,Engineer,0,4 +1538,Female,90,70030,86,Healthcare,1,2 +1539,Female,83,102083,24,Artist,1,1 +1540,Female,92,166163,87,Engineer,8,5 +1541,Female,6,182871,27,Engineer,8,6 +1542,Male,50,187545,61,Executive,4,6 +1543,Male,90,182910,86,Entertainment,0,1 +1544,Female,13,174530,30,Lawyer,1,6 +1545,Female,27,115438,37,Artist,0,6 +1546,Female,93,93964,80,Artist,4,2 +1547,Female,61,180341,75,Healthcare,1,3 +1548,Female,91,107323,1,Engineer,7,7 +1549,Female,79,119435,55,Entertainment,0,7 +1550,Female,80,68341,22,Artist,13,6 +1551,Female,16,95365,60,Artist,0,5 +1552,Male,4,131093,79,Lawyer,1,7 +1553,Female,34,100621,3,Healthcare,1,1 +1554,Male,10,116521,47,Doctor,0,2 +1555,Female,3,136316,88,Executive,0,3 +1556,Male,96,172039,51,Lawyer,0,6 +1557,Female,48,70844,22,Entertainment,0,3 +1558,Male,25,100964,96,Marketing,1,6 +1559,Female,98,128037,39,Entertainment,6,2 +1560,Male,84,97081,75,Marketing,1,3 +1561,Male,88,92247,47,Marketing,0,6 +1562,Male,86,129914,92,Artist,1,3 +1563,Female,0,94014,53,Engineer,9,5 +1564,Female,56,138864,93,Artist,0,5 +1565,Male,6,169299,46,Marketing,1,5 +1566,Male,2,119097,40,Healthcare,0,7 +1567,Female,73,68161,23,Doctor,1,2 +1568,Female,38,181108,32,Homemaker,1,1 +1569,Male,37,87764,59,Engineer,9,7 +1570,Female,41,102543,54,Artist,7,3 +1571,Male,94,139417,13,Artist,1,3 +1572,Female,57,81802,29,Homemaker,9,1 +1573,Female,96,102788,51,Artist,0,1 +1574,Female,59,163179,19,Healthcare,1,7 +1575,Male,87,71318,22,Healthcare,1,3 +1576,Male,55,63683,34,Healthcare,3,1 +1577,Female,16,189689,37,Healthcare,8,5 +1578,Male,82,121610,36,Artist,0,5 +1579,Female,83,150682,25,Artist,1,1 +1580,Female,96,124550,46,Marketing,0,3 +1581,Male,55,148875,99,Artist,0,4 +1582,Male,6,107117,44,Artist,1,3 +1583,Male,33,109223,43,Engineer,1,5 +1584,Female,0,120899,7,Marketing,2,6 +1585,Female,27,101948,31,Artist,0,5 +1586,Male,72,143169,58,Engineer,0,4 +1587,Female,13,167619,4,Healthcare,7,6 +1588,Female,19,181795,59,Healthcare,3,5 +1589,Female,48,186445,41,Engineer,0,1 +1590,Female,58,102205,24,Artist,1,1 +1591,Female,21,52326,69,Healthcare,0,2 +1592,Male,91,82992,5,Entertainment,1,5 +1593,Male,44,145520,55,Homemaker,1,7 +1594,Female,80,104820,96,Artist,2,4 +1595,Female,28,69025,79,Entertainment,0,2 +1596,Male,74,164976,89,Entertainment,0,4 +1597,Female,79,178576,51,Executive,5,5 +1598,Female,42,72415,52,Marketing,0,5 +1599,Male,80,112146,24,Entertainment,0,3 +1600,Male,8,144830,43,Artist,0,1 +1601,Female,24,51661,79,Entertainment,0,7 +1602,Female,71,152910,90,Artist,1,6 +1603,Male,1,114556,64,Entertainment,0,7 +1604,Male,0,143455,62,Healthcare,1,6 +1605,Male,30,173096,92,Healthcare,0,3 +1606,Female,52,121172,97,Healthcare,5,4 +1607,Female,34,56492,15,Homemaker,8,1 +1608,Male,64,156422,39,Entertainment,1,7 +1609,Male,17,131863,94,Artist,1,7 +1610,Male,71,118096,36,Lawyer,0,3 +1611,Male,87,149685,30,Executive,9,6 +1612,Female,68,89765,28,Artist,0,7 +1613,Female,14,177701,49,Entertainment,0,6 +1614,Male,24,64738,67,Artist,0,6 +1615,Female,10,92734,28,Lawyer,1,4 +1616,Female,53,146877,47,Healthcare,4,3 +1617,Female,39,62935,60,Artist,0,7 +1618,Female,16,67178,17,Entertainment,8,3 +1619,Female,64,115754,35,Engineer,1,3 +1620,Female,41,186470,21,Artist,0,7 +1621,Male,16,100939,34,Healthcare,7,6 +1622,Female,94,86172,55,Artist,4,4 +1623,Female,40,184222,17,Healthcare,0,2 +1624,Male,81,71543,1,Entertainment,1,4 +1625,Female,18,174836,63,Healthcare,0,4 +1626,Female,78,130706,72,,3,6 +1627,Male,8,74407,100,Doctor,0,6 +1628,Male,64,130055,46,Healthcare,2,1 +1629,Male,45,88707,81,Healthcare,0,5 +1630,Male,99,162762,52,Healthcare,1,1 +1631,Male,59,154821,77,Doctor,0,2 +1632,Male,53,57248,66,Lawyer,5,5 +1633,Female,66,99902,54,Engineer,10,2 +1634,Female,1,165711,50,Artist,1,2 +1635,Male,73,97455,55,,6,4 +1636,Female,34,93866,43,Entertainment,9,2 +1637,Female,1,141307,17,Healthcare,1,3 +1638,Male,73,172011,9,Doctor,1,5 +1639,Male,90,68138,18,Healthcare,2,7 +1640,Female,32,123246,100,Homemaker,8,6 +1641,Female,47,124194,32,Doctor,1,7 +1642,Male,15,188696,87,Homemaker,8,3 +1643,Female,78,91213,84,Lawyer,3,5 +1644,Female,83,166650,99,Healthcare,1,3 +1645,Male,2,52727,60,Artist,1,3 +1646,Male,75,126469,86,Entertainment,1,2 +1647,Male,45,138775,17,Executive,0,7 +1648,Female,49,68901,70,Doctor,7,7 +1649,Female,41,118621,7,Homemaker,0,7 +1650,Male,34,109263,77,Entertainment,0,1 +1651,Male,82,150012,83,Healthcare,3,6 +1652,Male,37,133850,85,Marketing,9,3 +1653,Female,25,81640,95,Entertainment,1,6 +1654,Female,52,133214,1,Marketing,9,7 +1655,Female,23,186723,42,Entertainment,8,5 +1656,Female,96,92100,23,Artist,9,3 +1657,Male,5,64484,10,Homemaker,0,5 +1658,Female,47,69024,3,Healthcare,4,5 +1659,Male,81,171194,55,Artist,0,5 +1660,Female,4,183282,34,Artist,1,1 +1661,Female,8,100099,74,Healthcare,1,3 +1662,Female,35,164435,26,Lawyer,1,3 +1663,Male,67,172407,60,Doctor,9,3 +1664,Female,9,84781,14,Executive,1,3 +1665,Male,82,186130,61,Lawyer,3,7 +1666,Female,2,56782,10,Artist,9,5 +1667,Male,95,137206,4,Artist,0,4 +1668,Female,9,146950,92,Doctor,6,5 +1669,Female,99,174275,4,Healthcare,0,2 +1670,Male,96,97705,41,Homemaker,8,2 +1671,Male,92,188984,69,Lawyer,1,4 +1672,Male,24,119238,55,Artist,1,3 +1673,Male,58,87923,19,Entertainment,0,5 +1674,Male,15,128573,97,Executive,1,1 +1675,Female,13,132374,96,Marketing,0,3 +1676,Female,51,135164,75,Artist,9,3 +1677,Male,9,165194,10,Artist,8,3 +1678,Male,0,126060,92,Doctor,1,3 +1679,Male,67,89366,55,Healthcare,9,3 +1680,Male,58,95172,77,Healthcare,1,5 +1681,Female,55,95975,49,Executive,0,1 +1682,Female,52,165573,59,Healthcare,0,7 +1683,Male,83,180887,59,Entertainment,1,1 +1684,Female,83,142720,86,Executive,0,1 +1685,Female,90,113460,54,Lawyer,1,7 +1686,Male,87,110434,20,Artist,7,3 +1687,Female,67,146016,38,Artist,1,6 +1688,Male,81,101073,67,Executive,0,7 +1689,Female,36,62617,10,Artist,9,3 +1690,Female,51,96028,37,Artist,0,5 +1691,Female,31,186334,37,Artist,0,1 +1692,Female,57,163473,52,Artist,0,1 +1693,Male,83,89819,59,Artist,4,2 +1694,Female,51,69388,33,Engineer,3,4 +1695,Female,15,134748,76,Marketing,1,6 +1696,Female,18,149915,94,Doctor,14,1 +1697,Female,88,104098,48,Healthcare,1,6 +1698,Male,70,80160,10,Artist,8,5 +1699,Male,9,124125,91,Artist,1,2 +1700,Male,6,170226,31,Lawyer,0,3 +1701,Female,8,53306,98,Engineer,0,2 +1702,Male,55,103933,31,Executive,6,3 +1703,Female,69,85401,10,Entertainment,4,6 +1704,Female,18,53812,32,Homemaker,9,5 +1705,Female,13,60771,50,Entertainment,1,7 +1706,Female,69,56398,75,Entertainment,8,3 +1707,Female,69,171118,91,Engineer,9,3 +1708,Male,69,79806,73,Healthcare,0,5 +1709,Female,89,150187,35,Healthcare,0,5 +1710,Female,45,129455,14,Lawyer,0,3 +1711,Female,75,116813,72,Entertainment,10,6 +1712,Female,54,95734,39,Homemaker,8,7 +1713,Male,33,76654,48,Artist,4,1 +1714,Male,67,86289,96,Artist,1,5 +1715,Male,26,176147,19,Healthcare,0,1 +1716,Female,5,142351,97,Entertainment,0,7 +1717,Male,65,186673,51,Doctor,1,1 +1718,Female,94,131521,62,Artist,0,6 +1719,Female,95,50223,15,Entertainment,8,1 +1720,Female,48,74308,23,Entertainment,1,2 +1721,Female,41,155881,22,Lawyer,0,7 +1722,Female,92,168303,16,Executive,9,4 +1723,Male,44,182748,58,Engineer,1,7 +1724,Female,35,52374,73,Artist,1,1 +1725,Female,34,86154,17,Doctor,1,2 +1726,Female,52,163612,51,Executive,0,5 +1727,Female,64,64756,17,Marketing,10,1 +1728,Male,62,185257,58,Artist,1,4 +1729,Male,58,78669,75,Artist,1,7 +1730,Male,15,164520,47,Artist,1,7 +1731,Female,65,92135,49,Homemaker,6,4 +1732,Male,20,103195,68,Doctor,0,7 +1733,Female,21,161663,36,Executive,1,7 +1734,Female,79,57039,34,Artist,2,6 +1735,Female,91,54754,4,Artist,0,2 +1736,Female,92,136531,76,Engineer,1,4 +1737,Male,62,120838,79,Artist,1,4 +1738,Male,94,127927,48,Doctor,0,4 +1739,Male,10,164214,77,Lawyer,0,4 +1740,Female,53,145498,66,Artist,8,4 +1741,Male,7,129215,69,Entertainment,9,6 +1742,Female,92,152429,76,Entertainment,0,2 +1743,Female,12,89252,31,Entertainment,0,5 +1744,Female,31,147447,23,Doctor,6,7 +1745,Female,93,74467,33,Lawyer,5,1 +1746,Female,66,127410,37,Engineer,8,2 +1747,Male,49,91290,44,Healthcare,7,7 +1748,Female,64,92812,97,Artist,5,7 +1749,Female,27,170166,18,Artist,10,4 +1750,Female,33,150823,75,Artist,4,1 +1751,Male,79,95839,30,Executive,7,2 +1752,Female,14,60175,60,Executive,9,7 +1753,Female,22,153024,91,Artist,10,7 +1754,Female,8,116858,67,Artist,5,7 +1755,Female,6,122961,47,Doctor,8,2 +1756,Male,81,141471,45,Artist,8,6 +1757,Male,69,76155,14,Healthcare,8,7 +1758,Male,0,108169,24,Executive,10,3 +1759,Female,61,139520,39,Artist,8,4 +1760,Male,62,182631,52,Artist,5,3 +1761,Female,95,177134,78,Healthcare,10,2 +1762,Female,32,181703,54,Lawyer,6,2 +1763,Female,13,61917,16,Artist,7,2 +1764,Female,1,140648,36,Executive,9,7 +1765,Female,63,176783,40,Doctor,9,4 +1766,Male,75,59741,67,Artist,10,5 +1767,Female,43,156567,89,Engineer,7,6 +1768,Female,29,110309,21,Artist,6,2 +1769,Female,82,111077,55,Artist,9,7 +1770,Female,87,170333,96,Entertainment,4,2 +1771,Male,66,183339,39,Artist,7,4 +1772,Female,99,84167,46,Artist,10,7 +1773,Female,54,184815,50,Lawyer,6,3 +1774,Female,49,122556,74,Artist,9,7 +1775,Female,60,174768,66,Entertainment,9,2 +1776,Male,75,172309,82,Executive,4,1 +1777,Male,77,117920,4,Doctor,10,4 +1778,Male,34,134882,61,Artist,10,3 +1779,Female,63,77259,11,Lawyer,6,6 +1780,Male,38,170019,38,Artist,7,2 +1781,Female,68,176884,94,Engineer,10,2 +1782,Female,80,106709,93,Marketing,10,2 +1783,Female,8,168723,31,Homemaker,7,2 +1784,Female,86,90228,68,Engineer,7,5 +1785,Female,1,89473,85,Lawyer,10,4 +1786,Male,56,131911,42,Healthcare,7,7 +1787,Female,14,140107,63,Marketing,6,6 +1788,Female,4,170403,44,Artist,4,5 +1789,Female,58,51416,46,,7,5 +1790,Female,6,52648,2,Artist,5,2 +1791,Male,17,125471,48,Engineer,7,1 +1792,Female,55,106153,62,Artist,10,1 +1793,Male,14,124785,28,Lawyer,7,2 +1794,Female,22,101474,14,Homemaker,10,2 +1795,Female,8,141359,65,Healthcare,4,5 +1796,Female,70,57596,96,Artist,4,1 +1797,Female,67,78489,81,Artist,7,5 +1798,Male,50,112957,71,Executive,5,3 +1799,Male,72,82377,37,Engineer,9,2 +1800,Male,76,82315,53,Engineer,6,1 +1801,Male,80,93253,51,Artist,4,5 +1802,Male,20,189650,60,Lawyer,8,4 +1803,Female,89,114858,53,Artist,10,1 +1804,Female,18,62151,18,Artist,8,2 +1805,Female,75,135159,12,Engineer,7,6 +1806,Female,5,126263,55,Marketing,6,3 +1807,Female,79,123064,41,Artist,10,4 +1808,Female,31,181773,40,Healthcare,8,1 +1809,Male,92,171794,65,Artist,6,5 +1810,Female,15,156339,27,Homemaker,6,2 +1811,Male,94,65483,84,Marketing,10,7 +1812,Female,35,145654,22,Executive,6,3 +1813,Female,68,91609,43,Entertainment,8,1 +1814,Female,29,53002,73,Lawyer,5,5 +1815,Male,87,115699,61,Healthcare,9,1 +1816,Male,33,149609,44,Executive,9,2 +1817,Female,29,165254,7,Executive,9,7 +1818,Male,43,50418,49,Healthcare,5,1 +1819,Male,43,103531,90,Artist,10,5 +1820,Female,66,184060,98,Artist,10,5 +1821,Male,23,75961,70,Executive,5,7 +1822,Male,87,174163,28,Artist,4,2 +1823,Female,81,105255,54,Executive,8,3 +1824,Male,42,51860,4,Lawyer,4,5 +1825,Female,32,185218,83,Healthcare,4,6 +1826,Male,7,189709,18,Artist,6,6 +1827,Female,91,134665,66,Artist,7,2 +1828,Male,95,91352,9,Doctor,7,3 +1829,Female,10,154623,21,Artist,6,6 +1830,Female,20,113767,88,Artist,6,2 +1831,Male,5,160469,61,Lawyer,8,1 +1832,Female,84,99418,27,Artist,4,2 +1833,Male,54,56215,34,Healthcare,10,4 +1834,Male,12,55639,63,Healthcare,8,1 +1835,Female,90,62504,99,Artist,10,4 +1836,Female,19,151382,38,Lawyer,1,1 +1837,Female,91,156574,96,Marketing,0,7 +1838,Female,90,60998,35,Entertainment,1,7 +1839,Female,60,108509,36,Doctor,0,2 +1840,Female,68,85540,49,Homemaker,9,1 +1841,Female,43,73915,47,Artist,11,2 +1842,Male,52,148901,77,Healthcare,4,4 +1843,Male,81,152602,91,Entertainment,0,1 +1844,Female,54,58999,22,Entertainment,7,3 +1845,Female,43,133740,37,Artist,5,4 +1846,Female,20,113217,41,Lawyer,9,1 +1847,Female,71,60209,46,Artist,1,3 +1848,Female,26,145491,72,Entertainment,9,5 +1849,Female,75,61393,65,Doctor,7,5 +1850,Female,52,133252,55,Artist,1,1 +1851,Female,40,187234,14,Doctor,0,5 +1852,Male,5,145563,60,Entertainment,9,6 +1853,Female,46,165810,38,Healthcare,3,5 +1854,Male,98,125181,30,Artist,0,7 +1855,Female,84,56809,96,Healthcare,1,2 +1856,Male,35,69419,68,Healthcare,9,1 +1857,Female,78,70689,54,Artist,1,4 +1858,Male,64,55011,53,Artist,1,7 +1859,Female,98,87955,79,Engineer,0,2 +1860,Male,66,153660,24,Healthcare,0,5 +1861,Male,32,104494,28,Healthcare,6,4 +1862,Male,22,184443,44,Executive,3,7 +1863,Female,17,150778,35,Entertainment,1,7 +1864,Female,22,88729,81,Engineer,1,1 +1865,Male,9,151902,18,Artist,0,2 +1866,Male,24,51604,4,Artist,0,2 +1867,Female,8,157316,75,Artist,9,3 +1868,Female,52,125508,15,Artist,1,6 +1869,Male,62,186157,54,Healthcare,1,1 +1870,Female,37,169381,45,Entertainment,0,4 +1871,Male,68,110195,47,Homemaker,9,2 +1872,Female,63,81199,80,Entertainment,1,2 +1873,Female,15,58459,67,Executive,0,6 +1874,Female,44,173682,89,Artist,12,6 +1875,Male,18,162983,16,Entertainment,0,6 +1876,Male,30,94480,1,Executive,0,4 +1877,Female,69,168710,80,Doctor,1,4 +1878,Male,16,150193,83,Engineer,2,2 +1879,Female,71,91823,74,Artist,1,4 +1880,Female,24,173091,24,Entertainment,6,2 +1881,Male,57,102692,94,Healthcare,0,2 +1882,Male,97,156812,77,Healthcare,0,6 +1883,Male,68,51468,48,Artist,0,3 +1884,Female,11,114071,37,Healthcare,0,2 +1885,Female,63,155638,81,,1,4 +1886,Male,68,129971,61,Artist,8,3 +1887,Female,69,104160,77,Engineer,4,4 +1888,Female,77,124995,66,Healthcare,0,1 +1889,Female,73,180437,50,Entertainment,1,5 +1890,Female,19,134644,96,Executive,1,2 +1891,Female,1,130089,67,Artist,0,5 +1892,Male,71,149318,27,Artist,4,1 +1893,Male,6,125591,79,Healthcare,8,6 +1894,Female,68,173047,17,Healthcare,0,3 +1895,Female,39,61298,91,Artist,0,5 +1896,Male,75,132993,55,Entertainment,8,2 +1897,Female,65,72313,36,Lawyer,1,5 +1898,Female,30,84885,9,Entertainment,6,5 +1899,Male,46,126228,95,Marketing,8,2 +1900,Male,40,51199,29,Executive,7,7 +1901,Female,40,54631,70,Artist,0,6 +1902,Female,20,131810,16,Healthcare,5,7 +1903,Male,88,138482,59,Marketing,8,4 +1904,Male,85,74081,87,Healthcare,4,3 +1905,Male,94,112426,54,Engineer,9,6 +1906,Female,52,164038,53,,5,4 +1907,Female,68,53552,97,Marketing,7,6 +1908,Male,15,142147,78,Artist,8,4 +1909,Male,4,180324,41,Artist,9,2 +1910,Male,59,149067,78,Doctor,9,7 +1911,Male,32,184408,38,Entertainment,6,7 +1912,Female,8,59116,45,Artist,10,6 +1913,Female,92,174786,94,Executive,4,3 +1914,Male,9,71076,2,Artist,8,1 +1915,Female,41,56837,4,Healthcare,8,4 +1916,Female,18,134752,47,Engineer,6,5 +1917,Female,78,112887,80,Entertainment,9,6 +1918,Female,0,73128,74,Artist,7,5 +1919,Female,11,152765,17,Healthcare,8,1 +1920,Female,36,140637,19,Executive,8,7 +1921,Male,46,137973,50,Healthcare,7,7 +1922,Female,95,126791,34,Artist,6,4 +1923,Female,97,75125,89,Executive,8,3 +1924,Male,2,101718,11,Executive,8,3 +1925,Female,94,69654,30,Homemaker,4,4 +1926,Female,0,105935,46,Doctor,4,5 +1927,Male,3,74607,69,Healthcare,6,1 +1928,Male,77,151985,29,Healthcare,4,7 +1929,Male,70,76892,64,Executive,5,2 +1930,Male,58,87602,25,Executive,5,3 +1931,Male,72,182317,46,Healthcare,8,6 +1932,Male,90,158280,92,Executive,6,7 +1933,Female,23,59905,79,,7,5 +1934,Female,87,128153,42,Artist,7,6 +1935,Male,64,142612,58,Doctor,4,6 +1936,Female,15,180163,9,Doctor,10,7 +1937,Female,14,68009,17,Artist,9,3 +1938,Male,54,166183,65,Artist,7,6 +1939,Male,76,132537,44,Doctor,5,3 +1940,Female,76,146308,49,Artist,5,1 +1941,Female,52,63454,38,Artist,5,5 +1942,Male,96,110519,6,Artist,9,4 +1943,Female,55,66728,50,Healthcare,10,5 +1944,Female,54,170638,64,Artist,4,5 +1945,Male,19,129635,100,Artist,6,4 +1946,Male,29,133587,74,Marketing,5,3 +1947,Male,96,126225,47,Engineer,7,4 +1948,Female,20,148776,21,Artist,8,5 +1949,Female,91,142602,64,Lawyer,7,6 +1950,Male,37,102413,38,Healthcare,5,5 +1951,Male,42,68765,69,Entertainment,4,1 +1952,Male,1,57522,75,Artist,10,5 +1953,Female,58,149237,80,Entertainment,8,6 +1954,Female,42,184844,24,Entertainment,6,1 +1955,Female,48,131656,45,Lawyer,9,6 +1956,Female,11,181026,39,Marketing,6,2 +1957,Male,59,101698,87,Artist,9,3 +1958,Female,45,152560,32,Entertainment,9,2 +1959,Male,73,142502,97,Doctor,5,1 +1960,Female,85,155432,21,Engineer,4,6 +1961,Female,70,108544,49,Entertainment,4,5 +1962,Female,52,106530,46,Engineer,7,2 +1963,Male,70,124359,51,Homemaker,7,7 +1964,Female,88,146970,90,Artist,7,6 +1965,Male,61,182176,96,Artist,9,5 +1966,Female,46,114435,34,Artist,8,3 +1967,Male,65,134213,32,Homemaker,8,4 +1968,Female,84,115580,73,Entertainment,8,5 +1969,Female,76,124034,88,Executive,10,2 +1970,Male,31,67894,42,Doctor,9,1 +1971,Male,55,107099,89,Executive,4,6 +1972,Male,45,140263,88,Entertainment,10,5 +1973,Male,98,104249,12,Engineer,5,2 +1974,Male,40,168821,36,Executive,4,5 +1975,Female,14,153145,59,Healthcare,8,6 +1976,Female,41,128960,43,Executive,9,4 +1977,Male,60,127438,82,Engineer,7,2 +1978,Male,60,125968,100,Lawyer,8,2 +1979,Male,84,104589,85,Artist,10,2 +1980,Male,0,165321,93,Doctor,8,1 +1981,Female,10,86925,76,Artist,7,2 +1982,Female,62,149797,19,Artist,5,6 +1983,Male,33,137094,68,Lawyer,4,1 +1984,Female,52,55395,41,Marketing,10,1 +1985,Female,2,153622,51,Lawyer,6,6 +1986,Male,27,74050,44,Entertainment,8,1 +1987,Female,4,68094,61,Doctor,4,7 +1988,Male,63,59244,80,Artist,7,1 +1989,Female,54,118944,77,Artist,4,4 +1990,Female,47,75293,55,Doctor,6,7 +1991,Female,30,166983,69,Artist,7,3 +1992,Female,97,129444,96,Entertainment,5,6 +1993,Male,94,181183,24,Marketing,9,3 +1994,Female,64,175254,100,Artist,9,5 +1995,Female,19,54121,89,Engineer,6,3 +1996,Female,71,184387,40,Artist,8,7 +1997,Female,91,73158,32,Doctor,7,7 +1998,Male,87,90961,14,Healthcare,9,2 +1999,Male,77,182109,4,Executive,7,2 +2000,Male,90,110610,52,Entertainment,5,2 diff --git a/LICENSE b/LICENSE index c7ffc1a..cb76ea6 100644 --- a/LICENSE +++ b/LICENSE @@ -1 +1 @@ -"THE BEER-WARE LICENSE" (Revision 42): wrote this file. As long as you retain this notice you can do whatever you want with this stuff. If we meet some day, and you think this stuff is worth it, you can buy me a beer in return Poul-Henning Kamp +"THE BEER-WARE LICENSE" (Revision 42): wrote this file. As long as you retain this notice you can do whatever you want with this stuff. If we meet some day, and you think this stuff is worth it, you can buy me a beer in return Poul-Henning Kamp diff --git a/README.md b/README.md index 533e5bb..cbd5192 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,3 @@ -# ium_452627 - -Rozwiązania zadań do przedmiotu Inżynieria Uczenia Maszynowego \ No newline at end of file +# ium_452627 + +Rozwiązania zadań do przedmiotu: Inżynieria Uczenia Maszynowego \ No newline at end of file diff --git a/zadanie1.ipynb b/zadanie1.ipynb new file mode 100644 index 0000000..5bbd709 --- /dev/null +++ b/zadanie1.ipynb @@ -0,0 +1,186 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " CustomerID Gender Age Annual Income ($) Spending Score (1-100) \\\n", + "0 1 Male 19 15000 39 \n", + "1 2 Male 21 35000 81 \n", + "2 3 Female 20 86000 6 \n", + "3 4 Female 23 59000 77 \n", + "4 5 Female 31 38000 40 \n", + "5 6 Female 22 58000 76 \n", + "6 7 Female 35 31000 6 \n", + "7 8 Female 23 84000 94 \n", + "8 9 Male 64 97000 3 \n", + "9 10 Female 30 98000 72 \n", + "\n", + " Profession Work Experience Family Size \n", + "0 Healthcare 1 4 \n", + "1 Engineer 3 3 \n", + "2 Engineer 1 1 \n", + "3 Lawyer 0 2 \n", + "4 Entertainment 2 6 \n", + "5 Artist 0 2 \n", + "6 Healthcare 1 3 \n", + "7 Healthcare 1 3 \n", + "8 Engineer 0 3 \n", + "9 Artist 1 4 \n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "\n", + "data = pd.read_csv(\"Customers.csv\")\n", + "print(data[:10])" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Gender Age Annual Income ($) Spending Score (1-100) Profession \\\n", + "0 0.0 0.191919 0.078958 0.39 0.111111 \n", + "1 0.0 0.212121 0.184236 0.81 0.222222 \n", + "2 1.0 0.202020 0.452694 0.06 0.222222 \n", + "3 1.0 0.232323 0.310569 0.77 0.333333 \n", + "4 1.0 0.313131 0.200027 0.40 0.444444 \n", + "5 1.0 0.222222 0.305305 0.76 0.555556 \n", + "6 1.0 0.353535 0.163180 0.06 0.111111 \n", + "7 1.0 0.232323 0.442166 0.94 0.111111 \n", + "8 0.0 0.646465 0.510596 0.03 0.222222 \n", + "9 1.0 0.303030 0.515860 0.72 0.555556 \n", + "\n", + " Work Experience Family Size \n", + "0 0.058824 0.375 \n", + "1 0.176471 0.250 \n", + "2 0.058824 0.000 \n", + "3 0.000000 0.125 \n", + "4 0.117647 0.625 \n", + "5 0.000000 0.125 \n", + "6 0.058824 0.250 \n", + "7 0.058824 0.250 \n", + "8 0.000000 0.250 \n", + "9 0.058824 0.375 \n" + ] + } + ], + "source": [ + "dataF = data\n", + "\n", + "# Changing words to numbers\n", + "\n", + "mapping = {'NaN' : 0, 'Healthcare' : 1, 'Engineer' : 2, 'Lawyer' : 3, 'Entertainment' : 4, 'Artist' : 5, 'Executive' : 6,\n", + " 'Doctor' : 7, 'Homemaker' : 8, 'Marketing' : 9}\n", + "\n", + "mapping2 = {'Male' : 0, 'Female' : 1}\n", + "\n", + "dataF = dataF.replace({'Profession': mapping})\n", + "dataF = dataF.replace({'Gender': mapping2})\n", + "\n", + "dataF = dataF.drop(columns=['CustomerID'])\n", + "\n", + "# Normalization\n", + "\n", + "dataF['Profession'] = dataF['Profession'].fillna(0)\n", + "\n", + "normalized_dataF = (dataF - dataF.min())/(dataF.max() - dataF.min())\n", + "\n", + "print(normalized_dataF[:10])" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [], + "source": [ + "train_data = normalized_dataF[0:1600]\n", + "dev_data = normalized_dataF[1600:1800]\n", + "test_data = normalized_dataF[1800:]" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Wielkość zbioru Customers: 2000 elementów\n", + "Wielkość zbioru trenującego: 1600 elementów\n", + "Wielkość zbioru walidującego: 200 elementów\n", + "Wielkość zbioru testującego: 200 elementów\n", + " \n", + "Dane i wartości na temat zbioru: \n", + " \n", + " Gender Age Annual Income ($) Spending Score (1-100) \\\n", + "count 2000.000000 2000.000000 2000.000000 2000.000000 \n", + "mean 0.593000 0.494545 0.582879 0.509625 \n", + "std 0.491398 0.287169 0.240767 0.279347 \n", + "min 0.000000 0.000000 0.000000 0.000000 \n", + "25% 0.000000 0.252525 0.392538 0.280000 \n", + "50% 1.000000 0.484848 0.579263 0.500000 \n", + "75% 1.000000 0.737374 0.784806 0.750000 \n", + "max 1.000000 1.000000 1.000000 1.000000 \n", + "\n", + " Profession Work Experience Family Size \n", + "count 2000.000000 2000.000000 2000.000000 \n", + "mean 0.467167 0.241324 0.346062 \n", + "std 0.250289 0.230718 0.246344 \n", + "min 0.000000 0.000000 0.000000 \n", + "25% 0.222222 0.058824 0.125000 \n", + "50% 0.555556 0.176471 0.375000 \n", + "75% 0.555556 0.411765 0.500000 \n", + "max 1.000000 1.000000 1.000000 \n" + ] + } + ], + "source": [ + "print(f\"Wielkość zbioru Customers: {len(data)} elementów\")\n", + "print(f\"Wielkość zbioru trenującego: {len(train_data)} elementów\")\n", + "print(f\"Wielkość zbioru walidującego: {len(dev_data)} elementów\")\n", + "print(f\"Wielkość zbioru testującego: {len(test_data)} elementów\")\n", + "\n", + "print(f\" \\nDane i wartości na temat zbioru: \\n \\n {normalized_dataF.describe()}\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.6" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +}