├── Lecture 2
    └── Data Visualisation
    │   ├── 1976-2016-president.csv
    │   └── Data Visualisation .ipynb
├── Lecture 3
    └── EDA
    │   ├── EDA.ipynb
    │   ├── bank.csv
    │   └── test
├── Lecture 4
    └── Network Analysis
    │   ├── NetworkX.ipynb
    │   ├── knuth_miles.txt.gz
    │   ├── quaker_network.gexf
    │   ├── quakers_edgelist.csv
    │   ├── quakers_nodelist.csv
    │   └── readme.md
├── Lecture 5
    └── Supervised_learning
    │   ├── Iris.csv
    │   ├── Supervised Learning.ipynb
    │   └── readme.md
├── Lecture 6
    ├── Unsupervised Learning.ipynb
    ├── readme.md
    └── shopping-data.csv
├── README.md
└── Webscraping
    ├── Webscraping.ipynb
    └── test


/Lecture 3/EDA/test:
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1 | 
2 | 


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/Lecture 4/Network Analysis/knuth_miles.txt.gz:
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https://raw.githubusercontent.com/sepinouda/Intro_to_Data_Science/15d7d7a6099d0313c8a9040011c68a158e625b61/Lecture 4/Network Analysis/knuth_miles.txt.gz


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/Lecture 4/Network Analysis/quaker_network.gexf:
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1006 |       </node>
1007 |       <node id="Anthony Sharp" label="Anthony Sharp">
1008 |         <attvalues>
1009 |           <attvalue for="0" value="Quaker leader" />
1010 |           <attvalue for="1" value="male" />
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1019 |       </node>
1020 |       <node id="Mary Fisher" label="Mary Fisher">
1021 |         <attvalues>
1022 |           <attvalue for="0" value="Quaker missionary" />
1023 |           <attvalue for="1" value="female" />
1024 |           <attvalue for="2" value="1623" />
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1030 |           <attvalue for="8" value="2" />
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1032 |       </node>
1033 |       <node id="Anne Conway Viscountess Conway and Killultagh" label="Anne Conway Viscountess Conway and Killultagh">
1034 |         <attvalues>
1035 |           <attvalue for="0" value="philosopher" />
1036 |           <attvalue for="1" value="female" />
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1046 |       <node id="Samuel Fisher" label="Samuel Fisher">
1047 |         <attvalues>
1048 |           <attvalue for="0" value="Quaker preacher and writer" />
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1058 |       </node>
1059 |       <node id="Francis Bugg" label="Francis Bugg">
1060 |         <attvalues>
1061 |           <attvalue for="0" value="Quaker apostate" />
1062 |           <attvalue for="1" value="male" />
1063 |           <attvalue for="2" value="1640" />
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1072 |       <node id="Sarah Gibbons" label="Sarah Gibbons">
1073 |         <attvalues>
1074 |           <attvalue for="0" value="Quaker preacher in America" />
1075 |           <attvalue for="1" value="female" />
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1082 |           <attvalue for="8" value="17" />
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1084 |       </node>
1085 |       <node id="William Tomlinson" label="William Tomlinson">
1086 |         <attvalues>
1087 |           <attvalue for="0" value="religious writer" />
1088 |           <attvalue for="1" value="male" />
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1097 |       </node>
1098 |       <node id="Humphrey Norton" label="Humphrey Norton">
1099 |         <attvalues>
1100 |           <attvalue for="0" value="Quaker missionary and author" />
1101 |           <attvalue for="1" value="male" />
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1103 |           <attvalue for="3" value="1660" />
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1110 |       </node>
1111 |       <node id="William Gibson" label="William Gibson">
1112 |         <attvalues>
1113 |           <attvalue for="0" value="Quaker leader" />
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1120 |           <attvalue for="7" value="0.0006606084017907253" />
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1123 |       </node>
1124 |       <node id="Gideon Wanton" label="Gideon Wanton">
1125 |         <attvalues>
1126 |           <attvalue for="0" value="merchant and colonial governor" />
1127 |           <attvalue for="1" value="male" />
1128 |           <attvalue for="2" value="1693" />
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1131 |           <attvalue for="5" value="1" />
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1136 |       </node>
1137 |       <node id="John Wanton" label="John Wanton">
1138 |         <attvalues>
1139 |           <attvalue for="0" value="merchant and colonial governor" />
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1146 |           <attvalue for="7" value="8.138875606113617e-16" />
1147 |           <attvalue for="8" value="12" />
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1149 |       </node>
1150 |       <node id="Grace Chamber" label="Grace Chamber">
1151 |         <attvalues>
1152 |           <attvalue for="0" value="Quaker minister" />
1153 |           <attvalue for="1" value="female" />
1154 |           <attvalue for="2" value="1676" />
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1159 |           <attvalue for="7" value="8.138875606113617e-16" />
1160 |           <attvalue for="8" value="13" />
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1162 |       </node>
1163 |       <node id="Mary Prince" label="Mary Prince">
1164 |         <attvalues>
1165 |           <attvalue for="0" value="Quaker preacher" />
1166 |           <attvalue for="1" value="female" />
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1175 |       </node>
1176 |       <node id="John Bartram" label="John Bartram">
1177 |         <attvalues>
1178 |           <attvalue for="0" value="botanist and explorer in America" />
1179 |           <attvalue for="1" value="male" />
1180 |           <attvalue for="2" value="1699" />
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1188 |       </node>
1189 |       <node id="Edward Haistwell" label="Edward Haistwell">
1190 |         <attvalues>
1191 |           <attvalue for="0" value="merchant" />
1192 |           <attvalue for="1" value="male" />
1193 |           <attvalue for="2" value="1658" />
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1199 |           <attvalue for="8" value="0" />
1200 |         </attvalues>
1201 |       </node>
1202 |       <node id="John ap John" label="John ap John">
1203 |         <attvalues>
1204 |           <attvalue for="0" value="Quaker leader" />
1205 |           <attvalue for="1" value="male" />
1206 |           <attvalue for="2" value="1625" />
1207 |           <attvalue for="3" value="1697" />
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1211 |           <attvalue for="7" value="0.0072628803585529705" />
1212 |           <attvalue for="8" value="4" />
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1214 |       </node>
1215 |       <node id="John Rous" label="John Rous">
1216 |         <attvalues>
1217 |           <attvalue for="0" value="Quaker missionary" />
1218 |           <attvalue for="1" value="male" />
1219 |           <attvalue for="2" value="1585" />
1220 |           <attvalue for="3" value="1695" />
1221 |           <attvalue for="4" value="10010488" />
1222 |           <attvalue for="5" value="1" />
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1224 |           <attvalue for="7" value="8.138875606113617e-16" />
1225 |           <attvalue for="8" value="14" />
1226 |         </attvalues>
1227 |       </node>
1228 |       <node id="Anthony Pearson" label="Anthony Pearson">
1229 |         <attvalues>
1230 |           <attvalue for="0" value="Quaker administrator" />
1231 |           <attvalue for="1" value="male" />
1232 |           <attvalue for="2" value="1627" />
1233 |           <attvalue for="3" value="1666" />
1234 |           <attvalue for="4" value="10009470" />
1235 |           <attvalue for="5" value="5" />
1236 |           <attvalue for="6" value="0.015228023702599968" />
1237 |           <attvalue for="7" value="0.11120476725256784" />
1238 |           <attvalue for="8" value="1" />
1239 |         </attvalues>
1240 |       </node>
1241 |       <node id="Solomon Eccles" label="Solomon Eccles">
1242 |         <attvalues>
1243 |           <attvalue for="0" value="musician and Quaker missionary" />
1244 |           <attvalue for="1" value="male" />
1245 |           <attvalue for="2" value="1617" />
1246 |           <attvalue for="3" value="1682" />
1247 |           <attvalue for="4" value="10003859" />
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1250 |           <attvalue for="7" value="0.024201245545910778" />
1251 |           <attvalue for="8" value="6" />
1252 |         </attvalues>
1253 |       </node>
1254 |       <node id="John Burnyeat" label="John Burnyeat">
1255 |         <attvalues>
1256 |           <attvalue for="0" value="Quaker minister" />
1257 |           <attvalue for="1" value="male" />
1258 |           <attvalue for="2" value="1631" />
1259 |           <attvalue for="3" value="1690" />
1260 |           <attvalue for="4" value="10001815" />
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1263 |           <attvalue for="7" value="0.053419324518696305" />
1264 |           <attvalue for="8" value="4" />
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1266 |       </node>
1267 |       <node id="Edward Burrough" label="Edward Burrough">
1268 |         <attvalues>
1269 |           <attvalue for="0" value="Quaker activist and writer" />
1270 |           <attvalue for="1" value="male" />
1271 |           <attvalue for="2" value="1633" />
1272 |           <attvalue for="3" value="1663" />
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1274 |           <attvalue for="5" value="9" />
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1276 |           <attvalue for="7" value="0.23147427604862297" />
1277 |           <attvalue for="8" value="2" />
1278 |         </attvalues>
1279 |       </node>
1280 |       <node id="Rebecca Travers" label="Rebecca Travers">
1281 |         <attvalues>
1282 |           <attvalue for="0" value="Quaker preacher and writer" />
1283 |           <attvalue for="1" value="female" />
1284 |           <attvalue for="2" value="1609" />
1285 |           <attvalue for="3" value="1688" />
1286 |           <attvalue for="4" value="10012062" />
1287 |           <attvalue for="5" value="4" />
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1289 |           <attvalue for="7" value="0.1184804064465093" />
1290 |           <attvalue for="8" value="3" />
1291 |         </attvalues>
1292 |       </node>
1293 |       <node id="William Edmundson" label="William Edmundson">
1294 |         <attvalues>
1295 |           <attvalue for="0" value="Quaker leader" />
1296 |           <attvalue for="1" value="male" />
1297 |           <attvalue for="2" value="1627" />
1298 |           <attvalue for="3" value="1712" />
1299 |           <attvalue for="4" value="10003882" />
1300 |           <attvalue for="5" value="2" />
1301 |           <attvalue for="6" value="0.002773121417189214" />
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1303 |           <attvalue for="8" value="4" />
1304 |         </attvalues>
1305 |       </node>
1306 |       <node id="Sarah Cheevers" label="Sarah Cheevers">
1307 |         <attvalues>
1308 |           <attvalue for="0" value="Quaker missionary" />
1309 |           <attvalue for="1" value="female" />
1310 |           <attvalue for="2" value="1608" />
1311 |           <attvalue for="3" value="1664" />
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1313 |           <attvalue for="5" value="1" />
1314 |           <attvalue for="6" value="0.0" />
1315 |           <attvalue for="7" value="8.138875606113617e-16" />
1316 |           <attvalue for="8" value="15" />
1317 |         </attvalues>
1318 |       </node>
1319 |       <node id="Edward Pyott" label="Edward Pyott">
1320 |         <attvalues>
1321 |           <attvalue for="0" value="parliamentarian army officer" />
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1323 |           <attvalue for="2" value="1560" />
1324 |           <attvalue for="3" value="1670" />
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1326 |           <attvalue for="5" value="2" />
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1329 |           <attvalue for="8" value="6" />
1330 |         </attvalues>
1331 |       </node>
1332 |       <node id="Daniel Quare" label="Daniel Quare">
1333 |         <attvalues>
1334 |           <attvalue for="0" value="maker of clocks, watches, and barometers" />
1335 |           <attvalue for="1" value="male" />
1336 |           <attvalue for="2" value="1648" />
1337 |           <attvalue for="3" value="1724" />
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1339 |           <attvalue for="5" value="2" />
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1341 |           <attvalue for="7" value="0.03459352181508865" />
1342 |           <attvalue for="8" value="3" />
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1344 |       </node>
1345 |       <node id="John Penington" label="John Penington">
1346 |         <attvalues>
1347 |           <attvalue for="0" value="Quaker apologist and controversialist" />
1348 |           <attvalue for="1" value="male" />
1349 |           <attvalue for="2" value="1655" />
1350 |           <attvalue for="3" value="1710" />
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1354 |           <attvalue for="7" value="0.00928139241833698" />
1355 |           <attvalue for="8" value="4" />
1356 |         </attvalues>
1357 |       </node>
1358 |       <node id="Mary Penington" label="Mary Penington">
1359 |         <attvalues>
1360 |           <attvalue for="0" value="Quaker and writer" />
1361 |           <attvalue for="1" value="female" />
1362 |           <attvalue for="2" value="1623" />
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1369 |         </attvalues>
1370 |       </node>
1371 |       <node id="Charles Marshall" label="Charles Marshall">
1372 |         <attvalues>
1373 |           <attvalue for="0" value="Quaker preacher and apothecary" />
1374 |           <attvalue for="1" value="male" />
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1381 |           <attvalue for="8" value="6" />
1382 |         </attvalues>
1383 |       </node>
1384 |       <node id="Humphrey Woolrich" label="Humphrey Woolrich">
1385 |         <attvalues>
1386 |           <attvalue for="0" value="religious writer" />
1387 |           <attvalue for="1" value="male" />
1388 |           <attvalue for="2" value="1633" />
1389 |           <attvalue for="3" value="1707" />
1390 |           <attvalue for="4" value="10013112" />
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1392 |           <attvalue for="6" value="0.0" />
1393 |           <attvalue for="7" value="8.138875606113617e-16" />
1394 |           <attvalue for="8" value="16" />
1395 |         </attvalues>
1396 |       </node>
1397 |       <node id="William Penn" label="William Penn">
1398 |         <attvalues>
1399 |           <attvalue for="0" value="Quaker leader and founder of Pennsylvania" />
1400 |           <attvalue for="1" value="male" />
1401 |           <attvalue for="2" value="1644" />
1402 |           <attvalue for="3" value="1718" />
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1406 |           <attvalue for="7" value="0.2703220115399868" />
1407 |           <attvalue for="8" value="0" />
1408 |         </attvalues>
1409 |       </node>
1410 |       <node id="Mary Pennyman" label="Mary Pennyman">
1411 |         <attvalues>
1412 |           <attvalue for="0" value="" />
1413 |           <attvalue for="1" value="female" />
1414 |           <attvalue for="2" value="1630" />
1415 |           <attvalue for="3" value="1701" />
1416 |           <attvalue for="4" value="10009535" />
1417 |           <attvalue for="5" value="1" />
1418 |           <attvalue for="6" value="0.0" />
1419 |           <attvalue for="7" value="8.138875606113617e-16" />
1420 |           <attvalue for="8" value="16" />
1421 |         </attvalues>
1422 |       </node>
1423 |       <node id="Dorothy Waugh" label="Dorothy Waugh">
1424 |         <attvalues>
1425 |           <attvalue for="0" value="Quaker preacher" />
1426 |           <attvalue for="1" value="female" />
1427 |           <attvalue for="2" value="1636" />
1428 |           <attvalue for="3" value="1666" />
1429 |           <attvalue for="4" value="10012614" />
1430 |           <attvalue for="5" value="1" />
1431 |           <attvalue for="6" value="0.0" />
1432 |           <attvalue for="7" value="8.138875606113617e-16" />
1433 |           <attvalue for="8" value="17" />
1434 |         </attvalues>
1435 |       </node>
1436 |       <node id="David Lloyd" label="David Lloyd">
1437 |         <attvalues>
1438 |           <attvalue for="0" value="lawyer and politician in America" />
1439 |           <attvalue for="1" value="male" />
1440 |           <attvalue for="2" value="1656" />
1441 |           <attvalue for="3" value="1731" />
1442 |           <attvalue for="4" value="10007509" />
1443 |           <attvalue for="5" value="2" />
1444 |           <attvalue for="6" value="0.0" />
1445 |           <attvalue for="7" value="0.04279916936862534" />
1446 |           <attvalue for="8" value="0" />
1447 |         </attvalues>
1448 |       </node>
1449 |       <node id="Lewis Morris" label="Lewis Morris">
1450 |         <attvalues>
1451 |           <attvalue for="0" value="politician in America" />
1452 |           <attvalue for="1" value="male" />
1453 |           <attvalue for="2" value="1671" />
1454 |           <attvalue for="3" value="1746" />
1455 |           <attvalue for="4" value="10008534" />
1456 |           <attvalue for="5" value="1" />
1457 |           <attvalue for="6" value="0.0" />
1458 |           <attvalue for="7" value="0.002182251595057408" />
1459 |           <attvalue for="8" value="3" />
1460 |         </attvalues>
1461 |       </node>
1462 |       <node id="Martha Simmonds" label="Martha Simmonds">
1463 |         <attvalues>
1464 |           <attvalue for="0" value="Quaker and author" />
1465 |           <attvalue for="1" value="female" />
1466 |           <attvalue for="2" value="1624" />
1467 |           <attvalue for="3" value="1665" />
1468 |           <attvalue for="4" value="10011100" />
1469 |           <attvalue for="5" value="3" />
1470 |           <attvalue for="6" value="0.0003500893331401806" />
1471 |           <attvalue for="7" value="0.07920519864438022" />
1472 |           <attvalue for="8" value="1" />
1473 |         </attvalues>
1474 |       </node>
1475 |       <node id="John Story" label="John Story">
1476 |         <attvalues>
1477 |           <attvalue for="0" value="Quaker schismatic" />
1478 |           <attvalue for="1" value="male" />
1479 |           <attvalue for="2" value="1571" />
1480 |           <attvalue for="3" value="1681" />
1481 |           <attvalue for="4" value="10011613" />
1482 |           <attvalue for="5" value="6" />
1483 |           <attvalue for="6" value="0.028990098622866983" />
1484 |           <attvalue for="7" value="0.08267743160271737" />
1485 |           <attvalue for="8" value="6" />
1486 |         </attvalues>
1487 |       </node>
1488 |       <node id="Thomas Story" label="Thomas Story">
1489 |         <attvalues>
1490 |           <attvalue for="0" value="Quaker minister and journal writer" />
1491 |           <attvalue for="1" value="male" />
1492 |           <attvalue for="2" value="1670" />
1493 |           <attvalue for="3" value="1742" />
1494 |           <attvalue for="4" value="10011614" />
1495 |           <attvalue for="5" value="1" />
1496 |           <attvalue for="6" value="0.0" />
1497 |           <attvalue for="7" value="0.03675236423658965" />
1498 |           <attvalue for="8" value="0" />
1499 |         </attvalues>
1500 |       </node>
1501 |       <node id="Thomas Ellwood" label="Thomas Ellwood">
1502 |         <attvalues>
1503 |           <attvalue for="0" value="religious controversialist" />
1504 |           <attvalue for="1" value="male" />
1505 |           <attvalue for="2" value="1639" />
1506 |           <attvalue for="3" value="1713" />
1507 |           <attvalue for="4" value="10003945" />
1508 |           <attvalue for="5" value="8" />
1509 |           <attvalue for="6" value="0.046190623885104545" />
1510 |           <attvalue for="7" value="0.17608142535843857" />
1511 |           <attvalue for="8" value="4" />
1512 |         </attvalues>
1513 |       </node>
1514 |       <node id="William Simpson" label="William Simpson">
1515 |         <attvalues>
1516 |           <attvalue for="0" value="Quaker preacher" />
1517 |           <attvalue for="1" value="male" />
1518 |           <attvalue for="2" value="1627" />
1519 |           <attvalue for="3" value="1671" />
1520 |           <attvalue for="4" value="10011114" />
1521 |           <attvalue for="5" value="1" />
1522 |           <attvalue for="6" value="0.0" />
1523 |           <attvalue for="7" value="0.006314722046904029" />
1524 |           <attvalue for="8" value="4" />
1525 |         </attvalues>
1526 |       </node>
1527 |       <node id="Samuel Bownas" label="Samuel Bownas">
1528 |         <attvalues>
1529 |           <attvalue for="0" value="Quaker minister and writer" />
1530 |           <attvalue for="1" value="male" />
1531 |           <attvalue for="2" value="1677" />
1532 |           <attvalue for="3" value="1753" />
1533 |           <attvalue for="4" value="10001390" />
1534 |           <attvalue for="5" value="1" />
1535 |           <attvalue for="6" value="0.0" />
1536 |           <attvalue for="7" value="0.0007054780307821075" />
1537 |           <attvalue for="8" value="0" />
1538 |         </attvalues>
1539 |       </node>
1540 |       <node id="John Perrot" label="John Perrot">
1541 |         <attvalues>
1542 |           <attvalue for="0" value="Quaker schismatic" />
1543 |           <attvalue for="1" value="male" />
1544 |           <attvalue for="2" value="1555" />
1545 |           <attvalue for="3" value="1665" />
1546 |           <attvalue for="4" value="10009584" />
1547 |           <attvalue for="5" value="7" />
1548 |           <attvalue for="6" value="0.02829566854990583" />
1549 |           <attvalue for="7" value="0.1849692807795611" />
1550 |           <attvalue for="8" value="2" />
1551 |         </attvalues>
1552 |       </node>
1553 |       <node id="Hannah Stranger" label="Hannah Stranger">
1554 |         <attvalues>
1555 |           <attvalue for="0" value="Quaker missionary" />
1556 |           <attvalue for="1" value="female" />
1557 |           <attvalue for="2" value="1656" />
1558 |           <attvalue for="3" value="1671" />
1559 |           <attvalue for="4" value="10011632" />
1560 |           <attvalue for="5" value="2" />
1561 |           <attvalue for="6" value="0.0" />
1562 |           <attvalue for="7" value="0.05635184926227045" />
1563 |           <attvalue for="8" value="1" />
1564 |         </attvalues>
1565 |       </node>
1566 |     </nodes>
1567 |     <edges>
1568 |       <edge id="0" source="Joseph Wyeth" target="Thomas Ellwood" />
1569 |       <edge id="1" source="Alexander Skene of Newtyle" target="Lilias Skene" />
1570 |       <edge id="2" source="James Logan" target="Peter Collinson" />
1571 |       <edge id="3" source="James Logan" target="John Bartram" />
1572 |       <edge id="4" source="James Logan" target="William Penn" />
1573 |       <edge id="5" source="James Logan" target="David Lloyd" />
1574 |       <edge id="6" source="Dorcas Erbery" target="James Nayler" />
1575 |       <edge id="7" source="William Mucklow" target="George Fox" />
1576 |       <edge id="8" source="Thomas Salthouse" target="George Fox" />
1577 |       <edge id="9" source="Thomas Salthouse" target="Margaret Fell" />
1578 |       <edge id="10" source="William Dewsbury" target="Edward Burrough" />
1579 |       <edge id="11" source="William Dewsbury" target="George Fox" />
1580 |       <edge id="12" source="William Dewsbury" target="John Crook" />
1581 |       <edge id="13" source="John Audland" target="John Camm" />
1582 |       <edge id="14" source="John Audland" target="Francis Howgill" />
1583 |       <edge id="15" source="John Audland" target="Edward Pyott" />
1584 |       <edge id="16" source="John Audland" target="Charles Marshall" />
1585 |       <edge id="17" source="John Audland" target="George Fox" />
1586 |       <edge id="18" source="John Audland" target="Anne Camm" />
1587 |       <edge id="19" source="Richard Claridge" target="Joseph Besse" />
1588 |       <edge id="20" source="Richard Claridge" target="William Penn" />
1589 |       <edge id="21" source="William Bradford" target="George Keith" />
1590 |       <edge id="22" source="William Bradford" target="William Penn" />
1591 |       <edge id="23" source="William Bradford" target="Tace Sowle" />
1592 |       <edge id="24" source="Fettiplace Bellers" target="John Bellers" />
1593 |       <edge id="25" source="Isabel Yeamans" target="William Penn" />
1594 |       <edge id="26" source="George Fox the younger" target="Margaret Fell" />
1595 |       <edge id="27" source="George Fox" target="George Keith" />
1596 |       <edge id="28" source="George Fox" target="Francis Howgill" />
1597 |       <edge id="29" source="George Fox" target="Ellis Hookes" />
1598 |       <edge id="30" source="George Fox" target="William Mead" />
1599 |       <edge id="31" source="George Fox" target="Elizabeth Hooten" />
1600 |       <edge id="32" source="George Fox" target="Margaret Fell" />
1601 |       <edge id="33" source="George Fox" target="John Crook" />
1602 |       <edge id="34" source="George Fox" target="George Whitehead" />
1603 |       <edge id="35" source="George Fox" target="Benjamin Furly" />
1604 |       <edge id="36" source="George Fox" target="James Nayler" />
1605 |       <edge id="37" source="George Fox" target="Edward Burrough" />
1606 |       <edge id="38" source="George Fox" target="John Wilkinson" />
1607 |       <edge id="39" source="George Fox" target="Thomas Ellwood" />
1608 |       <edge id="40" source="George Fox" target="William Coddington" />
1609 |       <edge id="41" source="George Fox" target="John Stubbs" />
1610 |       <edge id="42" source="George Fox" target="John Perrot" />
1611 |       <edge id="43" source="George Fox" target="Leonard Fell" />
1612 |       <edge id="44" source="George Fox" target="William Penn" />
1613 |       <edge id="45" source="John Stubbs" target="Benjamin Furly" />
1614 |       <edge id="46" source="John Stubbs" target="William Caton" />
1615 |       <edge id="47" source="John Stubbs" target="Samuel Fisher" />
1616 |       <edge id="48" source="John Stubbs" target="John Burnyeat" />
1617 |       <edge id="49" source="Anne Camm" target="Thomas Camm" />
1618 |       <edge id="50" source="John Camm" target="Charles Marshall" />
1619 |       <edge id="51" source="John Camm" target="Thomas Camm" />
1620 |       <edge id="52" source="John Camm" target="Edward Pyott" />
1621 |       <edge id="53" source="Thomas Camm" target="John Story" />
1622 |       <edge id="54" source="Katharine Evans" target="Sarah Cheevers" />
1623 |       <edge id="55" source="Lydia Lancaster" target="Grace Chamber" />
1624 |       <edge id="56" source="Samuel Clarridge" target="Anthony Sharp" />
1625 |       <edge id="57" source="Samuel Clarridge" target="James Claypoole" />
1626 |       <edge id="58" source="Thomas Lower" target="Margaret Fell" />
1627 |       <edge id="59" source="Gervase Benson" target="James Nayler" />
1628 |       <edge id="60" source="Gervase Benson" target="Anthony Pearson" />
1629 |       <edge id="61" source="Stephen Crisp" target="James Parnel" />
1630 |       <edge id="62" source="Stephen Crisp" target="William Caton" />
1631 |       <edge id="63" source="Stephen Crisp" target="Benjamin Furly" />
1632 |       <edge id="64" source="James Claypoole" target="William Penn" />
1633 |       <edge id="65" source="Thomas Holme" target="William Gibson" />
1634 |       <edge id="66" source="Thomas Holme" target="Elizabeth Leavens" />
1635 |       <edge id="67" source="John Freame" target="David Barclay" />
1636 |       <edge id="68" source="John Swinton" target="David Barclay of Ury" />
1637 |       <edge id="69" source="William Mead" target="Margaret Fell" />
1638 |       <edge id="70" source="Henry Pickworth" target="Francis Bugg" />
1639 |       <edge id="71" source="John Crook" target="John Perrot" />
1640 |       <edge id="72" source="John Crook" target="Edward Burrough" />
1641 |       <edge id="73" source="Gilbert Latey" target="Edward Burrough" />
1642 |       <edge id="74" source="Gilbert Latey" target="George Whitehead" />
1643 |       <edge id="75" source="Joseph Besse" target="Samuel Bownas" />
1644 |       <edge id="76" source="James Nayler" target="Francis Howgill" />
1645 |       <edge id="77" source="James Nayler" target="Martha Simmonds" />
1646 |       <edge id="78" source="James Nayler" target="Hannah Stranger" />
1647 |       <edge id="79" source="James Nayler" target="Margaret Fell" />
1648 |       <edge id="80" source="James Nayler" target="Richard Farnworth" />
1649 |       <edge id="81" source="James Nayler" target="George Whitehead" />
1650 |       <edge id="82" source="James Nayler" target="John Perrot" />
1651 |       <edge id="83" source="James Nayler" target="Robert Rich" />
1652 |       <edge id="84" source="James Nayler" target="Anthony Pearson" />
1653 |       <edge id="85" source="James Nayler" target="Thomas Ellwood" />
1654 |       <edge id="86" source="James Nayler" target="Edward Burrough" />
1655 |       <edge id="87" source="James Nayler" target="Rebecca Travers" />
1656 |       <edge id="88" source="James Nayler" target="William Tomlinson" />
1657 |       <edge id="89" source="George Whitehead" target="George Keith" />
1658 |       <edge id="90" source="George Whitehead" target="William Rogers" />
1659 |       <edge id="91" source="George Whitehead" target="Francis Bugg" />
1660 |       <edge id="92" source="George Whitehead" target="Richard Hubberthorne" />
1661 |       <edge id="93" source="George Whitehead" target="Alexander Parker" />
1662 |       <edge id="94" source="George Whitehead" target="John Whitehead" />
1663 |       <edge id="95" source="George Whitehead" target="Daniel Quare" />
1664 |       <edge id="96" source="George Whitehead" target="William Penn" />
1665 |       <edge id="97" source="George Whitehead" target="John Story" />
1666 |       <edge id="98" source="George Whitehead" target="Rebecca Travers" />
1667 |       <edge id="99" source="William Crouch" target="Francis Howgill" />
1668 |       <edge id="100" source="William Crouch" target="Edward Burrough" />
1669 |       <edge id="101" source="Benjamin Furly" target="George Keith" />
1670 |       <edge id="102" source="Benjamin Furly" target="James Parnel" />
1671 |       <edge id="103" source="Benjamin Furly" target="Franciscus Mercurius van Helmont" />
1672 |       <edge id="104" source="Benjamin Furly" target="Robert Barclay" />
1673 |       <edge id="105" source="Benjamin Furly" target="Alexander Parker" />
1674 |       <edge id="106" source="Benjamin Furly" target="William Caton" />
1675 |       <edge id="107" source="Benjamin Furly" target="William Penn" />
1676 |       <edge id="108" source="Silvanus Bevan" target="Daniel Quare" />
1677 |       <edge id="109" source="Robert Rich" target="William Tomlinson" />
1678 |       <edge id="110" source="John Whiting" target="Christopher Taylor" />
1679 |       <edge id="111" source="Christopher Taylor" target="Thomas Taylor" />
1680 |       <edge id="112" source="Thomas Lawson" target="Margaret Fell" />
1681 |       <edge id="113" source="Thomas Lawson" target="Alexander Parker" />
1682 |       <edge id="114" source="Richard Farnworth" target="Francis Howgill" />
1683 |       <edge id="115" source="Richard Farnworth" target="Richard Hubberthorne" />
1684 |       <edge id="116" source="Richard Farnworth" target="John Perrot" />
1685 |       <edge id="117" source="Richard Farnworth" target="Margaret Fell" />
1686 |       <edge id="118" source="Richard Farnworth" target="Anthony Pearson" />
1687 |       <edge id="119" source="Richard Vickris" target="George Bishop" />
1688 |       <edge id="120" source="Robert Barclay" target="George Keith" />
1689 |       <edge id="121" source="Robert Barclay" target="David Barclay of Ury" />
1690 |       <edge id="122" source="Jane Sowle" target="Tace Sowle" />
1691 |       <edge id="123" source="Tace Sowle" target="William Penn" />
1692 |       <edge id="124" source="Margaret Fell" target="William Caton" />
1693 |       <edge id="125" source="Margaret Fell" target="William Penn" />
1694 |       <edge id="126" source="Margaret Fell" target="Alexander Parker" />
1695 |       <edge id="127" source="Margaret Fell" target="Elizabeth Leavens" />
1696 |       <edge id="128" source="Margaret Fell" target="Anthony Pearson" />
1697 |       <edge id="129" source="Thomas Curtis" target="Anthony Sharp" />
1698 |       <edge id="130" source="Thomas Curtis" target="Mary Penington" />
1699 |       <edge id="131" source="Thomas Curtis" target="Thomas Ellwood" />
1700 |       <edge id="132" source="Thomas Curtis" target="William Simpson" />
1701 |       <edge id="133" source="Thomas Curtis" target="John Story" />
1702 |       <edge id="134" source="Alice Curwen" target="Rebecca Travers" />
1703 |       <edge id="135" source="Alexander Parker" target="John Wilkinson" />
1704 |       <edge id="136" source="Alexander Parker" target="Sir Charles Wager" />
1705 |       <edge id="137" source="John Wilkinson" target="Charles Marshall" />
1706 |       <edge id="138" source="John Wilkinson" target="Solomon Eccles" />
1707 |       <edge id="139" source="John Wilkinson" target="John Story" />
1708 |       <edge id="140" source="Thomas Aldam" target="Anthony Pearson" />
1709 |       <edge id="141" source="Sir Charles Wager" target="Lewis Morris" />
1710 |       <edge id="142" source="George Keith" target="Anne Conway Viscountess Conway and Killultagh" />
1711 |       <edge id="143" source="George Keith" target="Franciscus Mercurius van Helmont" />
1712 |       <edge id="144" source="George Keith" target="William Penn" />
1713 |       <edge id="145" source="Peter Collinson" target="John Bartram" />
1714 |       <edge id="146" source="William Caton" target="William Ames" />
1715 |       <edge id="147" source="Francis Howgill" target="Martha Simmonds" />
1716 |       <edge id="148" source="Francis Howgill" target="Edward Burrough" />
1717 |       <edge id="149" source="William Rogers" target="Thomas Ellwood" />
1718 |       <edge id="150" source="Isaac Norris" target="William Penn" />
1719 |       <edge id="151" source="Anthony Sharp" target="William Edmundson" />
1720 |       <edge id="152" source="Mary Fisher" target="John Perrot" />
1721 |       <edge id="153" source="Mary Fisher" target="Mary Prince" />
1722 |       <edge id="154" source="Sarah Gibbons" target="Dorothy Waugh" />
1723 |       <edge id="155" source="Humphrey Norton" target="John Rous" />
1724 |       <edge id="156" source="Gideon Wanton" target="John Wanton" />
1725 |       <edge id="157" source="Mary Prince" target="John Perrot" />
1726 |       <edge id="158" source="Edward Haistwell" target="William Penn" />
1727 |       <edge id="159" source="John ap John" target="John Burnyeat" />
1728 |       <edge id="160" source="Solomon Eccles" target="John Story" />
1729 |       <edge id="161" source="John Burnyeat" target="William Edmundson" />
1730 |       <edge id="162" source="John Burnyeat" target="William Penn" />
1731 |       <edge id="163" source="Edward Burrough" target="John Perrot" />
1732 |       <edge id="164" source="Edward Burrough" target="Thomas Ellwood" />
1733 |       <edge id="165" source="Rebecca Travers" target="William Penn" />
1734 |       <edge id="166" source="John Penington" target="Mary Penington" />
1735 |       <edge id="167" source="Mary Penington" target="William Penn" />
1736 |       <edge id="168" source="Mary Penington" target="Thomas Ellwood" />
1737 |       <edge id="169" source="Humphrey Woolrich" target="Mary Pennyman" />
1738 |       <edge id="170" source="William Penn" target="Thomas Story" />
1739 |       <edge id="171" source="William Penn" target="David Lloyd" />
1740 |       <edge id="172" source="Martha Simmonds" target="Hannah Stranger" />
1741 |       <edge id="173" source="John Story" target="Thomas Ellwood" />
1742 |     </edges>
1743 |   </graph>
1744 | </gexf>
1745 | 


--------------------------------------------------------------------------------
/Lecture 4/Network Analysis/quakers_edgelist.csv:
--------------------------------------------------------------------------------
  1 | Source,Target
  2 | George Keith,Robert Barclay
  3 | George Keith,Benjamin Furly
  4 | George Keith,Anne Conway Viscountess Conway and Killultagh
  5 | George Keith,Franciscus Mercurius van Helmont
  6 | George Keith,William Penn
  7 | George Keith,George Fox
  8 | George Keith,George Whitehead
  9 | George Keith,William Bradford
 10 | James Parnel,Benjamin Furly
 11 | James Parnel,Stephen Crisp
 12 | Peter Collinson,John Bartram
 13 | Peter Collinson,James Logan
 14 | Joseph Wyeth,Thomas Ellwood
 15 | Alexander Skene of Newtyle,Lilias Skene
 16 | Dorcas Erbery,James Nayler
 17 | William Mucklow,George Fox
 18 | Franciscus Mercurius van Helmont,Benjamin Furly
 19 | William Dewsbury,Edward Burrough
 20 | William Dewsbury,George Fox
 21 | William Dewsbury,John Crook
 22 | John Audland,John Camm
 23 | John Audland,Francis Howgill
 24 | John Audland,Edward Pyott
 25 | John Audland,Charles Marshall
 26 | John Audland,George Fox
 27 | John Audland,Anne Camm
 28 | Francis Howgill,Martha Simmonds
 29 | Francis Howgill,James Nayler
 30 | Francis Howgill,Edward Burrough
 31 | Francis Howgill,George Fox
 32 | Francis Howgill,Richard Farnworth
 33 | Francis Howgill,William Crouch
 34 | William Bradford,William Penn
 35 | William Bradford,Tace Sowle
 36 | John Bellers,Fettiplace Bellers
 37 | William Rogers,Thomas Ellwood
 38 | William Rogers,George Whitehead
 39 | Martha Simmonds,Hannah Stranger
 40 | Martha Simmonds,James Nayler
 41 | Isabel Yeamans,William Penn
 42 | George Fox the younger,Margaret Fell
 43 | George Fox,Ellis Hookes
 44 | George Fox,William Mead
 45 | George Fox,Elizabeth Hooten
 46 | George Fox,Margaret Fell
 47 | George Fox,John Crook
 48 | George Fox,George Whitehead
 49 | George Fox,Benjamin Furly
 50 | George Fox,Thomas Salthouse
 51 | George Fox,James Nayler
 52 | George Fox,Edward Burrough
 53 | George Fox,John Wilkinson
 54 | George Fox,Thomas Ellwood
 55 | George Fox,William Coddington
 56 | George Fox,John Stubbs
 57 | George Fox,John Perrot
 58 | George Fox,Leonard Fell
 59 | George Fox,William Penn
 60 | John Stubbs,Benjamin Furly
 61 | John Stubbs,William Caton
 62 | John Stubbs,Samuel Fisher
 63 | John Stubbs,John Burnyeat
 64 | John Camm,Charles Marshall
 65 | John Camm,Thomas Camm
 66 | John Camm,Edward Pyott
 67 | Thomas Camm,John Story
 68 | Thomas Camm,Anne Camm
 69 | John Wilkinson,Charles Marshall
 70 | John Wilkinson,Solomon Eccles
 71 | John Wilkinson,John Story
 72 | John Wilkinson,Alexander Parker
 73 | Isaac Norris,William Penn
 74 | John Swinton,David Barclay of Ury
 75 | James Nayler,Hannah Stranger
 76 | James Nayler,Gervase Benson
 77 | James Nayler,Margaret Fell
 78 | James Nayler,Richard Farnworth
 79 | James Nayler,George Whitehead
 80 | James Nayler,John Perrot
 81 | James Nayler,Robert Rich
 82 | James Nayler,Anthony Pearson
 83 | James Nayler,Thomas Ellwood
 84 | James Nayler,Edward Burrough
 85 | James Nayler,Rebecca Travers
 86 | James Nayler,William Tomlinson
 87 | Anthony Sharp,Samuel Clarridge
 88 | Anthony Sharp,Thomas Curtis
 89 | Anthony Sharp,William Edmundson
 90 | Thomas Salthouse,Margaret Fell
 91 | William Ames,William Caton
 92 | Mary Fisher,John Perrot
 93 | Mary Fisher,Mary Prince
 94 | Lydia Lancaster,Grace Chamber
 95 | Henry Pickworth,Francis Bugg
 96 | Samuel Clarridge,James Claypoole
 97 | Francis Bugg,George Whitehead
 98 | Thomas Lower,Margaret Fell
 99 | Sarah Gibbons,Dorothy Waugh
100 | Gervase Benson,Anthony Pearson
101 | Stephen Crisp,William Caton
102 | Stephen Crisp,Benjamin Furly
103 | John Freame,David Barclay
104 | Humphrey Norton,John Rous
105 | William Gibson,Thomas Holme
106 | Gideon Wanton,John Wanton
107 | William Mead,Margaret Fell
108 | Benjamin Furly,Robert Barclay
109 | Benjamin Furly,Alexander Parker
110 | Benjamin Furly,William Caton
111 | Benjamin Furly,William Penn
112 | James Logan,John Bartram
113 | James Logan,William Penn
114 | James Logan,David Lloyd
115 | Mary Prince,John Perrot
116 | Edward Haistwell,William Penn
117 | John ap John,John Burnyeat
118 | John Crook,John Perrot
119 | John Crook,Edward Burrough
120 | Gilbert Latey,Edward Burrough
121 | Gilbert Latey,George Whitehead
122 | Richard Hubberthorne,George Whitehead
123 | Richard Hubberthorne,Richard Farnworth
124 | Joseph Besse,Richard Claridge
125 | Joseph Besse,Samuel Bownas
126 | George Whitehead,Alexander Parker
127 | George Whitehead,John Whitehead
128 | George Whitehead,Daniel Quare
129 | George Whitehead,William Penn
130 | George Whitehead,John Story
131 | George Whitehead,Rebecca Travers
132 | Silvanus Bevan,Daniel Quare
133 | Solomon Eccles,John Story
134 | Robert Rich,William Tomlinson
135 | John Burnyeat,William Edmundson
136 | John Burnyeat,William Penn
137 | Katharine Evans,Sarah Cheevers
138 | Edward Burrough,John Perrot
139 | Edward Burrough,Thomas Ellwood
140 | Edward Burrough,William Crouch
141 | John Whiting,Christopher Taylor
142 | Rebecca Travers,Alice Curwen
143 | Rebecca Travers,William Penn
144 | William Caton,Margaret Fell
145 | Thomas Lawson,Margaret Fell
146 | Thomas Lawson,Alexander Parker
147 | Richard Farnworth,John Perrot
148 | Richard Farnworth,Margaret Fell
149 | Richard Farnworth,Anthony Pearson
150 | Thomas Taylor,Christopher Taylor
151 | John Penington,Mary Penington
152 | Humphrey Woolrich,Mary Pennyman
153 | William Penn,Tace Sowle
154 | William Penn,James Claypoole
155 | William Penn,Thomas Story
156 | William Penn,Mary Penington
157 | William Penn,David Lloyd
158 | William Penn,Margaret Fell
159 | William Penn,Richard Claridge
160 | Richard Vickris,George Bishop
161 | Robert Barclay,David Barclay of Ury
162 | Jane Sowle,Tace Sowle
163 | Margaret Fell,Alexander Parker
164 | Margaret Fell,Elizabeth Leavens
165 | Margaret Fell,Anthony Pearson
166 | Elizabeth Leavens,Thomas Holme
167 | Lewis Morris,Sir Charles Wager
168 | Mary Penington,Thomas Curtis
169 | Mary Penington,Thomas Ellwood
170 | Thomas Curtis,Thomas Ellwood
171 | Thomas Curtis,William Simpson
172 | Thomas Curtis,John Story
173 | Alexander Parker,Sir Charles Wager
174 | John Story,Thomas Ellwood
175 | Thomas Aldam,Anthony Pearson
176 | 


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/Lecture 4/Network Analysis/quakers_nodelist.csv:
--------------------------------------------------------------------------------
  1 | Name,Historical Significance,Gender,Birthdate,Deathdate,ID
  2 | Joseph Wyeth,religious writer,male,1663,1731,10013191
  3 | Alexander Skene of Newtyle,local politician and author,male,1621,1694,10011149
  4 | James Logan,colonial official and scholar,male,1674,1751,10007567
  5 | Dorcas Erbery,Quaker preacher,female,1656,1659,10003983
  6 | Lilias Skene,Quaker preacher and poet,male,1626,1697,10011152
  7 | William Mucklow,religious writer,male,1630,1713,10008595
  8 | Thomas Salthouse,Quaker preacher and writer,male,1630,1691,10010643
  9 | William Dewsbury,Quaker activist,male,1621,1688,10003478
 10 | John Audland,Quaker preacher,male,1630,1664,10000411
 11 | Richard Claridge,Quaker minister and schoolmaster,male,1649,1723,10002469
 12 | William Bradford,printer,male,1663,1752,10001445
 13 | Fettiplace Bellers,philosophical writer and playwright,male,1687,1750,10000933
 14 | John Bellers,political economist and cloth merchant,male,1654,1725,10000934
 15 | Isabel Yeamans,Quaker preacher,female,1637,1704,10013226
 16 | George Fox the younger,religious writer,male,1551,1661,10004523
 17 | George Fox, a founder of the Religious Society of Friends (Quakers),male,1624,1691,10004524
 18 | John Stubbs,Quaker minister,male,1618,1675,10011695
 19 | Anne Camm,Quaker preacher,female,1627,1705,10001967
 20 | John Camm,Quaker preacher,male,1605,1657,10001968
 21 | Thomas Camm,Quaker preacher and writer,male,1640,1708,10001969
 22 | Katharine Evans,Quaker missionary,female,1618,1692,10004036
 23 | Lydia Lancaster,Quaker minister,female,1683,1761,10007110
 24 | Samuel Clarridge,Quaker activist,male,1631,1704,10002504
 25 | Thomas Lower,Quaker activist and physician,male,1633,1720,10007626
 26 | Gervase Benson,Quaker leader,male,1569,1679,10000972
 27 | Stephen Crisp,Quaker activist and writer,male,1628,1692,10003022
 28 | James Claypoole,merchant and pioneer settler in America,male,1634,1687,10002513
 29 | Thomas Holme,Quaker missionary,male,1626,1666,10006100
 30 | John Freame,banker and lobbyist,male,1665,1745,10004564
 31 | John Swinton,politician,male,1620,1679,10011742
 32 | William Mead,Quaker patron and merchant,male,1627,1713,10008161
 33 | Henry Pickworth,religious controversialist,male,1673,1738,10009697
 34 | John Crook,Quaker leader and writer,male,1616,1699,10003063
 35 | Gilbert Latey,Quaker activist,male,1626,1705,10007166
 36 | Ellis Hookes,Quaker administrator,male,1635,1681,10006146
 37 | Joseph Besse,historian of Quakerism,male,1683,1757,10001027
 38 | James Nayler,Quaker preacher and writer,male,1618,1660,10008713
 39 | Elizabeth Hooten,Quaker preacher,female,1562,1672,10006153
 40 | George Whitehead,Quaker leader and writer,male,1637,1724,10012813
 41 | John Whitehead,Quaker minister and preacher,male,1630,1696,10012815
 42 | William Crouch,Quaker leader and writer,male,1628,1711,10003087
 43 | Benjamin Furly,merchant and religious writer,male,1636,1714,10004625
 44 | Silvanus Bevan,apothecary,male,1691,1765,10001041
 45 | Robert Rich,Quaker adherent and sectary,male,1607,1679,10010260
 46 | John Whiting,Quaker bibliographer and writer,male,1656,1722,10012829
 47 | Christopher Taylor,religious writer and schoolmaster,male,1614,1686,10011811
 48 | Thomas Lawson,Quaker minister and botanist,male,1630,1691,10007210
 49 | Richard Farnworth,Quaker preacher and writer,male,1630,1666,10004141
 50 | William Coddington,merchant and official in America,male,1601,1678,10002606
 51 | Thomas Taylor,Quaker minister and writer,male,1617,1682,10011824
 52 | Richard Vickris,religious writer,male,1590,1700,10012350
 53 | Robert Barclay,religious writer and colonial governor,male,1648,1690,10054848
 54 | Jane Sowle,,female,1631,1711,10011331
 55 | Tace Sowle,printer and bookseller,male,1666,1749,10011332
 56 | Leonard Fell,Quaker missionary and writer,male,1624,1701,10004169
 57 | Margaret Fell,Quaker leader,female,1614,1702,10004170
 58 | George Bishop,government official and religious writer,male,1558,1668,10001097
 59 | Elizabeth Leavens,Quaker missionary,female,1555,1665,10007246
 60 | Thomas Curtis,Quaker schismatic,male,1602,1712,10003161
 61 | Alice Curwen,Quaker missionary,female,1619,1679,10003162
 62 | Alexander Parker,Quaker preacher and author,male,1628,1689,10009307
 63 | John Wilkinson,Quaker schismatic,male,1652,1683,10012893
 64 | Thomas Aldam,Quaker preacher and writer,male,1616,1660,10000099
 65 | David Barclay of Ury,soldier and politician,male,1610,1686,10000621
 66 | David Barclay,merchant,male,1682,1769,10000622
 67 | Sir Charles Wager,naval officer and politician,male,1666,1743,10012403
 68 | George Keith,Quaker schismatic and Church of England clergyman,male,1638,1716,10006784
 69 | James Parnel,Quaker martyr,male,1636,1656,10009347
 70 | Peter Collinson,botanist,male,1694,1768,10002694
 71 | Franciscus Mercurius van Helmont,physician and cabbalist,male,1614,1698,10005781
 72 | William Caton,Quaker preacher,male,1636,1665,10002203
 73 | Francis Howgill,Quaker activist,male,1618,1669,10006305
 74 | Richard Hubberthorne,Quaker activist,male,1628,1662,10006314
 75 | William Ames,Quaker preacher,male,1552,1662,10000175
 76 | William Rogers,Quaker schismatic,male,1601,1711,10010417
 77 | Isaac Norris,colonial official and merchant,male,1671,1735,10008884
 78 | Anthony Sharp,Quaker leader,male,1643,1707,10010941
 79 | Mary Fisher,Quaker missionary,female,1623,1698,10004290
 80 | Anne Conway Viscountess Conway and Killultagh,philosopher,female,1631,1679,10002755
 81 | Samuel Fisher,Quaker preacher and writer,male,1604,1665,10004292
 82 | Francis Bugg,Quaker apostate,male,1640,1727,10001737
 83 | Sarah Gibbons,Quaker preacher in America,female,1634,1659,10004811
 84 | William Tomlinson,religious writer,male,1650,1696,10011989
 85 | Humphrey Norton,Quaker missionary and author,male,1655,1660,10008917
 86 | William Gibson,Quaker leader,male,1628,1684,10004827
 87 | Gideon Wanton,merchant and colonial governor,male,1693,1767,10012509
 88 | John Wanton,merchant and colonial governor,male,1672,1740,10012510
 89 | Grace Chamber,Quaker minister,female,1676,1762,10002274
 90 | Mary Prince,Quaker preacher,female,1569,1679,10009959
 91 | John Bartram,botanist and explorer in America,male,1699,1777,10000745
 92 | Edward Haistwell,merchant,male,1658,1709,10005359
 93 | John ap John,Quaker leader,male,1625,1697,10000243
 94 | John Rous,Quaker missionary,male,1585,1695,10010488
 95 | Anthony Pearson,Quaker administrator,male,1627,1666,10009470
 96 | Solomon Eccles,musician and Quaker missionary,male,1617,1682,10003859
 97 | John Burnyeat,Quaker minister,male,1631,1690,10001815
 98 | Edward Burrough,Quaker activist and writer,male,1633,1663,10001818
 99 | Rebecca Travers,Quaker preacher and writer,female,1609,1688,10012062
100 | William Edmundson,Quaker leader,male,1627,1712,10003882
101 | Sarah Cheevers,Quaker missionary,female,1608,1664,10002354
102 | Edward Pyott,parliamentarian army officer,male,1560,1670,10010036
103 | Daniel Quare,"maker of clocks, watches, and barometers",male,1648,1724,10010037
104 | John Penington,Quaker apologist and controversialist,male,1655,1710,10009526
105 | Mary Penington,Quaker and writer,female,1623,1682,10009527
106 | Charles Marshall,Quaker preacher and apothecary,male,1637,1698,10007992
107 | Humphrey Woolrich,religious writer,male,1633,1707,10013112
108 | William Penn,Quaker leader and founder of Pennsylvania,male,1644,1718,10009531
109 | Mary Pennyman,,female,1630,1701,10009535
110 | Dorothy Waugh,Quaker preacher,female,1636,1666,10012614
111 | David Lloyd,lawyer and politician in America,male,1656,1731,10007509
112 | Lewis Morris,politician in America,male,1671,1746,10008534
113 | Martha Simmonds,Quaker and author,female,1624,1665,10011100
114 | John Story,Quaker schismatic,male,1571,1681,10011613
115 | Thomas Story,Quaker minister and journal writer,male,1670,1742,10011614
116 | Thomas Ellwood,religious controversialist,male,1639,1713,10003945
117 | William Simpson,Quaker preacher,male,1627,1671,10011114
118 | Samuel Bownas,Quaker minister and writer,male,1677,1753,10001390
119 | John Perrot,Quaker schismatic,male,1555,1665,10009584
120 | Hannah Stranger,Quaker missionary,female,1656,1671,10011632
121 | 


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/Lecture 4/Network Analysis/readme.md:
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1 | 
2 | 


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/Lecture 5/Supervised_learning/Iris.csv:
--------------------------------------------------------------------------------
  1 | Id,SepalLengthCm,SepalWidthCm,PetalLengthCm,PetalWidthCm,Species
  2 | 1,5.1,3.5,1.4,0.2,Iris-setosa
  3 | 2,4.9,3.0,1.4,0.2,Iris-setosa
  4 | 3,4.7,3.2,1.3,0.2,Iris-setosa
  5 | 4,4.6,3.1,1.5,0.2,Iris-setosa
  6 | 5,5.0,3.6,1.4,0.2,Iris-setosa
  7 | 6,5.4,3.9,1.7,0.4,Iris-setosa
  8 | 7,4.6,3.4,1.4,0.3,Iris-setosa
  9 | 8,5.0,3.4,1.5,0.2,Iris-setosa
 10 | 9,4.4,2.9,1.4,0.2,Iris-setosa
 11 | 10,4.9,3.1,1.5,0.1,Iris-setosa
 12 | 11,5.4,3.7,1.5,0.2,Iris-setosa
 13 | 12,4.8,3.4,1.6,0.2,Iris-setosa
 14 | 13,4.8,3.0,1.4,0.1,Iris-setosa
 15 | 14,4.3,3.0,1.1,0.1,Iris-setosa
 16 | 15,5.8,4.0,1.2,0.2,Iris-setosa
 17 | 16,5.7,4.4,1.5,0.4,Iris-setosa
 18 | 17,5.4,3.9,1.3,0.4,Iris-setosa
 19 | 18,5.1,3.5,1.4,0.3,Iris-setosa
 20 | 19,5.7,3.8,1.7,0.3,Iris-setosa
 21 | 20,5.1,3.8,1.5,0.3,Iris-setosa
 22 | 21,5.4,3.4,1.7,0.2,Iris-setosa
 23 | 22,5.1,3.7,1.5,0.4,Iris-setosa
 24 | 23,4.6,3.6,1.0,0.2,Iris-setosa
 25 | 24,5.1,3.3,1.7,0.5,Iris-setosa
 26 | 25,4.8,3.4,1.9,0.2,Iris-setosa
 27 | 26,5.0,3.0,1.6,0.2,Iris-setosa
 28 | 27,5.0,3.4,1.6,0.4,Iris-setosa
 29 | 28,5.2,3.5,1.5,0.2,Iris-setosa
 30 | 29,5.2,3.4,1.4,0.2,Iris-setosa
 31 | 30,4.7,3.2,1.6,0.2,Iris-setosa
 32 | 31,4.8,3.1,1.6,0.2,Iris-setosa
 33 | 32,5.4,3.4,1.5,0.4,Iris-setosa
 34 | 33,5.2,4.1,1.5,0.1,Iris-setosa
 35 | 34,5.5,4.2,1.4,0.2,Iris-setosa
 36 | 35,4.9,3.1,1.5,0.1,Iris-setosa
 37 | 36,5.0,3.2,1.2,0.2,Iris-setosa
 38 | 37,5.5,3.5,1.3,0.2,Iris-setosa
 39 | 38,4.9,3.1,1.5,0.1,Iris-setosa
 40 | 39,4.4,3.0,1.3,0.2,Iris-setosa
 41 | 40,5.1,3.4,1.5,0.2,Iris-setosa
 42 | 41,5.0,3.5,1.3,0.3,Iris-setosa
 43 | 42,4.5,2.3,1.3,0.3,Iris-setosa
 44 | 43,4.4,3.2,1.3,0.2,Iris-setosa
 45 | 44,5.0,3.5,1.6,0.6,Iris-setosa
 46 | 45,5.1,3.8,1.9,0.4,Iris-setosa
 47 | 46,4.8,3.0,1.4,0.3,Iris-setosa
 48 | 47,5.1,3.8,1.6,0.2,Iris-setosa
 49 | 48,4.6,3.2,1.4,0.2,Iris-setosa
 50 | 49,5.3,3.7,1.5,0.2,Iris-setosa
 51 | 50,5.0,3.3,1.4,0.2,Iris-setosa
 52 | 51,7.0,3.2,4.7,1.4,Iris-versicolor
 53 | 52,6.4,3.2,4.5,1.5,Iris-versicolor
 54 | 53,6.9,3.1,4.9,1.5,Iris-versicolor
 55 | 54,5.5,2.3,4.0,1.3,Iris-versicolor
 56 | 55,6.5,2.8,4.6,1.5,Iris-versicolor
 57 | 56,5.7,2.8,4.5,1.3,Iris-versicolor
 58 | 57,6.3,3.3,4.7,1.6,Iris-versicolor
 59 | 58,4.9,2.4,3.3,1.0,Iris-versicolor
 60 | 59,6.6,2.9,4.6,1.3,Iris-versicolor
 61 | 60,5.2,2.7,3.9,1.4,Iris-versicolor
 62 | 61,5.0,2.0,3.5,1.0,Iris-versicolor
 63 | 62,5.9,3.0,4.2,1.5,Iris-versicolor
 64 | 63,6.0,2.2,4.0,1.0,Iris-versicolor
 65 | 64,6.1,2.9,4.7,1.4,Iris-versicolor
 66 | 65,5.6,2.9,3.6,1.3,Iris-versicolor
 67 | 66,6.7,3.1,4.4,1.4,Iris-versicolor
 68 | 67,5.6,3.0,4.5,1.5,Iris-versicolor
 69 | 68,5.8,2.7,4.1,1.0,Iris-versicolor
 70 | 69,6.2,2.2,4.5,1.5,Iris-versicolor
 71 | 70,5.6,2.5,3.9,1.1,Iris-versicolor
 72 | 71,5.9,3.2,4.8,1.8,Iris-versicolor
 73 | 72,6.1,2.8,4.0,1.3,Iris-versicolor
 74 | 73,6.3,2.5,4.9,1.5,Iris-versicolor
 75 | 74,6.1,2.8,4.7,1.2,Iris-versicolor
 76 | 75,6.4,2.9,4.3,1.3,Iris-versicolor
 77 | 76,6.6,3.0,4.4,1.4,Iris-versicolor
 78 | 77,6.8,2.8,4.8,1.4,Iris-versicolor
 79 | 78,6.7,3.0,5.0,1.7,Iris-versicolor
 80 | 79,6.0,2.9,4.5,1.5,Iris-versicolor
 81 | 80,5.7,2.6,3.5,1.0,Iris-versicolor
 82 | 81,5.5,2.4,3.8,1.1,Iris-versicolor
 83 | 82,5.5,2.4,3.7,1.0,Iris-versicolor
 84 | 83,5.8,2.7,3.9,1.2,Iris-versicolor
 85 | 84,6.0,2.7,5.1,1.6,Iris-versicolor
 86 | 85,5.4,3.0,4.5,1.5,Iris-versicolor
 87 | 86,6.0,3.4,4.5,1.6,Iris-versicolor
 88 | 87,6.7,3.1,4.7,1.5,Iris-versicolor
 89 | 88,6.3,2.3,4.4,1.3,Iris-versicolor
 90 | 89,5.6,3.0,4.1,1.3,Iris-versicolor
 91 | 90,5.5,2.5,4.0,1.3,Iris-versicolor
 92 | 91,5.5,2.6,4.4,1.2,Iris-versicolor
 93 | 92,6.1,3.0,4.6,1.4,Iris-versicolor
 94 | 93,5.8,2.6,4.0,1.2,Iris-versicolor
 95 | 94,5.0,2.3,3.3,1.0,Iris-versicolor
 96 | 95,5.6,2.7,4.2,1.3,Iris-versicolor
 97 | 96,5.7,3.0,4.2,1.2,Iris-versicolor
 98 | 97,5.7,2.9,4.2,1.3,Iris-versicolor
 99 | 98,6.2,2.9,4.3,1.3,Iris-versicolor
100 | 99,5.1,2.5,3.0,1.1,Iris-versicolor
101 | 100,5.7,2.8,4.1,1.3,Iris-versicolor
102 | 101,6.3,3.3,6.0,2.5,Iris-virginica
103 | 102,5.8,2.7,5.1,1.9,Iris-virginica
104 | 103,7.1,3.0,5.9,2.1,Iris-virginica
105 | 104,6.3,2.9,5.6,1.8,Iris-virginica
106 | 105,6.5,3.0,5.8,2.2,Iris-virginica
107 | 106,7.6,3.0,6.6,2.1,Iris-virginica
108 | 107,4.9,2.5,4.5,1.7,Iris-virginica
109 | 108,7.3,2.9,6.3,1.8,Iris-virginica
110 | 109,6.7,2.5,5.8,1.8,Iris-virginica
111 | 110,7.2,3.6,6.1,2.5,Iris-virginica
112 | 111,6.5,3.2,5.1,2.0,Iris-virginica
113 | 112,6.4,2.7,5.3,1.9,Iris-virginica
114 | 113,6.8,3.0,5.5,2.1,Iris-virginica
115 | 114,5.7,2.5,5.0,2.0,Iris-virginica
116 | 115,5.8,2.8,5.1,2.4,Iris-virginica
117 | 116,6.4,3.2,5.3,2.3,Iris-virginica
118 | 117,6.5,3.0,5.5,1.8,Iris-virginica
119 | 118,7.7,3.8,6.7,2.2,Iris-virginica
120 | 119,7.7,2.6,6.9,2.3,Iris-virginica
121 | 120,6.0,2.2,5.0,1.5,Iris-virginica
122 | 121,6.9,3.2,5.7,2.3,Iris-virginica
123 | 122,5.6,2.8,4.9,2.0,Iris-virginica
124 | 123,7.7,2.8,6.7,2.0,Iris-virginica
125 | 124,6.3,2.7,4.9,1.8,Iris-virginica
126 | 125,6.7,3.3,5.7,2.1,Iris-virginica
127 | 126,7.2,3.2,6.0,1.8,Iris-virginica
128 | 127,6.2,2.8,4.8,1.8,Iris-virginica
129 | 128,6.1,3.0,4.9,1.8,Iris-virginica
130 | 129,6.4,2.8,5.6,2.1,Iris-virginica
131 | 130,7.2,3.0,5.8,1.6,Iris-virginica
132 | 131,7.4,2.8,6.1,1.9,Iris-virginica
133 | 132,7.9,3.8,6.4,2.0,Iris-virginica
134 | 133,6.4,2.8,5.6,2.2,Iris-virginica
135 | 134,6.3,2.8,5.1,1.5,Iris-virginica
136 | 135,6.1,2.6,5.6,1.4,Iris-virginica
137 | 136,7.7,3.0,6.1,2.3,Iris-virginica
138 | 137,6.3,3.4,5.6,2.4,Iris-virginica
139 | 138,6.4,3.1,5.5,1.8,Iris-virginica
140 | 139,6.0,3.0,4.8,1.8,Iris-virginica
141 | 140,6.9,3.1,5.4,2.1,Iris-virginica
142 | 141,6.7,3.1,5.6,2.4,Iris-virginica
143 | 142,6.9,3.1,5.1,2.3,Iris-virginica
144 | 143,5.8,2.7,5.1,1.9,Iris-virginica
145 | 144,6.8,3.2,5.9,2.3,Iris-virginica
146 | 145,6.7,3.3,5.7,2.5,Iris-virginica
147 | 146,6.7,3.0,5.2,2.3,Iris-virginica
148 | 147,6.3,2.5,5.0,1.9,Iris-virginica
149 | 148,6.5,3.0,5.2,2.0,Iris-virginica
150 | 149,6.2,3.4,5.4,2.3,Iris-virginica
151 | 150,5.9,3.0,5.1,1.8,Iris-virginica
152 | 


--------------------------------------------------------------------------------
/Lecture 5/Supervised_learning/readme.md:
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1 | 
2 | 


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/Lecture 6/Unsupervised Learning.ipynb:
--------------------------------------------------------------------------------
  1 | {
  2 |  "cells": [
  3 |   {
  4 |    "cell_type": "markdown",
  5 |    "metadata": {},
  6 |    "source": [
  7 |     "# Hierarchical Clustering"
  8 |    ]
  9 |   },
 10 |   {
 11 |    "cell_type": "code",
 12 |    "execution_count": 1,
 13 |    "metadata": {},
 14 |    "outputs": [],
 15 |    "source": [
 16 |     "import matplotlib.pyplot as plt\n",
 17 |     "import pandas as pd\n",
 18 |     "%matplotlib inline\n",
 19 |     "import numpy as np"
 20 |    ]
 21 |   },
 22 |   {
 23 |    "cell_type": "code",
 24 |    "execution_count": 2,
 25 |    "metadata": {},
 26 |    "outputs": [],
 27 |    "source": [
 28 |     "customer_data = pd.read_csv('shopping-data.csv')\n"
 29 |    ]
 30 |   },
 31 |   {
 32 |    "cell_type": "code",
 33 |    "execution_count": 3,
 34 |    "metadata": {},
 35 |    "outputs": [
 36 |     {
 37 |      "data": {
 38 |       "text/plain": [
 39 |        "(200, 5)"
 40 |       ]
 41 |      },
 42 |      "execution_count": 3,
 43 |      "metadata": {},
 44 |      "output_type": "execute_result"
 45 |     }
 46 |    ],
 47 |    "source": [
 48 |     "customer_data.shape"
 49 |    ]
 50 |   },
 51 |   {
 52 |    "cell_type": "code",
 53 |    "execution_count": 4,
 54 |    "metadata": {},
 55 |    "outputs": [
 56 |     {
 57 |      "data": {
 58 |       "text/html": [
 59 |        "<div>\n",
 60 |        "<style scoped>\n",
 61 |        "    .dataframe tbody tr th:only-of-type {\n",
 62 |        "        vertical-align: middle;\n",
 63 |        "    }\n",
 64 |        "\n",
 65 |        "    .dataframe tbody tr th {\n",
 66 |        "        vertical-align: top;\n",
 67 |        "    }\n",
 68 |        "\n",
 69 |        "    .dataframe thead th {\n",
 70 |        "        text-align: right;\n",
 71 |        "    }\n",
 72 |        "</style>\n",
 73 |        "<table border=\"1\" class=\"dataframe\">\n",
 74 |        "  <thead>\n",
 75 |        "    <tr style=\"text-align: right;\">\n",
 76 |        "      <th></th>\n",
 77 |        "      <th>CustomerID</th>\n",
 78 |        "      <th>Genre</th>\n",
 79 |        "      <th>Age</th>\n",
 80 |        "      <th>Annual Income (k$)</th>\n",
 81 |        "      <th>Spending Score (1-100)</th>\n",
 82 |        "    </tr>\n",
 83 |        "  </thead>\n",
 84 |        "  <tbody>\n",
 85 |        "    <tr>\n",
 86 |        "      <th>0</th>\n",
 87 |        "      <td>1</td>\n",
 88 |        "      <td>Male</td>\n",
 89 |        "      <td>19</td>\n",
 90 |        "      <td>15</td>\n",
 91 |        "      <td>39</td>\n",
 92 |        "    </tr>\n",
 93 |        "    <tr>\n",
 94 |        "      <th>1</th>\n",
 95 |        "      <td>2</td>\n",
 96 |        "      <td>Male</td>\n",
 97 |        "      <td>21</td>\n",
 98 |        "      <td>15</td>\n",
 99 |        "      <td>81</td>\n",
100 |        "    </tr>\n",
101 |        "    <tr>\n",
102 |        "      <th>2</th>\n",
103 |        "      <td>3</td>\n",
104 |        "      <td>Female</td>\n",
105 |        "      <td>20</td>\n",
106 |        "      <td>16</td>\n",
107 |        "      <td>6</td>\n",
108 |        "    </tr>\n",
109 |        "    <tr>\n",
110 |        "      <th>3</th>\n",
111 |        "      <td>4</td>\n",
112 |        "      <td>Female</td>\n",
113 |        "      <td>23</td>\n",
114 |        "      <td>16</td>\n",
115 |        "      <td>77</td>\n",
116 |        "    </tr>\n",
117 |        "    <tr>\n",
118 |        "      <th>4</th>\n",
119 |        "      <td>5</td>\n",
120 |        "      <td>Female</td>\n",
121 |        "      <td>31</td>\n",
122 |        "      <td>17</td>\n",
123 |        "      <td>40</td>\n",
124 |        "    </tr>\n",
125 |        "  </tbody>\n",
126 |        "</table>\n",
127 |        "</div>"
128 |       ],
129 |       "text/plain": [
130 |        "   CustomerID   Genre  Age  Annual Income (k$)  Spending Score (1-100)\n",
131 |        "0           1    Male   19                  15                      39\n",
132 |        "1           2    Male   21                  15                      81\n",
133 |        "2           3  Female   20                  16                       6\n",
134 |        "3           4  Female   23                  16                      77\n",
135 |        "4           5  Female   31                  17                      40"
136 |       ]
137 |      },
138 |      "execution_count": 4,
139 |      "metadata": {},
140 |      "output_type": "execute_result"
141 |     }
142 |    ],
143 |    "source": [
144 |     "customer_data.head()"
145 |    ]
146 |   },
147 |   {
148 |    "cell_type": "code",
149 |    "execution_count": 5,
150 |    "metadata": {},
151 |    "outputs": [],
152 |    "source": [
153 |     "data = customer_data.iloc[:, 3:5].values"
154 |    ]
155 |   },
156 |   {
157 |    "cell_type": "code",
158 |    "execution_count": 6,
159 |    "metadata": {},
160 |    "outputs": [
161 |     {
162 |      "data": {
163 |       "image/png": 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\n",
164 |       "text/plain": [
165 |        "<Figure size 720x504 with 1 Axes>"
166 |       ]
167 |      },
168 |      "metadata": {
169 |       "needs_background": "light"
170 |      },
171 |      "output_type": "display_data"
172 |     }
173 |    ],
174 |    "source": [
175 |     "import scipy.cluster.hierarchy as shc\n",
176 |     "\n",
177 |     "plt.figure(figsize=(10, 7))\n",
178 |     "plt.title(\"Customer Dendograms\")\n",
179 |     "dend = shc.dendrogram(shc.linkage(data, method='ward'))"
180 |    ]
181 |   },
182 |   {
183 |    "cell_type": "code",
184 |    "execution_count": 7,
185 |    "metadata": {},
186 |    "outputs": [
187 |     {
188 |      "data": {
189 |       "text/plain": [
190 |        "array([4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3,\n",
191 |        "       4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4, 1,\n",
192 |        "       4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
193 |        "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
194 |        "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
195 |        "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 0, 2, 0, 2,\n",
196 |        "       1, 2, 0, 2, 0, 2, 0, 2, 0, 2, 1, 2, 0, 2, 1, 2, 0, 2, 0, 2, 0, 2,\n",
197 |        "       0, 2, 0, 2, 0, 2, 1, 2, 0, 2, 0, 2, 0, 2, 0, 2, 0, 2, 0, 2, 0, 2,\n",
198 |        "       0, 2, 0, 2, 0, 2, 0, 2, 0, 2, 0, 2, 0, 2, 0, 2, 0, 2, 0, 2, 0, 2,\n",
199 |        "       0, 2])"
200 |       ]
201 |      },
202 |      "execution_count": 7,
203 |      "metadata": {},
204 |      "output_type": "execute_result"
205 |     }
206 |    ],
207 |    "source": [
208 |     "from sklearn.cluster import AgglomerativeClustering\n",
209 |     "\n",
210 |     "cluster = AgglomerativeClustering(n_clusters=5, affinity='euclidean', linkage='ward')\n",
211 |     "cluster.fit_predict(data)"
212 |    ]
213 |   },
214 |   {
215 |    "cell_type": "code",
216 |    "execution_count": 8,
217 |    "metadata": {},
218 |    "outputs": [
219 |     {
220 |      "data": {
221 |       "text/plain": [
222 |        "<matplotlib.collections.PathCollection at 0x1a1b71aba8>"
223 |       ]
224 |      },
225 |      "execution_count": 8,
226 |      "metadata": {},
227 |      "output_type": "execute_result"
228 |     },
229 |     {
230 |      "data": {
231 |       "image/png": 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\n",
232 |       "text/plain": [
233 |        "<Figure size 720x504 with 1 Axes>"
234 |       ]
235 |      },
236 |      "metadata": {
237 |       "needs_background": "light"
238 |      },
239 |      "output_type": "display_data"
240 |     }
241 |    ],
242 |    "source": [
243 |     "plt.figure(figsize=(10, 7))\n",
244 |     "plt.scatter(data[:,0], data[:,1], c=cluster.labels_, cmap='rainbow')"
245 |    ]
246 |   },
247 |   {
248 |    "cell_type": "markdown",
249 |    "metadata": {},
250 |    "source": [
251 |     "# K-Means"
252 |    ]
253 |   },
254 |   {
255 |    "cell_type": "code",
256 |    "execution_count": 9,
257 |    "metadata": {},
258 |    "outputs": [],
259 |    "source": [
260 |     "from sklearn.datasets import make_blobs\n",
261 |     "from sklearn.cluster import KMeans"
262 |    ]
263 |   },
264 |   {
265 |    "cell_type": "code",
266 |    "execution_count": 10,
267 |    "metadata": {},
268 |    "outputs": [],
269 |    "source": [
270 |     "num_samples_total = 1000\n",
271 |     "cluster_centers = [(20,20), (4,4)]\n",
272 |     "num_classes = len(cluster_centers)\n"
273 |    ]
274 |   },
275 |   {
276 |    "cell_type": "code",
277 |    "execution_count": 11,
278 |    "metadata": {},
279 |    "outputs": [],
280 |    "source": [
281 |     "X, targets = make_blobs(n_samples = num_samples_total, centers = cluster_centers, n_features = num_classes, center_box=(0, 1), cluster_std = 2)"
282 |    ]
283 |   },
284 |   {
285 |    "cell_type": "code",
286 |    "execution_count": 12,
287 |    "metadata": {},
288 |    "outputs": [],
289 |    "source": [
290 |     "np.save('./clusters.npy', X)\n",
291 |     "X = np.load('./clusters.npy')"
292 |    ]
293 |   },
294 |   {
295 |    "cell_type": "code",
296 |    "execution_count": 13,
297 |    "metadata": {},
298 |    "outputs": [
299 |     {
300 |      "data": {
301 |       "text/plain": [
302 |        "KMeans(n_clusters=2)"
303 |       ]
304 |      },
305 |      "execution_count": 13,
306 |      "metadata": {},
307 |      "output_type": "execute_result"
308 |     }
309 |    ],
310 |    "source": [
311 |     "kmeans = KMeans(init='k-means++', n_clusters=num_classes, n_init=10)\n",
312 |     "kmeans.fit(X)"
313 |    ]
314 |   },
315 |   {
316 |    "cell_type": "code",
317 |    "execution_count": null,
318 |    "metadata": {},
319 |    "outputs": [],
320 |    "source": [
321 |     "P = kmeans.predict(X)"
322 |    ]
323 |   },
324 |   {
325 |    "cell_type": "code",
326 |    "execution_count": null,
327 |    "metadata": {},
328 |    "outputs": [],
329 |    "source": [
330 |     "colors = list(map(lambda x: '#3b4cc0' if x == 1 else '#b40426', P))\n",
331 |     "plt.scatter(X[:,0], X[:,1], c=colors, marker=\"o\", picker=True)\n",
332 |     "plt.title('Two clusters of data')\n",
333 |     "plt.xlabel('Temperature yesterday')\n",
334 |     "plt.ylabel('Temperature today')\n",
335 |     "plt.show()"
336 |    ]
337 |   },
338 |   {
339 |    "cell_type": "code",
340 |    "execution_count": null,
341 |    "metadata": {},
342 |    "outputs": [],
343 |    "source": []
344 |   }
345 |  ],
346 |  "metadata": {
347 |   "kernelspec": {
348 |    "display_name": "Python 3",
349 |    "language": "python",
350 |    "name": "python3"
351 |   },
352 |   "language_info": {
353 |    "codemirror_mode": {
354 |     "name": "ipython",
355 |     "version": 3
356 |    },
357 |    "file_extension": ".py",
358 |    "mimetype": "text/x-python",
359 |    "name": "python",
360 |    "nbconvert_exporter": "python",
361 |    "pygments_lexer": "ipython3",
362 |    "version": "3.6.10"
363 |   }
364 |  },
365 |  "nbformat": 4,
366 |  "nbformat_minor": 4
367 | }
368 | 


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/Lecture 6/readme.md:
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1 | 
2 | 


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/Lecture 6/shopping-data.csv:
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  1 | CustomerID,Genre,Age,Annual Income (k$),Spending Score (1-100)
  2 | 0001,Male,19,15,39
  3 | 0002,Male,21,15,81
  4 | 0003,Female,20,16,6
  5 | 0004,Female,23,16,77
  6 | 0005,Female,31,17,40
  7 | 0006,Female,22,17,76
  8 | 0007,Female,35,18,6
  9 | 0008,Female,23,18,94
 10 | 0009,Male,64,19,3
 11 | 0010,Female,30,19,72
 12 | 0011,Male,67,19,14
 13 | 0012,Female,35,19,99
 14 | 0013,Female,58,20,15
 15 | 0014,Female,24,20,77
 16 | 0015,Male,37,20,13
 17 | 0016,Male,22,20,79
 18 | 0017,Female,35,21,35
 19 | 0018,Male,20,21,66
 20 | 0019,Male,52,23,29
 21 | 0020,Female,35,23,98
 22 | 0021,Male,35,24,35
 23 | 0022,Male,25,24,73
 24 | 0023,Female,46,25,5
 25 | 0024,Male,31,25,73
 26 | 0025,Female,54,28,14
 27 | 0026,Male,29,28,82
 28 | 0027,Female,45,28,32
 29 | 0028,Male,35,28,61
 30 | 0029,Female,40,29,31
 31 | 0030,Female,23,29,87
 32 | 0031,Male,60,30,4
 33 | 0032,Female,21,30,73
 34 | 0033,Male,53,33,4
 35 | 0034,Male,18,33,92
 36 | 0035,Female,49,33,14
 37 | 0036,Female,21,33,81
 38 | 0037,Female,42,34,17
 39 | 0038,Female,30,34,73
 40 | 0039,Female,36,37,26
 41 | 0040,Female,20,37,75
 42 | 0041,Female,65,38,35
 43 | 0042,Male,24,38,92
 44 | 0043,Male,48,39,36
 45 | 0044,Female,31,39,61
 46 | 0045,Female,49,39,28
 47 | 0046,Female,24,39,65
 48 | 0047,Female,50,40,55
 49 | 0048,Female,27,40,47
 50 | 0049,Female,29,40,42
 51 | 0050,Female,31,40,42
 52 | 0051,Female,49,42,52
 53 | 0052,Male,33,42,60
 54 | 0053,Female,31,43,54
 55 | 0054,Male,59,43,60
 56 | 0055,Female,50,43,45
 57 | 0056,Male,47,43,41
 58 | 0057,Female,51,44,50
 59 | 0058,Male,69,44,46
 60 | 0059,Female,27,46,51
 61 | 0060,Male,53,46,46
 62 | 0061,Male,70,46,56
 63 | 0062,Male,19,46,55
 64 | 0063,Female,67,47,52
 65 | 0064,Female,54,47,59
 66 | 0065,Male,63,48,51
 67 | 0066,Male,18,48,59
 68 | 0067,Female,43,48,50
 69 | 0068,Female,68,48,48
 70 | 0069,Male,19,48,59
 71 | 0070,Female,32,48,47
 72 | 0071,Male,70,49,55
 73 | 0072,Female,47,49,42
 74 | 0073,Female,60,50,49
 75 | 0074,Female,60,50,56
 76 | 0075,Male,59,54,47
 77 | 0076,Male,26,54,54
 78 | 0077,Female,45,54,53
 79 | 0078,Male,40,54,48
 80 | 0079,Female,23,54,52
 81 | 0080,Female,49,54,42
 82 | 0081,Male,57,54,51
 83 | 0082,Male,38,54,55
 84 | 0083,Male,67,54,41
 85 | 0084,Female,46,54,44
 86 | 0085,Female,21,54,57
 87 | 0086,Male,48,54,46
 88 | 0087,Female,55,57,58
 89 | 0088,Female,22,57,55
 90 | 0089,Female,34,58,60
 91 | 0090,Female,50,58,46
 92 | 0091,Female,68,59,55
 93 | 0092,Male,18,59,41
 94 | 0093,Male,48,60,49
 95 | 0094,Female,40,60,40
 96 | 0095,Female,32,60,42
 97 | 0096,Male,24,60,52
 98 | 0097,Female,47,60,47
 99 | 0098,Female,27,60,50
100 | 0099,Male,48,61,42
101 | 0100,Male,20,61,49
102 | 0101,Female,23,62,41
103 | 0102,Female,49,62,48
104 | 0103,Male,67,62,59
105 | 0104,Male,26,62,55
106 | 0105,Male,49,62,56
107 | 0106,Female,21,62,42
108 | 0107,Female,66,63,50
109 | 0108,Male,54,63,46
110 | 0109,Male,68,63,43
111 | 0110,Male,66,63,48
112 | 0111,Male,65,63,52
113 | 0112,Female,19,63,54
114 | 0113,Female,38,64,42
115 | 0114,Male,19,64,46
116 | 0115,Female,18,65,48
117 | 0116,Female,19,65,50
118 | 0117,Female,63,65,43
119 | 0118,Female,49,65,59
120 | 0119,Female,51,67,43
121 | 0120,Female,50,67,57
122 | 0121,Male,27,67,56
123 | 0122,Female,38,67,40
124 | 0123,Female,40,69,58
125 | 0124,Male,39,69,91
126 | 0125,Female,23,70,29
127 | 0126,Female,31,70,77
128 | 0127,Male,43,71,35
129 | 0128,Male,40,71,95
130 | 0129,Male,59,71,11
131 | 0130,Male,38,71,75
132 | 0131,Male,47,71,9
133 | 0132,Male,39,71,75
134 | 0133,Female,25,72,34
135 | 0134,Female,31,72,71
136 | 0135,Male,20,73,5
137 | 0136,Female,29,73,88
138 | 0137,Female,44,73,7
139 | 0138,Male,32,73,73
140 | 0139,Male,19,74,10
141 | 0140,Female,35,74,72
142 | 0141,Female,57,75,5
143 | 0142,Male,32,75,93
144 | 0143,Female,28,76,40
145 | 0144,Female,32,76,87
146 | 0145,Male,25,77,12
147 | 0146,Male,28,77,97
148 | 0147,Male,48,77,36
149 | 0148,Female,32,77,74
150 | 0149,Female,34,78,22
151 | 0150,Male,34,78,90
152 | 0151,Male,43,78,17
153 | 0152,Male,39,78,88
154 | 0153,Female,44,78,20
155 | 0154,Female,38,78,76
156 | 0155,Female,47,78,16
157 | 0156,Female,27,78,89
158 | 0157,Male,37,78,1
159 | 0158,Female,30,78,78
160 | 0159,Male,34,78,1
161 | 0160,Female,30,78,73
162 | 0161,Female,56,79,35
163 | 0162,Female,29,79,83
164 | 0163,Male,19,81,5
165 | 0164,Female,31,81,93
166 | 0165,Male,50,85,26
167 | 0166,Female,36,85,75
168 | 0167,Male,42,86,20
169 | 0168,Female,33,86,95
170 | 0169,Female,36,87,27
171 | 0170,Male,32,87,63
172 | 0171,Male,40,87,13
173 | 0172,Male,28,87,75
174 | 0173,Male,36,87,10
175 | 0174,Male,36,87,92
176 | 0175,Female,52,88,13
177 | 0176,Female,30,88,86
178 | 0177,Male,58,88,15
179 | 0178,Male,27,88,69
180 | 0179,Male,59,93,14
181 | 0180,Male,35,93,90
182 | 0181,Female,37,97,32
183 | 0182,Female,32,97,86
184 | 0183,Male,46,98,15
185 | 0184,Female,29,98,88
186 | 0185,Female,41,99,39
187 | 0186,Male,30,99,97
188 | 0187,Female,54,101,24
189 | 0188,Male,28,101,68
190 | 0189,Female,41,103,17
191 | 0190,Female,36,103,85
192 | 0191,Female,34,103,23
193 | 0192,Female,32,103,69
194 | 0193,Male,33,113,8
195 | 0194,Female,38,113,91
196 | 0195,Female,47,120,16
197 | 0196,Female,35,120,79
198 | 0197,Female,45,126,28
199 | 0198,Male,32,126,74
200 | 0199,Male,32,137,18
201 | 0200,Male,30,137,83


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/README.md:
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1 | # Introduction to Data Science
2 | This is the repository for the course Introduction to Data Science offered by the Department of Information Technologies, Åbo Akademi University, Finland
3 | 


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/Webscraping/test:
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1 | 
2 | 


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