text:
Q: How to do a partial autocorrelation plot with many zeros in r I have a dataset of ER admissions with many zeros. These are daily admissions from 2016-06-05 to 2019-12-31. This is my data:
df<-structure(list(date = structure(c(1465084800, 1465171200, 1465257600,
1465344000, 1465430400, 1465516800, 1465603200, 1465689600, 1465776000,
1465862400, 1465948800, 1466035200, 1466121600, 1466208000, 1466294400,
1466380800, 1466467200, 1466553600, 1466640000, 1466726400, 1466812800,
1466899200, 1466985600, 1467072000, 1467158400, 1467244800, 1467331200,
1467417600, 1467504000, 1467590400, 1467676800, 1467763200, 1467849600,
1467936000, 1468022400, 1468108800, 1468195200, 1468281600, 1468368000,
1468454400, 1468540800, 1468627200, 1468713600, 1468800000, 1468886400,
1468972800, 1469059200, 1469145600, 1469232000, 1469318400, 1469404800,
1469491200, 1469577600, 1469664000, 1469750400, 1469836800, 1469923200,
1470009600, 1470096000, 1470182400, 1470268800, 1470355200, 1470441600,
1470528000, 1470614400, 1470700800, 1470787200, 1470873600, 1470960000,
1471046400, 1471132800, 1471219200, 1471305600, 1471392000, 1471478400,
1471564800, 1471651200, 1471737600, 1471824000, 1471910400, 1471996800,
1472083200, 1472169600, 1472256000, 1472342400, 1472428800, 1472515200,
1472601600, 1472688000, 1472774400, 1472860800, 1472947200, 1473033600,
1473120000, 1473206400, 1473292800, 1473379200, 1473465600, 1473552000,
1473638400, 1473724800, 1473811200, 1473897600, 1473984000, 1474070400,
1474156800, 1474243200, 1474329600, 1474416000, 1474502400, 1474588800,
1474675200, 1474761600, 1474848000, 1474934400, 1475020800, 1475107200,
1475193600, 1475280000, 1475366400, 1475452800, 1475539200, 1475625600,
1475712000, 1475798400, 1475884800, 1475971200, 1476057600, 1476144000,
1476230400, 1476316800, 1476403200, 1476489600, 1476576000, 1476662400,
1476748800, 1476835200, 1476921600, 1477008000, 1477094400, 1477180800,
1477267200, 1477353600, 1477440000, 1477526400, 1477612800, 1477699200,
1477785600, 1477872000, 1477958400, 1478044800, 1478131200, 1478217600,
1478304000, 1478390400, 1478476800, 1478563200, 1478649600, 1478736000,
1478822400, 1478908800, 1478995200, 1479081600, 1479168000, 1479254400,
1479340800, 1479427200, 1479513600, 1479600000, 1479686400, 1479772800,
1479859200, 1479945600, 1480032000, 1480118400, 1480204800, 1480291200,
1480377600, 1480464000, 1480550400, 1480636800, 1480723200, 1480809600,
1480896000, 1480982400, 1481068800, 1481155200, 1481241600, 1481328000,
1481414400, 1481500800, 1481587200, 1481673600, 1481760000, 1481846400,
1481932800, 1482019200, 1482105600, 1482192000, 1482278400, 1482364800,
1482451200, 1482537600, 1482624000, 1482710400, 1482796800, 1482883200,
1482969600, 1483056000, 1483142400, 1483228800, 1483315200, 1483401600,
1483488000, 1483574400, 1483660800, 1483747200, 1483833600, 1483920000,
1484006400, 1484092800, 1484179200, 1484352000, 1484438400, 1484524800,
1484611200, 1484697600, 1484784000, 1484870400, 1484956800, 1485043200,
1485129600, 1485216000, 1485302400, 1485388800, 1485475200, 1485561600,
1485648000, 1485734400, 1485820800, 1485907200, 1485993600, 1486080000,
1486166400, 1486252800, 1486339200, 1486425600, 1486512000, 1486598400,
1486684800, 1486771200, 1486857600, 1486944000, 1487030400, 1487116800,
1487203200, 1487289600, 1487376000, 1487462400, 1487548800, 1487635200,
1487721600, 1487808000, 1487894400, 1487980800, 1488067200, 1488153600,
1488240000, 1488326400, 1488412800, 1488499200, 1488585600, 1488672000,
1488758400, 1488844800, 1488931200, 1489017600, 1489104000, 1489190400,
1489276800, 1489363200, 1489449600, 1489536000, 1489622400, 1489708800,
1489795200, 1489881600, 1489968000, 1490054400, 1490140800, 1490227200,
1490313600, 1490400000, 1490486400, 1490572800, 1490659200, 1490745600,
1490832000, 1490918400, 1491004800, 1491091200, 1491177600, 1491264000,
1491350400, 1491436800, 1491523200, 1491609600, 1491696000, 1491782400,
1491868800, 1491955200, 1492041600, 1492128000, 1492214400, 1492300800,
1492387200, 1492473600, 1492560000, 1492646400, 1492732800, 1492819200,
1492905600, 1492992000, 1493078400, 1493164800, 1493251200, 1493337600,
1493424000, 1493510400, 1493596800, 1493683200, 1493769600, 1493856000,
1493942400, 1494028800, 1494115200, 1494201600, 1494288000, 1494374400,
1494460800, 1494547200, 1494633600, 1494720000, 1494806400, 1494892800,
1494979200, 1495065600, 1495152000, 1495238400, 1495324800, 1495411200,
1495497600, 1495584000, 1495670400, 1495756800, 1495843200, 1495929600,
1496016000, 1496102400, 1496188800, 1496275200, 1496361600, 1496448000,
1496534400, 1496620800, 1496707200, 1496793600, 1496880000, 1496966400,
1497052800, 1497139200, 1497225600, 1497312000, 1497398400, 1497484800,
1497571200, 1497657600, 1497744000, 1497830400, 1497916800, 1498003200,
1498089600, 1498176000, 1498262400, 1498348800, 1498435200, 1498521600,
1498608000, 1498694400, 1498780800, 1498867200, 1498953600, 1499040000,
1499126400, 1499212800, 1499299200, 1499385600, 1499472000, 1499558400,
1499644800, 1499731200, 1499817600, 1499904000, 1499990400, 1500076800,
1500163200, 1500249600, 1500336000, 1500422400, 1500508800, 1500595200,
1500681600, 1500768000, 1500854400, 1500940800, 1501027200, 1501113600,
1501200000, 1501286400, 1501372800, 1501459200, 1501545600, 1501632000,
1501718400, 1501804800, 1501891200, 1501977600, 1502064000, 1502150400,
1502236800, 1502323200, 1502409600, 1502496000, 1502582400, 1502668800,
1502755200, 1502841600, 1502928000, 1503014400, 1503100800, 1503187200,
1503273600, 1503360000, 1503446400, 1503532800, 1503619200, 1503705600,
1503792000, 1503878400, 1503964800, 1504051200, 1504137600, 1504224000,
1504310400, 1504396800, 1504483200, 1504569600, 1504656000, 1504742400,
1504828800, 1504915200, 1505001600, 1505088000, 1505174400, 1505260800,
1505347200, 1505433600, 1505520000, 1505606400, 1505692800, 1505779200,
1505865600, 1505952000, 1506038400, 1506124800, 1506211200, 1506297600,
1506384000, 1506470400, 1506556800, 1506643200, 1506729600, 1506816000,
1506902400, 1506988800, 1507075200, 1507161600, 1507248000, 1507334400,
1507420800, 1507507200, 1507593600, 1507680000, 1507766400, 1507852800,
1507939200, 1508025600, 1508112000, 1508198400, 1508284800, 1508371200,
1508457600, 1508544000, 1508630400, 1508716800, 1508803200, 1508889600,
1508976000, 1509062400, 1509148800, 1509235200, 1509321600, 1509408000,
1509494400, 1509580800, 1509667200, 1509753600, 1509840000, 1509926400,
1510012800, 1510099200, 1510185600, 1510272000, 1510358400, 1510444800,
1510531200, 1510617600, 1510704000, 1510790400, 1510876800, 1510963200,
1511049600, 1511136000, 1511222400, 1511308800, 1511395200, 1511481600,
1511568000, 1511654400, 1511740800, 1511827200, 1511913600, 1.512e+09,
1512086400, 1512172800, 1512259200, 1512345600, 1512432000, 1512518400,
1512604800, 1512691200, 1512777600, 1512864000, 1512950400, 1513036800,
1513123200, 1513209600, 1513296000, 1513382400, 1513468800, 1513555200,
1513641600, 1513728000, 1513814400, 1513900800, 1513987200, 1514073600,
1514160000, 1514246400, 1514332800, 1514419200, 1514505600, 1514592000,
1514678400, 1514764800, 1514851200, 1514937600, 1515024000, 1515110400,
1515196800, 1515283200, 1515369600, 1515456000, 1515542400, 1515628800,
1515715200, 1515801600, 1515888000, 1515974400, 1516060800, 1516147200,
1516233600, 1516320000, 1516406400, 1516492800, 1516579200, 1516665600,
1516752000, 1516838400, 1516924800, 1517011200, 1517097600, 1517184000,
1517270400, 1517356800, 1517443200, 1517529600, 1517616000, 1517702400,
1517788800, 1517875200, 1517961600, 1518048000, 1518134400, 1518220800,
1518307200, 1518393600, 1518480000, 1518566400, 1518652800, 1518739200,
1518825600, 1518912000, 1518998400, 1519084800, 1519171200, 1519257600,
1519344000, 1519430400, 1519516800, 1519603200, 1519689600, 1519776000,
1519862400, 1519948800, 1520035200, 1520121600, 1520208000, 1520294400,
1520380800, 1520467200, 1520553600, 1520640000, 1520726400, 1520812800,
1520899200, 1520985600, 1521072000, 1521158400, 1521244800, 1521331200,
1521417600, 1521504000, 1521590400, 1521676800, 1521763200, 1521849600,
1521936000, 1522022400, 1522108800, 1522195200, 1522281600, 1522368000,
1522454400, 1522540800, 1522627200, 1522713600, 1522800000, 1522886400,
1522972800, 1523059200, 1523145600, 1523232000, 1523318400, 1523404800,
1523491200, 1523577600, 1523664000, 1523750400, 1523836800, 1523923200,
1524009600, 1524096000, 1524182400, 1524268800, 1524355200, 1524441600,
1524528000, 1524614400, 1524700800, 1524787200, 1524873600, 1524960000,
1525046400, 1525132800, 1525219200, 1525305600, 1525392000, 1525478400,
1525564800, 1525651200, 1525737600, 1525824000, 1525910400, 1525996800,
1526083200, 1526169600, 1526256000, 1526342400, 1526428800, 1526515200,
1526601600, 1526688000, 1526774400, 1526860800, 1526947200, 1527033600,
1527120000, 1527206400, 1527292800, 1527379200, 1527465600, 1527552000,
1527638400, 1527724800, 1527811200, 1527897600, 1527984000, 1528070400,
1528156800, 1528243200, 1528329600, 1528416000, 1528502400, 1528588800,
1528675200, 1528761600, 1528848000, 1528934400, 1529020800, 1529107200,
1529193600, 1529280000, 1529366400, 1529452800, 1529539200, 1529625600,
1529712000, 1529798400, 1529884800, 1529971200, 1530057600, 1530144000,
1530230400, 1530316800, 1530403200, 1530489600, 1530576000, 1530662400,
1530748800, 1530835200, 1530921600, 1531008000, 1531094400, 1531180800,
1531267200, 1531353600, 1531440000, 1531526400, 1531612800, 1531699200,
1531785600, 1531872000, 1531958400, 1532044800, 1532131200, 1532217600,
1532304000, 1532390400, 1532476800, 1532563200, 1532649600, 1532736000,
1532822400, 1532908800, 1532995200, 1533081600, 1533168000, 1533254400,
1533340800, 1533427200, 1533513600, 1533600000, 1533686400, 1533772800,
1533859200, 1533945600, 1534032000, 1534118400, 1534204800, 1534291200,
1534377600, 1534464000, 1534550400, 1534636800, 1534723200, 1534809600,
1534896000, 1534982400, 1535068800, 1535155200, 1535241600, 1535328000,
1535414400, 1535500800, 1535587200, 1535673600, 1535760000, 1535846400,
1535932800, 1536019200, 1536105600, 1536192000, 1536278400, 1536364800,
1536451200, 1536537600, 1536624000, 1536710400, 1536796800, 1536883200,
1536969600, 1537056000, 1537142400, 1537228800, 1537315200, 1537401600,
1537488000, 1537574400, 1537660800, 1537747200, 1537833600, 1537920000,
1538006400, 1538092800, 1538179200, 1538265600, 1538352000, 1538438400,
1538524800, 1538611200, 1538697600, 1538784000, 1538870400, 1538956800,
1539043200, 1539129600, 1539216000, 1539302400, 1539388800, 1539475200,
1539561600, 1539648000, 1539734400, 1539820800, 1539907200, 1539993600,
1540080000, 1540166400, 1540252800, 1540339200, 1540425600, 1540512000,
1540598400, 1540684800, 1540771200, 1540857600, 1540944000, 1541030400,
1541116800, 1541203200, 1541289600, 1541376000, 1541462400, 1541548800,
1541635200, 1541721600, 1541808000, 1541894400, 1541980800, 1542067200,
1542153600, 1542240000, 1542326400, 1542412800, 1542499200, 1542585600,
1542672000, 1542758400, 1542844800, 1542931200, 1543017600, 1543104000,
1543190400, 1543276800, 1543363200, 1543449600, 1543536000, 1543622400,
1543708800, 1543795200, 1543881600, 1543968000, 1544054400, 1544140800,
1544227200, 1544313600, 1544400000, 1544486400, 1544572800, 1544659200,
1544745600, 1544832000, 1544918400, 1545004800, 1545091200, 1545177600,
1545264000, 1545350400, 1545436800, 1545523200, 1545609600, 1545696000,
1545782400, 1545868800, 1545955200, 1546041600, 1546128000, 1546214400,
1546300800, 1546387200, 1546473600, 1546560000, 1546646400, 1546732800,
1546819200, 1546905600, 1546992000, 1547078400, 1547164800, 1547251200,
1547337600, 1547424000, 1547510400, 1547596800, 1547683200, 1547769600,
1547856000, 1547942400, 1548028800, 1548115200, 1548201600, 1548288000,
1548374400, 1548460800, 1548547200, 1548633600, 1548720000, 1548806400,
1548892800, 1548979200, 1549065600, 1549152000, 1549238400, 1549324800,
1549411200, 1549497600, 1549584000, 1549670400, 1549756800, 1549843200,
1549929600, 1550016000, 1550102400, 1550188800, 1550275200, 1550361600,
1550448000, 1550534400, 1550620800, 1550707200, 1550793600, 1550880000,
1550966400, 1551052800, 1551139200, 1551225600, 1551312000, 1551398400,
1551484800, 1551571200, 1551657600, 1551744000, 1551830400, 1551916800,
1552003200, 1552089600, 1552176000, 1552262400, 1552348800, 1552435200,
1552521600, 1552608000, 1552694400, 1552780800, 1552867200, 1552953600,
1553040000, 1553126400, 1553212800, 1553299200, 1553385600, 1553472000,
1553558400, 1553644800, 1553731200, 1553817600, 1553904000, 1553990400,
1554076800, 1554163200, 1554249600, 1554336000, 1554422400, 1554508800,
1554595200, 1554681600, 1554768000, 1554854400, 1554940800, 1555027200,
1555113600, 1555200000, 1555286400, 1555372800, 1555459200, 1555545600,
1555632000, 1555718400, 1555804800, 1555891200, 1555977600, 1556064000,
1556150400, 1556236800, 1556323200, 1556409600, 1556496000, 1556582400,
1556668800, 1556755200, 1556841600, 1556928000, 1557014400, 1557100800,
1557187200, 1557273600, 1557360000, 1557446400, 1557532800, 1557619200,
1557705600, 1557792000, 1557878400, 1557964800, 1558051200, 1558137600,
1558224000, 1558310400, 1558396800, 1558483200, 1558569600, 1558656000,
1558742400, 1558828800, 1558915200, 1559001600, 1559088000, 1559174400,
1559260800, 1559347200, 1559433600, 1559520000, 1559606400, 1559692800,
1559779200, 1559865600, 1559952000, 1560038400, 1560124800, 1560211200,
1560297600, 1560384000, 1560470400, 1560556800, 1560643200, 1560729600,
1560816000, 1560902400, 1560988800, 1561075200, 1561161600, 1561248000,
1561334400, 1561420800, 1561507200, 1561593600, 1561680000, 1561766400,
1561852800, 1561939200, 1562025600, 1562112000, 1562198400, 1562284800,
1562371200, 1562457600, 1562544000, 1562630400, 1562716800, 1562803200,
1562889600, 1562976000, 1563062400, 1563148800, 1563235200, 1563321600,
1563408000, 1563494400, 1563580800, 1563667200, 1563753600, 1563840000,
1563926400, 1564012800, 1564099200, 1564185600, 1564272000, 1564358400,
1564444800, 1564531200, 1564617600, 1564704000, 1564790400, 1564876800,
1564963200, 1565049600, 1565136000, 1565222400, 1565308800, 1565395200,
1565481600, 1565568000, 1565654400, 1565740800, 1565827200, 1565913600,
1.566e+09, 1566086400, 1566172800, 1566259200, 1566345600, 1566432000,
1566518400, 1566604800, 1566691200, 1566777600, 1566864000, 1566950400,
1567036800, 1567123200, 1567209600, 1567296000, 1567382400, 1567468800,
1567555200, 1567641600, 1567728000, 1567814400, 1567900800, 1567987200,
1568073600, 1568160000, 1568246400, 1568332800, 1568419200, 1568505600,
1568592000, 1568678400, 1568764800, 1568851200, 1568937600, 1569024000,
1569110400, 1569196800, 1569283200, 1569369600, 1569456000, 1569542400,
1569628800, 1569715200, 1569801600, 1569888000, 1569974400, 1570060800,
1570147200, 1570233600, 1570320000, 1570406400, 1570492800, 1570579200,
1570665600, 1570752000, 1570838400, 1570924800, 1571011200, 1571097600,
1571184000, 1571270400, 1571356800, 1571443200, 1571529600, 1571616000,
1571702400, 1571788800, 1571875200, 1571961600, 1572048000, 1572134400,
1572220800, 1572307200, 1572393600, 1572480000, 1572566400, 1572652800,
1572739200, 1572825600, 1572912000, 1572998400, 1573084800, 1573171200,
1573257600, 1573344000, 1573430400, 1573516800, 1573603200, 1573689600,
1573776000, 1573862400, 1573948800, 1574035200, 1574121600, 1574208000,
1574294400, 1574380800, 1574467200, 1574553600, 1574640000, 1574726400,
1574812800, 1574899200, 1574985600, 1575072000, 1575158400, 1575244800,
1575331200, 1575417600, 1575504000, 1575590400, 1575676800, 1575763200,
1575849600, 1575936000, 1576022400, 1576108800, 1576195200, 1576281600,
1576368000, 1576454400, 1576540800, 1576627200, 1576713600, 1576800000,
1576886400, 1576972800, 1577059200, 1577145600, 1577232000, 1577318400,
1577404800, 1577491200, 1577577600, 1577664000, 1577750400), class = c("POSIXct",
"POSIXt"), tzone = "UTC"), adm = c(1L, 4L, 5L, 10L, 13L,
8L, 3L, 5L, 13L, 9L, 5L, 10L, 9L, 4L, 4L, 13L, 10L, 10L, 7L,
7L, 3L, 1L, 11L, 4L, 5L, 9L, 10L, 3L, 2L, 7L, 8L, 4L, 5L, 6L,
3L, 4L, 13L, 7L, 8L, 6L, 5L, 3L, 10L, 4L, 8L, 8L, 2L, 9L, 5L,
2L, 8L, 7L, 6L, 6L, 6L, 4L, 3L, 9L, 11L, 6L, 7L, 7L, 3L, 4L,
18L, 14L, 8L, 9L, 5L, 3L, 7L, 3L, 8L, 3L, 9L, 3L, 4L, 7L, 7L,
5L, 8L, 7L, 10L, 9L, 9L, 11L, 8L, 3L, 9L, 10L, 11L, 9L, 12L,
13L, 9L, 15L, 11L, 13L, 3L, 24L, 11L, 13L, 14L, 14L, 5L, 10L,
6L, 10L, 8L, 9L, 13L, 5L, 8L, 8L, 6L, 17L, 11L, 11L, 8L, 2L,
14L, 6L, 1L, 7L, 5L, 3L, 12L, 6L, 10L, 7L, 15L, 9L, 7L, 3L, 9L,
11L, 3L, 5L, 14L, 7L, 3L, 20L, 17L, 14L, 7L, 11L, 11L, 2L, 4L,
9L, 5L, 10L, 7L, 10L, 13L, 7L, 18L, 13L, 18L, 20L, 16L, 9L, 5L,
13L, 16L, 11L, 9L, 7L, 12L, 13L, 21L, 9L, 7L, 13L, 4L, 7L, 5L,
13L, 19L, 17L, 8L, 7L, 4L, 18L, 14L, 8L, 8L, 16L, 13L, 9L, 14L,
8L, 20L, 7L, 12L, 14L, 8L, 16L, 10L, 9L, 20L, 5L, 7L, 8L, 16L,
11L, 10L, 12L, 20L, 5L, 2L, 21L, 16L, 18L, 0L, 16L, 4L, 6L, 16L,
6L, 15L, 15L, 10L, 8L, 13L, 22L, 14L, 5L, 8L, 11L, 14L, 7L, 9L,
7L, 7L, 8L, 5L, 12L, 6L, 20L, 10L, 17L, 9L, 7L, 13L, 9L, 13L,
15L, 18L, 10L, 8L, 10L, 12L, 16L, 16L, 11L, 13L, 8L, 8L, 20L,
16L, 11L, 14L, 18L, 10L, 8L, 17L, 24L, 8L, 15L, 16L, 9L, 10L,
22L, 15L, 16L, 16L, 20L, 16L, 7L, 12L, 10L, 16L, 16L, 17L, 16L,
13L, 4L, 14L, 14L, 18L, 11L, 4L, 3L, 10L, 19L, 9L, 9L, 10L, 4L,
9L, 9L, 5L, 6L, 13L, 7L, 4L, 2L, 7L, 13L, 6L, 4L, 3L, 6L, 5L,
2L, 9L, 6L, 10L, 9L, 3L, 2L, 7L, 12L, 14L, 12L, 12L, 2L, 4L,
7L, 5L, 7L, 9L, 5L, 6L, 6L, 9L, 10L, 6L, 11L, 4L, 6L, 3L, 5L,
3L, 5L, 4L, 10L, 7L, 4L, 6L, 9L, 11L, 6L, 10L, 3L, 1L, 9L, 9L,
11L, 8L, 3L, 5L, 7L, 6L, 8L, 8L, 9L, 4L, 2L, 5L, 7L, 13L, 6L,
12L, 3L, 9L, 7L, 4L, 6L, 8L, 11L, 9L, 4L, 5L, 10L, 11L, 17L,
15L, 3L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L,
0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L,
0L, 0L, 0L, 1L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
2L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 2L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L,
0L, 0L, 0L, 1L, 0L, 1L, 2L, 1L, 2L, 0L, 1L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 3L, 16L, 17L, 6L,
6L, 9L, 6L, 12L, 6L, 13L, 6L, 5L, 9L, 6L, 14L, 2L, 17L, 4L, 10L,
6L, 1L, 15L, 8L, 8L, 5L, 7L, 7L, 8L, 12L, 2L, 3L, 7L, 11L, 6L,
9L, 10L, 11L, 11L, 4L, 12L, 1L, 7L, 6L, 3L, 8L, 11L, 7L, 6L,
5L, 5L, 11L, 7L, 7L, 6L, 7L, 5L, 7L, 10L, 5L, 4L, 7L, 5L, 9L,
7L, 14L, 10L, 4L, 9L, 5L, 10L, 12L, 14L, 6L, 5L, 12L, 5L, 3L,
8L, 8L, 4L, 9L, 9L, 12L, 2L, 8L, 5L, 4L, 5L, 1L, 4L, 4L, 7L,
6L, 8L, 10L, 13L, 9L, 4L, 8L, 8L, 9L, 12L, 4L, 7L, 6L, 5L, 5L,
7L, 2L, 5L, 10L, 0L, 4L, 6L, 5L, 3L, 8L, 2L, 1L, 1L, 6L, 6L,
1L, 2L, 5L, 9L, 10L, 7L, 10L, 3L, 12L, 7L, 4L, 1L, 5L, 6L, 6L,
5L, 4L, 1L, 5L, 0L, 8L, 6L, 4L, 1L, 7L, 5L, 3L, 8L, 3L, 0L, 3L,
2L, 0L, 6L, 10L, 0L, 8L, 3L, 0L, 1L, 1L, 5L, 7L, 0L, 1L, 0L,
3L, 1L, 9L, 2L, 8L, 1L, 0L, 0L, 5L, 1L, 0L, 2L, 1L, 0L, 7L, 1L,
2L, 0L, 0L, 4L, 4L, 10L, 0L, 6L, 4L, 3L, 0L, 4L, 1L, 3L, 1L,
0L, 0L, 0L, 5L, 0L, 6L, 6L, 3L, 5L, 0L, 4L, 0L, 2L, 3L, 5L, 2L,
4L, 3L, 1L, 1L, 0L, 2L, 0L, 3L, 0L, 3L, 4L, 4L, 7L, 0L, 0L, 1L,
9L, 0L, 3L, 0L, 4L, 0L, 3L, 4L, 5L, 0L, 0L, 4L, 3L, 0L, 1L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 1L, 0L,
0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L,
0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L,
1L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L,
0L, 0L, 1L, 2L, 0L, 0L, 0L, 2L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L,
1L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L,
1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 2L, 0L, 0L, 0L, 0L, 2L, 0L,
1L, 1L, 0L, 0L, 0L, 0L, 13L, 10L, 13L, 10L, 11L, 8L, 27L, 8L,
12L, 20L, 15L, 9L, 10L, 3L, 8L, 13L, 16L, 13L, 12L, 13L, 10L,
14L, 14L, 10L, 10L, 7L, 13L, 12L, 12L, 23L, 7L, 12L, 6L, 7L,
10L, 8L, 13L, 16L, 10L, 11L, 18L, 7L, 15L, 18L, 10L, 9L, 15L,
4L, 3L, 9L, 12L, 2L, 6L, 4L, 4L, 8L, 4L, 7L, 11L, 9L, 7L, 9L,
15L, 7L, 7L, 14L, 15L, 6L, 3L, 7L, 6L, 22L, 7L, 8L, 6L, 12L,
7L, 11L, 10L, 6L, 10L, 6L, 5L, 16L, 11L, 11L, 6L, 9L, 10L, 4L,
14L, 7L, 6L, 4L, 9L, 4L, 7L, 10L, 11L, 8L, 6L, 7L, 3L, 8L, 8L,
12L, 7L, 13L, 5L, 4L, 10L, 6L, 8L, 7L, 11L, 3L, 3L, 5L, 4L, 4L,
11L, 3L, 3L, 3L, 3L, 7L, 4L, 5L, 3L, 5L, 1L, 5L, 2L, 5L, 6L,
6L, 4L, 3L, 6L, 7L, 3L, 8L, 1L, 3L, 5L, 9L, 9L, 10L, 6L, 9L,
7L, 5L, 5L, 10L, 6L, 9L, 2L, 6L, 6L, 1L, 6L, 4L, 5L, 3L, 3L,
3L, 3L, 3L, 2L, 6L, 1L, 5L, 3L, 4L, 9L, 3L, 8L, 5L, 7L, 5L, 10L,
5L, 4L, 0L, 8L, 6L, 4L, 6L, 7L, 4L, 3L, 1L, 3L, 3L, 6L, 5L, 7L,
3L, 7L, 2L, 2L, 6L, 4L, 3L, 3L, 2L, 2L, 4L, 2L, 5L, 5L, 7L, 3L,
5L, 2L, 2L, 1L, 5L, 1L, 3L, 2L, 5L, 3L, 1L, 4L, 0L, 1L, 4L, 3L,
2L, 2L, 2L, 6L, 3L, 4L, 2L, 2L, 8L, 4L, 3L, 6L, 6L, 2L, 4L, 11L,
3L, 4L, 4L, 5L, 5L, 1L, 5L, 2L, 7L, 3L, 2L, 4L, 2L, 3L, 6L, 3L,
11L, 7L, 5L, 9L, 5L, 6L, 5L, 9L, 6L, 5L, 7L, 1L, 14L, 7L, 7L,
7L, 2L, 5L, 5L, 9L, 2L, 9L, 2L, 6L, 2L, 9L, 4L, 3L, 4L, 9L, 7L,
6L, 5L, 4L, 5L, 6L, 4L, 5L, 2L, 5L, 4L, 7L, 3L, 9L, 6L, 9L, 7L,
2L, 7L, 6L, 7L, 3L, 4L, 8L, 3L, 8L, 10L, 3L, 3L, 5L, 4L, 8L,
6L, 5L, 4L, 5L, 1L, 6L, 6L, 8L, 9L, 5L, 10L, 1L, 8L, 7L, 7L,
6L, 5L, 1L, 5L, 8L, 11L, 2L, 6L, 7L, 6L, 5L, 20L, 8L, 10L, 7L,
5L, 2L, 5L, 3L, 17L, 6L, 5L, 0L, 1L, 1L, 9L, 1L)), row.names = c(NA,
-1304L), class = "data.frame")

I want to do a time series analysis with it.
I transformed it into a ts to get a pacf
ts1 <- zoo(df$adm, df$date)
ts <- as.xts(ts1)
pacf(ts)

The problem is that the x-axis, usually showing lags like, 1,2,3...is showing lags in magnitudes of hundred of thousands.

How can I correct this?

A: TL;DR: The pacf() function converts its main argument to ts by calling as.ts() and then computes the PACF from that. In your application you probably just want to treat the observations as an equidistant series so it's easiest to strip the time index and just compute the PACF of the data vector. You can do that via:
pacf(coredata(ts1))
pacf(coredata(ts))

Both lead to identical results.
Details: The as.ts() methods for both zoo and xts try to preserve the time index when creating the ts object. While the zoo method does not assume any knowledge about the time class and just converts it to numeric, the xts method behaves somewhat differently because it "understands" what a POSIXct object is.
In either case the time index gets coerced to numeric which is the time in seconds since 1970-01-01 for POSIXct. Therefore the distance between the observations is 1 day = 86400 seconds and hence the frequency is 1/86400 = 1.157407e-05. Using the simple Date class instead of POSIXct would avoid this problem.
Finally, pacf(ts1) fails because as.ts(ts1) creates a ts series with one missing value because there is one gap in the data:
ts1[221:224]
## 2017-01-11 2017-01-12 2017-01-14 2017-01-15
##         15         15         10          8

Possibly it may be sensible to fill the observation for 2017-01-13 with 0?

A: Using the fpp3 forecasting packages I get the daily PACF lags per below if that helps.
(I don't use zoo/xts myself so can't say why that's showing the larger magnitudes.)
library(fpp3)

df <- structure(list(date = structure(c(
  1465084800, 1465171200, 1465257600,
  1465344000, 1465430400, 1465516800, 1465603200, 1465689600, 1465776000,
  1465862400, 1465948800, 1466035200, 1466121600, 1466208000, 1466294400,
  1466380800, 1466467200, 1466553600, 1466640000, 1466726400, 1466812800,
  1466899200, 1466985600, 1467072000, 1467158400, 1467244800, 1467331200,
  1467417600, 1467504000, 1467590400, 1467676800, 1467763200, 1467849600,
  1467936000, 1468022400, 1468108800, 1468195200, 1468281600, 1468368000,
  1468454400, 1468540800, 1468627200, 1468713600, 1468800000, 1468886400,
  1468972800, 1469059200, 1469145600, 1469232000, 1469318400, 1469404800,
  1469491200, 1469577600, 1469664000, 1469750400, 1469836800, 1469923200,
  1470009600, 1470096000, 1470182400, 1470268800, 1470355200, 1470441600,
  1470528000, 1470614400, 1470700800, 1470787200, 1470873600, 1470960000,
  1471046400, 1471132800, 1471219200, 1471305600, 1471392000, 1471478400,
  1471564800, 1471651200, 1471737600, 1471824000, 1471910400, 1471996800,
  1472083200, 1472169600, 1472256000, 1472342400, 1472428800, 1472515200,
  1472601600, 1472688000, 1472774400, 1472860800, 1472947200, 1473033600,
  1473120000, 1473206400, 1473292800, 1473379200, 1473465600, 1473552000,
  1473638400, 1473724800, 1473811200, 1473897600, 1473984000, 1474070400,
  1474156800, 1474243200, 1474329600, 1474416000, 1474502400, 1474588800,
  1474675200, 1474761600, 1474848000, 1474934400, 1475020800, 1475107200,
  1475193600, 1475280000, 1475366400, 1475452800, 1475539200, 1475625600,
  1475712000, 1475798400, 1475884800, 1475971200, 1476057600, 1476144000,
  1476230400, 1476316800, 1476403200, 1476489600, 1476576000, 1476662400,
  1476748800, 1476835200, 1476921600, 1477008000, 1477094400, 1477180800,
  1477267200, 1477353600, 1477440000, 1477526400, 1477612800, 1477699200,
  1477785600, 1477872000, 1477958400, 1478044800, 1478131200, 1478217600,
  1478304000, 1478390400, 1478476800, 1478563200, 1478649600, 1478736000,
  1478822400, 1478908800, 1478995200, 1479081600, 1479168000, 1479254400,
  1479340800, 1479427200, 1479513600, 1479600000, 1479686400, 1479772800,
  1479859200, 1479945600, 1480032000, 1480118400, 1480204800, 1480291200,
  1480377600, 1480464000, 1480550400, 1480636800, 1480723200, 1480809600,
  1480896000, 1480982400, 1481068800, 1481155200, 1481241600, 1481328000,
  1481414400, 1481500800, 1481587200, 1481673600, 1481760000, 1481846400,
  1481932800, 1482019200, 1482105600, 1482192000, 1482278400, 1482364800,
  1482451200, 1482537600, 1482624000, 1482710400, 1482796800, 1482883200,
  1482969600, 1483056000, 1483142400, 1483228800, 1483315200, 1483401600,
  1483488000, 1483574400, 1483660800, 1483747200, 1483833600, 1483920000,
  1484006400, 1484092800, 1484179200, 1484352000, 1484438400, 1484524800,
  1484611200, 1484697600, 1484784000, 1484870400, 1484956800, 1485043200,
  1485129600, 1485216000, 1485302400, 1485388800, 1485475200, 1485561600,
  1485648000, 1485734400, 1485820800, 1485907200, 1485993600, 1486080000,
  1486166400, 1486252800, 1486339200, 1486425600, 1486512000, 1486598400,
  1486684800, 1486771200, 1486857600, 1486944000, 1487030400, 1487116800,
  1487203200, 1487289600, 1487376000, 1487462400, 1487548800, 1487635200,
  1487721600, 1487808000, 1487894400, 1487980800, 1488067200, 1488153600,
  1488240000, 1488326400, 1488412800, 1488499200, 1488585600, 1488672000,
  1488758400, 1488844800, 1488931200, 1489017600, 1489104000, 1489190400,
  1489276800, 1489363200, 1489449600, 1489536000, 1489622400, 1489708800,
  1489795200, 1489881600, 1489968000, 1490054400, 1490140800, 1490227200,
  1490313600, 1490400000, 1490486400, 1490572800, 1490659200, 1490745600,
  1490832000, 1490918400, 1491004800, 1491091200, 1491177600, 1491264000,
  1491350400, 1491436800, 1491523200, 1491609600, 1491696000, 1491782400,
  1491868800, 1491955200, 1492041600, 1492128000, 1492214400, 1492300800,
  1492387200, 1492473600, 1492560000, 1492646400, 1492732800, 1492819200,
  1492905600, 1492992000, 1493078400, 1493164800, 1493251200, 1493337600,
  1493424000, 1493510400, 1493596800, 1493683200, 1493769600, 1493856000,
  1493942400, 1494028800, 1494115200, 1494201600, 1494288000, 1494374400,
  1494460800, 1494547200, 1494633600, 1494720000, 1494806400, 1494892800,
  1494979200, 1495065600, 1495152000, 1495238400, 1495324800, 1495411200,
  1495497600, 1495584000, 1495670400, 1495756800, 1495843200, 1495929600,
  1496016000, 1496102400, 1496188800, 1496275200, 1496361600, 1496448000,
  1496534400, 1496620800, 1496707200, 1496793600, 1496880000, 1496966400,
  1497052800, 1497139200, 1497225600, 1497312000, 1497398400, 1497484800,
  1497571200, 1497657600, 1497744000, 1497830400, 1497916800, 1498003200,
  1498089600, 1498176000, 1498262400, 1498348800, 1498435200, 1498521600,
  1498608000, 1498694400, 1498780800, 1498867200, 1498953600, 1499040000,
  1499126400, 1499212800, 1499299200, 1499385600, 1499472000, 1499558400,
  1499644800, 1499731200, 1499817600, 1499904000, 1499990400, 1500076800,
  1500163200, 1500249600, 1500336000, 1500422400, 1500508800, 1500595200,
  1500681600, 1500768000, 1500854400, 1500940800, 1501027200, 1501113600,
  1501200000, 1501286400, 1501372800, 1501459200, 1501545600, 1501632000,
  1501718400, 1501804800, 1501891200, 1501977600, 1502064000, 1502150400,
  1502236800, 1502323200, 1502409600, 1502496000, 1502582400, 1502668800,
  1502755200, 1502841600, 1502928000, 1503014400, 1503100800, 1503187200,
  1503273600, 1503360000, 1503446400, 1503532800, 1503619200, 1503705600,
  1503792000, 1503878400, 1503964800, 1504051200, 1504137600, 1504224000,
  1504310400, 1504396800, 1504483200, 1504569600, 1504656000, 1504742400,
  1504828800, 1504915200, 1505001600, 1505088000, 1505174400, 1505260800,
  1505347200, 1505433600, 1505520000, 1505606400, 1505692800, 1505779200,
  1505865600, 1505952000, 1506038400, 1506124800, 1506211200, 1506297600,
  1506384000, 1506470400, 1506556800, 1506643200, 1506729600, 1506816000,
  1506902400, 1506988800, 1507075200, 1507161600, 1507248000, 1507334400,
  1507420800, 1507507200, 1507593600, 1507680000, 1507766400, 1507852800,
  1507939200, 1508025600, 1508112000, 1508198400, 1508284800, 1508371200,
  1508457600, 1508544000, 1508630400, 1508716800, 1508803200, 1508889600,
  1508976000, 1509062400, 1509148800, 1509235200, 1509321600, 1509408000,
  1509494400, 1509580800, 1509667200, 1509753600, 1509840000, 1509926400,
  1510012800, 1510099200, 1510185600, 1510272000, 1510358400, 1510444800,
  1510531200, 1510617600, 1510704000, 1510790400, 1510876800, 1510963200,
  1511049600, 1511136000, 1511222400, 1511308800, 1511395200, 1511481600,
  1511568000, 1511654400, 1511740800, 1511827200, 1511913600, 1.512e+09,
  1512086400, 1512172800, 1512259200, 1512345600, 1512432000, 1512518400,
  1512604800, 1512691200, 1512777600, 1512864000, 1512950400, 1513036800,
  1513123200, 1513209600, 1513296000, 1513382400, 1513468800, 1513555200,
  1513641600, 1513728000, 1513814400, 1513900800, 1513987200, 1514073600,
  1514160000, 1514246400, 1514332800, 1514419200, 1514505600, 1514592000,
  1514678400, 1514764800, 1514851200, 1514937600, 1515024000, 1515110400,
  1515196800, 1515283200, 1515369600, 1515456000, 1515542400, 1515628800,
  1515715200, 1515801600, 1515888000, 1515974400, 1516060800, 1516147200,
  1516233600, 1516320000, 1516406400, 1516492800, 1516579200, 1516665600,
  1516752000, 1516838400, 1516924800, 1517011200, 1517097600, 1517184000,
  1517270400, 1517356800, 1517443200, 1517529600, 1517616000, 1517702400,
  1517788800, 1517875200, 1517961600, 1518048000, 1518134400, 1518220800,
  1518307200, 1518393600, 1518480000, 1518566400, 1518652800, 1518739200,
  1518825600, 1518912000, 1518998400, 1519084800, 1519171200, 1519257600,
  1519344000, 1519430400, 1519516800, 1519603200, 1519689600, 1519776000,
  1519862400, 1519948800, 1520035200, 1520121600, 1520208000, 1520294400,
  1520380800, 1520467200, 1520553600, 1520640000, 1520726400, 1520812800,
  1520899200, 1520985600, 1521072000, 1521158400, 1521244800, 1521331200,
  1521417600, 1521504000, 1521590400, 1521676800, 1521763200, 1521849600,
  1521936000, 1522022400, 1522108800, 1522195200, 1522281600, 1522368000,
  1522454400, 1522540800, 1522627200, 1522713600, 1522800000, 1522886400,
  1522972800, 1523059200, 1523145600, 1523232000, 1523318400, 1523404800,
  1523491200, 1523577600, 1523664000, 1523750400, 1523836800, 1523923200,
  1524009600, 1524096000, 1524182400, 1524268800, 1524355200, 1524441600,
  1524528000, 1524614400, 1524700800, 1524787200, 1524873600, 1524960000,
  1525046400, 1525132800, 1525219200, 1525305600, 1525392000, 1525478400,
  1525564800, 1525651200, 1525737600, 1525824000, 1525910400, 1525996800,
  1526083200, 1526169600, 1526256000, 1526342400, 1526428800, 1526515200,
  1526601600, 1526688000, 1526774400, 1526860800, 1526947200, 1527033600,
  1527120000, 1527206400, 1527292800, 1527379200, 1527465600, 1527552000,
  1527638400, 1527724800, 1527811200, 1527897600, 1527984000, 1528070400,
  1528156800, 1528243200, 1528329600, 1528416000, 1528502400, 1528588800,
  1528675200, 1528761600, 1528848000, 1528934400, 1529020800, 1529107200,
  1529193600, 1529280000, 1529366400, 1529452800, 1529539200, 1529625600,
  1529712000, 1529798400, 1529884800, 1529971200, 1530057600, 1530144000,
  1530230400, 1530316800, 1530403200, 1530489600, 1530576000, 1530662400,
  1530748800, 1530835200, 1530921600, 1531008000, 1531094400, 1531180800,
  1531267200, 1531353600, 1531440000, 1531526400, 1531612800, 1531699200,
  1531785600, 1531872000, 1531958400, 1532044800, 1532131200, 1532217600,
  1532304000, 1532390400, 1532476800, 1532563200, 1532649600, 1532736000,
  1532822400, 1532908800, 1532995200, 1533081600, 1533168000, 1533254400,
  1533340800, 1533427200, 1533513600, 1533600000, 1533686400, 1533772800,
  1533859200, 1533945600, 1534032000, 1534118400, 1534204800, 1534291200,
  1534377600, 1534464000, 1534550400, 1534636800, 1534723200, 1534809600,
  1534896000, 1534982400, 1535068800, 1535155200, 1535241600, 1535328000,
  1535414400, 1535500800, 1535587200, 1535673600, 1535760000, 1535846400,
  1535932800, 1536019200, 1536105600, 1536192000, 1536278400, 1536364800,
  1536451200, 1536537600, 1536624000, 1536710400, 1536796800, 1536883200,
  1536969600, 1537056000, 1537142400, 1537228800, 1537315200, 1537401600,
  1537488000, 1537574400, 1537660800, 1537747200, 1537833600, 1537920000,
  1538006400, 1538092800, 1538179200, 1538265600, 1538352000, 1538438400,
  1538524800, 1538611200, 1538697600, 1538784000, 1538870400, 1538956800,
  1539043200, 1539129600, 1539216000, 1539302400, 1539388800, 1539475200,
  1539561600, 1539648000, 1539734400, 1539820800, 1539907200, 1539993600,
  1540080000, 1540166400, 1540252800, 1540339200, 1540425600, 1540512000,
  1540598400, 1540684800, 1540771200, 1540857600, 1540944000, 1541030400,
  1541116800, 1541203200, 1541289600, 1541376000, 1541462400, 1541548800,
  1541635200, 1541721600, 1541808000, 1541894400, 1541980800, 1542067200,
  1542153600, 1542240000, 1542326400, 1542412800, 1542499200, 1542585600,
  1542672000, 1542758400, 1542844800, 1542931200, 1543017600, 1543104000,
  1543190400, 1543276800, 1543363200, 1543449600, 1543536000, 1543622400,
  1543708800, 1543795200, 1543881600, 1543968000, 1544054400, 1544140800,
  1544227200, 1544313600, 1544400000, 1544486400, 1544572800, 1544659200,
  1544745600, 1544832000, 1544918400, 1545004800, 1545091200, 1545177600,
  1545264000, 1545350400, 1545436800, 1545523200, 1545609600, 1545696000,
  1545782400, 1545868800, 1545955200, 1546041600, 1546128000, 1546214400,
  1546300800, 1546387200, 1546473600, 1546560000, 1546646400, 1546732800,
  1546819200, 1546905600, 1546992000, 1547078400, 1547164800, 1547251200,
  1547337600, 1547424000, 1547510400, 1547596800, 1547683200, 1547769600,
  1547856000, 1547942400, 1548028800, 1548115200, 1548201600, 1548288000,
  1548374400, 1548460800, 1548547200, 1548633600, 1548720000, 1548806400,
  1548892800, 1548979200, 1549065600, 1549152000, 1549238400, 1549324800,
  1549411200, 1549497600, 1549584000, 1549670400, 1549756800, 1549843200,
  1549929600, 1550016000, 1550102400, 1550188800, 1550275200, 1550361600,
  1550448000, 1550534400, 1550620800, 1550707200, 1550793600, 1550880000,
  1550966400, 1551052800, 1551139200, 1551225600, 1551312000, 1551398400,
  1551484800, 1551571200, 1551657600, 1551744000, 1551830400, 1551916800,
  1552003200, 1552089600, 1552176000, 1552262400, 1552348800, 1552435200,
  1552521600, 1552608000, 1552694400, 1552780800, 1552867200, 1552953600,
  1553040000, 1553126400, 1553212800, 1553299200, 1553385600, 1553472000,
  1553558400, 1553644800, 1553731200, 1553817600, 1553904000, 1553990400,
  1554076800, 1554163200, 1554249600, 1554336000, 1554422400, 1554508800,
  1554595200, 1554681600, 1554768000, 1554854400, 1554940800, 1555027200,
  1555113600, 1555200000, 1555286400, 1555372800, 1555459200, 1555545600,
  1555632000, 1555718400, 1555804800, 1555891200, 1555977600, 1556064000,
  1556150400, 1556236800, 1556323200, 1556409600, 1556496000, 1556582400,
  1556668800, 1556755200, 1556841600, 1556928000, 1557014400, 1557100800,
  1557187200, 1557273600, 1557360000, 1557446400, 1557532800, 1557619200,
  1557705600, 1557792000, 1557878400, 1557964800, 1558051200, 1558137600,
  1558224000, 1558310400, 1558396800, 1558483200, 1558569600, 1558656000,
  1558742400, 1558828800, 1558915200, 1559001600, 1559088000, 1559174400,
  1559260800, 1559347200, 1559433600, 1559520000, 1559606400, 1559692800,
  1559779200, 1559865600, 1559952000, 1560038400, 1560124800, 1560211200,
  1560297600, 1560384000, 1560470400, 1560556800, 1560643200, 1560729600,
  1560816000, 1560902400, 1560988800, 1561075200, 1561161600, 1561248000,
  1561334400, 1561420800, 1561507200, 1561593600, 1561680000, 1561766400,
  1561852800, 1561939200, 1562025600, 1562112000, 1562198400, 1562284800,
  1562371200, 1562457600, 1562544000, 1562630400, 1562716800, 1562803200,
  1562889600, 1562976000, 1563062400, 1563148800, 1563235200, 1563321600,
  1563408000, 1563494400, 1563580800, 1563667200, 1563753600, 1563840000,
  1563926400, 1564012800, 1564099200, 1564185600, 1564272000, 1564358400,
  1564444800, 1564531200, 1564617600, 1564704000, 1564790400, 1564876800,
  1564963200, 1565049600, 1565136000, 1565222400, 1565308800, 1565395200,
  1565481600, 1565568000, 1565654400, 1565740800, 1565827200, 1565913600,
  1.566e+09, 1566086400, 1566172800, 1566259200, 1566345600, 1566432000,
  1566518400, 1566604800, 1566691200, 1566777600, 1566864000, 1566950400,
  1567036800, 1567123200, 1567209600, 1567296000, 1567382400, 1567468800,
  1567555200, 1567641600, 1567728000, 1567814400, 1567900800, 1567987200,
  1568073600, 1568160000, 1568246400, 1568332800, 1568419200, 1568505600,
  1568592000, 1568678400, 1568764800, 1568851200, 1568937600, 1569024000,
  1569110400, 1569196800, 1569283200, 1569369600, 1569456000, 1569542400,
  1569628800, 1569715200, 1569801600, 1569888000, 1569974400, 1570060800,
  1570147200, 1570233600, 1570320000, 1570406400, 1570492800, 1570579200,
  1570665600, 1570752000, 1570838400, 1570924800, 1571011200, 1571097600,
  1571184000, 1571270400, 1571356800, 1571443200, 1571529600, 1571616000,
  1571702400, 1571788800, 1571875200, 1571961600, 1572048000, 1572134400,
  1572220800, 1572307200, 1572393600, 1572480000, 1572566400, 1572652800,
  1572739200, 1572825600, 1572912000, 1572998400, 1573084800, 1573171200,
  1573257600, 1573344000, 1573430400, 1573516800, 1573603200, 1573689600,
  1573776000, 1573862400, 1573948800, 1574035200, 1574121600, 1574208000,
  1574294400, 1574380800, 1574467200, 1574553600, 1574640000, 1574726400,
  1574812800, 1574899200, 1574985600, 1575072000, 1575158400, 1575244800,
  1575331200, 1575417600, 1575504000, 1575590400, 1575676800, 1575763200,
  1575849600, 1575936000, 1576022400, 1576108800, 1576195200, 1576281600,
  1576368000, 1576454400, 1576540800, 1576627200, 1576713600, 1576800000,
  1576886400, 1576972800, 1577059200, 1577145600, 1577232000, 1577318400,
  1577404800, 1577491200, 1577577600, 1577664000, 1577750400
), class = c(
  "POSIXct",
  "POSIXt"
), tzone = "UTC"), adm = c(
  1L, 4L, 5L, 10L, 13L,
  8L, 3L, 5L, 13L, 9L, 5L, 10L, 9L, 4L, 4L, 13L, 10L, 10L, 7L,
  7L, 3L, 1L, 11L, 4L, 5L, 9L, 10L, 3L, 2L, 7L, 8L, 4L, 5L, 6L,
  3L, 4L, 13L, 7L, 8L, 6L, 5L, 3L, 10L, 4L, 8L, 8L, 2L, 9L, 5L,
  2L, 8L, 7L, 6L, 6L, 6L, 4L, 3L, 9L, 11L, 6L, 7L, 7L, 3L, 4L,
  18L, 14L, 8L, 9L, 5L, 3L, 7L, 3L, 8L, 3L, 9L, 3L, 4L, 7L, 7L,
  5L, 8L, 7L, 10L, 9L, 9L, 11L, 8L, 3L, 9L, 10L, 11L, 9L, 12L,
  13L, 9L, 15L, 11L, 13L, 3L, 24L, 11L, 13L, 14L, 14L, 5L, 10L,
  6L, 10L, 8L, 9L, 13L, 5L, 8L, 8L, 6L, 17L, 11L, 11L, 8L, 2L,
  14L, 6L, 1L, 7L, 5L, 3L, 12L, 6L, 10L, 7L, 15L, 9L, 7L, 3L, 9L,
  11L, 3L, 5L, 14L, 7L, 3L, 20L, 17L, 14L, 7L, 11L, 11L, 2L, 4L,
  9L, 5L, 10L, 7L, 10L, 13L, 7L, 18L, 13L, 18L, 20L, 16L, 9L, 5L,
  13L, 16L, 11L, 9L, 7L, 12L, 13L, 21L, 9L, 7L, 13L, 4L, 7L, 5L,
  13L, 19L, 17L, 8L, 7L, 4L, 18L, 14L, 8L, 8L, 16L, 13L, 9L, 14L,
  8L, 20L, 7L, 12L, 14L, 8L, 16L, 10L, 9L, 20L, 5L, 7L, 8L, 16L,
  11L, 10L, 12L, 20L, 5L, 2L, 21L, 16L, 18L, 0L, 16L, 4L, 6L, 16L,
  6L, 15L, 15L, 10L, 8L, 13L, 22L, 14L, 5L, 8L, 11L, 14L, 7L, 9L,
  7L, 7L, 8L, 5L, 12L, 6L, 20L, 10L, 17L, 9L, 7L, 13L, 9L, 13L,
  15L, 18L, 10L, 8L, 10L, 12L, 16L, 16L, 11L, 13L, 8L, 8L, 20L,
  16L, 11L, 14L, 18L, 10L, 8L, 17L, 24L, 8L, 15L, 16L, 9L, 10L,
  22L, 15L, 16L, 16L, 20L, 16L, 7L, 12L, 10L, 16L, 16L, 17L, 16L,
  13L, 4L, 14L, 14L, 18L, 11L, 4L, 3L, 10L, 19L, 9L, 9L, 10L, 4L,
  9L, 9L, 5L, 6L, 13L, 7L, 4L, 2L, 7L, 13L, 6L, 4L, 3L, 6L, 5L,
  2L, 9L, 6L, 10L, 9L, 3L, 2L, 7L, 12L, 14L, 12L, 12L, 2L, 4L,
  7L, 5L, 7L, 9L, 5L, 6L, 6L, 9L, 10L, 6L, 11L, 4L, 6L, 3L, 5L,
  3L, 5L, 4L, 10L, 7L, 4L, 6L, 9L, 11L, 6L, 10L, 3L, 1L, 9L, 9L,
  11L, 8L, 3L, 5L, 7L, 6L, 8L, 8L, 9L, 4L, 2L, 5L, 7L, 13L, 6L,
  12L, 3L, 9L, 7L, 4L, 6L, 8L, 11L, 9L, 4L, 5L, 10L, 11L, 17L,
  15L, 3L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 0L,
  0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L,
  0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
  0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
  0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L,
  0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L,
  0L, 0L, 0L, 1L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
  2L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L,
  0L, 0L, 0L, 2L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L,
  0L, 0L, 0L, 1L, 0L, 1L, 2L, 1L, 2L, 0L, 1L, 0L, 0L, 0L, 0L, 0L,
  0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
  0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 3L, 16L, 17L, 6L,
  6L, 9L, 6L, 12L, 6L, 13L, 6L, 5L, 9L, 6L, 14L, 2L, 17L, 4L, 10L,
  6L, 1L, 15L, 8L, 8L, 5L, 7L, 7L, 8L, 12L, 2L, 3L, 7L, 11L, 6L,
  9L, 10L, 11L, 11L, 4L, 12L, 1L, 7L, 6L, 3L, 8L, 11L, 7L, 6L,
  5L, 5L, 11L, 7L, 7L, 6L, 7L, 5L, 7L, 10L, 5L, 4L, 7L, 5L, 9L,
  7L, 14L, 10L, 4L, 9L, 5L, 10L, 12L, 14L, 6L, 5L, 12L, 5L, 3L,
  8L, 8L, 4L, 9L, 9L, 12L, 2L, 8L, 5L, 4L, 5L, 1L, 4L, 4L, 7L,
  6L, 8L, 10L, 13L, 9L, 4L, 8L, 8L, 9L, 12L, 4L, 7L, 6L, 5L, 5L,
  7L, 2L, 5L, 10L, 0L, 4L, 6L, 5L, 3L, 8L, 2L, 1L, 1L, 6L, 6L,
  1L, 2L, 5L, 9L, 10L, 7L, 10L, 3L, 12L, 7L, 4L, 1L, 5L, 6L, 6L,
  5L, 4L, 1L, 5L, 0L, 8L, 6L, 4L, 1L, 7L, 5L, 3L, 8L, 3L, 0L, 3L,
  2L, 0L, 6L, 10L, 0L, 8L, 3L, 0L, 1L, 1L, 5L, 7L, 0L, 1L, 0L,
  3L, 1L, 9L, 2L, 8L, 1L, 0L, 0L, 5L, 1L, 0L, 2L, 1L, 0L, 7L, 1L,
  2L, 0L, 0L, 4L, 4L, 10L, 0L, 6L, 4L, 3L, 0L, 4L, 1L, 3L, 1L,
  0L, 0L, 0L, 5L, 0L, 6L, 6L, 3L, 5L, 0L, 4L, 0L, 2L, 3L, 5L, 2L,
  4L, 3L, 1L, 1L, 0L, 2L, 0L, 3L, 0L, 3L, 4L, 4L, 7L, 0L, 0L, 1L,
  9L, 0L, 3L, 0L, 4L, 0L, 3L, 4L, 5L, 0L, 0L, 4L, 3L, 0L, 1L, 0L,
  0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 1L, 0L,
  0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L,
  0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L,
  1L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L,
  0L, 0L, 1L, 2L, 0L, 0L, 0L, 2L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L,
  1L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L,
  1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 2L, 0L, 0L, 0L, 0L, 2L, 0L,
  1L, 1L, 0L, 0L, 0L, 0L, 13L, 10L, 13L, 10L, 11L, 8L, 27L, 8L,
  12L, 20L, 15L, 9L, 10L, 3L, 8L, 13L, 16L, 13L, 12L, 13L, 10L,
  14L, 14L, 10L, 10L, 7L, 13L, 12L, 12L, 23L, 7L, 12L, 6L, 7L,
  10L, 8L, 13L, 16L, 10L, 11L, 18L, 7L, 15L, 18L, 10L, 9L, 15L,
  4L, 3L, 9L, 12L, 2L, 6L, 4L, 4L, 8L, 4L, 7L, 11L, 9L, 7L, 9L,
  15L, 7L, 7L, 14L, 15L, 6L, 3L, 7L, 6L, 22L, 7L, 8L, 6L, 12L,
  7L, 11L, 10L, 6L, 10L, 6L, 5L, 16L, 11L, 11L, 6L, 9L, 10L, 4L,
  14L, 7L, 6L, 4L, 9L, 4L, 7L, 10L, 11L, 8L, 6L, 7L, 3L, 8L, 8L,
  12L, 7L, 13L, 5L, 4L, 10L, 6L, 8L, 7L, 11L, 3L, 3L, 5L, 4L, 4L,
  11L, 3L, 3L, 3L, 3L, 7L, 4L, 5L, 3L, 5L, 1L, 5L, 2L, 5L, 6L,
  6L, 4L, 3L, 6L, 7L, 3L, 8L, 1L, 3L, 5L, 9L, 9L, 10L, 6L, 9L,
  7L, 5L, 5L, 10L, 6L, 9L, 2L, 6L, 6L, 1L, 6L, 4L, 5L, 3L, 3L,
  3L, 3L, 3L, 2L, 6L, 1L, 5L, 3L, 4L, 9L, 3L, 8L, 5L, 7L, 5L, 10L,
  5L, 4L, 0L, 8L, 6L, 4L, 6L, 7L, 4L, 3L, 1L, 3L, 3L, 6L, 5L, 7L,
  3L, 7L, 2L, 2L, 6L, 4L, 3L, 3L, 2L, 2L, 4L, 2L, 5L, 5L, 7L, 3L,
  5L, 2L, 2L, 1L, 5L, 1L, 3L, 2L, 5L, 3L, 1L, 4L, 0L, 1L, 4L, 3L,
  2L, 2L, 2L, 6L, 3L, 4L, 2L, 2L, 8L, 4L, 3L, 6L, 6L, 2L, 4L, 11L,
  3L, 4L, 4L, 5L, 5L, 1L, 5L, 2L, 7L, 3L, 2L, 4L, 2L, 3L, 6L, 3L,
  11L, 7L, 5L, 9L, 5L, 6L, 5L, 9L, 6L, 5L, 7L, 1L, 14L, 7L, 7L,
  7L, 2L, 5L, 5L, 9L, 2L, 9L, 2L, 6L, 2L, 9L, 4L, 3L, 4L, 9L, 7L,
  6L, 5L, 4L, 5L, 6L, 4L, 5L, 2L, 5L, 4L, 7L, 3L, 9L, 6L, 9L, 7L,
  2L, 7L, 6L, 7L, 3L, 4L, 8L, 3L, 8L, 10L, 3L, 3L, 5L, 4L, 8L,
  6L, 5L, 4L, 5L, 1L, 6L, 6L, 8L, 9L, 5L, 10L, 1L, 8L, 7L, 7L,
  6L, 5L, 1L, 5L, 8L, 11L, 2L, 6L, 7L, 6L, 5L, 20L, 8L, 10L, 7L,
  5L, 2L, 5L, 3L, 17L, 6L, 5L, 0L, 1L, 1L, 9L, 1L
)), row.names = c(
  NA,
  -1304L
), class = "data.frame")

df |>
  mutate(date = as.Date(date)) |>
  tsibble(index = date) |>
  fill_gaps() |>
  PACF(adm) |>
  autoplot()

Created on 2022-06-30 by the reprex package (v2.0.1)

A: This is closely related to this question: Set frequency in xts object. The frequency is used in pacf here.
In particular, in your case the frequency (time in days between observations) is really small:
> frequency(ts)
[1] 1.157407e-05

You have daily data, so if you set attr(ts, 'frequency') <- 1 before pacf call, it will work.
ts1 <- zoo(df$adm, df$date)
ts <- xts::as.xts(ts1)
attr(ts, 'frequency') <- 1

pacf(ts)

A: You could solve your problem as below.
ts1 <- zoo(df$adm, df$date)
ts <- as.xts(ts1)

pl = pacf(ts, xaxt="n")
axis(1, pl$lag, seq_along(pl$lag))


text:
Q: Remove a SIP address from user via exchange I'm trying to remove only the SIP address from a user account via my C# application. I can successfully remove it via the exchange management shell with the following command.
Set-Mailbox "identity" -EmailAddresses @{Remove="sip: firstname.lastname@domain.com"}

In my c# app I've got the following but I'm not sure how to get the "@{Remove="sip:firstname.lastname@domain.com"}" in there.
string termUserEmail = txtboxTermFirstName + "." + txtboxTermLastName + "@domain.com";

PSCommand command1 = new PSCommand();
command1.AddCommand("Set-Mailbox");
command1.AddParameter("Identity", termUserEmail);

var sipAddress = new Hashtable();

sipAddress.Add("remove", termUserEmail);
command1.AddParameter("EmailAddresses", sipAddress);

So, I'm not sure how to get this thing to execute the command correctly. I did look at C# - Remove Exchange Email Address via Powershell Runspace which gt me this far.

A: After much hair pulling I've got this thing going. I was mistaken in thinking that I needed the double quotes. When I was issuing the ps commands it was putting the quotes for me which I didn't know. So basically it was a simple fix.
//remove sip address
        string idTermEmail = "sip:" + txtTermFirstName.Text + "." + txtTermLastName.Text + "@domain.com";

        PSCommand command3 = new PSCommand();
        command3.AddCommand("Set-Mailbox");
        command3.AddParameter("Identity", username);

        var sipAddress = new Hashtable();

        sipAddress.Add("remove", idTermEmail);
        command3.AddParameter("EmailAddresses", sipAddress);

        powershell.Commands = command3;
        powershell.Invoke();

Wam bam thank you ma'am all done. I hope others get some use out of this ;)

redpajama_set_name: RedPajamaStackExchange


text:
Q: Debugging Laravel Mail::send() On my shared host, PHP mail function works fine, but I can't send email using Laravel Mail::send().
when config/mail.php driver field is set to smtp, Mail::send() returns false when the field is set to mail the method returns true but the email isn't sent.
How can I debug this?

A: I don't know why, but when requests start with WWW, the Laravel Mail::send() works but with requests without WWW it fails so I just forced WWW using .htacess 301 redirects.


text:
Q: Cómo hago para que una etiqueta H1 no bloquee un evento de un DIV posicionado justo debajo Actualmente tengo un div con una imagen que cuando haces hover, ésta se cambia por otra imagen. Después, por otra parte, tengo una etiqueta h1 posicionada justo encima de la imagen y al pasar por encima de esta me bloquea el evento hover del div que contiene la imagen.
¿Existe alguna forma de solucionar esto?

A:
Después, por otra parte, tengo una etiqueta h1 posicionada justo encima de la imagen y al pasar por encima de esta me bloquea el evento hover del
 que contiene la imagen.

No es necesario utilizar jQuery ni javascript, esto puede hacerse por CSS directamente.
Utilizando pointer-events: none; en el
.
De esta forma, el
 se vuelve "transparente" a los eventos del ratón, como si no estuviera.
Ejemplo.

h1 {
  position: absolute;
  top: 0;
  /* esto lo hace transparente */
  pointer-events: none;
}

img:hover {
   border: 4px solid red;
}

Hola SOes

Si quieres hacerlo con javascript o jQuery, es lo mismo, pero activado por código, aunque en tu caso, si el efecto debe ser permanente, la mejor solución es ponerlo via CSS y listo. Por las dudas te dejo unos ejemplos:
Via Javascript:
document.getElementById('idDelH1').style.pointerEvents = 'none';

Via jQuery:
$('#idDelH1').css('pointer-events', 'none');


text:
Q: Switch d3 donut arc on selection I have more than one donut in my page, each donut will have a thinner portion (like unfilled) and another arc colored.
When user clicks on the colored arc, it should have a white border. And if user selects other arc (unfilled) the unfilled area get filled with color, changes the width like the other one and will have border, same time the filled one gets unfilled. To summarize the arc colored portion should get switched on selection.
Can I achieve this by applying class/styles? In one page there should be only one arc selected at a time, all other selections will be cleared.
// data
var dataset = [{
  color: "#5FC5EA",
  value: 70
}, {
  color: "transparent",
  value: 30
}];

// size
var width = 460,
  z
height = 300,
  radius = Math.min(width, height) / 2;

var pie = d3.layout.pie()
  .sort(null).value(function(d) {
    return d.value;
  });

// thin arc
var arc1 = d3.svg.arc()
  .innerRadius(radius - 20)
  .outerRadius(radius - 11);

// main arc
var arc = d3.svg.arc()
  .innerRadius(radius - 30)
  .outerRadius(radius);

// set svg
var svg = d3.select("#d3-setup-donut").append("svg")
  .attr("class", 'donut-chart')
  .attr("width", width)
  .attr("height", height)
  .append("g")
  .attr("transform", "translate(" + width / 2 + "," + height / 2 + ")")
  .on('mouseout', function() {
    d3.selectAll('.donut-tooltip').style('display', 'none');
  });

// tooltip
var div = d3.select("body")
  .append("div")
  .attr("class", "donut-tooltip");

// draw thinner arc
var path = svg.selectAll(".background")
  .data(pie([{
    color: "#222427",
    value: 1
  }]))
  .enter().append("path")
  .attr("class", "background")
  .attr("fill", function(d, i) {
    return d.data.color;
  })
  .attr("d", arc1)
  .on('click', function(d, i) {
    //
  })
  .on("mousemove", function(d, i) {
    var mouseVal = d3.mouse(this);
    div.style("display", "none");
    div.html(d.data.label + " : " + d.value)
      .style("left", (d3.event.pageX - 40) + "px")
      .style("top", (d3.event.pageY - 35) + "px")
      .style("opacity", 1)
      .style("display", "block");
  })
  .on("mouseout", function() {
    div.html(" ").style("display", "none");
  });

// draw main arc
var path = svg.selectAll(".foreground")
  .data(pie(dataset))
  .enter().append("path")
  .attr("class", "foreground")
  .attr("fill", function(d, i) {
    return d.data.color;
  })
  .attr("d", arc)
  .on('click', function(d, i) {
    d3.select(this)
      .classed('selected', true);
  })
  .on("mousemove", function(d, i) {
    var mouseVal = d3.mouse(this);
    div.style("display", "none");
    div.html(d.data.label + " : " + d.value)
      .style("left", (d3.event.pageX - 40) + "px")
      .style("top", (d3.event.pageY - 55) + "px")
      .style("opacity", 1)
      .style("display", "block");
  })
  .on("mouseout", function() {
    div.html(" ").style("display", "none");
  });

// draw inner text
svg.append("text")
  .text('60%')
  .attr("class", "donut-inner-val")
  //.attr("x", radius/12 - 30)
  //.attr("y", radius/12 - 10);

svg.append("text")
  .text('in progress')
  .attr("class", "donut-inner-text")
  .attr("x", (radius / 12) - 35)
  .attr("y", (radius / 12) + 10);

JSFiddle

A: Try this Code
  .on('click', function(d, i) {
        d3.selectAll(".foreground").classed('selected', false);
    if(d3.select(this).classed("active")){
        d3.select(this)
      .classed('selected', true);
    }else{
    d3.selectAll(".foreground").classed("active", false);
    d3.select(this).classed("active",true);

            d3.select(this)
      .classed('selected', true);
    }
  })

DEMO


text:
Q: I can't connect to AWS RDS from Terminal with MAC OS X Catalina I've been taking a course from Udemy on AWS and I am trying to connect to RDS using an instance. I've installed MySQL and am running MySQL Workbench. I'm trying to access my instance using terminal commands in Mac OS X Catalina. I'm using the command:
mysql> \connect admin@backspace-intro2-aws.c7doukhhpptr.us-east-1.rds.amazonaws.com;

Is this the correct command?
I get the error:
No connection. Trying to reconnect...
ERROR 1059 (42000): Identifier name ' admin@backspace-intro2-aws.c7doukhhpptr.us-east-1.rds.amazonaws.com' is too long
ERROR: Can't connect to the server

I've tried adjusting the security permissions and changed the TCP/IP but still no luck.

A: I spent a while trying to figure this out, but with the help of another computer savvy friend, you-tube videos, and a lot of trial and error I learned that I could access my RDS on AWS with the following command in terminal from zsh shell:
/usr/local/mysql/bin/mysql -u admin -p -h (*insert db endpoint here*);

It was not a question of whether the string was more than 64 characters.


text:
Q: Magento 2 cookies not working when all cache is enabled In an observer I'm setting a cookie like this:
$objectManager = \Magento\Framework\App\ObjectManager::getInstance();
$cookieManager = $objectManager->get('Magento\Framework\Stdlib\CookieManagerInterface');

$cookieManager->setPublicCookie('myvar', $myVar);

Everything is working when Full page caching is disabled. However, once I enable it, the cookie won't be set.
How can I fix this?

A: OK. I asked the question on the official GitHub. It is quite normal if you are (like me) trying to access a cookie in a Block.
I found this topic and especially this one and hope this will help.

A: I managed to set the cookie the same way magento sets it for store by using plugins.
See file for plugin definition: vendor/magento/module-store/etc/di.xml:265
<type name="Magento\Framework\App\FrontController">
    <plugin name="storeCookieValidate" type="Magento\Store\Model\Plugin\StoreCookie" sortOrder="10"/>
</type>

And here you have the actual cookie set on beforeDispatch() vendor/magento/module-store/Model/Plugin/StoreCookie.php:69


text:
Q: Why git fetch doesn't download anything? I'm trying to download my project which is uploaded on bitbucket on my local directory. As far as I know about git fetch, it should download the project (but not merge it).
Well I have a connection to my repository as well, an here is what I've done:

And this is the result of git fetch: (as you see it in the image above)
$ git fetch
remote: Counting objects: 114, done.
remote: Compressing objects: 100% (104/104), done.
remote: Total 114 (delta 6), reused 114 (delta 6)
Receiving objects: 100% (114/114), 10.32 MiB | 2.03 MiB/s, done.
Resolving deltas: 100% (6/6), done.
From https://bitbucket.org/lamtakam/lamtakam
 * [new branch]      master     -> origin/master

But nothing downloaded ..! Why? As you see, my local directory is empty (except .git folder). What's wrong?

A: git fetch simply update(s) your .git folder with the packed data.
It does not update your working directory only the internal .git folder.
Once all the data downloaded you can checkout any branch you want to work on.
git fetch

The git fetch command imports commits from a remote repository into your local repo (no to be confused with the local working directory).
The resulting commits are stored as remote branches instead of the
   normal local branches that we've been working with. This gives you a
   chance to review changes before integrating them into your copy of the
   project.

To see the list of available branches use the -a flag
# display all available branches
git branch -a

In order to work on specific branch simply check out the desired branch


text:
Q: Is there some way to check the key inside mysql returned array? i need some help with data extration from an array. I have an array $prices that is structured like (returned from mysql):
Array
(
    [0] => Array
        (
            [pricegroup] => doppia
            [date] => 2014-09-01
            [price] => 60
            [id] => 974
        )

    [1] => Array
        (
            [pricegroup] => doppia
            [date] => 2014-09-02
            [price] => 60
            [id] => 975
        ),
    ...
)

So i need to get the price out of that array given an date, currently i doing a loop but i think it's slow..and i dont like loops becouse i must do the same loop for about 30 times per request (for check every day price) D:
    <?

    $prices = json_decode('[{"pricegroup":"doppia","date":"2014-09-01","price":"60","id":"974"},{"pricegroup":"doppia","date":"2014-09-02","price":"60","id":"975"},{"pricegroup":"doppia","date":"2014-09-03","price":"60","id":"976"},{"pricegroup":"doppia","date":"2014-09-04","price":"70","id":"977"},{"pricegroup":"doppia","date":"2014-09-05","price":"60","id":"978"},{"pricegroup":"doppia","date":"2014-09-06","price":"60","id":"979"},{"pricegroup":"doppia","date":"2014-09-07","price":"60","id":"980"},{"pricegroup":"doppia","date":"2014-09-08","price":"60","id":"981"},{"pricegroup":"doppia","date":"2014-09-09","price":"60","id":"982"},{"pricegroup":"doppia","date":"2014-09-10","price":"60","id":"983"},{"pricegroup":"doppia","date":"2014-09-11","price":"60","id":"984"},{"pricegroup":"doppia","date":"2014-09-12","price":"60","id":"985"},{"pricegroup":"doppia","date":"2014-09-13","price":"60","id":"986"},{"pricegroup":"doppia","date":"2014-09-14","price":"60","id":"987"},{"pricegroup":"doppia","date":"2014-09-15","price":"60","id":"988"},{"pricegroup":"doppia","date":"2014-09-16","price":"60","id":"989"},{"pricegroup":"doppia","date":"2014-09-17","price":"60","id":"990"},{"pricegroup":"doppia","date":"2014-09-18","price":"60","id":"991"},{"pricegroup":"doppia","date":"2014-09-19","price":"60","id":"992"},{"pricegroup":"doppia","date":"2014-09-20","price":"60","id":"993"},{"pricegroup":"doppia","date":"2014-09-21","price":"60","id":"994"},{"pricegroup":"doppia","date":"2014-09-22","price":"60","id":"995"},{"pricegroup":"doppia","date":"2014-09-23","price":"60","id":"996"},{"pricegroup":"doppia","date":"2014-09-24","price":"60","id":"997"},{"pricegroup":"doppia","date":"2014-09-25","price":"60","id":"998"},{"pricegroup":"doppia","date":"2014-09-26","price":"60","id":"999"},{"pricegroup":"doppia","date":"2014-09-27","price":"60","id":"1000"},{"pricegroup":"doppia","date":"2014-09-28","price":"60","id":"1001"},{"pricegroup":"doppia","date":"2014-09-29","price":"60","id":"1002"},{"pricegroup":"doppia","date":"2014-09-30","price":"60","id":"1003"}]',true);

function getPriceOfDay($day,$from) {
  $res;  $loops = count($from)-1;

  for ($i = 0; $i <= $loops; $i++) {

    if($day === $from[$i][date]) {
      $res .= '
Found: '.$from[$i][date].' for '.$from[$i][price].'
';
    }
  }

  return $res;
}

echo getPriceOfDay('2014-09-01',$prices);
echo getPriceOfDay('2014-09-02',$prices);
echo getPriceOfDay('2014-09-03',$prices);
echo getPriceOfDay('2014-09-04',$prices);
echo getPriceOfDay('2014-09-05',$prices);
echo getPriceOfDay('2014-09-06',$prices);
echo getPriceOfDay('2014-09-07',$prices);
echo getPriceOfDay('2014-09-08',$prices);
echo getPriceOfDay('2014-09-09',$prices);
echo getPriceOfDay('2014-09-10',$prices);
echo getPriceOfDay('2014-09-11',$prices);
echo getPriceOfDay('2014-09-12',$prices);
echo getPriceOfDay('2014-09-13',$prices);
echo getPriceOfDay('2014-09-14',$prices);
echo getPriceOfDay('2014-09-15',$prices);
echo getPriceOfDay('2014-09-16',$prices);
echo getPriceOfDay('2014-09-17',$prices);
echo getPriceOfDay('2014-09-18',$prices);
echo getPriceOfDay('2014-09-19',$prices);
echo getPriceOfDay('2014-09-20',$prices);
echo getPriceOfDay('2014-09-21',$prices);
echo getPriceOfDay('2014-09-22',$prices);
echo getPriceOfDay('2014-09-23',$prices);
echo getPriceOfDay('2014-09-24',$prices);
echo getPriceOfDay('2014-09-25',$prices);
echo getPriceOfDay('2014-09-26',$prices);
echo getPriceOfDay('2014-09-27',$prices);
echo getPriceOfDay('2014-09-28',$prices);
echo getPriceOfDay('2014-09-29',$prices);
echo getPriceOfDay('2014-09-30',$prices);

echo '
';
print_r($prices);

A: You don't need to iterate like that on your array, add all the dates in one array and use in_array:
$my_dates = array("2014-09-08", "2014-09-09", ...);

function getPriceOfDay($my_dates, $values) {

  $res = "";
  foreach($values as $value) {
    if(in_array($value['date'], $my_dates)) {
      $res .= "
Found: " .$value['date'] . ' for '. $value['price'] . "
";
    }
  }

  return $res;
}
getPriceOfDay($my_dates, $prices);

At this point you will only need to pass the array once and all the results will be concatenated to $res.


text:
Q: Is angular momentum only in orbital or spin? While I am learning Quantum Mechanics with angular momentum and the two types of them:

*

*orbital angular momentum

*and internal angular momentum a.k.a. spin

*(and total angular momentum, but that is a combined version).
So,

Is there any other types of angular momentum that does not recorded in textbooks or common literature?

PS. I am just talking about angular momentum in general Physics

A: Not really. All angular momenta are either orbital, spin, or a linear combination of the two.
The worst you end up getting is wonky mixtures like these ones, where you mix the spin orbital angular momenta of different shells inside an atom in some weird order, or funky linear combinations of the two (and while we're at this, the photon spin has some tricky behaviour), but they all boil down to those two components.
More generally, there is a meaningful distinction between intrinsic angular momenta $\mathbf L_\mathrm{i}$, which do not change when you displace the origin, and extrinsic angular momenta $\mathbf L_\mathrm{e}$, which transform as
$$
\mathbf L_\mathrm e\mapsto \mathbf L_\mathrm e'=\mathbf L_e-\mathbf r_0\times\mathbf P
$$
when you displace the system as $\mathbf r\mapsto \mathbf r'=\mathbf r-\mathbf r_0$, and where $\mathbf P$ is the total angular momentum of the system. As regards your question, though, they are just descriptors that apply respectively to spin and orbital angular momenta.


text:
Q: Django URLconf error I am trying to build a website with Django. I am new to Django and have followed the Tango with Django tutorial.
I keep getting an URlconf error I do not understand.
I have a domain (www.example.com), an app (mainApp) and two views in mainApp (homePage, registration).
I want

*

*http://www.example.com to be matched with the homePage view

*http://www.example.com/registration/ to be matched with the registration view.

My urls.py file for the project is
from django.conf.urls import patterns, include, url
from django.contrib import admin

urlpatterns = patterns(
    '',
    url(r'^admin/', include(admin.site.urls)),
    url(r'^', include('mainApp.urls')),
)

The urls.py file for mainApp is
from django.conf.urls import patterns, url
from mainApp import views

urlpatterns = patterns(
    '',
    url(r'^$', views.homePage, name='homePage'),
    url(r'^registration/$', views.registration, name='registration'),
)

This configuration displays the homePage view correctly, but not the registration view. The error is:
Using the URLconf defined in myProject.urls, Django tried these URL
patterns, in this order:

    ^admin/
    ^$
    ^/

The current URL, registration/, didn't match any of these.

What causes the error?

A: It looks fine. If you're hosting it online you should restart the webapp, if hosting it locally then restart the local host. Without restarting it the changes don't register.


text:
Q: Rejections from search thread_pool Elasticsearch I have a elasticsearch cluster with 6 nodes. The heapsize is set as 50GB.(I know less than 32 is what is recommended but this was already set to 50Gb for some reason which I don't know). Now I am seeing a lot of rejections from search thread_pool.
[2020-10-26T12:50:32,730][DEBUG][o.e.a.s.TransportSearchAction] [IDC.node1.com] [indice_1][3], node[M4pYcHhzSTIj5NXA], [P], s[STARTED], a[id=IAQaCGTCTA-CkKGPw]: Failed to execute [SearchRequest{searchType=QUERY_THEN_FETCH, indices=[indice_1], indicesOptions=IndicesOptions[ignore_unavailable=false, allow_no_indices=true, expand_wildcards_open=true, expand_wildcards_closed=false, allow_aliases_to_multiple_indices=true, forbid_closed_indices=true, ignore_aliases=false, ignore_throttled=true], types=[_doc], routing='null', preference='null', requestCache=null, scroll=null, maxConcurrentShardRequests=0, batchedReduceSize=512, preFilterShardSize=128, allowPartialSearchResults=true, localClusterAlias=null, getOrCreateAbsoluteStartMillis=-1, ccsMinimizeRoundtrips=true, lastShard [true]
org.elasticsearch.transport.RemoteTransportException: [IDC.node1.com][node1:9300][indices:data/read/search[phase/query]]
Caused by: org.elasticsearch.common.util.concurrent.EsRejectedExecutionException: rejected execution of org.elasticsearch.common.util.concurrent.TimedRunnable@21060fcc on QueueResizingEsThreadPoolExecutor[name = IDC.node1.com/search, queue capacity = 1000, min queue capacity = 1000, max queue capacity = 1000, frame size = 2000, targeted response rate = 1s, task execution EWMA = 5.2s, adjustment amount = 50, org.elasticsearch.common.util.concurrent.QueueResizingEsThreadPoolExecutor@3c46a309[Running, pool size = 49, active threads = 49, queued tasks = 1063, completed tasks = 1693218669]]
        at org.elasticsearch.common.util.concurrent.EsAbortPolicy.rejectedExecution(EsAbortPolicy.java:48) ~[elasticsearch-7.4.2.jar:7.4.2]
        at java.util.concurrent.ThreadPoolExecutor.reject(ThreadPoolExecutor.java:825) ~[?:?]
        at java.util.concurrent.ThreadPoolExecutor.execute(ThreadPoolExecutor.java:1355) ~[?:?]
        at org.elasticsearch.common.util.concurrent.EsThreadPoolExecutor.execute(EsThreadPoolExecutor.java:84) ~[elasticsearch-7.4.2.jar:7.4.2]
        at org.elasticsearch.search.SearchService.lambda$rewriteShardRequest$8(SearchService.java:1043) ~[elasticsearch-7.4.2.jar:7.4.2]
        at org.elasticsearch.index.shard.IndexShard.awaitShardSearchActive(IndexShard.java:3247) ~[elasticsearch-7.4.2.jar:7.4.2]
        at org.elasticsearch.search.SearchService.lambda$rewriteShardRequest$9(SearchService.java:1043) ~[elasticsearch-7.4.2.jar:7.4.2]
        at org.elasticsearch.action.ActionListener$1.onResponse(ActionListener.java:62) ~[elasticsearch-7.4.2.jar:7.4.2]
        at org.elasticsearch.index.query.Rewriteable.rewriteAndFetch(Rewriteable.java:114) ~[elasticsearch-7.4.2.jar:7.4.2]
        at org.elasticsearch.index.query.Rewriteable.rewriteAndFetch(Rewriteable.java:87) ~[elasticsearch-7.4.2.jar:7.4.2]
        at org.elasticsearch.search.SearchService.rewriteShardRequest(SearchService.java:1048) ~[elasticsearch-7.4.2.jar:7.4.2]
        at org.elasticsearch.search.SearchService.executeQueryPhase(SearchService.java:340) ~[elasticsearch-7.4.2.jar:7.4.2]
        at org.elasticsearch.action.search.SearchTransportService.lambda$registerRequestHandler$6(SearchTransportService.java:335) ~[elasticsearch-7.4.2.jar:7.4.2]
        at org.elasticsearch.xpack.security.transport.SecurityServerTransportInterceptor$ProfileSecuredRequestHandler$1.doRun(SecurityServerTransportInterceptor.java:257) ~[?:?]
        at org.elasticsearch.common.util.concurrent.AbstractRunnable.run(AbstractRunnable.java:37) ~[elasticsearch-7.4.2.jar:7.4.2]
        at org.elasticsearch.xpack.security.transport.SecurityServerTransportInterceptor$ProfileSecuredRequestHandler.messageReceived(SecurityServerTransportInterceptor.java:315) ~[?:?]
        at org.elasticsearch.transport.RequestHandlerRegistry.processMessageReceived(RequestHandlerRegistry.java:63) ~[elasticsearch-7.4.2.jar:7.4.2]
        at org.elasticsearch.transport.InboundHandler$RequestHandler.doRun(InboundHandler.java:264) ~[elasticsearch-7.4.2.jar:7.4.2]
        at org.elasticsearch.common.util.concurrent.AbstractRunnable.run(AbstractRunnable.java:37) ~[elasticsearch-7.4.2.jar:7.4.2]
        at org.elasticsearch.common.util.concurrent.EsExecutors$DirectExecutorService.execute(EsExecutors.java:225) ~[elasticsearch-7.4.2.jar:7.4.2]
        at org.elasticsearch.transport.InboundHandler.handleRequest(InboundHandler.java:185) [elasticsearch-7.4.2.jar:7.4.2]
        at org.elasticsearch.transport.InboundHandler.messageReceived(InboundHandler.java:118) [elasticsearch-7.4.2.jar:7.4.2]
        at org.elasticsearch.transport.InboundHandler.inboundMessage(InboundHandler.java:102) [elasticsearch-7.4.2.jar:7.4.2]
        at org.elasticsearch.transport.TcpTransport.inboundMessage(TcpTransport.java:663) [elasticsearch-7.4.2.jar:7.4.2]
        at org.elasticsearch.transport.netty4.Netty4MessageChannelHandler.channelRead(Netty4MessageChannelHandler.java:62) [transport-netty4-client-7.4.2.jar:7.4.2]
        at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:374) [netty-transport-4.1.38.Final.jar:4.1.38.Final]
        at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:360) [netty-transport-4.1.38.Final.jar:4.1.38.Final]
        at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:352) [netty-transport-4.1.38.Final.jar:4.1.38.Final]
        at io.netty.handler.codec.ByteToMessageDecoder.fireChannelRead(ByteToMessageDecoder.java:328) [netty-codec-4.1.38.Final.jar:4.1.38.Final]
        at io.netty.handler.codec.ByteToMessageDecoder.channelRead(ByteToMessageDecoder.java:302) [netty-codec-4.1.38.Final.jar:4.1.38.Final]
        at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:374) [netty-transport-4.1.38.Final.jar:4.1.38.Final]
        at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:360) [netty-transport-4.1.38.Final.jar:4.1.38.Final]
        at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:352) [netty-transport-4.1.38.Final.jar:4.1.38.Final]
        at io.netty.handler.logging.LoggingHandler.channelRead(LoggingHandler.java:241) [netty-handler-4.1.38.Final.jar:4.1.38.Final]
        at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:374) [netty-transport-4.1.38.Final.jar:4.1.38.Final]
        at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:360) [netty-transport-4.1.38.Final.jar:4.1.38.Final]
        at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:352) [netty-transport-4.1.38.Final.jar:4.1.38.Final]
        at io.netty.channel.DefaultChannelPipeline$HeadContext.channelRead(DefaultChannelPipeline.java:1421) [netty-transport-4.1.38.Final.jar:4.1.38.Final]
        at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:374) [netty-transport-4.1.38.Final.jar:4.1.38.Final]
        at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:360) [netty-transport-4.1.38.Final.jar:4.1.38.Final]
        at io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:930) [netty-transport-4.1.38.Final.jar:4.1.38.Final]
        at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:163) [netty-transport-4.1.38.Final.jar:4.1.38.Final]
        at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:697) [netty-transport-4.1.38.Final.jar:4.1.38.Final]
        at io.netty.channel.nio.NioEventLoop.processSelectedKeysPlain(NioEventLoop.java:597) [netty-transport-4.1.38.Final.jar:4.1.38.Final]
        at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:551) [netty-transport-4.1.38.Final.jar:4.1.38.Final]
        at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:511) [netty-transport-4.1.38.Final.jar:4.1.38.Final]
        at io.netty.util.concurrent.SingleThreadEventExecutor$5.run(SingleThreadEventExecutor.java:918) [netty-common-4.1.38.Final.jar:4.1.38.Final]
        at io.netty.util.internal.ThreadExecutorMap$2.run(ThreadExecutorMap.java:74) [netty-common-4.1.38.Final.jar:4.1.38.Final]
        at java.lang.Thread.run(Thread.java:830) [?:?]

I can also "Pause Young (Allocation Failure)" happening constantly in gc log.
[2020-10-26T07:31:06.514+0000][61585][gc,start       ] GC(7139651) Pause Young (Allocation Failure)
[2020-10-26T07:31:06.514+0000][61585][gc,task        ] GC(7139651) Using 23 workers of 23 for evacuation
[2020-10-26T07:31:06.574+0000][61585][gc,age         ] GC(7139651) Desired survivor size 100302848 bytes, new threshold 6 (max threshold 6)
[2020-10-26T07:31:06.574+0000][61585][gc,age         ] GC(7139651) Age table with threshold 6 (max threshold 6)
[2020-10-26T07:31:06.574+0000][61585][gc,age         ] GC(7139651) - age   1:   40802096 bytes,   40802096 total
[2020-10-26T07:31:06.574+0000][61585][gc,age         ] GC(7139651) - age   2:   16714352 bytes,   57516448 total
[2020-10-26T07:31:06.574+0000][61585][gc,age         ] GC(7139651) - age   3:    8509976 bytes,   66026424 total
[2020-10-26T07:31:06.574+0000][61585][gc,age         ] GC(7139651) - age   4:    6906208 bytes,   72932632 total
[2020-10-26T07:31:06.574+0000][61585][gc,age         ] GC(7139651) - age   5:    4186344 bytes,   77118976 total
[2020-10-26T07:31:06.574+0000][61585][gc,age         ] GC(7139651) - age   6:    1960288 bytes,   79079264 total
[2020-10-26T07:31:06.574+0000][61585][gc,heap        ] GC(7139651) ParNew: 1631431K->102498K(1763584K)
[2020-10-26T07:31:06.574+0000][61585][gc,heap        ] GC(7139651) CMS: 35964431K->35966764K(50469312K)
[2020-10-26T07:31:06.574+0000][61585][gc,metaspace   ] GC(7139651) Metaspace: 112067K->112067K(118784K)
[2020-10-26T07:31:06.574+0000][61585][gc             ] GC(7139651) Pause Young (Allocation Failure) 36714M->35223M(51008M) 59.928ms
[2020-10-26T07:31:06.574+0000][61585][gc,cpu         ] GC(7139651) User=1.02s Sys=0.00s Real=0.06s
[2020-10-26T07:31:06.574+0000][61585][safepoint      ] Safepoint "GenCollectForAllocation", Time since last: 675463951 ns, Reaching safepoint: 1382982 ns, At safepoint: 60208788 ns, Total: 61591770 ns
[2020-10-26T07:31:07.575+0000][61585][safepoint      ] Safepoint "Cleanup", Time since last: 1000129984 ns, Reaching safepoint: 901989 ns, At safepoint: 39274 ns, Total: 941263 ns
[2020-10-26T07:31:08.529+0000][61585][gc,start       ] GC(7139652) Pause Young (Allocation Failure)
[2020-10-26T07:31:08.529+0000][61585][gc,task        ] GC(7139652) Using 23 workers of 23 for evacuation
[2020-10-26T07:31:08.584+0000][61585][gc,age         ] GC(7139652) Desired survivor size 100302848 bytes, new threshold 6 (max threshold 6)
[2020-10-26T07:31:08.584+0000][61585][gc,age         ] GC(7139652) Age table with threshold 6 (max threshold 6)
[2020-10-26T07:31:08.584+0000][61585][gc,age         ] GC(7139652) - age   1:   17722072 bytes,   17722072 total
[2020-10-26T07:31:08.585+0000][61585][gc,age         ] GC(7139652) - age   2:   15204416 bytes,   32926488 total
[2020-10-26T07:31:08.585+0000][61585][gc,age         ] GC(7139652) - age   3:   16712976 bytes,   49639464 total
[2020-10-26T07:31:08.585+0000][61585][gc,age         ] GC(7139652) - age   4:    8509664 bytes,   58149128 total
[2020-10-26T07:31:08.585+0000][61585][gc,age         ] GC(7139652) - age   5:    6501424 bytes,   64650552 total
[2020-10-26T07:31:08.585+0000][61585][gc,age         ] GC(7139652) - age   6:    3047280 bytes,   67697832 total
[2020-10-26T07:31:08.585+0000][61585][gc,heap        ] GC(7139652) ParNew: 1670178K->89020K(1763584K)
[2020-10-26T07:31:08.585+0000][61585][gc,heap        ] GC(7139652) CMS: 35966764K->35968680K(50469312K)
[2020-10-26T07:31:08.585+0000][61585][gc,metaspace   ] GC(7139652) Metaspace: 112067K->112067K(118784K)
[2020-10-26T07:31:08.585+0000][61585][gc             ] GC(7139652) Pause Young (Allocation Failure) 36754M->35212M(51008M) 56.177ms
[2020-10-26T07:31:08.585+0000][61585][gc,cpu         ] GC(7139652) User=0.87s Sys=0.00s Real=0.05s
[2020-10-26T07:31:08.585+0000][61585][safepoint      ] Safepoint "GenCollectForAllocation", Time since last: 948848143 ns, Reaching safepoint: 4487353 ns, At safepoint: 56505105 ns, Total: 60992458 ns
[2020-10-26T07:31:09.586+0000][61585][safepoint      ] Safepoint "Cleanup", Time since last: 1000188782 ns, Reaching safepoint: 807865 ns, At safepoint: 31141 ns, Total: 839006 ns
[2020-10-26T07:31:10.587+0000][61585][safepoint      ] Safepoint "Cleanup", Time since last: 1000218955 ns, Reaching safepoint: 947598 ns, At safepoint: 40468 ns, Total: 988066 ns
[2020-10-26T07:31:11.588+0000][61585][safepoint      ] Safepoint "Cleanup", Time since last: 1000252002 ns, Reaching safepoint: 688820 ns, At safepoint: 24744 ns, Total: 713564 ns
[2020-10-26T07:31:12.590+0000][61585][safepoint      ] Safepoint "Cleanup", Time since last: 1000168389 ns, Reaching safepoint: 978766 ns, At safepoint: 30805 ns, Total: 1009571 ns
[2020-10-26T07:31:13.497+0000][61585][gc,start       ] GC(7139653) Pause Young (Allocation Failure)
[2020-10-26T07:31:13.498+0000][61585][gc,task        ] GC(7139653) Using 23 workers of 23 for evacuation
[2020-10-26T07:31:13.560+0000][61585][gc,age         ] GC(7139653) Desired survivor size 100302848 bytes, new threshold 6 (max threshold 6)
[2020-10-26T07:31:13.560+0000][61585][gc,age         ] GC(7139653) Age table with threshold 6 (max threshold 6)
[2020-10-26T07:31:13.560+0000][61585][gc,age         ] GC(7139653) - age   1:   11416792 bytes,   11416792 total
[2020-10-26T07:31:13.560+0000][61585][gc,age         ] GC(7139653) - age   2:    4119704 bytes,   15536496 total
[2020-10-26T07:31:13.560+0000][61585][gc,age         ] GC(7139653) - age   3:   15256408 bytes,   30792904 total
[2020-10-26T07:31:13.560+0000][61585][gc,age         ] GC(7139653) - age   4:   17073416 bytes,   47866320 total
[2020-10-26T07:31:13.560+0000][61585][gc,age         ] GC(7139653) - age   5:    8509616 bytes,   56375936 total
[2020-10-26T07:31:13.560+0000][61585][gc,age         ] GC(7139653) - age   6:    5802544 bytes,   62178480 total
[2020-10-26T07:31:13.560+0000][61585][gc,heap        ] GC(7139653) ParNew: 1656700K->91797K(1763584K)
[2020-10-26T07:31:13.560+0000][61585][gc,heap        ] GC(7139653) CMS: 35968680K->35971272K(50469312K)
[2020-10-26T07:31:13.560+0000][61585][gc,metaspace   ] GC(7139653) Metaspace: 112067K->112067K(118784K)
[2020-10-26T07:31:13.561+0000][61585][gc             ] GC(7139653) Pause Young (Allocation Failure) 36743M->35217M(51008M) 63.001ms
[2020-10-26T07:31:13.561+0000][61585][gc,cpu         ] GC(7139653) User=0.99s Sys=0.00s Real=0.07s
[2020-10-26T07:31:13.561+0000][61585][safepoint      ] Safepoint "GenCollectForAllocation", Time since last: 906329704 ns, Reaching safepoint: 1247593 ns, At safepoint: 63668517 ns, Total: 64916110 ns

Should this happen this frequently?. Below is heap pool settings:
          "pools" : {
            "young" : {
              "used_in_bytes" : 731499608,
              "max_in_bytes" : 1605304320,
              "peak_used_in_bytes" : 1605304320,
              "peak_max_in_bytes" : 1605304320
            },
            "survivor" : {
              "used_in_bytes" : 187117000,
              "max_in_bytes" : 200605696,
              "peak_used_in_bytes" : 200605696,
              "peak_max_in_bytes" : 200605696
            },
            "old" : {
              "used_in_bytes" : 16461553480,
              "max_in_bytes" : 51680575488,
              "peak_used_in_bytes" : 50144794688,
              "peak_max_in_bytes" : 51680575488
            }

Are the rejections because of heapsize or cause the thread_pool being low. And why is "Pause Young" happening this rapidly?
Update
This update was asked as another question: Search thread_pool for particular nodes always at maximum

A: search thread_pool has an associated queue on which search worker threads work on and its default capacity is 1000(note its per node) which is consumed in your case, please refer thread_pools in ES for more info.
Now, queue capacity can be exhausted due to one of the below reasons:

*

*High search requests rate on your ES node, which your node might not be able to keep up with.

*Some slow queries which are taking a lot more time to process, and causing other requests to wait in the search queue, and ultimately leading to rejection.

*Your nodes and shards are not properly balanced in your cluster, this can cause few nodes to receive a high number of search queries.

You should look at the search slow-logs to filter the costly queries during the issue.
And if its legitimate increase in search traffic, you should scale your cluster to handle more search requests.
Regarding young heap logs, if it's not taking more time and under 50-70ms its not that bigger concern, and you should focus on fixing the search rejection issue which might solve or lower the heap issue and in any case you should have Max heap size lower than 32 GB for better performance.


text:
Q: Parsing paragraphs in applescript not working as expected Posting the code is losing the formatting that is causing the issue, copying what I in the post will actually do what it should. To bad that isn't an option in using the script, so I uploaded the script file here with an example of the text built in that is causing the issue. I will try to convey what the issue is still.
I am pulling text from mail.app. The emails I am parsing have within them a list of dates (amongst other things):
5/27/2012
5/28/2012
5/29/2012
5/30/2012
5/31/2012
6/1/2012
6/3/2012
6/4/2012
6/5/2012
6/6/2012
Now I'm trying to get the dates into a list. No problem I thought...
The following did NOT work:
Using paragraphs did NOT work, returned the entire thing as a paragraph
set AppleScript's text item delimiters to (ASCII character 13) -- (Carriage Return)

set AppleScript's text item delimiters to (ASCII character 10) -- (LF)

Neither of the delimiters worked. I wondered what exactly the ASCII code of the 'return' was so I made the following:
set rundates to "5/27/2012
   5/28/2012
   5/29/2012
   5/30/2012
   5/31/2012
   6/1/2012
   6/3/2012
   6/4/2012
   6/5/2012
   6/6/2012
   6/7/2012
   6/8/2012
   6/10/2012
   6/11/2012"
 set mylist to {}

 repeat with z from 1 to count of characters of rundates
        copy (ASCII number (character z of rundates)) to end of mylist
   end repeat

 --return mylist ---{53, 47, 50, 55, 47, 50, 48, 49, 50, 13, 53, 47, 50, 56, 47, 50, 48, 49, 50, 13, 53, 47, 50, 57, 47, 50, 48, 49, 50, 13, 53, 47, 51, 48, 47, 50, 48, 49, 50, 13, 53, 47, 51, 49, 47, 50, 48, 49, 50, 13, 54, 47, 49, 47, 50, 48, 49, 50, 13, 54, 47, 51, 47, 50, 48, 49, 50, 13, 54, 47, 52, 47, 50, 48, 49, 50, 13, 54, 47, 53, 47, 50, 48, 49, 50, 13, 54, 47, 54, 47, 50, 48, 49, 50, 13, 54, 47, 55, 47, 50, 48, 49, 50, 13, 54, 47, 56, 47, 50, 48, 49, 50, 13, 54, 47, 49, 48, 47, 50, 48, 49, 50, 13, 54, 47, 49, 49, 47, 50, 48, 49, 50}

---===== Notice the 13s? So this should work right? ====---
So my delimiter using 13 should have worked, but it doesn't.
Anyone have any ideas?

A: I get different results from your post of the ascii numbers. Actually now that applescript is unicode we use "id" now instead of ascii number. It seems your character is "8232". So use this in your code before you get the text items...
set AppleScript's text item delimiters to character id 8232


text:
Q: How to match elements from multiple columns from df1 with values from an array1 in R? I would like to match elements from V1 and V2 of df1 with values from an array1.
df1 <- data.frame(V1 = c('A','S','E','E','V','G','H','P','K','L','W','N','P','A','A','S','E','N','M','Y','S','G','D','R','H'),
V2 = c('E','D','S','N','A','K','K','R','P','L','W','D','A','C','A','P','E','Y','W','Y','D','D','R','E','M'))

array1

     1    2    3    4    5    6    7    8    9   10   11  12   13  14   15   16   17   18   19   20   21   22   23   24   25
A 0.15 0.00 0.10 0.10 0.05 0.00 0.05 0.00 0.00 0.05 0.00 0.0 0.00 0.0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.05 0.00 0.00 0.00
C 0.00 0.00 0.00 0.00 0.00 0.05 0.00 0.00 0.00 0.00 0.00 0.0 0.00 0.0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
D 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.05 0.05 0.00 0.0 0.10 0.0 0.00 0.25 0.10 0.20 0.10 0.00 0.15 0.05 0.00 0.00 0.05
E 0.05 0.10 0.05 0.05 0.00 0.05 0.00 0.10 0.10 0.20 0.00 0.0 0.05 0.0 0.00 0.00 0.05 0.10 0.00 0.20 0.10 0.05 0.15 0.10 0.10
F 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.05 0.00 0.00 0.05 0.0 0.05 0.0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
G 0.00 0.00 0.10 0.00 0.05 0.00 0.00 0.00 0.05 0.00 0.00 0.0 0.00 0.0 0.00 0.00 0.00 0.00 0.05 0.00 0.00 0.05 0.00 0.00 0.00
H 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0 0.00 0.0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
I 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.05 0.2 0.05 0.1 0.05 0.05 0.00 0.00 0.00 0.00 0.05 0.00 0.00 0.00 0.00
K 0.00 0.10 0.00 0.05 0.00 0.05 0.05 0.05 0.00 0.00 0.00 0.0 0.00 0.0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.05
L 0.00 0.00 0.05 0.05 0.05 0.05 0.10 0.00 0.10 0.00 0.00 0.0 0.00 0.2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.05 0.00
M 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0 0.00 0.0 0.00 0.00 0.05 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
N 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0 0.00 0.0 0.00 0.00 0.00 0.05 0.05 0.00 0.00 0.00 0.00 0.05 0.00
P 0.00 0.00 0.00 0.05 0.05 0.00 0.10 0.10 0.00 0.00 0.00 0.0 0.00 0.0 0.00 0.00 0.00 0.00 0.00 0.05 0.00 0.10 0.00 0.05 0.00
Q 0.00 0.05 0.05 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.05 0.0 0.00 0.1 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.05
R 0.00 0.00 0.05 0.00 0.05 0.15 0.00 0.00 0.00 0.05 0.00 0.0 0.00 0.0 0.00 0.00 0.00 0.00 0.05 0.00 0.00 0.00 0.00 0.00 0.00
S 0.10 0.10 0.00 0.00 0.05 0.00 0.00 0.00 0.00 0.00 0.05 0.0 0.00 0.0 0.15 0.10 0.20 0.05 0.10 0.10 0.05 0.00 0.05 0.05 0.10
T 0.00 0.00 0.00 0.05 0.00 0.05 0.00 0.05 0.05 0.00 0.00 0.0 0.00 0.0 0.05 0.00 0.00 0.00 0.00 0.00 0.00 0.05 0.05 0.05 0.00
V 0.05 0.05 0.00 0.05 0.00 0.00 0.00 0.05 0.05 0.00 0.10 0.2 0.15 0.0 0.15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
W 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0 0.00 0.0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Y 0.05 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.05 0.10 0.0 0.00 0.0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

The expected outcome can be a list or a df:
V1   0.15, 0.10, 0.05, 0.05, 0.00, 0.00, 0.00, 0.10, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.10, 0.05, 0.05, 0.00, 0.00, 0.05, 0.05, 0.00, 0.00, 0.00
V2 ...

That works perfectly, when I have just 'V1' to match:
array1[cbind(match(df1, rownames(array1)), 1:ncol(array1))]

A: Use sapply/lapply to match every column in the dataframe.
sapply(df1, function(x) array1[cbind(match(x, rownames(array1)), 1:ncol(array1))])


text:
Q: Android: What is the difference between "support" and "appcompat" I have come upon these lines in the build.gradle file:
compile 'com.android.support:support-v13...'
compile 'com.android.support:appcompat-v7...'

Until now I thought that for supporting older versions of android you use the AppCompat libs.
So what exactly is the difference between "support" and "appcompat"?

A: v4 Support Library
This library is designed to be used with Android 1.6 (API level 4) and higher. It includes the largest set of APIs compared to the other libraries, including support for application components, user interface features, accessibility, data handling, network connectivity, and programming utilities.
v7 Libraries
There are several libraries designed to be used with Android 2.1 (API level 7) and higher. These libraries provide specific feature sets and can be included in your application independently from each other.
v7 appcompat library
This library adds support for the Action Bar user interface design pattern.


text:
Q: Resizing an image has distorted it unrecognisable I run the following code to change the color and size of a cat image. However, the resized image distorted to something unrecognisable, like a piece of carpet. Could anyone please tell me what went wrong? Thanks!
import imageio

img = imageio.imread('D:/cat.jpg')
img_tinted = img * [1, 0.95, 0.9]
img_tinted = np.resize(img_tinted, (300, 300, 3))
img_tinted = img_tinted.astype(np.uint8)
imageio.imwrite('D:/cat_tinted.jpg', img_tinted)


text:
Q: Cannot boot xv6 after adding some codes to the kernel I only made a little bit changes to the xv6 kernel to support shared memory. After compiling, I cannot boot it under qemu. It just halts at "booting from the disk...". But I didn't do anything to the bootloader. Can somebody tell me what's wrong,please?
xv6 cannot boot

A: You should be more specific with what changes were made exactly.
Please include them here.


text:
Q: Which weapons can stand against a Lightsaber? We know as a fact that a lightsaber can be stopped during a fight by another lightsaber. Also I remember two more Imperial weapons that were able to stop a lightsaber:

*

*the Z6 riot control baton

*a weapon I saw being used by the robot protectors of General Grievous. I think it's the same weapon that Rey is using in The Force Awakens.

Do we know of any other similar weapons that can fight against a lightsaber?

A: Any weapon crafted using a Cortosis-weave could withstand a lightsaber wielding opponent.
There are references in Knights of the Old Republic game to the cortosis-weave technique in the making of weapons. I don't believe there is any specific movie canon reference to anti-lightsaber technology

A: In addition to @Rogue Jedi's fantastic answer, the race of Sith also produced weapons capable of deflecting lightsabers.
Sith Sword

A: Canon:

*

*Other lightsabers

*Z6 riot control batons

*Electrostaffs

*The darksaber
Legends:

*

*Any weapon made from Cortosis

*Lightsabers and the various lightsaber variants

*Any weapon made from Phrik, including Electrostaffs

*Any weapon made from Songsteel

*Any weapon made from Mandalorian Iron

*Force Weapons

*Amphistaffs

A: I'm going to list specific weapons by their effectiveness against a lightsaber in combat:
The Laser Scalpel. It most likely utilizes similar plasma tech to that of a lightsaber, but you'd be screwed fighting with one in most cases.
The Laser Knife. It's basically a lightsaber in the shape of a small knife. Unlike the laser scalpel, most people used it in combat, and it behaved quite like a lightsaber would.
Stun batons/electro-batons: Most stun batons probably wouldn't be able to penetrate the armor of a storm trooper, but some can do some real damage/block lightsabers.
Neuronic whips. Torture devices in the form of electric whips. Unpredictable, but it might work against an unskilled lightsaber wielder.
The Blastsword. It's a blaster you have to hit someone with, but I doubt you could actually properly defend yourself against a Jedi with.
Electroswords. This one really depends on what they're made of. Some can actually block lightsabers, but others cannot.
Power lances. I doubt these could really block a lightsaber, but they're so ridiculously huge that if you were to charge at a lightsaber wielder with one on a speederbike, it could pose a serious challenge for them.
Energy lances. These can shoot out energy beams so I think that might distract a lightsaber-wielding foe long enough for a good blow.
Felucian Skullblades. These can actually consistently defend against a lightsaber, so its probably a good idea to have this one as your first pick above the ones listed previously.
Electrowhips/shock whips. These things are really only used for torture, but they can consistently block lightsaber attacks. The downside is that using these weapons is quite hard, and they can also be unpredictable. But that might work to your advantage against a lightsaber-wielder.
Electrostaffs. Walmart grade lightsabers, but they can definitely block lightsabers and make life difficult for whoever is faced against them. So long as they're made of Phrik, that is.
Force pikes. A better version of the energy and power lances; these things can consistently block lightsabers and are very effective against them.
Praetorian guard weapons: Unless you're in a Star Wars sequel trilogy movie, you actually have a decent chance of defeating a lightsaber with one.
Force imbued blades/any Sith or Jedi artifact: Some of these are arguably BETTER than a lightsaber!
Lightfoils: Lightsabers for non-force wielders. Enough said.
Amphistaff: Living creatures that eat lightsabers for lunch.


text:
Q: get item detail through ebay api I am aim to get item detail (name, category, even price) through ebay api, JSON format.
Here is a sample item searched by ebay, EAN barcode 0705632085943:
https://www.ebay.co.uk/sch/i.html?_osacat=0&_odkw=0705632085943&_from=R40&_trksid=m570.l1313&_nkw=0705632085943&_sacat=0
I had read this page released by ebay: getProductDetails :
https://developer.ebay.com/devzone/product/CallRef/getProductDetails.html
So in my project, I used:
http://svcs.ebay.com/services/search/FindingService/v1?OPERATION-NAME=getProductDetails&SERVICE-VERSION=1.0.0&SECURITY-APPNAME=My-App-Name&RESPONSE-DATA-FORMAT=JSON&productDetailsRequest.productIdentifier.EAN = 5053826000186

But, back with:
{"errorMessage":[{"error":[{"errorId":["2000"],"domain":["CoreRuntime"],"severity":["Error"],"category":["Request"],"message":["Service operation getProductDetails is unknown"],"subdomain":["Inbound_Meta_Data"],"parameter":[{"@name":"Param1","__value__":"getProductDetails"}]}]}]}

I known little about web-language and started with Swift. Does there has any feasible advice in dealing with this?

A: This should work if you are using a valid EAN code from eBay
http://svcs.ebay.com/services/search/FindingService/v1?OPERATION-NAME=findItemsByProduct&SERVICE-VERSION=1.0.0&SECURITY-APPNAME=YOUR_APP_ID&RESPONSE-DATA-FORMAT=JSON&REST-PAYLOAD&paginationInput.entriesPerPage=2&productId.@type=EAN&productId=5053826000186
From the Doc:
The EAN value for books (most commonly used in European countries). If you know a book's EAN, you can use this instead of the eBay Reference ID to search for that book.
http://svcs.ebay.com/services/search/FindingService/v1?OPERATION-NAME=findItemsByProduct&SERVICE-VERSION=1.0.0&SECURITY-APPNAME=YOUR_APP_ID&RESPONSE-DATA-FORMAT=JSON&REST-PAYLOAD&paginationInput.entriesPerPage=2&productId.@type=ReferenceID&productId=53039031

A: you'd have to use method findItemsByProduct which needs a Request.productId (the EAN barcode).


text:
Q: Question on tangent circles Prove that two circles C1 and C2 (rays are R1 and R2 respectively, centers O1 and O2 respectively, and R1>R2) are tangent to each other (interior tangent, so C2 inside C1) if and only if O1O2=R1-R2 .
I was able to prove this analytically, using the equation of the circle, but I want to know a sinthetic proof, easy to understand. Thank you!

A: Let $P$ be point of tangency. Now, $O_1$ , $P$ and $O_2$ are collinear (as $O_1 P$ and $O_2P$ are perpendicular to same line, the tangent at $P$). Also, $O_2$ is between $O_1$ and $P$, because $C_2$ is smaller circle. Therefore, $$O_1O_2=O_1P-O_2P=R_1-R_2$$
Conversely, if the distance between centres is this, then the farthest point on $C_2$ from $O_1$ is $O_1O_2+R_2=R_1$ away. Hence, this point is point of tangency.
Hope it helps:)


text:
Q: Refused to display youtube video in iframe When I open up #myModal the modal appears and my video is playable, though, when I click on my #myModal2 the modal appears but the video is not shown...
What am I missing?

         Webbhistoria

     ABC

                    <button type="button" class="close" data-dismiss="modal">
                         ×</button>

Instruktionsvideo om...

Bla bla bla

                    <button type="button" class="btn btn-default"
                        data-dismiss="modal">Close</button>

             ABC

                    <button type="button" class="close"
                        data-dismiss="modal">×</button>

Instruktionsvideo om...

                    <button type="button" class="btn btn-default"
                        data-dismiss="modal">Close</button>

A: Change:
src="https://www.youtube.com/watch?v=IsXEVQRaTX8"

To:
src="https://www.youtube.com/embed/IsXEVQRaTX8"

The request is refused for security reasons:

Refused to display 'https://www.youtube.com/watch?v=IsXEVQRaTX8' in a frame because it set 'X-Frame-Options' to 'SAMEORIGIN'.

Use YouTube's Embed URL


text:
Q: Representative as in for contracts I am filling a form for staying on-campus on my university.
I am trying to figure out what the word representative means in this context.
Referring to item 4.
http://www.rta.qld.gov.au/zone_files/rooming_accommodation/r18.pdf
Dictionary:
"Representative - a person or thing that represents another or others."
What can I actually fill in here? I actually wrote myself, because no one is representing me.
Did I get the wrong idea?

A: Presumably you refer to representative in item 4.1, "Resident's Representative for Notices (see clause 29)".  In clause 29, on page 6, we find:

(9) In this clause –
  representative means a person acting for the resident under
  section 525(1)(c).

If you have a permanent address where "notices" -- whatever they might be -- should be sent, then you can designate a person at that address as an agent to receive notices at that address, on your behalf.
Comment-- Given all the legalistic language the document is stuffed with, you probably should telephone or email the university's housing department and discuss the form with them.

A: Unless there is someone else who can receive notices for you, you are your own representative.