I'm getting error Error in xy.coords(x, y) : 'x' and 'y' lengths differ
when plotting xts object RETURNS. The plotting function used is charts.PerformanceSummary, from the package PerformanceAnalytics.
Would anyone know how to fix this? It plots regardless of the error, but the presence of an error makes conversion to HTML with knitr package fail. Interestingly running the same plotting function on a similar xts object works fine. I'm baffled.
library(PerformanceAnalytics)
# THIS PROVIDES THE ERROR:
RETURNS <- structure(c(NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.0176761850129417, -0.00459544547441126, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), class = c("xts", "zoo"), index = structure(c(1388448000, 1403474400, 1403475300, 1403476200, 1403477100, 1403478000, 1403478900, 1403479800, 1403480700, 1403481600, 1403482500, 1403483400, 1403484300, 1403485200, 1403486100, 1403487000, 1403487900, 1403488800, 1403489700, 1403490600, 1403491500, 1403492400, 1403493300, 1403494200, 1403495100, 1403496000, 1403496900, 1403497800, 1403498700, 1403499600, 1403500500, 1403501400, 1403502300, 1403503200, 1403504100, 1403505000, 1403505900, 1403506800, 1403507700, 1403508600, 1403509500, 1403510400, 1403511300, 1403512200, 1403513100, 1403514000, 1403514900, 1403515800, 1403516700, 1403517600, 1403518500, 1403519400, 1403520300, 1403521200, 1403522100, 1403523000, 1403523900, 1403524800, 1403525700, 1403526600, 1403527500,
1403528400, 1403529300, 1403530200, 1403531100, 1403532000, 1403532900, 1403533800, 1403534700, 1403535600, 1403536500, 1403537400, 1403538300, 1403539200, 1403540100, 1403541000, 1403541900, 1403542800, 1403543700, 1403544600, 1403545500, 1403546400, 1403547300, 1403548200, 1403549100, 1403550000, 1403550900, 1403551800, 1403552700, 1403553600, 1403554500, 1403555400, 1403556300, 1403557200, 1403560800, 1403561700, 1403562600, 1403563500, 1403564400, 1403565300, 1403566200, 1403567100, 1403568000, 1403568900, 1403569800, 1403570700, 1403571600, 1403572500, 1403573400, 1403574300, 1403575200, 1403576100, 1403577000, 1403577900, 1403578800, 1403579700, 1403580600, 1403581500, 1403582400, 1403583300, 1403584200, 1403585100, 1403586000, 1403586900, 1403587800, 1403588700, 1403589600, 1403590500, 1403591400, 1403592300, 1403593200, 1403594100, 1403595000, 1403595900, 1403596800, 1403597700, 1403598600, 1403599500, 1403600400, 1403601300, 1403602200, 1403603100, 1403604000, 1403604900, 1403605800, 1403606700, 1403607600, 1403608500, 1403609400, 1403610300, 1403611200, 1403612100, 1403613000, 1403613900, 1403614800, 1403615700, 1403616600, 1403617500, 1403618400, 1403619300, 1403620200, 1403621100, 1403622000, 1403622900, 1403623800, 1403624700, 1403625600, 1403626500, 1403627400, 1403628300, 1403629200, 1403630100, 1403631000, 1403631900, 1403632800, 1403633700, 1403634600, 1403635500, 1403636400, 1403637300, 1403638200, 1403639100, 1403640000, 1403640900, 1403641800, 1403642700, 1403643600, 1403647200, 1403648100, 1403649000, 1403649900, 1403650800, 1403651700, 1403652600, 1403653500, 1403654400, 1403655300, 1403656200, 1403657100, 1403658000, 1403658900, 1403659800, 1403660700, 1403661600, 1403662500, 1403663400, 1403664300, 1403665200, 1403666100, 1403667000, 1403667900, 1403668800, 1403669700, 1403670600, 1403671500, 1403672400, 1403673300, 1403674200, 1403675100, 1403676000, 1403676900, 1403677800, 1403678700, 1403679600, 1403680500, 1403681400, 1403682300, 1403683200, 1403684100, 1403685000, 1403685900, 1403686800, 1403687700, 1403688600, 1403689500, 1403690400, 1403691300, 1403692200, 1403693100, 1403694000, 1403694900, 1403695800, 1403696700, 1403697600, 1403698500, 1403699400, 1403700300, 1403701200, 1403702100, 1403703000, 1403703900, 1403704800, 1403705700, 1403706600, 1403707500, 1403708400, 1403709300, 1403710200, 1403711100, 1403712000, 1403712900, 1403713800, 1403714700, 1403715600, 1403716500, 1403717400, 1403718300, 1403719200, 1403720100, 1403721000, 1403721900, 1403722800, 1403723700, 1403724600, 1403725500, 1403726400, 1403727300, 1403728200, 1403729100, 1403730000, 1403733600, 1403734500, 1403735400, 1403736300, 1403737200, 1403738100, 1403739000, 1403739900, 1403740800, 1403741700, 1403742600, 1403743500, 1403744400, 1403745300, 1403746200, 1403747100, 1403748000, 1403748900, 1403749800, 1403750700, 1403751600, 1403752500, 1403753400, 1403754300, 1403755200, 1403756100, 1403757000, 1403757900, 1403758800, 1403759700, 1403760600, 1403761500, 1403762400, 1403763300, 1403764200, 1403765100, 1403766000, 1403766900, 1403767800, 1403768700, 1403769600, 1403770500, 1403771400, 1403772300, 1403773200, 1403774100, 1403775000, 1403775900, 1403776800, 1403777700, 1403778600, 1403779500, 1403780400, 1403781300, 1403782200, 1403783100, 1403784000,
1403784900, 1403785800, 1403786700, 1403787600, 1403788500, 1403789400, 1403790300, 1403791200, 1403792100, 1403793000, 1403793900, 1403794800, 1403795700, 1403796600, 1403797500, 1403798400, 1403799300, 1403800200, 1403801100, 1403802000, 1403802900, 1403803800, 1403804700, 1403805600, 1403806500, 1403807400, 1403808300, 1403809200, 1403810100, 1403811000, 1403811900, 1403812800, 1403813700, 1403814600, 1403815500, 1403816400, 1403820000, 1403820900, 1403821800, 1403822700, 1403823600, 1403824500, 1403825400, 1403826300, 1403827200, 1403828100, 1403829000, 1403829900, 1403830800, 1403831700, 1403832600, 1403833500, 1403834400, 1403835300, 1403836200, 1403837100, 1403838000, 1403838900, 1403839800, 1403840700, 1403841600, 1403842500, 1403843400, 1403844300, 1403845200, 1403846100, 1403847000, 1403847900, 1403848800, 1403849700, 1403850600, 1403851500, 1403852400, 1403853300, 1403854200, 1403855100, 1403856000, 1403856900, 1403857800, 1403858700, 1403859600, 1403860500, 1403861400, 1403862300, 1403863200, 1403864100, 1403865000, 1403865900, 1403866800, 1403867700,
1403868600, 1403869500, 1403870400, 1403871300, 1403872200, 1403873100, 1403874000, 1403874900, 1403875800, 1403876700, 1403877600, 1403878500, 1403879400, 1403880300, 1403881200, 1403882100, 1403883000, 1403883900, 1403884800, 1403885700, 1403886600, 1403887500, 1403888400, 1403889300, 1403890200, 1403891100, 1403892000, 1403892900, 1403893800, 1403894700, 1403895600, 1403896500, 1403897400, 1403898300, 1403899200, 1403900100, 1403901000, 1403901900, 1403902800, 1404079200, 1404080100, 1404081000, 1404081900, 1404082800, 1404083700, 1404084600, 1404085500, 1404086400, 1404087300, 1404088200, 1404089100, 1404090000, 1404090900, 1404091800, 1404092700, 1404093600, 1404094500, 1404095400, 1404096300, 1404097200, 1404098100, 1404099000, 1404099900, 1404100800, 1404101700, 1404102600, 1404103500, 1404104400, 1404105300, 1404106200, 1404107100, 1404108000, 1404108900, 1404109800, 1404110700, 1404111600, 1404112500, 1404113400, 1404114300, 1404115200, 1404116100, 1404117000, 1404117900, 1404118800, 1404119700, 1404120600, 1404121500, 1404122400, 1404123300, 1404124200, 1404125100, 1404126000, 1404126900, 1404127800, 1404128700, 1404129600, 1404130500, 1404131400, 1404132300, 1404133200, 1404134100, 1404135000, 1404135900, 1404136800, 1404137700, 1404138600, 1404139500, 1404140400, 1404141300, 1404142200, 1404143100, 1404144000, 1404144900, 1404145800, 1404146700, 1404147600, 1404148500, 1404149400, 1404150300, 1404151200, 1404152100, 1404153000, 1404153900, 1404154800, 1404155700, 1404156600, 1404157500, 1404158400, 1404159300, 1404160200, 1404161100, 1404162000, 1404165600, 1404166500, 1404167400, 1404168300, 1404169200, 1404170100, 1404171000, 1404171900, 1404172800, 1404173700, 1404174600, 1404175500, 1404176400, 1404177300, 1404178200, 1404179100, 1404180000, 1404180900, 1404181800, 1404182700, 1404183600, 1404184500, 1404185400, 1404186300, 1404187200, 1404188100, 1404189000, 1404189900, 1404190800, 1404191700, 1404192600, 1404193500, 1404194400, 1404195300, 1404196200, 1404197100, 1404198000, 1404198900, 1404199800, 1404200700, 1404201600, 1404202500, 1404203400, 1404204300, 1404205200, 1404206100, 1404207000, 1404207900, 1404208800, 1404209700, 1404210600, 1404211500, 1404212400, 1404213300, 1404214200, 1404215100, 1404216000, 1404216900, 1404217800, 1404218700, 1404219600, 1404220500, 1404221400, 1404222300, 1404223200, 1404224100, 1404225000, 1404225900, 1404226800, 1404227700, 1404228600, 1404229500, 1404230400, 1404231300, 1404232200, 1404233100, 1404234000, 1404234900, 1404235800, 1404236700, 1404237600, 1404238500, 1404239400, 1404240300, 1404241200, 1404242100, 1404243000, 1404243900, 1404244800, 1404245700, 1404246600, 1404247500, 1404248400, 1404252000, 1404252900, 1404253800, 1404254700, 1404255600, 1404256500, 1404257400, 1404258300, 1404259200, 1404260100, 1404261000, 1404261900, 1404262800, 1404263700, 1404264600, 1404265500, 1404266400, 1404267300, 1404268200, 1404269100, 1404270000, 1404270900, 1404271800, 1404272700, 1404273600, 1404274500, 1404275400, 1404276300, 1404277200, 1404278100, 1404279000, 1404279900, 1404280800, 1404281700, 1404282600, 1404283500, 1404284400, 1404285300, 1404286200, 1404287100, 1404288000, 1404288900, 1404289800, 1404290700, 1404291600, 1404292500, 1404293400, 1404294300, 1404295200, 1404296100, 1404297000, 1404297900, 1404298800, 1404299700, 1404300600, 1404301500, 1404302400, 1404303300, 1404304200, 1404305100, 1404306000, 1404306900, 1404307800, 1404308700, 1404309600, 1404310500, 1404311400, 1404312300, 1404313200, 1404314100, 1404315000, 1404315900, 1404316800, 1404317700, 1404318600, 1404319500, 1404320400, 1404321300, 1404322200, 1404323100, 1404324000,
1404324900, 1404325800, 1404326700, 1404327600, 1404328500, 1404329400, 1404330300, 1404331200, 1404332100, 1404333000, 1404333900, 1404334800, 1404338400, 1404339300, 1404340200, 1404341100, 1404342000, 1404342900, 1404343800, 1404344700, 1404345600, 1404346500, 1404347400, 1404348300, 1404349200, 1404350100, 1404351000, 1404351900, 1404352800, 1404353700, 1404354600, 1404355500, 1404356400, 1404357300, 1404358200, 1404359100, 1404360000, 1404360900, 1404361800, 1404362700, 1404363600, 1404364500, 1404365400, 1404366300, 1404367200, 1404368100, 1404369000, 1404369900, 1404370800, 1404371700, 1404372600, 1404373500, 1404374400, 1404375300, 1404376200, 1404377100, 1404378000, 1404378900, 1404379800, 1404380700, 1404381600, 1404382500, 1404383400, 1404384300, 1404385200, 1404386100, 1404387000, 1404387900, 1404388800, 1404389700, 1404390600, 1404391500, 1404392400, 1404393300, 1404394200, 1404395100, 1404396000, 1404396900, 1404397800, 1404398700, 1404399600, 1404400500, 1404401400, 1404402300, 1404403200, 1404404100, 1404405000, 1404405900, 1404406800, 1404407700, 1404408600, 1404409500, 1404410400, 1404411300, 1404412200, 1404413100, 1404414000, 1404414900, 1404415800, 1404416700, 1404417600, 1404418500, 1404419400, 1404420300, 1404421200, 1404424800, 1404425700, 1404426600, 1404427500, 1404428400, 1404429300, 1404430200, 1404431100, 1404432000, 1404432900, 1404433800, 1404434700, 1404435600, 1404436500, 1404437400, 1404438300, 1404439200, 1404440100, 1404441000, 1404441900, 1404442800, 1404443700, 1404444600, 1404445500, 1404446400, 1404447300, 1404448200, 1404449100, 1404450000, 1404450900, 1404451800, 1404452700, 1404453600, 1404454500, 1404455400, 1404456300, 1404457200, 1404458100, 1404459000, 1404459900, 1404460800, 1404461700, 1404462600, 1404463500, 1404464400, 1404465300, 1404466200, 1404467100, 1404468000, 1404468900, 1404469800, 1404470700, 1404471600, 1404472500, 1404473400, 1404474300, 1404475200, 1404476100, 1404477000, 1404477900, 1404478800, 1404479700, 1404480600, 1404481500, 1404482400, 1404483300, 1404484200, 1404485100, 1404486000, 1404486900, 1404487800, 1404488700, 1404489600, 1404490500, 1404491400, 1404492300, 1404684000, 1404684900, 1404685800, 1404686700, 1404687600, 1404688500, 1404689400, 1404690300, 1404691200, 1404692100, 1404693000, 1404693900, 1404694800, 1404695700, 1404696600, 1404697500, 1404698400, 1404699300, 1404700200, 1404701100, 1404702000, 1404702900, 1404703800, 1404704700, 1404705600, 1404706500, 1404707400, 1404708300, 1404709200, 1404710100, 1404711000, 1404711900, 1404712800, 1404713700, 1404714600, 1404715500, 1404716400, 1404717300, 1404718200, 1404719100, 1404720000, 1404720900, 1404721800, 1404722700, 1404723600, 1404724500, 1404725400, 1404726300, 1404727200, 1404728100, 1404729000, 1404729900, 1404730800, 1404731700, 1404732600, 1404733500, 1404734400, 1404735300, 1404736200, 1404737100, 1404738000, 1404738900, 1404739800, 1404740700, 1404741600, 1404742500, 1404743400, 1404744300, 1404745200, 1404746100, 1404747000, 1404747900, 1404748800, 1404749700, 1404750600, 1404751500, 1404752400, 1404753300, 1404754200, 1404755100, 1404756000, 1404756900, 1404757800, 1404758700, 1404759600, 1404760500), tzone = "", tclass = c("POSIXct", "POSIXt")), .indexCLASS = c("POSIXct", "POSIXt"), .indexTZ = "", tclass = c("POSIXct", "POSIXt"), tzone = "", .Dim = c(1000L, 1L), .Dimnames = list(NULL, "End.Eq"))
charts.PerformanceSummary(RETURNS, na.rm=T)
# THIS PROVIDES NO ERROR:
RETSBYDAY <- structure(c(0, 0, 0.0131666666666667, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), index = structure(c(1403395200, 1403481600, 1403568000, 1403654400, 1403740800, 1403827200, 1.404e+09, 1404086400, 1404172800, 1404259200, 1404345600, 1404432000, 1404604800, 1404691200), tclass = "Date", tzone = "UTC"), .indexCLASS = "Date", .indexTZ = "", tclass = c("POSIXct", "POSIXt"), tzone = "", .Dim = c(14L, 1L), .Dimnames = list(NULL,"DTT3.DailyEndEq"), class = c("xts", "zoo"))
charts.PerformanceSummary(RETSBYDAY)
#RETURNS and RETSBYDAY are 1xN xts objects.
#RETURNS has an NA value and RETSBYDAY has none; including na.rm=T makes no difference.
I don't get an error using performanceanalytics version 1.4.3541. Perhaps update your version?
I do get warnings though, that "na.rm is not a graphical parameter" when calling charts.PerformanceSummary with na.rm = TRUE. This warning arises because na.rm = T is passed into the function as an extra parameter (because the function has the special parameter ...), which is then passed on to the charting functions inside charts.PerformanceSummary, which include chart.CumReturns, chart.BarVaR, and chart.Drawdown, all of which accept passthrough parameters via ... = ... in their function calls inside charts.PerformanceSummary.
You can't assume every function in R will use na.rm = TRUE to remove NAs. Just mostly base functions like mean, sum, etc... It would be safer to remove the NAs before passing data to a function, if you get errors arising from the NAs in the function call. In case you are not aware, this can usually be easily done in a one liner, such as RETURNS <- RETURNS[!is.na(RETURNS),]
Related
So I noticed that the default layout in igraph sometimes behave weird when there's only one component of the graph, specifically vertices form a cluster that overlap. Consider the following matrix:
mat <- structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(65L, 65L), .Dimnames = list(
NULL, NULL))
g <- graph_from_adjacency_matrix(mat)
plot(g)
Compared to when I add vertex 29 to the main component
mat[29, 44] <- 1
g <- graph_from_adjacency_matrix(mat)
plot(g)
In which case I get the following figure which is much uglier.
Of course, I can work around this by adding an invisible vertex or by creating my own layout but I would like to know why this happens or what is an appropriate layout, similar to the default layout, in the igraph package that doesn't cause the vertices to overlap when I remove the singleton component.
You can try
plot(add_edges(g, c("29", "44")), layout = layout_nicely(g))
I have a list of lists of matrices as shown below, I have posted the code that got me closest to my desired format and some reproducible data.
Here is picture showing the format of my data:
I would like it to be in a dataframe format, similar to that shown below:
V1 V2
1 2
1 2
1 2
1 2
1 2
1 2
The closest I got was with this code:
dt_list <- purrr::map(a, data.table::as.data.table)
dt <- data.table::rbindlist(dt_list, fill = TRUE)
But instead of putting the second list into a second row, this code adds it on to the bottom of the column.
Reproducible data:
data <- list(list(c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)), list(c(2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0)))
You can try unlist with option recursive = FALSE, e.g.,
list2DF(unlist(data, recursive = FALSE))
or use data.frame (thank #akrun's comment)
setNames(data.frame(data), paste0("V", seq_along(data)))
I think purrr::map_dfc(data, as.data.frame) may solve your problem.
I use this loop to connect to Elasticsearch, retrieve some data and add it into my data frame based on a common identifier:
library(elastic); library(jsonlite)
for (i in first_chats_eu$associate) {
firstchats_eu_body <- paste0(
'{"size":1,"query":{"bool":{"must":[{"term":{"associate":"',
i
,'"}},{"term":{"type":"conversation-archived"}}]}},"sort":{"time":"asc"}}'
)
firstchats_eu_connection <- Search(
index = "my_index",
type = "my_type",
body = firstchats_eu_body
)
first_chats_eu$firstChat[first_chats_eu$associate == i] <- fromJSON(toJSON(firstchats_eu_connection$hits$hits), flatten = TRUE)[1]$`_source.time`
}
The problem is that it always produces the following message:
Error in `$<-.data.frame`(`*tmp*`, "firstChat", value = list("2017-06-08T00:17:01.118Z", :
replacement has 445 rows, data has 446
I have looked at other answers on SO but the solutions appear to be specific to each case, and thus not applicable to mine.
What could be causing this?
If it is of any use, this loop sometimes partially succeeds, in that it returns the first 34 results and then fails for all other rows after that point.
Data frame:
structure(list(associate = c("Pm0jYumSjx", "PbjmBqnIdY", "Vq3VblKpZn",
"JUCx0MOygt", "9IxVPXPGvQ", "FUUobAsS2Z", "uflgsKMNze", "VzeedmQuiv",
"BWYbDAIPkr", "PNCzrO3TRA", "zwemlUrxQE", "y19AiLUxLN", "4hhURCoC8H",
"Ak13YJF63y", "aoQI4Ncrt4", "syaulepdzW", "ISdTwUISIG", "wncQ5pXq88",
"MYbsg1E2EQ", "OhkAz5aren", "A2wqC9F1WR", "ZDVmRyHkUY", "n5kKRmTMzj",
"mfek2ukQXk", "9Tz6HWSBTd", "b7JdFFaL7M", "TetbzmItfe", "NfCPXPfA8G",
"fc3QfKEgoI", "lWOiSbqDkN", "PXU7CqGO1S", "kEgnBQeUVH", "Zk182RMS4W",
"vzF3lzDKlx", "92PThwjFeO", "hunSRzc1p9", "n2xvlXoTS3", "AzJIMGGn4I",
"8DAm5dFPtN", "Qk6Dl1wgAG", "b6Z1C2RgYk", "FsHvmjOWu8", "SHqTI9YFFx",
"xhKjx5JJin", "RAPQXUNJbF", "vuq1KKylZY", "sBcaWcjEsk", "B4Z2TYT02E",
"u6iEcDrjRL", "Tv8FVDmFlN", "lTS0ZT24vu", "i2I0kykYo0", "N9Nqwu7XiM",
"0wFw3bY5De", "KEcKE4DRdT", "JcZWhBasDE", "FfLrHsnrT5", "ibOCROEWcG",
"b9K3V27GH7", "1TMLQZS5eR", "Yfo5sO7Hyj", "Q09sg2jrsI", "byzMzoS8QV",
"NKLbLwDA4b", "iKkQUDBXln", "Rutbihe39R", "T00E44PAAf", "PSKIFW2Bi3",
"ewJjvrT8H6", "rudiPWdyHj", "gShZwgHn0m", "dQmluy3ilM", "kO2hP2SNzJ",
"hG8iLjN6BD", "GuDBMuoht6", "AOzBVHetmK", "inSAsVD12e", "tYSXKOEhQB",
"ie5m9sDcd5", "31XpEIYYEd", "qrh9kSiCTh", "6cGqFJB1vh", "VPqvH3dHnz",
"tmg2iLu1f6", "a7nBJlzYRt", "D8jHgvvZfY", "pMwjxAV1iP", "0hD2vZYxf7",
"JFuSGQZmYq", "dCu6ebaRzu", "8kFAGY52xO", "8dq2kAKbnP", "FL3RRY9dbb",
"kJhRRpLQDu", "bRkAyVrvBf", "mMHRUeQEjd", "3ATe60itju", "t1IdGh570n",
"LT7PLxWjKh", "zanyzD8KHy", "zo2fOcIflj", "pLhZhgBSd6", "iTzqXtTlVc",
"6ZGJSIjfUK", "bp0JOkgL2n", "4fHmIsuzoR", "wr8pS9BIGn", "XjBFbgCbA6",
"aBDfBMlyhl", "bjpWS5Zi1d", "1m8RnFavmk", "BCbEV3YcWs", "WO3z2kXsHv",
"W4ziF0GFYp", "Dvdpoq3gZJ", "TeO490YGfr", "sMuDgfHnOY", "IBH2U18pLr",
"iWfUpGFrvN", "JiqDLRGEFX", "kyNo0jk8Z1", "93HElGBOHz", "5ZJCyJrVoO",
"2XS3g6lGJN", "BcLA5ChZHs", "kEVIPyQENZ", "xEHCoCz4kk", "2VP9YQHg0z",
"NE1PnnqgGk", "Ay1r8aB1p3", "KX6pPK8IYt", "oaPI42kqwl", "G8DQ2GKget",
"rrUNVhvaL6", "e1V2GXIIQi", "S1ABORMzvC", "P5SHJFevse", "G5oyD7KyNk",
"96uS2gpKKW", "oVokuIkcBH", "uvZwOIZkhC", "9g3a3lkaqK", "sL3CM1Ydmp",
"CeRfpJxt5l", "gywxLgJfwk", "ykryX7GvTZ", "6G3LCq9dTM", "zcbQHDmYlm",
"vb9zQCBcsC", "CHQR1sudJt", "aSPIsQtBW9", "vUF6TTncxg", "mfZwbqTdqs",
"6KFAVH1JfU", "5VC1MoGAPL", "dBT7WbCPbg", "hsiLXdTOlX", "RYCLZhFY90",
"q9SsmoL8Ig", "eHawNS1jr0", "GVgIzKB9UB", "v1RSMGUZAb", "2arkjePApM",
"FVNiv2T5i2", "2YI036CYSi", "bEe9hMOuPw", "SYHAbSA4Bo", "kIxHklYUvm",
"ea0HZio45e", "bJLyBCIDLq", "UOX1xE4I4m", "DUlIH2h7wi", "MYF1ueeXfe",
"1tOV5TEEK5", "oPt6FcBGj5", "jvyfvuEgaZ", "lNVTpT4hA9", "HqDMYSu1lC",
"al11gInzgN", "hIC4Q5JlBH", "ujvEUtatGU", "wU4B2gFWsH", "UbC2Fnef7t",
"4PMafQHS86", "pzgyPSDDR2", "HajTJzwD6s", "Vmb16EuXQd", "MLImxndCP8",
"JioVLn85XG", "ezeN1Jrfz7", "X3dVvzFpO7", "jXWNcEJF40", "1Dlxb9sFY1",
"I2rDM0GCQY", "ItEc62tlMD", "BQSEE0aw5j", "PcKSaFFCjc", "UZOQv40QpR",
"TpTUfAkH2j", "102Qub695d", "iYMYFVeO3a", "9q6smEyLHE", "Oft5GPL1Kz",
"RNgREArWYp", "6JpBEX0t5E", "FQGSnKhEHZ", "qhH4yU4GF4", "smal1c8nZI",
"XM22Vo5TMb", "wVNGHFxsrw", "bOhSejjY4F", "XstvxG2evH", "YSeaBFnCxC",
"aHvosVBvWF", "ECa32iNWUP", "ntNOwcH86q", "6sBSxrENuN", "TKrEDKGBP4",
"7goCPMibBX", "owne4NwFBU", "DzbUeksk3x", "GFmnRMNXLn", "z03bGKnR4K",
"yrickhqzXO", "orNL3qgRs5", "aZDhxK3MnT", "GfjLnYebLi", "ABzJScG4aF",
"MzDl5sIcEv", "nDPQ5ryX60", "wzYLWcEGt7", "fg4yEOCrMg", "cOxDNFSVJ1",
"N3xJGamqYg", "YCWeSx7FdA", "nS7j6dlHW1", "v8xHPHvF9I", "WTgftXNmQv",
"JhhRGHAiAv", "kA95elFmbl", "6SBhLJ10MA", "zB8PDYd3yi", "Id0K9bUgkh",
"wBkgvnElHb", "kQnwwfc7kJ", "6hNV4Y1C4A", "AmA4Y13eQd", "flON1gpb6N",
"f5DopCEFwK", "boFD2o0FU2", "yd2OuCsCSL", "nDzEFEpz2D", "fweWiQ6x6l",
"G1mT217Z6l", "rFt9fevsgu", "MGtbd36gdp", "K48dwo2BDj", "fzDa2HHq8k",
"q3MmPsZKB4", "O9yTAKQlCN", "tDpjeKpWIY", "wOgm4P7503", "4kXj6O1TWk",
"GTgOP6Ik3U", "AcCdmoQqtn", "F5fwdhj5l3", "AJnCAwFOdi", "ssvby6VgQp",
"qzh7xCHMLl", "T2VySRQ0M0", "0yfnFPWynB", "L7PqHs1f0H", "83GzTa9bxh",
"DOGXIreUyo", "PDsqEWLsu5", "sN3JstovsG", "knZx7l2hsk", "asCBJPBgTg",
"ytAmW9sTAP", "S9vuzwn13O", "nrXFr6Ww5O", "sFUB1beOAx", "CyCvAIDs5q",
"z2jmTzZVAo", "Zdd2fiDPVe", "MOQP5vAj8W", "rjx4tHVh6E", "2G3dquHI2q",
"BruK8mqzVI", "GAB1feRTKE", "TPwJ8jp6j2", "mprSpIdRuJ", "qBaU7KERwq",
"QNfCFKWXv5", "6IdSIlfhrz", "19SMR3CQID", "LxnNlx8DsD", "TEJeH1bZXz",
"bTmafqEayN", "9X18BUOA36", "NoYo4tT3oG", "yj5TyZZyNT", "kPVRWBJRXM",
"H3kVwfzGTe", "vq7qUUqGUr", "GLDCR4av3A", "xiYU2MDc6c", "qOGqanHpjw",
"5BaW31f0Nr", "4dJwcfCqkA", "UJzHhwFZRe", "dec0Qlz3eK", "0l7WDqbZb0",
"MMwd72FDCL", "EDMkdKIWMy", "2zLQmEuKpY", "1SUMAUhkZc", "BxXiWBTb8w",
"zFdVjcL7qz", "pfPOEmMTei", "HzjyCETszF", "b26xszWUlP", "AseQsOAqqY",
"lvDbmLqnyg", "L5WxvWWAyt", "X5WUvRm2BY", "t6XCwcOinz", "FG7pLFG8Uw",
"yLpMyvmHb2", "7Ac9pVAF0B", "sDN9UHNGm4", "9Z1L7RtlA3", "bVb8hjn1ju",
"F4nLAs89VO", "kB4aIQEpkf", "lov4Q42w2B", "jnFjq8covm", "tIuHe5uCaC",
"qsAssEo3Qr", "mW3HVtDHQj", "pFoLBb4EfI", "5UA1lbRTrF", "s1qrkLbTIU",
"RQrW6CtY7C", "xVIb7ymcmW", "Iw3AvXAlZK", "yW0P3oHRKp", "Ivf463pZ3k",
"07OAzJ3LMW", "5nB6O3rLm3", "QsI7HSwDZ6", "YN6V6flLDk", "B5RXoyGmeY",
"gt1VgDERw1", "FS2yKGf1vg", "BpUytkzSeS", "fKFSxBU4QG", "ueBhiB7lig",
"c901c019c5", "MKADBViZNz", "Vcb76RpM0z", "PnIACGOY1I", "EIYwDIB3od",
"B30kGNViyD", "YuAuj81ULa", "HBRNcgXjly", "CNFYrTCnkB", "0NG6oAIhrv",
"39OL0da3JB", "pEYsCPrejG", "imUsAjHivl", "D6QCEqCeEN", "pbARKO6WHG",
"mtx6Brb5rP", "oaLUE44A5W", "AgrZaWAFsg", "yvOMkkIZ1m", "Z6fXosz4Fa",
"2fthCJ5DpQ", "yzDHP6VC3C", "oACH3KkPl4", "OUpJGlVe7Q", "rTUsgI4HB1",
"BG0bfaNntS", "T6DgmUfrMS", "tjMwvgas9N", "gSYzWEbwH6", "6P9pRD9jft",
"h7jgprw5ZI", "9RYqSSNP4s", "pv51ewuo8J", "kPHNzPAsy7", "qDg9oiE5vO",
"8PxDnGjkT9", "czyeqBbnOJ", "uHSx9FbBZy", "Z2mdkJk7Tk", "A9lBq2pPB7",
"1MjXRGUpCL", "oS6oAKFqvi", "Ro2Cpuw7nB", "4LjJWDFiJU", "ASrmSlOd4j",
"f9BBXMzBju", "VHdzp3okgg", "zgCdOvoFoJ", "vm7dLCBAXu", "aohXymMv9M",
"rsATydK2xE", "l6erf0NNN8", "wtcNWItEK5", "XO9BfYHSuJ", "FIsDrDMEM6",
"wThiyvldqW", "n49e2LohLA", "ISPVKeaL8B", "QavdvrKCrJ", "Oc5GaqMvsD",
"dBgH5abgm4", "jbxXIMi5T3", "wOEbpBhvJO", "EcSEO5x8Aa", "IPYmcletaC",
"RccyJrXYSQ", "F044DDAL9U", "xCUcsCDnQd", "wkF3tx7M5N", "RNMO5oH2ce",
"KEUArjG58B", "TfBcBOhVZQ", "BpjQjjlTDg", "wSsnje6q39", "ITAESdcmae",
"XTzpZzZFxy", "UutDWic510", "TMgewBSCgi", "mhEM43wLRC", "FwXswHZJzn",
"jqvBb6v6CY", "1YJDIwy9q2", "ea7Hx9RXNl", "cAYtXFKDvK", "R8DhTwSDmg",
"a54nasvwuX", "bnNkM8nimD", "FSSGwmo5Qh"), accountCreation = structure(c(1521647203.675,
1519339418.982, 1520978846.791, 1521462847.464, 1521219528.448,
1525602918.744, 1521039530.235, 1521026513.49, 1521802344.631,
1523790193.342, 1523699716.79, 1522159355.724, 1520935894.587,
1525529531.887, 1524575967.739, 1521127935.332, 1521047835.094,
1521101424.346, 1520997141.963, 1521025271.346, 1521106469.437,
1520952168.279, 1522939980.072, 1521644559.484, 1520962152.598,
1520946377.448, 1521114036.503, 1523303212.556, 1520948768.796,
1521281304.856, 1521484713.426, 1521314445.804, 1521632072.396,
1524399853.238, 1524063742.962, 1524048668.223, 1521231047.543,
1524157639.65, 1521209831.34, 1521475186.089, 1521724609.138,
1523533039.228, 1523702955.539, 1522488605.67, 1521890183.374,
1521642579.3, 1522228581.673, 1523525372.293, 1521195229.708,
1520940268.528, 1521044364.138, 1527678100.482, 1524600058.621,
1522777239.275, 1523870518.667, 1521369133.225, 1522232575.542,
1521198325.682, 1523360584.136, 1521813258.386, 1521627226.595,
1521033049.721, 1523452387.623, 1522236488.509, 1521198246.297,
1524671994.275, 1521720640.095, 1522242402.263, 1521637447.34,
1521718413.354, 1521290525.148, 1521530545.831, 1521022229.054,
1521054255.295, 1522147616.899, 1521115359.397, 1525349801.15,
1520943213.673, 1523610221.63, 1521478193.229, 1521889281.441,
1523701184.22, 1521810788.09, 1520946831.645, 1521471304.719,
1521561858.612, 1521893506.908, 1521048628.327, 1521116277.724,
1522765167.032, 1521286311.531, 1521125237.2, 1521887929.78,
1525159037.328, 1524135123.072, 1519230466.413, 1521030848.111,
1520956865.733, 1521592739.521, 1521457270.104, 1521736081.412,
1521736093.529, 1522159760.701, 1524053386.664, 1524496291.977,
1524216088.817, 1520936977.191, 1520953090.937, 1521212807.586,
1521803151.728, 1521801343.725, 1524055557.569, 1522767163.557,
1521729513.656, 1524316353.148, 1520935603.264, 1523960278.276,
1521499028.577, 1521643199.88, 1524483302.128, 1525335512.042,
1521373117.292, 1520879030.594, 1521023257.287, 1521022157.451,
1523800300.841, 1520935205.484, 1521738187.203, 1521280970.99,
1521213783.986, 1523970332.086, 1522053669.333, 1521738166.805,
1522945933.897, 1520952792.799, 1524757978.638, 1521111905.664,
1524295064.907, 1521025774.074, 1522320956.043, 1521655757.989,
1521195220.823, 1521016193.598, 1521730985.238, 1521739086.354,
1520936329.814, 1520941866.452, 1521308647.796, 1520942541.479,
1520932451.164, 1520932450.409, 1524233637.038, 1523542112.437,
1521891391.694, 1520941112.597, 1521981704.61, 1524126540.184,
1521452436.923, 1521681150.112, 1521021271.162, 1523113077.121,
1524135121.181, 1521225075.835, 1521200485.608, 1521463364.621,
1522340866.586, 1522675782.65, 1522061257.085, 1520935213.165,
1521111379.722, 1522405319.784, 1521021777.312, 1521062469.007,
1524653489.931, 1521216029.087, 1520932450.074, 1522483910.384,
1521019100.815, 1524483561.903, 1521196200.601, 1521141925.275,
1524608679.675, 1520935615.677, 1524766524.32, 1521019881.426,
1520936989.662, 1523036547.916, 1521196426.438, 1521210908.376,
1521628649.889, 1521280983.286, 1521300046.167, 1524738218.644,
1523543199.814, 1521200519.952, 1524914417.224, 1524652840.984,
1525862276.545, 1521027321.217, 1521104801.584, 1521223553.524,
1521211503.42, 1521921773.167, 1520946989.043, 1523445841.807,
1521725990.924, 1521977244.334, 1521627508.652, 1525969006.645,
1525969022.093, 1521812644.345, 1520932449.817, 1521458377.453,
1521020768.777, 1521304861.478, 1520947823.441, 1521205017.765,
1520953961.96, 1520940974.834, 1523182530.64, 1521886711.101,
1521393592.616, 1521377252.798, 1521455570.819, 1521477410.136,
1524502991.311, 1521568209.362, 1520970930.145, 1523821413.628,
1521541778.729, 1519236437.627, 1523702049.192, 1522173164.254,
1524657516.266, 1521735865.479, 1521466638.454, 1521813538.683,
1521476092.325, 1521150151.59, 1521565928.114, 1522758779.981,
1521479231.715, 1520935850.699, 1521025111.789, 1522867701.541,
1521471989.26, 1524744993.667, 1520950428.393, 1523536553.54,
1522421382.988, 1521546156.87, 1521028394.686, 1521050335.668,
1521020456.866, 1522229659.937, 1521025286.049, 1521122727.912,
1521026467.854, 1521450006.649, 1521219087.52, 1521469866.623,
1521197195.734, 1521105260.349, 1521011471.989, 1521190524.789,
1521452303.022, 1520933421.224, 1521115127.677, 1523884939.943,
1520961138.002, 1521016753.264, 1521016893.143, 1521017010.196,
1521017173.526, 1521017281.13, 1521017606.628, 1521117180.29,
1521117300.792, 1521125450.611, 1521132242.791, 1521205674.621,
1521205950.641, 1521215731.346, 1521459082.156, 1521460316.99,
1521482702.085, 1521482815.695, 1521482903.143, 1521483099.712,
1521483278.868, 1521483371.324, 1521540692.887, 1521543890.489,
1521544034.707, 1521544160.551, 1521544235.273, 1521544330.989,
1521544485.786, 1521544609.88, 1521544764.696, 1521553643.038,
1521553739.931, 1521590910.434, 1521731535.229, 1521731535.928,
1521731546.759, 1521802978.117, 1521886145.182, 1521886194.283,
1521886413.213, 1521889580.687, 1522052985.205, 1522069337.077,
1522063483.939, 1522166738.438, 1522250898.347, 1522340911.64,
1522942459.588, 1523359215.503, 1523397047.86, 1523437988.256,
1523438083.426, 1523445420.319, 1523447633.945, 1523455566.243,
1523458605.986, 1523541116.105, 1523615795.787, 1523879249.334,
1523890699.033, 1523979871.23, 1523980654.125, 1524045405.981,
1524056257.89, 1524154119.955, 1524159979.146, 1524393026.557,
1524393845.931, 1524478733.191, 1524494492.895, 1524495293.313,
1524500425.993, 1524500660.969, 1524585635.173, 1524641288.518,
1524659670.369, 1524667611.839, 1524668269.638, 1524672949.857,
1524673079.627, 1524673178.774, 1524912901.694, 1525006502.237,
1525034518.791, 1525076940.386, 1525079238.038, 1525079979.214,
1525081785.524, 1525083082.759, 1525085456.7, 1525176437.685,
1525253930.6, 1525255054.744, 1525259664.818, 1525261014.423,
1525261500.246, 1525287238.277, 1525346162.325, 1525350313.866,
1525451045.815, 1525686874.633, 1525800629.92, 1525865551.171,
1525877902.633, 1525942349.151, 1525945093.268, 1526141141.217,
1526142261, 1526301362.64, 1526301431.797, 1526301861.592, 1526302079.545,
1526324313.439, 1526327287.226, 1526383076.912, 1526394120.405,
1526394871.906, 1526395540.302, 1526396440.737, 1526467461.013,
1526474515.013, 1526474851.867, 1526474950.656, 1526475027.807,
1526572192.208, 1526899111.332, 1526903749.417, 1526911124.083,
1526978640.406, 1526992033.825, 1527005249.155, 1527062775.068,
1527065597.18, 1527070549.853, 1527072673.61, 1527086220.387,
1527087986.751, 1527149254.527, 1527149382.032, 1527149716.254,
1527149851.777, 1527150283.992, 1527150450.301, 1527150553.517,
1527150666.548, 1527165902.1, 1527165998.747, 1527166128.254,
1527166243.866, 1527170994.7, 1527171081.964, 1527171158.104,
1527171239.335, 1527174965.995, 1527175065.505, 1527236752.65,
1527237081.146, 1527237162.074, 1527237333.16, 1527237518.202,
1527237606.934, 1527237676.797, 1527237786.63, 1527237891.106,
1527237979.302, 1527238310.444, 1527238397.71, 1527238467.749,
1527247882.085, 1527247921.493, 1527253757.25, 1527261991.607,
1527262528.413, 1527590487.952, 1527590606.241, 1527590748.119
), class = c("POSIXct", "POSIXt")), firstChat = list("2017-12-23T19:02:03.112Z",
"2017-06-08T00:17:01.118Z", "2016-12-11T15:20:54.019Z", "2017-03-10T11:41:44.036Z",
"2017-02-07T17:00:13.338Z", "2017-02-09T17:56:32.961Z", "2017-02-06T16:34:19.095Z",
"2017-06-07T12:11:15.257Z", "2017-02-21T14:58:31.850Z", "2017-02-09T15:17:40.920Z",
"2017-02-09T14:43:02.026Z", "2017-02-20T15:37:56.756Z", "2017-03-08T15:04:17.341Z",
"2017-03-03T19:43:19.287Z", "2017-07-16T09:47:28.713Z", "2017-03-30T17:57:47.205Z",
"2017-03-20T20:09:41.879Z", "2017-03-22T15:09:21.433Z", "2017-03-22T19:02:20.977Z",
"2017-04-06T10:46:50.105Z", "2017-04-19T17:12:18.318Z", "2017-04-21T15:21:48.603Z",
"2017-04-20T14:12:07.052Z", "2017-04-21T11:33:10.867Z", "2017-04-20T08:58:52.326Z",
"2017-04-21T13:34:01.145Z", "2017-04-24T17:50:07.694Z", "2017-04-21T11:02:15.512Z",
"2017-05-24T10:56:42.089Z", "2017-05-06T13:26:43.845Z", "2017-05-10T17:44:43.533Z",
"2017-05-04T15:14:47.320Z", "2017-05-16T15:28:05.820Z", "2017-05-17T19:29:16.809Z",
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)), row.names = c(NA,
446L), class = "data.frame")
Closed. This question needs details or clarity. It is not currently accepting answers.
Want to improve this question? Add details and clarify the problem by editing this post.
Closed 6 years ago.
Improve this question
I would like to put one line plot on each page of pdf file. All the data for plotting is stored in single data frame. Each row should be plotted.
That's how the data looks like:
structure(list(`10` = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), `34` = c(0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 370500, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1091361.9, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1512409.6,
0, 0, 0, 0, 0, 0), `59` = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 4231358.2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 5995680.4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 2266775, 0, 0, 0, 0, 0, 0, 6864490.1, 0, 0,
0, 0, 0, 0), `84` = c(0, 0, 0, 0, 1783350, 0, 0, 0, 1177650,
0, 0, 0, 0, 0, 0, 0, 0, 4316664.7, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 9262556.7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 2831286.1, 0, 0, 0, 0, 0, 0, 10643218.2,
0, 0, 0, 0, 0, 0), `110` = c(0, 0, 0, 0, 1778743.3, 0, 0, 0,
1465966.7, 0, 0, 0, 0, 0, 0, 0, 0, 3111700, 0, 0, 1955337.5,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5584784.4, 5584784.4,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3092525, 0,
0, 0, 0, 0, 0, 7847143.8, 0, 0, 0, 0, 0, 0), `134` = c(0, 0,
0, 0, 1121869.4, 0, 0, 0, 1439430.6, 0, 0, 0, 0, 0, 0, 0, 0,
2854250, 0, 0, 0, 0, 0, 0, 914890, 0, 0, 847880, 0, 0, 0, 0,
0, 0, 0, 8191800, 0, 0, 0, 0, 0, 0, 1830904.5, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1650150, 0, 0, 837130, 0, 0, 0, 4925095.1, 0,
0, 0, 0, 0, 0), `165` = c(0, 0, 0, 0, 1432775, 0, 0, 0, 1394186.1,
0, 1120183.3, 0, 0, 0, 0, 0, 0, 2262421.7, 0, 0, 0, 615660, 0,
0, 1292795.8, 0, 0, 712622.5, 0, 0, 0, 0, 0, 0, 0, 2683469.4,
0, 0, 0, 0, 0, 0, 2318485.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1561800,
0, 0, 0, 0, 0, 0, 4382993.7, 0, 0, 763460, 0, 0, 0), `199` = c(0,
0, 0, 0, 1314220, 0, 0, 0, 1439718.8, 0, 1929266.7, 0, 0, 0,
1101800, 0, 0, 2759366.7, 0, 0, 0, 1291728.6, 0, 0, 2489775.6,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2858345.8, 0, 0, 0, 1819542.1,
0, 0, 1497640.3, 0, 0, 0, 1300250, 0, 0, 0, 0, 0, 0, 1566875,
0, 0, 0, 0, 0, 0, 4625895.6, 0, 0, 1308158.3, 0, 0, 0), `234` = c(1257250,
0, 0, 0, 0, 0, 0, 0, 1276080, 0, 1848500, 0, 0, 0, 1529350, 0,
0, 2155275, 0, 0, 0, 2023041.9, 0, 0, 1966447.7, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1184200, 1184200, 0, 0, 1652350, 0, 0, 2018581.7,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1835225, 0, 0, 0, 0, 0, 0, 4639414.7,
0, 0, 720715, 0, 0, 0), `257` = c(0, 0, 0, 0, 0, 669442.5, 0,
0, 1253026.7, 0, 960410, 960410, 0, 0, 1258267.5, 0, 0, 1707392.5,
0, 0, 0, 563280, 0, 0, 2403237.9, 0, 0, 0, 1044100, 0, 2075700,
0, 0, 0, 0, 0, 5718450, 0, 0, 1704550, 0, 0, 1350286.9, 0, 0,
0, 0, 2011700, 0, 0, 0, 0, 0, 1739500, 0, 0, 0, 0, 0, 0, 4612520.8,
4612520.8, 0, 0, 0, 0, 0), `362` = c(0, 1593500, 0, 0, 0, 1610625.3,
0, 0, 1234902.5, 0, 0, 1481036.8, 0, 0, 1583647.5, 0, 0, 1752089.2,
0, 0, 0, 0, 0, 0, 2410809.2, 0, 0, 0, 654940, 0, 0, 0, 0, 0,
0, 0, 7014905.6, 0, 0, 0, 0, 0, 1165672.1, 0, 0, 0, 0, 0, 0,
0, 1029910, 0, 0, 2153087.5, 0, 0, 0, 422920, 0, 0, 0, 7495855.9,
0, 0, 0, 0, 0), `433` = c(0, 0, 0, 0, 0, 1340283.9, 0, 0, 1268996.9,
0, 0, 1416683.3, 0, 0, 1047862.5, 0, 0, 1819653.8, 0, 0, 0, 0,
0, 0, 2227565.7, 0, 0, 0, 763765, 0, 0, 1595430, 0, 0, 0, 0,
4894549, 0, 0, 0, 0, 0, 1061375.4, 0, 0, 0, 0, 0, 2251950, 0,
1042130, 0, 0, 2055300, 0, 0, 0, 696278.3, 0, 0, 0, 5353797.8,
0, 0, 0, 0, 0), `506` = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2020300,
2020300, 0, 0, 0, 0, 0, 0, 7681526, 0, 0, 0, 0, 0), `581` = c(0,
0, 1749237.5, 0, 0, 0, 2421665.8, 0, 0, 1773262.5, 0, 0, 2251004.3,
0, 0, 2570175, 0, 0, 3379756.9, 0, 0, 0, 2054455.6, 0, 0, 2518270.8,
0, 0, 0, 0, 0, 0, 2917968.2, 0, 0, 0, 0, 7004350, 0, 0, 1451600,
0, 0, 1394411, 0, 0, 0, 0, 0, 2507858.3, 0, 2377012.5, 0, 0,
3719165.4, 0, 0, 0, 1472870.3, 0, 0, 9666916.1, 0, 0, 1730300,
0, 0), `652` = c(0, 0, 476910, 476910, 0, 0, 1149078.8, 1149078.8,
0, 1082468.7, 0, 0, 882769.7, 0, 0, 1370449.4, 1370449.4, 0,
1529049, 1529049, 0, 0, 943632.2, 0, 0, 916587.8, 0, 0, 0, 988261.1,
0, 0, 1778007.1, 1778007.1, 0, 0, 0, 3087304.8, 3087304.8, 0,
782860, 782860, 0, 510158.5, 510158.5, 0, 0, 0, 0, 1503750, 0,
1100677.5, 1100677.5, 0, 1669260, 1669260, 0, 0, 770733.2, 0,
0, 4939242.8, 4939242.8, 0, 643564.4, 643564.4, 0), `733` = c(0,
0, 0, 1095060, 0, 0, 0, 1674089.3, 0, 1252101.3, 0, 0, 1259111,
0, 0, 0, 2429293.3, 0, 0, 2326928.3, 0, 0, 1259216.5, 0, 0, 1238837.5,
0, 0, 0, 1224858.3, 0, 0, 0, 2952529.9, 0, 0, 0, 0, 4626414.7,
0, 0, 1121440, 0, 0, 1025386.2, 0, 0, 0, 0, 1917900, 0, 0, 2197533.3,
0, 0, 2840155.5, 0, 0, 1054285.7, 0, 0, 0, 7516814.2, 0, 0, 1329434.4,
0), `818` = c(0, 0, 0, 720551.1, 0, 0, 0, 714662.7, 0, 617012.9,
0, 0, 549850.8, 0, 0, 0, 1197460, 0, 0, 771979.2, 0, 0, 585847.5,
585847.5, 0, 875475.4, 0, 0, 0, 576774, 0, 0, 0, 1147389.8, 0,
0, 0, 0, 2292421.7, 0, 0, 755258.3, 0, 0, 0, 0, 0, 0, 0, 858930,
0, 0, 1242668.3, 0, 0, 1580088.3, 0, 0, 641938.6, 641938.6, 0,
0, 3838660.4, 0, 0, 733140.8, 733140.8), `896` = c(0, 0, 0, 590480,
0, 0, 0, 817087.6, 0, 569869.5, 0, 0, 650822.5, 650822.5, 0,
0, 1624052.5, 0, 0, 682570.8, 0, 0, 0, 1538800, 0, 690488.6,
690488.6, 0, 0, 797923.9, 0, 0, 0, 1204889.3, 0, 0, 0, 0, 2184432.2,
0, 0, 676654.7, 0, 0, 0, 210680, 0, 0, 0, 791152.5, 0, 0, 1599855.8,
0, 0, 1358543.8, 0, 0, 0, 931288, 0, 0, 4683895.2, 0, 0, 0, 1202806
), `972` = c(0, 0, 0, 799116.4, 0, 0, 0, 759169.9, 0, 408845,
0, 0, 0, 948980, 0, 0, 968766.7, 0, 0, 675349.7, 0, 0, 0, 0,
0, 0, 1811117.6, 0, 0, 609098.5, 0, 0, 0, 1073749.1, 0, 0, 0,
0, 2392258.9, 0, 0, 743580, 0, 0, 0, 1020485, 0, 0, 0, 446596.7,
0, 0, 1178583, 0, 0, 1438261.7, 0, 0, 0, 1133057.9, 0, 0, 4445814.7,
0, 0, 0, 1057776.9), `1039` = c(0, 0, 0, 447255.3, 0, 0, 0, 609409.1,
0, 304340, 0, 0, 0, 0, 0, 0, 694232.8, 0, 0, 473015.3, 0, 0,
0, 0, 0, 0, 419524.9, 0, 0, 447760.6, 0, 0, 0, 932513.5, 0, 0,
0, 0, 1251960.5, 0, 0, 276560, 0, 0, 0, 259640, 0, 0, 0, 354995,
0, 0, 1570222.5, 0, 0, 1021822, 0, 0, 0, 811614, 0, 0, 2941698.2,
0, 0, 0, 1199942.5), Gene = 1:67), .Names = c("10", "34", "59",
"84", "110", "134", "165", "199", "234", "257", "362", "433",
"506", "581", "652", "733", "818", "896", "972", "1039", "Gene"
), row.names = c(NA, 67L), class = "data.frame")
I have tried something like that so far...:
for(i in 1:nrow(Tra_decon)){
Tra_decon_melt <- melt(Tra_decon[i,], id = "Gene")
pdf("Test_plot.pdf", onefile = TRUE)
ggplot(Tra_decon_melt, aes(variable, log10(value), group=factor(Gene))) +
theme(legend.title=element_blank()) +
ylab("XXX") +
xlab("XXX") +
geom_line(aes(color=factor(Gene)), size = 1.2) +
ggtitle("XXXX") +
theme(axis.text.x = element_text(angle = 90, hjust = 1))
dev.off()
}
A solution without a for loop (and so faster) is this one:
plots <- lapply(1:nrow(Tra_decon), function(i){
Tra_decon_melt <- melt(Tra_decon[i,], id = "Gene")
ggplot(Tra_decon_melt, aes(variable, log10(value), group=factor(Gene))) +
theme(legend.title=element_blank()) +
ylab("XXX") +
xlab("XXX") +
geom_line(aes(color=factor(Gene)), size = 1.2) +
ggtitle("XXXX") +
theme(axis.text.x = element_text(angle = 90, hjust = 1))
})
pdf("Test_plot.pdf", onefile = TRUE)
plots
dev.off()
This works for me:
pdf("Test_plot.pdf", onefile = TRUE)
for(i in 1:nrow(Tra_decon)){
Tra_decon_melt <- melt(Tra_decon[i,], id.vars = "Gene")
plot<-list()
plot[[i]]<-ggplot(Tra_decon_melt, aes(variable, log10(value), group=factor(Gene))) +
theme(legend.title=element_blank()) +
ylab("XXX") +
xlab("XXX") +
geom_line(aes(color=factor(Gene)), size = 1.2) +
ggtitle("XXXX") +
theme(axis.text.x = element_text(angle = 90, hjust = 1))
print(plot[[i]])
}
dev.off()
I'm trying to write a script to analyze my data. Would be great if you can help me with that.
Let's start with my data:
> dput(tbl_alles[1:100,])
structure(list(`10` = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0), `20` = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0), `52.5` = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0.7306675, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0), `81` = c(0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0.91538769,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0), `110` = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0.85441768, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0.61947266, 0, 0, 0), `140.5` = c(0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5664111,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.6800275, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0.6300494, 0, 0, 0), `189` = c(0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0.6234154, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0.987181, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.6194727,
0, 0, 0), `222.5` = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0.8632862, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0.3456471, 1, 0, 0), `278` = c(0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0.61502309,
0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0.44036184, 1,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.42691496, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0.32234716, 0, 0, 0, 0.08890253, 0.67918373,
0, 0), `340` = c(0, 0, 0, 0, 0, 0, 0.583163048, 0, 0, 0, 0, 0,
1, 1, 0, 0, 0, 0, 1, 0.218194067, 0.325932107, 1, 0, 0, 1, 0,
0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.663889907, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0.789927058, 0, 0.44201215,
0, 0, 0, 0, 0.134339392, 0, 0.668372028, 0, 0, 0, 0, 0, 0, 0,
0.387740087, 0, 0, 0, 0, 0, 0, 0), `397` = c(0, 1, 0, 0, 0, 0,
1, 0, 1, 0, 0, 0, 0, 0.63953839, 0, 1, 0, 0, 0, 1, 1, 0.81888525,
0.89884151, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0.51459601, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0.75141988, 0, 0, 0, 0, 0, 0, 0, 0, 0.65763553, 1, 0, 0,
0, 0, 1, 0, 1, 0.67607045, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0,
0, 0.80260185, 0, 0, 0, 0, 0, 0, 1), `453.5` = c(0, 0.66069369,
0, 0, 0, 1, 0.57541627, 1, 1, 0, 0, 0, 1, 0.64615661, 0, 0.45209671,
0, 0, 0, 0.17022498, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0.02056466, 0.08765142, 1, 0, 0, 0, 0, 0, 1, 0.53107365,
0, 0, 1, 0, 0.47454662, 1, 0.58701126, 1, 0.83194495, 0, 0, 1,
0, 0, 0, 0, 0.04550448, 0, 1, 0, 0.65763553, 1, 1, 0.05581525,
0, 0, 0.78992706, 1, 0.80859968, 0.80441503, 1, 1, 0, 0.5866736,
0, 0, 0.75623688, 0.36602167, 0, 0, 1, 0, 0.31053744, 1, 0.52549512,
1, 0, 0, 0, 0, 0.51742419), `529` = c(0, 0.521435654, 0, 0, 1,
0, 0.175996209, 0, 0, 0, 1, 0, 0, 0, 0, 0.886059888, 0, 0, 0,
0.17022498, 0, 0, 0.643526362, 0, 0, 0, 0, 0, 0.438237074, 0.01594858,
0, 0.383182117, 0, 0, 0, 0, 0, 0, 1, 0.101027654, 1, 0, 0, 0,
0, 0, 0, 0.733614607, 0.89648659, 0, 0, 0.703255538, 0, 1, 0.383200069,
0.868653232, 1, 0.065540432, 0, 0, 0.221275397, 0.229618981,
0, 0, 0, 0.14131076, 0, 0.665883882, 0, 0.399096177, 0.570186116,
0.917797708, 0.349222091, 0, 0, 0.872987981, 0, 0, 1, 1, 0.58275186,
0, 0.211497647, 0, 0, 0.929066091, 0.826799766, 0, 0, 0, 0, 0.148043509,
0.802601847, 1, 0.780383116, 0, 0, 0, 0, 0.340224249), `580` = c(0,
0.437291195, 0, 0, 1, 0, 0.20731698, 0, 0, 0, 1, 0, 0, 0, 0,
0.719755907, 0, 0, 0, 0.033248127, 0, 0, 0, 0, 0, 0, 0, 0, 0.443305568,
0, 0, 0.558877749, 0, 0, 0, 0, 0, 0, 1, 0.171621995, 1, 0, 0,
0, 0, 0, 0, 0.28952456, 1, 1, 0, 0.470920245, 0, 0.690299657,
0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0.111377617, 0.740623952, 0,
0, 0.53029633, 0, 0.917797708, 0.395559317, 0, 0, 0.484708125,
0, 0, 0.174273053, 0, 0.693355663, 0, 0.050471201, 1, 0, 0, 1,
0, 0, 0, 0, 0.698359908, 0.298609118, 0.702753583, 0.926794372,
0, 0, 0, 0, 0.320673115), `630.5` = c(0, 0.52204783, 0, 0, 0,
0, 0.48815538, 0, 0, 0, 0, 1, 0, 0, 0, 0.82709638, 0, 0, 0, 0.09539534,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0.45656691,
0.74836669, 0, 0, 0, 0, 0, 0, 0, 0.95701562, 1, 0, 0.67884433,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0.65763553,
0, 0, 1, 0, 0, 0.77875219, 0, 0, 0.25002477, 0, 1, 0, 0, 0, 0,
0, 0.82679977, 0, 0, 0, 0, 0.84843874, 0.38138487, 0.79820877,
0, 0, 0, 0, 0, 0.51876177), `683.5` = c(0, 0.52429838, 0, 0,
0, 0, 0.59605685, 0, 0, 0, 0, 0, 0, 0, 0, 0.27845748, 0.28224351,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0.94942976, 0, 0, 0, 0, 0, 0.74467188, 0, 0, 0.31501511,
0, 0, 0, 0, 0, 0, 0, 0.73190143, 0, 0, 0, 0, 0, 0.90254266, 0.42921624,
0, 0, 0.56841245, 0, 0, 0.48306937, 0.54177946, 0, 0.70689046,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0.72875619, 0, 0, 0, 0, 1, 0.26676304,
0.77778861, 0, 0, 0, 0, 0, 0.17064527), `735.5` = c(1, 0.3768651,
0, 1, 0, 0, 0.51381348, 0, 0, 0, 0, 0, 0, 0, 0, 0.39914361, 0.22206677,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0.42663351, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.61727598,
0, 0, 0, 0, 0, 0, 0.70045244, 0, 0, 0, 0, 1, 0.62631217, 0, 0,
0, 0, 0, 0, 0.14653411, 1, 1, 0.27513455, 0, 0, 0, 0, 0.75025613,
0, 0, 0, 0, 0, 0.92484335, 0, 1, 0, 1, 0.84843874, 0.12198269,
0.58556836, 0, 0, 0, 0, 0, 0.09714178), `784` = c(0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.45656691, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0.61727598, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 1, 0, 0, 0.84843874, 0, 0, 0, 0, 0, 0, 0, 0
), `832` = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0.16189002, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0.2511846, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0.23427262, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0.45750616,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0.86974453,
1, 0, 0, 0.48180864, 0, 0, 0, 0.93083267, 0, 0, 0, 0), `882.5` = c(0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.3111616,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.63931007, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0.73948906, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0), `926.5` = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0.63485498, 0, 0, 0, 0, 0, 0, 1, 0,
0.68547559, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.35567368,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0.84973396, 0, 0, 1, 0), `973` = c(0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.86100786, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0.68128251, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0.30811206, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.79599822, 0,
0, 0, 0), `1108` = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0.75365872, 0, 0, 1, 0, 0, 0, 0, 0, 0.52862914,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.20061435, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0.93083267, 0, 0, 0, 0), `1200` = c(0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0.67241551, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0.55638877, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)), .Names = c("10",
"20", "52.5", "81", "110", "140.5", "189", "222.5", "278", "340",
"397", "453.5", "529", "580", "630.5", "683.5", "735.5", "784",
"832", "882.5", "926.5", "973", "1108", "1200"), row.names = c("at1g01050.1",
"at1g01080.1", "at1g01090.1", "at1g01220.1", "at1g01420.1", "at1g01470.1",
"at1g01800.1", "at1g01910.5", "at1g01920.2", "at1g01980.1", "at1g02020.2",
"at1g02100.2", "at1g02130.1", "at1g02140.1", "at1g02150.1", "at1g02500.2",
"at1g02560.1", "at1g02780.1", "at1g02880.3", "at1g02920.1", "at1g02930.2",
"at1g03030.1", "at1g03110.1", "at1g03130.1", "at1g03210.1", "at1g03220.1",
"at1g03230.1", "at1g03310.2", "at1g03330.1", "at1g03475.1", "at1g03630.2",
"at1g03680.1", "at1g03870.1", "at1g03900.1", "at1g04130.1", "at1g04170.1",
"at1g04190.1", "at1g04270.2", "at1g04350.1", "at1g04410.1", "at1g04420.1",
"at1g04530.1", "at1g04640.2", "at1g04690.1", "at1g04750.2", "at1g04810.1",
"at1g04850.1", "at1g04870.2", "at1g05010.1", "at1g05180.1", "at1g05320.3",
"at1g05350.1", "at1g05520.1", "at1g05560.1", "at1g05620.2", "at1g06000.1",
"at1g06110.1", "at1g06130.2", "at1g06290.1", "at1g06410.1", "at1g06550.1",
"at1g06560.1", "at1g06570.1", "at1g06620.1", "at1g06650.2", "at1g06680.2",
"at1g06900.1", "at1g07080.1", "at1g07110.1", "at1g07140.1", "at1g07240.1",
"at1g07250.1", "at1g07440.1", "at1g07750.1", "at1g07780.4", "at1g07890.8",
"at1g07990.1", "at1g08110.3", "at1g08200.1", "at1g08360.1", "at1g08490.1",
"at1g08520.1", "at1g08550.2", "at1g08820.2", "at1g08830.2", "at1g08980.1",
"at1g09010.1", "at1g09020.1", "at1g09130.2", "at1g09210.1", "at1g09300.2",
"at1g09310.1", "at1g09340.1", "at1g09430.1", "at1g09490.2", "at1g09620.1",
"at1g09640.1", "at1g09750.1", "at1g09760.1", "at1g09780.1"), class = "data.frame")
As you can see most of cells contain a number "0".
I would like to create a subsets of my data. Let's call them "clusters". I would like to put in the same cluster "elements" (row.names) which has any value (different than 0) in the same column.
So for example:
row.name Column1 Column2 Column3 Column4
at1g02560.1 0 0.12 0 0
at1g02020.2 1 0 0.55 0.31
at1g14560.2 0.15 0.47 0 0
As you see at1g02560.1 has a value only in column 2, there is one more row which contains any value in the column 2, it's at1g14560.2. That means that they belong to the same cluster (let's say cluster 1).
The problem is that at1g02020.2 and at1g14560.2 has a value different than 0 in the column 1. They should be in the same cluster aswell (cluster 2).
In summary at1g14560.2 belong to two different clusters (cluster 1 and cluster 2).
As a result I would like to add additional column to my data named clusters and fill it with the numbers.
Example:
row.name data data data data Clusters
at1g02560.1 1
at1g14560.2 1,2
at1g02020.2 2
Is it even possible to do with R ?
Yes, it is possible to do with R. Here's one way using apply:
res <- cbind(tbl_alles,
Clusters=apply(tbl_alles, 1, function(x) paste(which(x!=0), collapse=",")))
head(res[, c(1:5, ncol(res))])
# 10 20 52.5 81 110 Clusters
# at1g01050.1 0 0 0 0 0 17
# at1g01080.1 0 0 0 0 0 11,12,13,14,15,16,17
# at1g01090.1 0 0 0 1 0 4
# at1g01220.1 0 0 0 0 0 17
# at1g01420.1 0 0 0 0 0 13,14
# at1g01470.1 0 0 0 0 0 12
You may also try:
indx <- which(!!tbl_alles,arr.ind=T)
tbl_alles$Clusters <- tapply(indx[,2],indx[,1], FUN=paste, collapse=",")
tbl_alles[1:5,c(1:5, ncol(tbl_alles))]
# 10 20 52.5 81 110 Clusters
#at1g01050.1 0 0 0 0 0 17
#at1g01080.1 0 0 0 0 0 11,12,13,14,15,16,17
#at1g01090.1 0 0 0 1 0 4
#at1g01220.1 0 0 0 0 0 17
#at1g01420.1 0 0 0 0 0 13,14