将 CSV 分成三部分并计算平均值

Question

我有一个文件包含：

Time                     60Ni                     61Ni            62Ni                 63Cu                64Ni                       65Cu               66Zn

0.  9.13242244720459    0.406570166349411   1.326429009437561   5.754200458526611   0.4233334958553314  2.68562912940979    4.148788005113602e-002  
8.390999794006348   9.187464714050293   0.4089393615722656  1.334462523460388   5.790649890899658   0.425884485244751   2.702604055404663   4.17313240468502e-002   
16.78300094604492   9.254316329956055   0.4119723737239838  1.344084143638611   5.832504749298096   0.428943395614624   2.722275018692017   4.203101620078087e-002  
25.17399978637695   9.19857120513916    0.4094997346401215  1.336091756820679   5.791898727416992   0.4264563024044037  2.703336715698242   4.185733571648598e-002  
33.56499862670898   9.194388389587402   0.4092871248722076  1.335391044616699   5.794968605041504   0.4264419078826904  2.704529047012329   4.192239791154862e-002  
41.95600128173828   9.162041664123535   0.4078944325447083  1.330722570419312   5.766440868377686   0.425002932548523   2.691519498825073   4.182799160480499e-002  
50.34700012207031   9.190646171569824   0.4091125726699829  1.334963202476502   5.786285877227783   0.426413893699646   2.700882434844971   4.196327552199364e-002  
58.73799896240234   9.211565971374512   0.4100649058818817  1.337916374206543   5.8003830909729 0.4273969829082489  2.707314252853394   4.207673668861389e-002  
67.12799835205078   9.240947723388672   0.4113766849040985  1.342136979103088   5.822870254516602   0.4287911653518677  2.717630624771118   4.222121462225914e-002  
75.51899719238281   9.208130836486816   0.4099342525005341  1.337505698204041   5.802256584167481   0.4273860156536102  2.708084583282471   4.214133694767952e-002  
83.91000366210938   9.196262359619141   0.4093911945819855  1.335786700248718   5.799176692962647   0.4268693923950195  2.706451416015625   4.215647280216217e-002  
92.30100250244141   9.213265419006348   0.4101545214653015  1.338128447532654   5.807514190673828   0.4277283549308777  2.71068549156189    4.221603646874428e-002  
100.6920013427734   9.163029670715332   0.407885879278183   1.330831050872803   5.775251865386963   0.4254410266876221  2.695534229278565   4.204751178622246e-002  
109.0839996337891   9.144490242004395   0.4070722758769989  1.328153848648071   5.764679908752441   0.4246650040149689  2.690402746200562   4.198652133345604e-002  
117.4749984741211   9.114171028137207   0.4057718515396118  1.32369875907898    5.745044231414795   0.4233448505401611  2.681406497955322   4.190905019640923e-002  
125.8659973144531   9.149589538574219   0.407274603843689   1.328810453414917   5.766050815582275   0.4248199760913849  2.691139459609985   4.200970754027367e-002  
134.2570037841797   9.168668746948242   0.4081465899944305  1.331702351570129   5.777794361114502   0.4256783723831177  2.696741819381714   4.206346347928047e-002  
142.6479949951172   9.11380672454834    0.4057287871837616  1.323864817619324   5.740524291992188   0.4232001006603241  2.67945122718811    4.187140986323357e-002  
151.0390014648438   9.100893974304199   0.4051263332366943  1.321851253509522   5.729655265808106   0.4226666390895844  2.674278259277344   4.182597994804382e-002  
159.4299926757813   9.072731971740723   0.4039073586463928  1.317763328552246   5.713830471038818   0.4213792979717255  2.666974782943726   4.169051349163055e-002  
167.8209991455078   9.186164855957031   0.4089057147502899  1.334116697311401   5.786634922027588   0.4264728426933289  2.700879812240601   4.211126267910004e-002  
176.2129974365234   9.13982105255127    0.4068569839000702  1.327479124069214   5.76115083694458    0.4244593381881714  2.688895463943481   4.199059307575226e-002  
184.60400390625 9.146007537841797   0.4071221053600311  1.328468441963196   5.762693881988525   0.4247534275054932  2.689634084701538   4.1985172778368e-002    
192.9949951171875   9.18150806427002    0.4086942672729492  1.333438873291016   5.785679817199707   0.4262394905090332  2.700178623199463   4.207265004515648e-002  
201.3860015869141   9.134004592895508   0.4066038727760315  1.326677560806274   5.753909587860107   0.424109697341919   2.685543775558472   4.191514849662781e-002  
209.7769927978516   9.192599296569824   0.4091922044754028  1.335113883018494   5.792657852172852   0.4266164898872376  2.703598737716675   4.208896681666374e-002  
218.1679992675781   9.166966438293457   0.4080702364444733  1.331447958946228   5.776984214782715   0.4254603683948517  2.696239709854126   4.19912114739418e-002   
226.5590057373047   9.166423797607422   0.4080766439437866  1.331416010856628   5.771696090698242   0.4254250526428223  2.693812847137451   4.191195592284203e-002  
234.9510040283203   9.122139930725098   0.4060815274715424  1.325031995773315   5.74381160736084    0.4234589040279388  2.680959224700928   4.174426198005676e-002  
243.3419952392578   9.178729057312012   0.4085982143878937  1.333097338676453   5.783432006835938   0.4259471595287323  2.699411153793335   4.196531698107719e-002  
251.7330017089844   9.196023941040039   0.4093179702758789  1.335668444633484   5.792133331298828   0.4266210496425629  2.703416347503662   4.196692258119583e-002  
260.1239929199219   9.195613861083984   0.4093446731567383  1.33561098575592    5.790852546691895   0.4264806509017944  2.702755451202393   4.19374406337738e-002   
268.5150146484375   9.124658584594727   0.4061901867389679  1.325218439102173   5.749895572662354   0.4233379364013672  2.683579206466675   4.166891798377037e-002  
276.906005859375    9.071592330932617   0.4038631021976471  1.317633748054504   5.711780071258545   0.4209088683128357  2.666091680526733   4.146279022097588e-002  
285.2969970703125   9.090703010559082   0.4047099351882935  1.320350289344788   5.724553108215332   0.4218063056468964  2.671880960464478   4.148663952946663e-002  
293.68798828125 9.049410820007324   0.4028385281562805  1.314435601234436   5.699662208557129   0.4198987782001495  2.660340070724487   4.135752841830254e-002  
302.0790100097656   9.158493995666504   0.4077092707157135  1.330130934715271   5.770212650299072   0.4247544705867767  2.693133354187012   4.172087088227272e-002  
310.4700012207031   9.294267654418945   0.4137440025806427  1.350019454956055   5.85582971572876    0.4307662844657898  2.733232498168945   4.217509180307388e-002  
318.8609924316406   9.266000747680664   0.4124558866024017  1.34581983089447    5.838682651519775   0.429353654384613   2.724989175796509   4.206011816859245e-002  
327.2520141601563   9.227903366088867   0.4107420146465302  1.340180039405823   5.813295841217041   0.4277106523513794  2.713207006454468   4.191378504037857e-002  
335.6430053710938   9.248990058898926   0.4117128551006317  1.343235015869141   5.836093425750732   0.4286618232727051  2.72357988357544    4.200825467705727e-002  
344.0339965820313   9.200018882751465   0.4095089137554169  1.336208343505859   5.805673122406006   0.4264824092388153  2.709526300430298   4.185647144913673e-002  
352.4259948730469   9.162602424621582   0.4079090356826782  1.330750703811646   5.780079364776611   0.4248281121253967  2.697546243667603   4.17003221809864e-002   
360.8169860839844   9.165441513061523   0.4079831540584564  1.331099987030029   5.780121326446533   0.424967348575592   2.697607517242432   4.169800505042076e-002  
369.2070007324219   9.242767333984375   0.4114582240581513  1.342459917068481   5.828019142150879   0.4283893704414368  2.719994068145752   4.194791615009308e-002  
377.5989990234375   9.211434364318848   0.4100139439105988  1.337894320487976   5.801908493041992   0.4268820583820343  2.708046913146973   4.185103997588158e-002  
385.989990234375    9.168110847473145   0.4081266224384308  1.33171010017395    5.772421360015869   0.4250668585300446  2.694308280944824   4.166359454393387e-002  
394.3810119628906   9.162002563476563   0.4078731238842011  1.330778479576111   5.770648956298828   0.4247135519981384  2.693532466888428   4.165602847933769e-002  
402.7720031738281   9.219051361083984   0.4104039072990418  1.339054584503174   5.805272579193115   0.4273586571216583  2.709418296813965   4.186749085783958e-002  
411.1640014648438   9.225748062133789   0.4106448590755463  1.340008854866028   5.808595180511475   0.4276045560836792  2.711185216903687   4.189140349626541e-002  
425.0020141601563   9.11283016204834    0.4056265950202942  1.323553919792175   5.742629528045654   0.4226277768611908  2.680011749267578   4.150775447487831e-002  
433.3930053710938   9.15496826171875    0.4075464010238648  1.329663395881653   5.76693058013916    0.4244976043701172  2.691663980484009   4.165017232298851e-002  
441.7839965820313   9.179342269897461   0.4086317718029022  1.333258748054504   5.783347606658936   0.4256252646446228  2.699387073516846   4.177364706993103e-002  
450.1759948730469   9.202337265014648   0.4096647799015045  1.336641907691956   5.799064636230469   0.4267286956310272  2.706497669219971   4.189135506749153e-002  
458.5669860839844   9.126877784729004   0.4062632024288178  1.325594425201416   5.7450852394104 0.4234336316585541  2.681554317474365   4.164514690637589e-002  
466.9580078125  9.130221366882324   0.4063588082790375  1.326080322265625   5.750959873199463   0.4235436022281647  2.6843581199646 4.169851914048195e-002  
475.3489990234375   9.142138481140137   0.4069503247737885  1.32788360118866    5.753814697265625   0.4240946471691132  2.685687065124512   4.17218841612339e-002   
483.739990234375    9.144487380981445   0.4070816040039063  1.328163623809815   5.764283180236816   0.4243338704109192  2.69016432762146    4.180238768458366e-002  
492.1310119628906   9.213832855224609   0.4101627767086029  1.338177442550659   5.806262969970703   0.4273685812950134  2.709989309310913   4.204079136252403e-002  
500.5220031738281   9.151962280273438   0.4073929488658905  1.329235196113586   5.765473365783691   0.4247141480445862  2.691080808639526   4.187702387571335e-002  
508.9129943847656   9.133262634277344   0.4065472185611725  1.326548576354981   5.755089282989502   0.4239353835582733  2.685916900634766   4.184074699878693e-002  
517.3040161132813   9.194231033325195   0.4092318415641785  1.335361480712891   5.791540622711182   0.4266365468502045  2.703181505203247   4.204431921243668e-002  
525.6950073242188   9.174141883850098   0.4084053635597229  1.332433700561523   5.780707836151123   0.4258663356304169  2.697983264923096   4.203671962022781e-002  
534.0869750976563   9.127938270568848   0.4063973724842072  1.325674772262573   5.753820896148682   0.4238673448562622  2.685414791107178   4.189241677522659e-002  
542.4769897460938   9.228574752807617   0.4108735322952271  1.340509295463562   5.816771030426025   0.4283493161201477  2.714869976043701   4.227539896965027e-002  
550.8679809570313   9.247261047363281   0.4116438031196594  1.34306275844574    5.829936504364014   0.4292499721050263  2.720824480056763   4.234698414802551e-002  
559.2589721679688   9.259587287902832   0.4121484756469727  1.344773530960083   5.840207099914551   0.4296930134296417  2.725474834442139   4.239725694060326e-002  
567.6500244140625   9.236879348754883   0.4112152457237244  1.341552734375  5.824738502502441   0.4288162887096405  2.718418121337891   4.232741147279739e-002  
576.041015625   9.265199661254883   0.4123806655406952  1.345624566078186   5.837865352630615   0.4300332069396973  2.724727630615234   4.243086278438568e-002  
584.4310302734375   9.193467140197754   0.4092609882354736  1.335316061973572   5.791056632995606   0.4267773926258087  2.702801465988159   4.214197397232056e-002  
592.822021484375    9.178906440734863   0.408621221780777   1.333141565322876   5.783803462982178   0.4262367188930512  2.699366569519043   4.21367958188057e-002   
601.2139892578125   9.179999351501465   0.4086976051330566  1.333412766456604   5.781562805175781   0.4262183606624603  2.698424100875855   4.212524741888046e-002  
609.60498046875 9.158502578735352   0.4077076315879822  1.330240249633789   5.771774768829346   0.4252981841564179  2.693920612335205   4.206201061606407e-002  
617.9949951171875   9.168906211853027   0.4081432521343231  1.331776857376099   5.777164459228516   0.4257596433162689  2.696363210678101   4.212769865989685e-002  
626.385986328125    9.148199081420898   0.4072228968143463  1.328739166259766   5.764687061309815   0.4248482882976532  2.690601110458374   4.204926639795303e-002  
634.7769775390625   9.153997421264648   0.4075290560722351  1.329600691795349   5.76605749130249    0.4250805974006653  2.691195011138916   4.203818738460541e-002  
643.1680297851563   9.142102241516113   0.4070025384426117  1.327812790870667   5.758194923400879   0.4244733154773712  2.687539577484131   4.197685047984123e-002  
651.5599975585938   9.157526016235352   0.4076575040817261  1.33014190196991    5.771289825439453   0.4252424538135529  2.693483829498291   4.207025840878487e-002  
659.9509887695313   9.142055511474609   0.4069408476352692  1.327834606170654   5.75890064239502    0.4245132505893707  2.687950849533081   4.196911677718163e-002  
668.3410034179688   9.163941383361816   0.4079061448574066  1.331052899360657   5.773416519165039   0.425525963306427   2.694749593734741   4.208214208483696e-002  
676.7329711914063   9.214210510253906   0.4101268947124481  1.338269472122192   5.804011821746826   0.4277287721633911  2.70874834060669    4.224084317684174e-002  
685.1240234375  9.221725463867188   0.410546600818634   1.33942449092865    5.808478832244873   0.4280569553375244  2.710729837417603   4.224072396755219e-002  
693.5139770507813   9.195225715637207   0.4093619287014008  1.335615515708923   5.792295932769775   0.4269255101680756  2.703481912612915   4.215554893016815e-002  
701.905029296875    9.236662864685059   0.4111031889915466  1.341474533081055   5.820279121398926   0.4286713898181915  2.716408491134644   4.231745004653931e-002  
710.2969970703125   9.219303131103516   0.4103749394416809  1.33903431892395    5.809108257293701   0.4279004633426666  2.711240530014038   4.220414161682129e-002  
718.68798828125 9.196757316589356   0.4093507528305054  1.335767865180969   5.794125556945801   0.4269102811813355  2.704240798950195   4.217429086565971e-002  
727.0789794921875   9.169294357299805   0.4081831276416779  1.331677913665772   5.778267860412598   0.4257012009620667  2.696781396865845   4.20493595302105e-002   
735.468994140625    9.254044532775879   0.4119507372379303  1.344122529029846   5.83418083190918    0.4294586181640625  2.722884654998779   4.238997399806976e-002  
743.8610229492188   9.224509239196777   0.4105926156044006  1.339867234230042   5.812450408935547   0.4280983507633209  2.712637424468994   4.227783530950546e-002  
752.2520141601563   9.167038917541504   0.4080414175987244  1.331365466117859   5.778883457183838   0.4256396591663361  2.697120428085327   4.206839948892593e-002  
760.6430053710938   9.156136512756348   0.407585471868515   1.329828977584839   5.771244049072266   0.4251766502857208  2.693709135055542   4.204395413398743e-002  
769.0339965820313   9.206752777099609   0.4098866879940033  1.337259769439697   5.798995018005371   0.4273804128170013  2.706660270690918   4.218916967511177e-002  
777.4249877929688   9.185664176940918   0.4088890254497528  1.33407187461853    5.787529468536377   0.426471084356308   2.701387643814087   4.21074777841568e-002   
785.8159790039063   9.148477554321289   0.4072705209255219  1.328797459602356   5.764423847198486   0.4247606992721558  2.690322160720825   4.200183600187302e-002  
794.2069702148438   9.139849662780762   0.4068310558795929  1.327486157417297   5.760977268218994   0.4244396984577179  2.688838005065918   4.198827594518662e-002  
802.5980224609375   9.198716163635254   0.409488320350647   1.336077690124512   5.797767639160156   0.4270517528057098  2.705855131149292   4.215721413493156e-002  
810.989013671875    9.175697326660156   0.4084174335002899  1.332631826400757   5.781099796295166   0.425992488861084   2.698201894760132   4.206936806440353e-002  
819.3800048828125   9.106189727783203   0.4053537547588348  1.322664737701416   5.740387916564941   0.4229016602039337  2.679165840148926   4.18708510696888e-002   
827.77099609375 9.11962890625   0.4059470593929291  1.324671149253845   5.745753765106201   0.4235488474369049  2.681836843490601   4.189123585820198e-002  
836.1619873046875   9.221225738525391   0.4104022979736328  1.33923864364624    5.813970565795898   0.4279847741127014  2.713436365127564   4.224034398794174e-002  
849.9970092773438   9.109155654907227   0.4055195748806 1.323018074035645   5.738785743713379   0.4229097962379456  2.678738832473755   4.17560487985611e-002   
858.3880004882813   9.081585884094238   0.4043126106262207  1.319140315055847   5.720804691314697   0.4216950535774231  2.670202732086182   4.168836399912834e-002  
866.7789916992188   9.1737060546875 0.4083895683288574  1.332486510276794   5.779799461364746   0.4258598983287811  2.697497129440308   4.201843962073326e-002  
875.1699829101563   9.215715408325195   0.4102407991886139  1.33849024772644    5.806502342224121   0.4276199042797089  2.710031509399414   4.214433580636978e-002  
883.5609741210938   9.29750919342041    0.4138506650924683  1.350215315818787   5.858696460723877   0.4313125610351563  2.734477758407593   4.240995645523071e-002  
891.9520263671875   9.251111030578613   0.411830872297287   1.343641996383667   5.826048374176025   0.4292575418949127  2.719125270843506   4.226363822817802e-002  
900.343017578125    9.236968994140625   0.411191999912262   1.341637492179871   5.816394329071045   0.4285323023796082  2.71470046043396    4.218020662665367e-002  
908.7340087890625   9.18012809753418    0.4086549580097199  1.333361864089966   5.780932903289795   0.4260410964488983  2.698340177536011   4.198113456368446e-002  
917.125 9.18910026550293    0.4090204238891602  1.334587931632996   5.791236877441406   0.426427572965622   2.702847242355347   4.205641150474548e-002  
925.5159912109375   9.163248062133789   0.4078385829925537  1.330891489982605   5.775006771087647   0.4252764880657196  2.695378065109253   4.195348545908928e-002  
933.906982421875    9.184928894042969   0.4089162349700928  1.334069848060608   5.789799213409424   0.42618727684021    2.702196598052979   4.199947416782379e-002  
942.2979736328125   9.157343864440918   0.4076671004295349  1.330055475234985   5.770273208618164   0.4249707460403442  2.693178653717041   4.188660532236099e-002  
950.6890258789063   9.162631988525391   0.4078827202320099  1.330793499946594   5.77417516708374    0.4251722097396851  2.695005416870117   4.190302640199661e-002  
959.0800170898438   9.114273071289063   0.4057436585426331  1.323749780654907   5.743786811828613   0.4230408370494843  2.680756568908691   4.173881560564041e-002  
967.4710083007813   9.244811058044434   0.4115355014801025  1.34266197681427    5.823981761932373   0.4288525879383087  2.718071460723877   4.214448481798172e-002  
975.8619995117188   9.219685554504395   0.4104566872119904  1.339130640029907   5.808487892150879   0.4276332259178162  2.710957288742065   4.206658154726028e-002  
984.2529907226563   9.184207916259766   0.4088565707206726  1.33392071723938    5.792478561401367   0.4260831475257874  2.703508853912354   4.195259138941765e-002  
992.6439819335938   9.13871955871582    0.4068254828453064  1.327333569526672   5.761001586914063   0.4240987598896027  2.688708066940308   4.179005324840546e-002  
1001.034973144531   9.151439666748047   0.4073895514011383  1.329284429550171   5.767615795135498   0.4246693849563599  2.691930532455444   4.182363301515579e-002  
1009.424987792969   9.19940185546875    0.409492164850235   1.335996866226196   5.800271034240723   0.4267957508563995  2.70706057548523    4.198677837848663e-002  
1017.815979003906   9.255974769592285   0.4120437800884247  1.344139099121094   5.840244770050049   0.4293366670608521  2.725528001785278   4.220050573348999e-002  
1026.20703125   9.220073699951172   0.4104630351066589  1.339051723480225   5.81441593170166    0.4276903867721558  2.713610172271729   4.208677262067795e-002  
1034.598022460938   9.158895492553711   0.4077011644840241  1.330096125602722   5.776969432830811   0.4249850511550903  2.696006536483765   4.186514392495155e-002  
1042.989013671875   9.135567665100098   0.4066715240478516  1.326890826225281   5.756415843963623   0.423865556716919   2.686625719070435   4.174899682402611e-002  
1051.380981445313   9.150594711303711   0.4073532521724701  1.329049825668335   5.765689849853516   0.4245824813842773  2.691075325012207   4.179978370666504e-002  
1059.77197265625    9.146571159362793   0.4071609079837799  1.32847785949707    5.760791778564453   0.4242803156375885  2.688825607299805   4.17768582701683e-002   
1068.162963867188   9.131063461303711   0.4064978063106537  1.326229453086853   5.752644538879395   0.4236991405487061  2.684972286224365   4.172741994261742e-002  
1076.553955078125   9.098221778869629   0.4049918949604034  1.321496725082398   5.731342792510986   0.4222320318222046  2.675036668777466   4.162869602441788e-002  
1084.944946289063   9.169441223144531   0.4081719219684601  1.331780910491943   5.776838779449463   0.4254011511802673  2.696260452270508   4.184866324067116e-002  
1093.337036132813   9.187003135681152   0.4089777171611786  1.334323048591614   5.790809154510498   0.4261792898178101  2.702747344970703   4.196572676301003e-002  
1101.72802734375    9.179986953735352   0.4086208045482636  1.333386778831482   5.783829689025879   0.4258585274219513  2.699674844741821   4.191147163510323e-002  
1110.119018554688   9.200528144836426   0.4095506370067596  1.336296439170837   5.797418117523193   0.4267379641532898  2.7057945728302 4.19546514749527e-002   
1118.509033203125   9.158334732055664   0.4076752066612244  1.330214262008667   5.770383834838867   0.4248470067977905  2.693165063858032   4.180992022156715e-002  
1126.900024414063   9.194581985473633   0.4093466997146606  1.335410833358765   5.798298358917236   0.4264914393424988  2.706053495407105   4.194727912545204e-002  
1135.291015625  9.176510810852051   0.4084961414337158  1.3328697681427 5.778421401977539   0.4256733357906342  2.697108507156372   4.18514646589756e-002   
1143.682983398438   9.163573265075684   0.4079014360904694  1.330968260765076   5.773004055023193   0.4250616133213043  2.694518804550171   4.183558747172356e-002  
1152.072998046875   9.159396171569824   0.4077317416667938  1.330322265625  5.771379947662354   0.4248954653739929  2.693806171417236   4.181275144219399e-002  
1160.464965820313   9.165866851806641   0.4080128371715546  1.331347465515137   5.772171497344971   0.4252021610736847  2.694234848022461   4.181317612528801e-002  
1168.85595703125    9.151269912719727   0.407374233007431   1.329119086265564   5.760807991027832   0.424500435590744   2.688781023025513   4.176882281899452e-002  
1177.246948242188   9.141792297363281   0.4069608747959137  1.327713966369629   5.75624418258667    0.4241056740283966  2.68661379814148    4.173726961016655e-002  
1185.636962890625   9.130838394165039   0.406494677066803   1.326230525970459   5.751668930053711   0.4236221015453339  2.684362649917603   4.168353974819183e-002  
1194.027954101563   9.206241607666016   0.4098086059093475  1.337079763412476   5.802299022674561   0.4269396662712097  2.707928895950317   4.194400832056999e-002  
1202.4189453125 9.17149543762207    0.4083086550235748  1.332085609436035   5.776546001434326   0.4253532886505127  2.696049451828003   4.180750250816345e-002  
1210.81005859375    9.140050888061523   0.4068616330623627  1.327504873275757   5.760209083557129   0.4239790141582489  2.6883225440979 4.170787334442139e-002  
1219.201049804688   9.165439605712891   0.4079880714416504  1.331203103065491   5.77871561050415    0.4250532984733582  2.697003841400147   4.180311039090157e-002  
1227.593017578125   9.177500724792481   0.4085498750209808  1.332932233810425   5.783236026763916   0.4255987405776978  2.699163913726807   4.181493073701859e-002  
1235.984008789063   9.177756309509277   0.408606618642807   1.33305811882019    5.782862663269043   0.4256067276000977  2.699074268341065   4.182154312729836e-002  
1244.375    9.143049240112305   0.4070280194282532  1.327925682067871   5.766200542449951   0.4240804016590118  2.691066265106201   4.171686246991158e-002  
1252.765991210938   9.110544204711914   0.4055243730545044  1.323151469230652   5.742761135101318   0.422651082277298   2.680213212966919   4.159015789628029e-002  
1261.156982421875   9.153350830078125   0.4074757993221283  1.329340934753418   5.772144794464111   0.4244934320449829  2.693885564804077   4.173129424452782e-002  

我想将文件分成三部分 á 50 行：

data = pd.read_csv(file, sep='\t', names=['Time', '60Ni', '61Ni', '62Ni', '63Cu', '64Ni', '65Cu', '66Zn'], skiprows=3, nrows=50, index_col=False, dtype=float)
data2 = pd.read_csv(file, sep='\t', names=['Time', '60Ni', '61Ni', '62Ni', '63Cu', '64Ni', '65Cu', '66Zn'], skiprows=53, nrows=50, index_col=False, dtype=float)
data3 = pd.read_csv(file, sep='\t', names=['Time', '60Ni', '61Ni', '62Ni', '63Cu', '64Ni', '65Cu', '66Zn'], skiprows=103, nrows=50, index_col=False, dtype=float)

然后我用以下内容删除异常值：

cols = list(data.drop(columns='Time').columns)
datao = pd.DataFrame({'Time':data['Time']})
datao[cols] = data[cols].where(np.abs(stats.zscore(data[cols])) < 2)   

cols = list(data2.drop(columns='Time').columns)
data2o = pd.DataFrame({'Time':data2['Time']})
data2o[cols] = data2[cols].where(np.abs(stats.zscore(data2[cols])) < 2)
data2o[cols] = data2o[cols].mean()

cols = list(data3.drop(columns='Time').columns)
data3o = pd.DataFrame({'Time':data3['Time']})
data3o[cols] = data3[cols].where(np.abs(stats.zscore(data3[cols])) < 2)    
data3o[cols] = data3o[cols].mean()

到目前为止这有意义吗？

现在我想分别创建 datao、data2o 和 data3o 的平均值，从而得到 60Ni、61Ni、62Ni、63Cu、64Ni、65Cu、66Zn 的三个值。之后，我想再次对这三个值求平均值。我该怎么做？

我试图这样做：

mean_filtered_transposed = pd.DataFrame(data=np.mean(data)).T
mean_filtered_transposed['Time'] = pd.to_datetime(mean_filtered_transposed["Time"], unit='s')mean_filtered_transposed = pd.DataFrame(data=np.mean(data)).T
mean_filtered_transposed['Time'] = pd.to_datetime(mean_filtered_transposed["Time"], unit='s')
mean_filtered_transposed2 = pd.DataFrame(data=np.mean(data2)).T
mean_filtered_transposed2['Time'] = pd.to_datetime(mean_filtered_transposed["Time"], unit='s')
mean_filtered_transposed3 = pd.DataFrame(data=np.mean(data3)).T
mean_filtered_transposed3['Time'] = pd.to_datetime(mean_filtered_transposed3["Time"], unit='s')
mean_all = pd.concat(mean_filtered_transposed, mean_filtered_transposed2, mean_filtered_transposed3)

但是，这会导致：

“类型错误：第一个参数必须是 pandas 对象的可迭代对象，您传递了类型为“DataFrame”的对象”

Answer 1

基于文档：

objs：Series 或 DataFrame 对象的序列或映射

因此：

s1 = pd.Series(['a', 'b'])
s2 = pd.Series(['c', 'd'])
pd.concat([s1, s2])

结果：

但是：

s1 = pd.Series(['a', 'b'])
s2 = pd.Series(['c', 'd'])
pd.concat(s1, s2)

生成：