Mehrere Datensätze nach bestimmten Kriterien aus Daten aufteilen, die auf mehrere Datenrahmen aufgeteilt sind

Question

Ich habe mehrere Datenrahmen, von denen jeder Daten aus mehreren Quellen enthält. Ich muss in der Lage sein, Daten anhand bestimmter Kriterien zu plotten. Zum Beispiel möchte ich in der Lage sein, alle Datensätze mit season=="wet" zu plotten, aber auch die Kriterien canopy_understory=="c" von jedem Datenrahmen in einem Diagramm und die Spalte temp_sd als Fehlerleiste zu verwenden. Die Daten sind auf diese Art und Weise strukturiert, aufgrund der Art und Weise, wie sie gesammelt wurden und was als die vernünftigste Art der Analyse angesehen wurde.

Mein Versuch, Daten zu extrahieren with Verwendung hat:

with(valley_ls,temp_mean[season=="dry"&canopy_understory=="c"]) 
with(valley_ls,hour[season=="dry"&canopy_understory=="c"]) 
with(ridge_ls,temp_mean[season=="dry"&canopy_understory=="c"]) 
with(ridge_ls,hour[season=="wet"&canopy_understory=="u"]) 

Dies wird mir die hour oder temp_mean, die die Kriterien Ich möchte treffen, aber ich muss in der Lage sein, zu extrahieren und Handlung die temp_mean und die temp_sd als eine Fehlerleiste. Ich habe versucht, diese in neue Datenrahmen zu unterteilen, aber das ist fehleranfällig und angespannt.

Ein Beispiel für das Plotten, die ich ist, die mehrere Datenrahmen getan haben mit diesem:

ggplot(data=ridge_u_w_summary,aes(x = times,y=means))+ 
    geom_errorbar(data=ridge_u_w_summary,aes(ymin=means-sd,ymax=means+sd),colour="red")+ 
    geom_line(aes(y=means),colour="red")+ 
    geom_line(data = valley_u_w_summary,aes(x=times,y=means))+ 
    geom_errorbar(data=valley_u_w_summary,aes(ymin=means-sd,ymax=means+sd))+ 
    geom_line(data = edge_u_w_summary,aes(x=times,y=means),colour="blue")+ 
    theme_classic()+ 
    geom_errorbar(data=edge_u_w_summary,aes(ymin=means-sd,ymax=means+sd),colour="blue")+ 
    labs(x="Time",y=expression("Temperature in understory May to December *C")) 

Welche das, was ich will, so etwas wie dieses Diagramm erzeugt:

Die Regelung über Werke gut, aber unhaltbar für die Verwendung mit anderen Daten, weil es einfach ist, die Aufteilung in viele Datenrahmen zu vermasseln. Ich möchte in der Lage sein, mehrere Diagramme mit denselben Datenrahmen basierend auf verschiedenen Kriterien zu erstellen.

dput von dump(list="valley_ls",file="dump_valley") :

valley_ls <- 
structure(list(canopy_understory = c("c", "c", "c", "c", "c", 
"c", "c", "c", "c", "c", "c", "c", "c", "c", "c", "c", "c", "c", 
"c", "c", "c", "c", "c", "c", "c", "c", "c", "c", "c", "c", "c", 
"c", "c", "c", "c", "c", "c", "c", "c", "c", "c", "c", "c", "c", 
"c", "c", "c", "c", "c", "u", "u", "u", "u", "u", "u", "u", "u", 
"u", "u", "u", "u", "u", "u", "u", "u", "u", "u", "u", "u", "u", 
"u", "u", "u", "u", "u", "u", "u", "u", "u", "u", "u", "u", "u", 
"u", "u", "u", "u", "u", "u", "u", "u", "u", "u", "u", "u", "u", 
"u", "u", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA), season = c("dry", "dry", "dry", 
"dry", "dry", "dry", "dry", "dry", "dry", "dry", "dry", "dry", 
"dry", "dry", "dry", "dry", "dry", "dry", "dry", "dry", "dry", 
"dry", "dry", "dry", "wet", "wet", "wet", "wet", "wet", "wet", 
"wet", "wet", "wet", "wet", "wet", "wet", "wet", "wet", "wet", 
"wet", "wet", "wet", "wet", "wet", "wet", "wet", "wet", "wet", 
NA, "dry", "dry", "dry", "dry", "dry", "dry", "dry", "dry", "dry", 
"dry", "dry", "dry", "dry", "dry", "dry", "dry", "dry", "dry", 
"dry", "dry", "dry", "dry", "dry", "dry", "wet", "wet", "wet", 
"wet", "wet", "wet", "wet", "wet", "wet", "wet", "wet", "wet", 
"wet", "wet", "wet", "wet", "wet", "wet", "wet", "wet", "wet", 
"wet", "wet", "wet", NA, "dry", "dry", "dry", "dry", "dry", "dry", 
"dry", "dry", "dry", "dry", "dry", "dry", "wet", "wet", "wet", 
"wet", "wet", "wet", "wet", "wet", "wet", "wet", "wet", "wet", 
"wet", "wet", "wet", "wet", "wet", "wet", "wet", "wet", "wet", 
"wet", "wet", "wet", NA), hour = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 
10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 1, 
2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 
20, 21, 22, 23, 24, NA, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 
13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 1, 2, 3, 4, 5, 
6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 
23, 24, NA, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 1, 2, 
3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 
20, 21, 22, 23, 24, NA), temp_mean = c(21.9729388942774, 21.9202365308804, 
21.5160349854227, 21.6135348226018, 21.1698250728863, 21.3997371879106, 
21.7561224489796, 23.4584756898817, 25.5064233576642, 27.1829172141919, 
28.0613372093023, 28.7192358366271, 29.0794202898551, 28.9577075098814, 
28.4787572254335, 27.3324538258575, 26.3749638205499, 25.0135883905013, 
24.0727930535456, 23.5505277044855, 22.8426917510854, 22.7254617414248, 
22.49001447178, 22.9443645083933, 23.8475672877847, 23.6520574162679, 
23.6787136294028, 23.4181818181818, 23.5110260336907, 23.3245229007634, 
23.7951145038168, 25.3284351145038, 25.8448854961832, 27.8920801526718, 
28.0074809160305, 28.9004770992366, 28.6725190839695, 28.6689408396947, 
28.1945038167939, 27.1498808956646, 26.8738131699847, 25.4554337464252, 
25.493415007657, 24.6676358436606, 24.7966309341501, 24.2493803622498, 
24.2797856049005, 24.0876998769988, NA, 23.1587893864013, 23.0023631840796, 
22.7586842105263, 22.6404228855721, 22.4468421052632, 22.4090796019901, 
22.6627140974967, 23.479202988792, 24.4139841688654, 25.2576059850374, 
25.9127799736495, 26.2339152119701, 26.4725, 26.4246882793017, 
26.1284403669725, 25.7063511830635, 25.3211764705882, 24.8449004975124, 
24.4806535947712, 24.1813432835821, 23.9767320261438, 23.7926616915423, 
23.5675816993464, 23.7533333333333, 24.1737847222222, 23.9264961636829, 
24.0318639798489, 23.716010230179, 23.8171284634761, 23.5848191543556, 
23.9746231155779, 24.5888436067244, 25.1335427135678, 25.9691288843607, 
26.2968592964824, 26.6237391747326, 26.7585427135678, 26.5575140091696, 
26.4639447236181, 25.9500254971953, 25.8959748427673, 25.2427332993371, 
25.3163727959698, 24.7879591836735, 24.8969773299748, 24.4647448979592, 
24.5764483627204, 24.2546432062561, NA, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 24.3333333333333, 0, 24.25, 0, 24.0166666666667, 
0, 24.1583333333333, 0, 25.4, 0, 26.2333333333333, 0, 27.2109375, 
0, 27.375, 0, 26.2946428571429, 0, 24.9107142857143, 0, 24.7142857142857, 
0, 24.475, 0, NA), temp_sd = c(7.10368938706592, 6.31619559434987, 
6.63273716936668, 5.98207526384219, 6.81785819259387, 6.09008468822777, 
6.42905917510137, 6.12792441805719, 5.89400673610928, 4.93074376846361, 
5.68493137940986, 4.53882099065438, 5.67276330328425, 4.86289494479903, 
5.0064903940218, 4.50620321541371, 5.23548052610922, 5.73166481558604, 
6.9423848917103, 6.25916235030702, 7.02150223339283, 6.63198273255056, 
6.30121694018913, 1.16737424849318, 0.974447902019749, 0.883662726834489, 
1.1694960633107, 1.00119820290862, 0.950686394394519, 0.960508895273812, 
1.02435507152398, 1.9800105189055, 1.77743259093255, 2.28365035950242, 
2.41005581403749, 2.52263637550233, 2.58958905490024, 2.48794401404523, 
2.37928117718197, 1.9660860877379, 1.79705886384754, 1.22734366140094, 
1.39948592913543, 0.874295812773333, 1.97436507929567, 0.831676233519675, 
1.18463655086496, 0.809942069607868, NA, 1.22357269970187, 1.3197350152676, 
1.37832968945031, 1.34012520382106, 1.34142100192936, 1.34726498418677, 
1.31592378988696, 1.28713308691543, 1.42138403898271, 1.70993228486995, 
2.07113789555289, 2.01605834952938, 2.08999601275536, 1.93479577003559, 
1.71785163242327, 1.58992997264445, 1.56194809778642, 1.4394673032447, 
1.37240648943917, 1.29257875472938, 1.31372428816748, 1.29167595764256, 
1.31947555529684, 1.55319421073715, 0.875684015185201, 0.885810900384003, 
0.968966012850972, 0.903583472065802, 0.929241275404384, 0.928693033054035, 
0.885940062806948, 0.812794500845774, 1.05374707833118, 1.20584906712117, 
1.52863738732854, 1.49350509511768, 1.764425507212, 1.4427075343768, 
1.50555166076425, 1.11778354361208, 1.10212019137791, 0.916392369153426, 
0.963107068443978, 0.845676581451727, 0.971090795785566, 0.855977353338137, 
0.980098036879563, 0.959837031977444, NA, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0.711303297442365, 0, 0.490990253030983, 0, 0.599230657553818, 
0, 0.512057009474903, 0, 1.95724387122008, 0, 1.75564565521254, 
0, 2.59194214104019, 0, 2.33853586673371, 0, 1.64200213656485, 
0, 0.903290687394742, 0, 0.498624481575437, 0, 0.668487097856047, 
0, NA)), row.names = c(NA, -135L), vars = list(quote(canopy_understory), 
    quote(season)), drop = TRUE, .Names = c("canopy_understory", 
"season", "hour", "temp_mean", "temp_sd"), class = c("grouped_df", 
"tbl_df", "tbl", "data.frame")) 

Ausgabe von dump(list="ridge_ls",file="dump_ridge")

ridge_ls <- 
structure(list(canopy_understory = c("c", "c", "c", "c", "c", 
"c", "c", "c", "c", "c", "c", "c", "c", "c", "c", "c", "c", "c", 
"c", "c", "c", "c", "c", "c", "c", "c", "c", "c", "c", "c", "c", 
"c", "c", "c", "c", "c", "c", "c", "c", "c", "c", "c", "c", "c", 
"c", "c", "c", "c", "c", "u", "u", "u", "u", "u", "u", "u", "u", 
"u", "u", "u", "u", "u", "u", "u", "u", "u", "u", "u", "u", "u", 
"u", "u", "u", "u", "u", "u", "u", "u", "u", "u", "u", "u", "u", 
"u", "u", "u", "u", "u", "u", "u", "u", "u", "u", "u", "u", "u", 
"u", "u"), season = c("dry", "dry", "dry", "dry", "dry", "dry", 
"dry", "dry", "dry", "dry", "dry", "dry", "dry", "dry", "dry", 
"dry", "dry", "dry", "dry", "dry", "dry", "dry", "dry", "dry", 
"wet", "wet", "wet", "wet", "wet", "wet", "wet", "wet", "wet", 
"wet", "wet", "wet", "wet", "wet", "wet", "wet", "wet", "wet", 
"wet", "wet", "wet", "wet", "wet", "wet", NA, "dry", "dry", "dry", 
"dry", "dry", "dry", "dry", "dry", "dry", "dry", "dry", "dry", 
"dry", "dry", "dry", "dry", "dry", "dry", "dry", "dry", "dry", 
"dry", "dry", "dry", "wet", "wet", "wet", "wet", "wet", "wet", 
"wet", "wet", "wet", "wet", "wet", "wet", "wet", "wet", "wet", 
"wet", "wet", "wet", "wet", "wet", "wet", "wet", "wet", "wet", 
NA), hour = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 
11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 
24L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 
14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, NA, 1L, 
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 
16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 1L, 2L, 3L, 4L, 
5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 
19L, 20L, 21L, 22L, 23L, 24L, NA), .Label = c("[0,100]", "(100,200]", 
"(200,300]", "(300,400]", "(400,500]", "(500,600]", "(600,700]", 
"(700,800]", "(800,900]", "(900,1e+03]", "(1e+03,1.1e+03]", "(1.1e+03,1.2e+03]", 
"(1.2e+03,1.3e+03]", "(1.3e+03,1.4e+03]", "(1.4e+03,1.5e+03]", 
"(1.5e+03,1.6e+03]", "(1.6e+03,1.7e+03]", "(1.7e+03,1.8e+03]", 
"(1.8e+03,1.9e+03]", "(1.9e+03,2e+03]", "(2e+03,2.1e+03]", "(2.1e+03,2.2e+03]", 
"(2.2e+03,2.3e+03]", "(2.3e+03,2.4e+03]"), class = "factor"), 
    temp_mean = c(22.562356127285, 21.8575176589304, 22.2091712707182, 
    21.4594349142281, 21.8741436464088, 21.2627648839556, 22.5725966850829, 
    23.8943491422805, 26.5008830022075, 27.0156407669021, 28.582398239824, 
    28.2173562058527, 29.3534065934066, 28.4145454545455, 28.5924259055982, 
    26.9787878787879, 26.7398685651698, 24.8841253791709, 24.7435307017544, 
    23.5766430738119, 23.8053728070175, 22.9302325581395, 23.238048245614, 
    22.4414285714286, 21.217952694843, 20.0397517730496, 23.4641860465116, 
    19.8450354609929, 23.2626356589147, 19.7900423728814, 24.0725581395349, 
    21.725918079096, 26.9862015503876, 23.7948799435028, 28.9759689922481, 
    24.5474390674673, 29.5715838509317, 24.3418226774991, 28.5812111801242, 
    23.115411806292, 26.9599378881988, 21.66085572843, 25.3357142857143, 
    20.9439179632249, 24.6169517884914, 20.5703218960028, 24.1321928460342, 
    20.0532657657658, NA, 22.7831422791639, 22.5624888093107, 
    22.2762711864407, 22.232139659803, 21.9816550348953, 22.0190689346464, 
    22.0713858424726, 22.9452103849597, 23.977390438247, 25.0091397849462, 
    25.7459163346614, 26.1808968609865, 26.4856007944389, 26.529226618705, 
    26.3300893743793, 25.837376460018, 25.3583580613254, 24.7221422142214, 
    24.2077304261645, 23.820702070207, 23.5147817460317, 23.3325225225225, 
    23.065376984127, 22.8946456692913, 23.837513397642, 23.646668909825, 
    23.6674418604651, 23.4305079044736, 23.4649224806202, 23.2881367292225, 
    23.5646034816248, 24.3536863270777, 24.9369439071567, 25.8866957104558, 
    26.5365570599613, 26.7293565683646, 27.253488372093, 26.7179624664879, 
    27.0480620155039, 26.019235924933, 26.193786407767, 25.1097217566209, 
    25.2966990291262, 24.5485417365069, 24.6792233009709, 24.2033199195171, 
    24.2778210116732, 23.9984624846248, NA), temp_sd = c(2.73648774464832, 
    3.89501902764261, 1.17914861593683, 3.84962929916136, 1.21627739822434, 
    3.843890078235, 1.48694927255381, 4.53475560968754, 2.4692449230815, 
    5.31072172311035, 2.7801646331622, 5.60552770772567, 3.00665642895969, 
    5.37991344736766, 2.54329494228649, 4.9109846279159, 2.01316086028232, 
    4.31184236532998, 1.40152881522735, 3.98898666713388, 1.17969636144613, 
    3.85727479873907, 1.1230885583311, 3.52267091349933, 7.52465558906129, 
    8.51904516252295, 0.89825806034385, 8.44060231674709, 0.894435454152911, 
    8.40140354279228, 0.954983885810659, 9.28188638752829, 2.08714908301206, 
    10.2555288869657, 2.55244904907137, 10.6329140791161, 2.78976411219072, 
    10.5641962864403, 2.62101883698402, 9.99645036090208, 2.06715648209951, 
    9.26879044865175, 1.22008755481441, 8.9245381254764, 0.956910613039714, 
    8.76186042815369, 0.872979293848191, 8.86368969220654, NA, 
    1.07371319492319, 1.09881749779836, 1.21307549226642, 1.2598629477623, 
    1.31286527191395, 1.36683838145348, 1.4137155267231, 1.42622231911717, 
    1.67860763496765, 1.79425260160877, 2.07042827387483, 2.10731458932958, 
    2.25919838602871, 2.13163564157989, 2.00443799155384, 1.78306510492528, 
    1.6813351820614, 1.41841025766038, 1.31504560496238, 1.16441372650497, 
    1.13358486644718, 1.04842014209596, 1.04971819964, 1.03129409017733, 
    0.781095011320959, 0.81578111612132, 0.84436800431466, 0.852579597106629, 
    0.861309791588296, 0.900921426522036, 0.850538183149708, 
    0.86563230808076, 1.13990715262908, 1.29807379664268, 1.71755587993833, 
    1.64101678624236, 1.995102606277, 1.63987330277186, 1.83556454743413, 
    1.35735241712701, 1.49013625660173, 1.02009949230349, 1.07160411808372, 
    0.800509386066778, 0.854705093200672, 0.765802355814258, 
    0.819364989149883, 0.77707386292288, NA)), class = c("grouped_df", 
"tbl_df", "tbl", "data.frame"), row.names = c(NA, -98L), vars = list(
    quote(canopy_understory), quote(season)), drop = TRUE, .Names = c("canopy_understory", 
"season", "hour", "temp_mean", "temp_sd")) 

Answer 1

Was ich schließlich tat, war zu Teilmengen von jeder Bedingung zu erstellen, die ich grafisch darstellen wollte. Das ist nicht so elegant wie ich es wollte, aber es funktioniert.

valley_dry_canopy_subset <-subset(valley_ls,season=="dry"&canopy_understory=="c") 
valley_wet_canopy_subset <-subset(valley_ls,season=="wet"&canopy_understory=="c") 
valley_dry_understory_subset <-subset(valley_ls,season=="dry"&canopy_understory=="u") 
valley_wet_understory_subset <-subset(valley_ls,season=="wet"&canopy_understory=="u") 

ridge_dry_canopy_subset <-subset(ridge_ls,season=="dry"&canopy_understory=="c") 
ridge_wet_canopy_subset <-subset(ridge_ls,season=="dry"&canopy_understory=="c") 
ridge_dry_understory_subset <-subset(ridge_ls,season=="dry"&canopy_understory=="u") 
ridge_wet_understory_subset <-subset(ridge_ls,season=="dry"&canopy_understory=="u") 

edge_dry_canopy_subset <-subset(edge_ls,season=="dry"&canopy_understory=="c") 
edge_wet_canopy_subset <-subset(edge_ls,season=="dry"&canopy_understory=="c") 
edge_dry_understory_subset <-subset(edge_ls,season=="dry"&canopy_understory=="u") 
edge_wet_understory_subset <-subset(edge_ls,season=="dry"&canopy_understory=="u") 

Eines der Grundstücke kann wie folgt grafisch dargestellt werden:

ggplot(data=na.omit(valley_wet_canopy_subset),aes(x = hour,y=temp_mean))+ 
    geom_errorbar(aes(ymin=temp_mean-temp_sd,ymax=temp_mean+temp_sd),colour="black")+ 
    geom_line(aes(y=temp_mean),colour="black",size=1)+ 
    geom_errorbar(data=ridge_wet_canopy_subset,aes(ymin=temp_mean-temp_sd,ymax=temp_mean+temp_sd),colour="red")+ 
    geom_line(aes(y=temp_mean),colour="black",size=1)+ 
    geom_errorbar(data=edge_wet_canopy_subset,aes(ymin=temp_mean-temp_sd,ymax=temp_mean+temp_sd),colour="blue")+ 
    theme_classic()+ 
    labs(x="Time",y="Temperature in canopy May to December")