개별 세포를 제공하고 싶은 배열의 두 열이 있습니다. 예를 들어 내 열은 현재 다음과 같습니다.
| NDVI | 날짜 |
|---|---|
| [0.1,0.5,0.7] | [1.54E12, 1.54E12, 1.54E12] |
이것을 가져다가 다시 포맷하려면 어떻게해야합니까?
| NDVI | 날짜 |
|---|---|
| 0.1 | 1.54E12 |
| 0.5 | 1.54E12 |
| 0.7 | 1.54E12 |
다음은 몇 가지 예시 데이터입니다.
df <- structure(list(NDVIs = c("[0.0048532285033119]", "[0.031866426092985685, 0.0346768172783618, 0.05690584716758292, 0.05963840093735323, 0.049984507125651834, 0.05225985971236913, 0.05248901349444936, 0.05518163825042716, -0.010183523082805207, -0.001665440442765531, 0.03987908018516375, 0.04187215406831169, 0.08414429526637883, 0.08715243094329189, -0.005957091678983289, -0.009527640910524507, 0.010492166097587687, 0.026020594673257052, 0.002104522074938855, 0.003507257657688491, 0.06828452153139898, 0.07606416388481754, 0.06883156241096627, 0.07718980197474816, 0.06544808609317253, 0.07474777221051583, 0.10378917503028039, 0.11123383912244203, 0.05613527636023197, 0.06331642130827059, 0.06924611219668912, 0.07666941206343858, 0.06120038033501253, 0.07040186289113536, 0.0641993427579592, 0.07613137403151546, 0.02045492869437104, 0.0331589149611709, 0.07758880477807421, 0.08753787069131283, 0.07957631716729259, 0.08952965234407557, 0.0885082162194797, 0.09848859431952328, -0.0020876210575472842, 0.00246885618171861, 0.10852078141016781, 0.11765974025773, -0.026210051068679536, -0.017421882870782675, 0.10807407562845053, 0.11710267730586506, 0.11281567251547685, 0.12184561048692327, 0.07186643839535878, 0.07790008153091242, 0.022632037271678205, 0.0365365472967711]",
"[0.03529428376870003, 0.009603157045076827, 0.010105041611001576, 0.022109721139215967, 0.04320847194846547, 0.06382705400539401, 0.01733482969659961]",
"[0.05067307147600608, 0.04650335539685854, 0.04230580325409252, 0.019941600277439516, 0.03878433876933318, 0.027594882066713636, 0.032576179777168805, 0.006187539680589851, 0.0018615082099339225, 0.042639901745788876, 0.04555515255591705, 0.05557934077121789, 0.03141074118001885, -0.024594166196115066, 0.06226281017212869, 0.02775252318220509]",
"[0.22694578827413947, 0.30629362044983743, 0.26378399913683515, 0.2582198975762179, 0.25641849395215666, 0.23752142045041516, 0.23781654568851535, 0.14139758147170572, 0.2541489741719387, 0.2419639056967162, 0.2275033844898179, 0.24470134691705184, 0.22140420350534376, 0.22465304694290103, 0.21744809821978436, 0.20724760985497206, 0.19287780410696884]",
"[0.02437980239793386, 0.046501630291612854, 0.03515690678492754, 0.03996495641681273, 0.02565338402629212, 0.02522057544087444, 0.016355304453160305, 0.010076012002045382, 0.024906389352811975, 0.040025952670788865, 0.05043572220046672, 0.0676703068532929, 0.08040324690810197, 0.011653761506917892, 0.07901386245569544, 0.14084622762340893, 0.13315404483239526, 0.14297013211925677]",
"[0.0696531704758789, 0.06968717739514622, 0.060495302532228894, 0.060465281863641605, 0.050631820224526766, 0.05069794600355197, 0.04996845148127263, 0.050053255940312645, 0.052401506092804355, 0.0524735297646711, 0.040763890820717345, 0.04078582273414091, 0.04106548840491197, 0.04103821234740117, 0.003195298620254946, -0.005673033858736476, -0.0018119432210428274, 0.0015232350000433797, 0.04386980266596469, 0.044086120151773434, 0.046401011127926925, 0.04647825535002269, 0.03833234785505313, 0.03824161507110303, 0.06037120877605433, 0.06055975876554486, 0.0592133770889435, 0.05950182701095346, 0.05530416996051339, 0.05463335706292855, 0.033097906541426636, 0.02467463272473935, 0.0580151510674638, 0.05815851281926995, 0.05560044632496825, 0.05621848408403043]",
"[0.40218207770330455, 0.3833707257903159, 0.3498789365559936, 0.3415851169240495, 0.11857246658703605, 0.09110434200774196, 0.02929675584172094, 0.13218157545304937, 0.00568591277213531, 0.2312335955409189, 0.06118283356210741, 0.23127376963601848, 0.07698393284205111, 0.05667080989824748, 0.11169816100135183, 0.018740255299188605, 0.07543980191846927]",
"[0.04179551280868712, 0.0383419807710962, 0.0504998226331591, 0.0011002529304645489, 0.031002814569137, 0.022506919207544558, 0.03933692454785477, 0.029375815795034198, 0.04674437953418841, 0.04864569790993668, 0.036774224525189025, 0.002999267453586999, 0.03965538865956306, 0.04553202255868567, 0.012738284285019974, 0.05355605970787331, 0.03678091244450905]",
"[0.023817638054132135, 0.02855430777145022, 0.08243891605296151, 0.014681590484211679, 0.14321736621086276, 0.07733703130141825, 0.015297125457766068, 0.10985901950753231, 0.12587086535155378, 0.13064566485984275, 0.1297667968282656]"
), dates = c("[1.527502095E12]", "[1.544955875E12, 1.544955875E12, 1.545126378E12, 1.545126378E12, 1.545394367E12, 1.545394367E12, 1.545561339E12, 1.545561339E12, 1.545820928E12, 1.545820928E12, 1.545993046E12, 1.545993046E12, 1.546250253E12, 1.546250253E12, 1.546425701E12, 1.546425701E12, 1.546684843E12, 1.546684843E12, 1.546854495E12, 1.546854495E12, 1.547112218E12, 1.547112218E12, 1.547288454E12, 1.547288454E12, 1.547546364E12, 1.547546364E12, 1.547718166E12, 1.547718166E12, 1.547980939E12, 1.547980939E12, 1.548153141E12, 1.548153141E12, 1.548413046E12, 1.548413046E12, 1.548585114E12, 1.548585114E12, 1.548842378E12, 1.548842378E12, 1.549019277E12, 1.549019277E12, 1.549276707E12, 1.549276707E12, 1.549447219E12, 1.549447219E12, 1.549708493E12, 1.549708493E12, 1.549880513E12, 1.549880513E12, 1.550138768E12, 1.550138768E12, 1.550312936E12, 1.550312936E12, 1.55057479E12, 1.55057479E12, 1.550745218E12, 1.550745218E12, 1.551007067E12, 1.551007067E12]",
"[1.544868896E12, 1.545732881E12, 1.546164507E12, 1.546599228E12, 1.547030531E12, 1.547460976E12, 1.547892521E12]",
"[1.562323826E12, 1.562755476E12, 1.563185103E12, 1.563624031E12, 1.56405523E12, 1.564483439E12, 1.564915837E12, 1.565347309E12, 1.565777661E12, 1.566215882E12, 1.566643642E12, 1.567097272E12, 1.567507638E12, 1.568369457E12, 1.56880789E12, 1.569668195E12]",
"[1.552392943E12, 1.552819566E12, 1.553251718E12, 1.553682704E12, 1.554112987E12, 1.55454323E12, 1.554975918E12, 1.555408185E12, 1.555841425E12, 1.556271571E12, 1.55670391E12, 1.557135402E12, 1.557568058E12, 1.557998903E12, 1.558863212E12, 1.55929586E12, 1.559728791E12]",
"[1.561454836E12, 1.561888229E12, 1.562320207E12, 1.562751856E12, 1.563181463E12, 1.563618614E12, 1.564046906E12, 1.564480274E12, 1.564912267E12, 1.565343999E12, 1.565773615E12, 1.566210466E12, 1.566639283E12, 1.567072243E12, 1.567504618E12, 1.567936832E12, 1.568366042E12, 1.568802771E12]",
"[1.561028124E12, 1.561028124E12, 1.561460566E12, 1.561460566E12, 1.561887116E12, 1.561887116E12, 1.562321887E12, 1.562321887E12, 1.562750997E12, 1.562750997E12, 1.563188512E12, 1.563188512E12, 1.563622208E12, 1.563622208E12, 1.564052361E12, 1.564052361E12, 1.564478817E12, 1.564478817E12, 1.564913968E12, 1.564913968E12, 1.565342227E12, 1.565342227E12, 1.565780829E12, 1.565780829E12, 1.566212692E12, 1.566212692E12, 1.566646344E12, 1.566646344E12, 1.567071334E12, 1.567071334E12, 1.567508507E12, 1.567508507E12, 1.567935649E12, 1.567935649E12, 1.568374212E12, 1.568374212E12]",
"[1.558863212E12, 1.55929586E12, 1.559728791E12, 1.5601599E12, 1.560589582E12, 1.561026607E12, 1.561454836E12, 1.561888229E12, 1.562320207E12, 1.562751856E12, 1.563181463E12, 1.563618614E12, 1.564047988E12, 1.564480274E12, 1.564912267E12, 1.565343999E12, 1.565773615E12]",
"[1.568719125E12, 1.569150328E12, 1.569583549E12, 1.570013418E12, 1.570451296E12, 1.570878011E12, 1.571311086E12, 1.571742422E12, 1.572172948E12, 1.572604827E12, 1.573038304E12, 1.573470317E12, 1.573899161E12, 1.574334225E12, 1.575196752E12, 1.57562775E12, 1.5760617E12]",
"[1.545124633E12, 1.545561224E12, 1.545990899E12, 1.546423114E12, 1.546853425E12, 1.547287051E12, 1.547718865E12, 1.548155787E12, 1.548586075E12, 1.549015326E12, 1.549447719E12]"
)), row.names = c(NA, -10L), class = "data.frame")
우리는 수없는 문자 추출 할 수 ]을 성공 그 [와 str_extract_all반환 list, 다음 unnest열을, 그리고에서 열 값을 분할 ,(하나 이상의 공백 뒤에 \\s+포함)separate_rows
library(dplyr)
library(stringr)
library(tidyr)
df %>%
mutate(across(everything(), str_extract_all, "(?<=\\[)[^]]+")) %>%
unnest(c(NDVIs, dates)) %>%
separate_rows(c(NDVIs, dates), sep=",\\s+", convert = TRUE)
-산출
# A tibble: 198 x 2
# NDVIs dates
# <dbl> <dbl>
# 1 0.00485 1527502095000
# 2 0.0319 1544955875000
# 3 0.0347 1544955875000
# 4 0.0569 1545126378000
# 5 0.0596 1545126378000
# 6 0.0500 1545394367000
# 7 0.0523 1545394367000
# 8 0.0525 1545561339000
# 9 0.0552 1545561339000
#10 -0.0102 1545820928000
# … with 188 more rows
(가) 또는 []모든 요소가 아닌, 다음으로 이미 기존 제거 str_remove_all및 사용을separate_rows
df %>%
mutate(across(everything(), str_remove_all, "\\[|\\]")) %>%
separate_rows(c(NDVIs, dates), sep=",\\s+", convert = TRUE)
# A tibble: 198 x 2
# NDVIs dates
# <dbl> <dbl>
# 1 0.00485 1527502095000
# 2 0.0319 1544955875000
# 3 0.0347 1544955875000
# 4 0.0569 1545126378000
# 5 0.0596 1545126378000
# 6 0.0500 1545394367000
# 7 0.0523 1545394367000
# 8 0.0525 1545561339000
# 9 0.0552 1545561339000
#10 -0.0102 1545820928000
# … with 188 more rows
이 기사는 인터넷에서 수집됩니다. 재 인쇄 할 때 출처를 알려주십시오.
침해가 발생한 경우 연락 주시기 바랍니다[email protected] 삭제
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