1
2つの米国状態マップをプロットするのが理想的ですが、同じカラースケールを持つデータフレームがあります。あなたが見ることができるように例えば1.6の値は両方のマップ私は2つのマップに同じ色の罫線をプロットしてプロットすることができます。
library(plotly)
library(tidyverse)
df <- structure(list(stateID = 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, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L,
33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L,
46L, 47L, 48L, 49L, 50L, 51L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L,
9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L,
22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L,
35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L,
48L, 49L, 50L, 51L), .Label = c("AK", "AL", "AR", "AZ", "CA",
"CO", "CT", "DC", "DE", "FL", "GA", "HI", "IA", "ID", "IL", "IN",
"KS", "KY", "LA", "MA", "MD", "ME", "MI", "MN", "MO", "MS", "MT",
"NC", "ND", "NE", "NH", "NJ", "NM", "NV", "NY", "OH", "OK", "OR",
"PA", "RI", "SC", "SD", "TN", "TX", "UT", "VA", "VT", "WA", "WI",
"WV", "WY"), class = "factor"), category = structure(c(1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L), .Label = c("small", "large"), class = "factor"),
values = c(1.49852796690539, 1.149561395403, 1.24566150736064,
1.00189715065062, 0.987562097609043, 0.231859257910401, 1.64033870631829,
0.12613168777898, 1.91596280829981, 1.35835290746763, 0.792609711177647,
1.97339694341645, 0.376533678267151, 1.63516522897407, 0.225585919804871,
0.505839260760695, 0.0116439824923873, 1.51879569422454,
1.35506999026984, 0.907982874661684, 1.08905055327341, 1.43553646048531,
1.88463490083814, 0.908853257540613, 0.902149567846209, 1.5428032441996,
1.62871437706053, 0.623223986010998, 1.38058050535619, 1.57016781903803,
1.8731079204008, 0.297486190218478, 1.27625703299418, 0.519723014440387,
0.848097313195467, 0.471342021599412, 1.98357644258067, 1.82963251601905,
0.626917572226375, 0.140670910011977, 1.1393640646711, 1.99097026558593,
1.70624398859218, 0.0956417261622846, 1.53923089429736, 1.25705669261515,
1.89643088867888, 1.88176721381024, 1.44151636445895, 0.435520166531205,
1.18845809064806, 2.95685278996825, 1.37898187059909, 2.95418810285628,
1.94776474731043, 1.98949646670371, 1.37768995529041, 2.0124197602272,
1.33321205340326, 2.07528439210728, 2.49668326042593, 2.69146995106712,
1.52930808160454, 1.90695044351742, 1.74849874572828, 2.3098370959051,
1.59070889744908, 1.52278333622962, 2.13915946660563, 1.52873482694849,
1.39334590546787, 1.82181124016643, 2.44108150294051, 2.21637984598055,
1.99761381838471, 2.33465715777129, 2.53672145865858, 2.98815744556487,
1.09659902472049, 1.13088199263439, 1.91391275310889, 1.07779059326276,
1.03311925474554, 1.25638853525743, 2.84107198892161, 2.64419505093247,
1.85066655138507, 2.65426727430895, 2.37351916264743, 1.45171522675082,
2.54493401898071, 1.40593391284347, 1.82211668742821, 1.36818132549524,
2.88858095230535, 2.54271147632971, 2.90091867512092, 1.5358378039673,
2.86527143837884, 2.71315307915211, 2.09380666306242, 2.02881665108725
)), .Names = c("stateID", "category", "values"), row.names = c(NA,
102L), class = "data.frame")
small <-df %>%
filter(category=="small") %>%
plot_geo(locationmode = 'USA-states') %>%
add_trace(
z = ~values, color = ~values, colors = "Blues",
locations = ~stateID) %>%
layout(geo=list(scope='usa'))
small
large <-df %>%
filter(category=="large") %>%
plot_geo(locationmode = 'USA-states') %>%
add_trace(
z = ~values, color = ~values, colors = "Blues",
locations = ~stateID) %>%
layout(geo=list(scope='usa'))
large
に同じ色を持つことになり、同じカラースケールは、各マップに異なる値をカバーしています。私は範囲0-3の単一のカラースケールが欲しいです。シーケンシャルオプション
TIA
おかげで多くを、V。はい、私は参考文献が圧倒的であると思います! – pssguy