在R图中对齐双轴 _大数据知识库

我想创建一个双轴图。数据可以在下面找到：

dput(df)
structure(list(OBS_DATE = structure(c(10957, 11048, 11139, 11231, 
11323, 11413, 11504, 11596, 11688, 11778, 11869, 11961, 12053, 
12143, 12234, 12326, 12418, 12509, 12600, 12692, 12784, 12874, 
12965, 13057, 13149, 13239, 13330, 13422, 13514, 13604, 13695, 
13787, 13879, 13970, 14061, 14153, 14245, 14335, 14426, 14518, 
14610, 14700, 14791, 14883, 14975, 15065, 15156, 15248, 15340, 
15431, 15522, 15614, 15706, 15796, 15887, 15979, 16071, 16161, 
16252, 16344, 16436, 16526, 16617, 16709, 16801, 16892, 16983, 
17075, 17167, 17257, 17348, 17440, 17532, 17622, 17713, 17805, 
17897, 17987, 18078, 18170, 18262, 18353, 18444, 18536, 18628, 
18718, 18809, 18901, 18993, 19083), class = "Date"), Net_operating_surplus_to_value_added = c(36.9656739231445, 
36.8689864882343, 36.6317520083419, 36.8317643474959, 37.6935121500197, 
38.5018034788891, 38.9957638139427, 39.1885608912447, 38.6092136149497, 
38.2770183401821, 38.4489120097893, 38.3537299053262, 38.4156940299523, 
38.137139643167, 37.8894433308562, 37.7064555602493, 37.9839392196746, 
38.3746788684954, 38.6020160570843, 38.8268119307867, 38.5613405710757, 
38.7101242715524, 38.8273476727589, 38.8869873772993, 39.720479442795, 
39.6658712861905, 39.8767955423033, 40.3180414586718, 40.9445739166353, 
41.4504448781142, 42.1689391948721, 42.5475515086736, 42.0065894935759, 
41.8235800428308, 41.0535110327202, 39.3776111728045, 37.2918935656955, 
34.7987917589771, 33.6060430866382, 33.2333240074088, 33.5352650692288, 
34.0870394255266, 34.4296192872216, 34.9379435365405, 35.4951911949687, 
35.5398028603395, 35.5785861381144, 35.0406777120541, 34.4467029671623, 
33.4624900670117, 32.6226354628198, 31.8258664477327, 31.2901452931081, 
31.3585743099158, 31.6843235126606, 32.0760017276417, 32.5304675296323, 
32.5073363450562, 32.6352221514581, 32.7957586698719, 33.3467283704801, 
33.9694837972178, 34.5433408050505, 35.1956294062996, 35.0685963830019, 
35.607294642208, 35.581902998671, 35.7209284106957, 35.9308759449264, 
35.6894948426784, 36.2947609108182, 36.2938680510367, 36.2653856458804, 
36.08587682079, 35.182630097821, 34.6910386509771, 34.5456518897842, 
34.046625027426, 34.2605143927775, 34.2141127409063, 33.1221766349027, 
31.0095937520034, 30.2453076663821, 30.2414563984248, 31.704392011148, 
34.5010174977904, 34.8147384445836, 34.7697905115992, 34.43625109411, 
33.8841955271951), Met_retained_earnings_to_value_added = c(3.65946513678856, 
2.99463238024132, 2.49514650123736, 3.02457398855396, 3.52170627766491, 
3.65874887644949, 3.75035993710115, 4.19023687395792, 5.03705154102929, 
5.57632125508043, 8.2495415198731, 9.1177952075909, 8.39854897090696, 
7.90761699297047, 6.61882380938546, 5.82196030311438, 6.14631242125481, 
6.17680298128492, 6.07542512868537, 6.01032154224047, 5.66854842968337, 
5.47974183094731, 5.26498409983987, 5.0098922839463, 5.5332050888931, 
4.46960255520707, 4.37466881326977, 4.15148205815225, 4.52903352953872, 
4.45114690933355, 5.03266104719299, 4.95052573926497, 3.97052831893563, 
3.50569271340267, 2.44196835732784, 1.5954474561901, 0.389019198525782, 
0.491438385056609, 1.53710358969239, 3.326229908946, 5.04170916975847, 
5.60436479062756, 6.57740686481843, 6.02041199986632, 5.60803794337375, 
5.78906824166877, 4.75880249860857, 5.05756309766792, 4.51410756786046, 
4.34574033479928, 3.45056503904027, 2.77862946386903, 3.39068127274666, 
3.87423424368168, 5.060146724212, 5.59504392224852, 5.94120589707917, 
5.38305476870492, 5.44128431403496, 5.9577367772693, 6.5888030147431, 
7.1133680406906, 7.53087422774044, 8.18386901533204, 8.2264735443145, 
8.95382429921373, 9.51201069521699, 9.5114820156883, 9.64064423866319, 
9.05512739701095, 9.40881852811793, 10.0114821239402, 9.5692691653021, 
9.0906823904455, 8.47113772060278, 7.64711815518838, 8.0943097283881, 
7.77194975031624, 8.04157404171203, 8.3642302611957, 7.11751092092824, 
6.1040017121415, 5.52587902763856, 5.87309706295293, 7.38715617317306, 
10.082162546155, 10.5674522055678, 9.83495111956979, 9.30377793666422, 
6.87773746393322)), class = "data.frame", row.names = c(NA, -90L
))

下面是我正在使用的代码

min_Date <-  as.Date("2021-01-01")  
max_Date <- df$OBS_DATE[length(df$OBS_DATE)]
start_point <-  c(min_Date, max_Date)

chart2 <- plot_ly(x = df$OBS_DATE, y = df$Net_operating_surplus_to_value_added, type = 'scatter',  mode = 'lines', name = "Net operating surplus to value added (LHS)", line = list(color = "#003299") ) %>% 
            
add_trace(y = df$Met_retained_earnings_to_value_added,  name = "Met retained earnings to value added (RHS)", line = list(color = "#FFB400" ), yaxis = "y2") %>% 

layout(barmode = 'relative', barbase = 0, xaxis = list(range = start_point), yaxis = list(range = c(30,44)),  yaxis2 = list(overlaying = "y", side = "right",range = c(0, 14)))

通过这种方式，我可以在图表的缩放版本中对齐轴

]
然而，当我看整个系列时，网格线变得不对齐。

> min(df$Net_operating_surplus_to_value_added)
[1] 30.24146
> max(df$Net_operating_surplus_to_value_added)
[1] 42.54755

> max(df$Met_retained_earnings_to_value_added)
[1] 10.56745
> min(df$Met_retained_earnings_to_value_added)
[1] 0.3890192

我能做些什么来解决这个问题呢？

我无法双击绘图来获取整个数据集。但是，如果我单击“自动缩放”，我可以获取所有数据。当您定义范围时，它会将缩放设置为手动。通过选择“自动缩放”，您将删除这些设置。
但是，如果您希望从现有的开始，并保持缩放比例，则使用scaleratio、constraintowards，并添加两条不可见的迹线，以说明范围的差异（如果我们设置ratio = 1，则它是字面的）。
添加一条y值范围在30到44之间并与y对齐的线。添加另一条y值范围在0到14之间并与y2对齐的线。
你看

(chart2 <- plot_ly(x = df$OBS_DATE, 
                  y = df$Net_operating_surplus_to_value_added, 
                  type = 'scatter',  mode = 'lines', 
                  name = "Net operating surplus to value added (LHS)",
                  line = list(color = "#003299") ) %>% 
  add_trace(y = c(30, rep(44, nrow(df) - 1)), line = list(width = .0001),
            showlegend = F) %>%                      # <----- hidden trace
  add_trace(y = df$Met_retained_earnings_to_value_added, 
            name = "Met retained earnings to value added (RHS)", 
            line = list(color = "#FFB400" ), yaxis = "y2") %>% 
  add_trace(y = c(0, rep(14, nrow(df) - 1)), line = list(width = .0001),
            yaxis = "y2", showlegend = F) %>%        # <----- hidden trace
  layout(barmode = 'relative', barbase = 0, 
         xaxis = list(range = start_point), 
         yaxis = list(range = c(30, 44)),  
         yaxis2 = list(overlaying = "y", 
                       scaleratio = 1, scaleanchor = "y",
                       constraintoward = "bottom",
                       side = "right", range = c(0, 14))))

现在当你计算autoscale时，你要保持你想保持的比率。
此外，根据您对该图所做的操作，您可能希望先调用两条不可见的迹线，以便它们位于底部。

在R图中对齐双轴

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