從 ggplot 中刪除 plotly 的標簽工具提示

Question

我正在嘗試使用 ggplotly 來轉換 ggplot，同時為每個點旁邊和懸停文本框上的標簽設置不同的字段。 當我嘗試在我的 ggplot 中明確設置它時，標簽不知何故也有一個不需要的工具提示。

例如，如果我的 ggplot 是這樣編碼的：

p1 <- ggplot(randomData, 
    aes(d30cumarpu, d30mult, col=cumarpu_mult_cluster, label=ip_country,
    text=paste('Country:', ip_country, '<br>',
               'd30cumarpu:', format(d30cumarpu, digits=2), '<br>',
               'd30mult:', format(d30mult, digits=2)))) +
    xlim(range(randomData[,'d30cumarpu'])[1]-2, range(randomData[,'d30cumarpu'])[2]) +
    geom_point() +
    geom_text(aes(x=d30cumarpu - 1.25), show.legend = FALSE) +
    labs(title = paste('ip_country',  'Clusters', sep = ' '))

然后它將根據需要生成此圖像。

但是，當我將其轉換為 plotly 時

plotly1 <- ggplotly(p1, tooltip=c('text'))

除了使用“比較懸停數據”時顯示的點之外，標簽現在還有懸停工具提示，我得到了相同的圖表。

有沒有辦法擺脫標簽的懸停工具提示？

我已經能夠僅使用 plot_ly 並為我添加的文本設置 hoverinfo='none' 來構建相同的東西，但我無法弄清楚如何將 ggplot 轉換為 plotly。

plotly1 <- plot_ly(finaldata, x = ~d30cumarpu, y = ~d30mult, color=~cumarpu_mult_cluster, 
    text=~paste('Country:', ip_country, '<br>',
                'd30cumarpu:', format(d30cumarpu, digits=3), '<br>',
                'd30mult:', format(d30mult, digits=3)),
    hoverinfo='text') %>%
    add_markers() %>%
    add_text(x = ~d30cumarpu-1,
             y = ~d30mult,
             text = ~ip_country,
             color=~cumarpu_mult_cluster,
             hoverinfo='none',
             showlegend=FALSE)

如果有人想玩玩，這里有一個隨機生成和聚類數據的示例：

> dput(randomData)
structure(list(ip_country = structure(c(215L, 107L, 73L, 179L, 
37L, 71L, 55L, 103L, 209L, 181L, 13L, 223L, 148L, 203L, 99L, 
31L, 95L, 100L, 211L, 166L, 113L, 156L, 64L, 149L, 57L, 42L, 
97L, 20L, 186L, 63L, 185L, 90L, 3L, 213L, 114L, 110L, 168L, 12L, 
160L, 54L, 157L, 94L, 177L, 118L, 116L, 167L, 45L, 106L, 85L, 
230L), .Label = c("??", "AD", "AE", "AF", "AG", "AI", "AL", "AM", 
"AO", "AR", "AS", "AT", "AU", "AW", "AX", "AZ", "BA", "BB", "BD", 
"BE", "BF", "BG", "BH", "BI", "BJ", "BL", "BM", "BN", "BO", "BQ", 
"BR", "BS", "BT", "BW", "BY", "BZ", "CA", "CC", "CD", "CF", "CG", 
"CH", "CI", "CK", "CL", "CM", "CN", "CO", "CR", "CV", "CW", "CX", 
"CY", "CZ", "DE", "DJ", "DK", "DM", "DO", "DZ", "EC", "EE", "EG", 
"ES", "ET", "FI", "FJ", "FK", "FM", "FO", "FR", "GA", "GB", "GD", 
"GE", "GF", "GG", "GH", "GI", "GL", "GM", "GN", "GP", "GQ", "GR", 
"GT", "GU", "GW", "GY", "HK", "HN", "HR", "HT", "HU", "ID", "IE", 
"IL", "IM", "IN", "IQ", "IR", "IS", "IT", "JE", "JM", "JO", "JP", 
"KE", "KG", "KH", "KM", "KN", "KR", "KW", "KY", "KZ", "LA", "LB", 
"LC", "LI", "LK", "LR", "LS", "LT", "LU", "LV", "LY", "MA", "MC", 
"MD", "ME", "MF", "MG", "MH", "MK", "ML", "MM", "MN", "MO", "MP", 
"MQ", "MR", "MS", "MT", "MU", "MV", "MW", "MX", "MY", "MZ", "NA", 
"NC", "NE", "NG", "NI", "NL", "NO", "NP", "NR", "NZ", "OM", "PA", 
"PE", "PF", "PG", "PH", "PK", "PL", "PM", "PR", "PS", "PT", "PW", 
"PY", "QA", "RE", "RO", "RS", "RU", "RW", "SA", "SB", "SC", "SD", 
"SE", "SG", "SI", "SK", "SL", "SM", "SN", "SO", "SR", "SS", "ST", 
"SV", "SX", "SY", "SZ", "TC", "TD", "TG", "TH", "TJ", "TL", "TM", 
"TN", "TO", "TR", "TT", "TW", "TZ", "UA", "UG", "US", "UY", "UZ", 
"VA", "VC", "VE", "VG", "VI", "VN", "VU", "WF", "WS", "XK", "YE", 
"YT", "ZA", "ZM", "ZW"), class = "factor"), cumarpu_mult_cluster = c("Tier 2", 
"Tier 1", "Tier 1", "Tier 3", "Tier 1", "Tier 1", "Tier 3", "Tier 2", 
"Tier 1", "Tier 1", "Tier 3", "Tier 1", "Tier 2", "Tier 2", "Tier 1", 
"Tier 1", "Tier 2", "Tier 1", "Tier 3", "Tier 2", "Tier 1", "Tier 2", 
"Tier 3", "Tier 2", "Tier 3", "Tier 1", "Tier 1", "Tier 3", "Tier 2", 
"Tier 3", "Tier 3", "Tier 3", "Tier 2", "Tier 1", "Tier 1", "Tier 2", 
"Tier 1", "Tier 2", "Tier 2", "Tier 1", "Tier 2", "Tier 3", "Tier 3", 
"Tier 3", "Tier 1", "Tier 2", "Tier 1", "Tier 1", "Tier 1", "Tier 2"
), d30cumarpu = c(107.930131712991, 105.222512638255, 117.462222411898, 
87.2866387698602, 121.973895325548, 104.33130777092, 84.2980036951461, 
90.6509433292393, 100.634933452598, 99.9760666381899, 77.2321875975337, 
107.574122251255, 94.5159444597197, 101.725494778504, 105.628530677554, 
115.118179594377, 106.590251691644, 111.220280746746, 92.1535863085354, 
95.7430771118969, 103.929975913722, 100.367571298246, 89.6791633877171, 
87.3513852861858, 97.7303471477638, 107.45589304708, 103.328191803325, 
88.7595954264223, 92.9386921777103, 92.7245613539153, 81.6568561472558, 
95.9231205973952, 100.268611947988, 109.116286375609, 116.343464755087, 
100.606856143597, 118.475725278658, 100.801249546513, 114.185558829789, 
114.586159354469, 100.558773396012, 84.8275942303004, 99.5142078508797, 
97.8564336084652, 120.958181976138, 102.023229068152, 105.177237108215, 
116.781432058498, 103.852448050474, 87.1811277597501), d30mult = c(94.1784926403024, 
117.741186943482, 97.8932802054684, 96.4789309381206, 105.851723262244, 
110.136846977567, 99.7743057140667, 90.9684514320939, 109.077729534112, 
111.61942897035, 95.420466027981, 109.279566678046, 78.9706486359243, 
83.2283288606423, 117.656557686126, 107.944474212631, 95.1613044154245, 
119.283591488307, 96.1588380493214, 84.1332253212426, 102.143017063566, 
88.6171827803067, 104.894135074642, 82.4736323889036, 105.010170995538, 
100.867562053473, 101.910735336673, 108.318390254185, 93.2096763159969, 
102.95862295423, 111.121658595741, 103.625898970539, 97.2908492702806, 
98.0305434605323, 100.669545180646, 91.3219833174809, 96.3799435914652, 
88.6044983529687, 91.8462867022671, 113.102456329798, 97.4163905941743, 
106.062648944944, 103.134482165704, 100.536030819785, 111.28253787677, 
94.4186654082415, 115.359589458142, 99.3755364766521, 100.215752153621, 
79.1017256181289)), .Names = c("ip_country", "cumarpu_mult_cluster", 
"d30cumarpu", "d30mult"), class = "data.frame", row.names = c(421L, 
209L, 142L, 351L, 73L, 138L, 107L, 201L, 409L, 355L, 26L, 436L, 
290L, 397L, 193L, 61L, 185L, 195L, 413L, 325L, 221L, 306L, 125L, 
292L, 111L, 81L, 189L, 40L, 364L, 123L, 362L, 175L, 6L, 417L, 
223L, 215L, 329L, 24L, 313L, 105L, 308L, 183L, 347L, 231L, 227L, 
327L, 87L, 207L, 166L, 449L))

Answer 1

因此，我能夠通過查找列表中的哪些點與標簽對應並最終解決它來深入研究情節結構並將 hoverinfo 變為無

for(i in 4:6){
    plotly1$x$data[[i]]$hoverinfo = 'none'
}

然而，這似乎不可持續，所以如果有任何其他方法，我很樂意聽到它們！