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r - geom_dotplot 中未对齐的点

问题描述

我有一个点图，但由于某种原因，并非我的所有点都沿中心对齐。相反，这些点似乎“浮动”在每个类别的中心网格线上方。如何调整它们的位置？

在此处输入图像描述

当前图的代码：

ggplot(data = filter(lastDet,
                     !ID %in% c("NB2015.341", "NB2018.7", 
                                "NB2018.43", "NB2018.45")),
       aes(x = speciesEN, y = yday(depDate))) + 
  geom_dotplot(aes(fill = factor(year), colour = factor(year)), 
               binaxis = 'y', stackdir = 'center', dotsize = 0.7,
               stackgroups = TRUE, 
               binpositions = "all", 
               method = "histodot") +
  stat_summary(fun.y = mean, geom = "point",
               colour = "black", shape = 4, size = 4) +
  scale_y_continuous(limits = c(181, max(yday(lastDet$depDate))),
                     breaks = c(181, 196, 212, 227, 243),
                     labels = c("1 Jul", "15 Jul", "1 Aug",
                                "15 Aug", "1 Sep")) + 
  scale_colour_manual(values = c("white", "white", "white"),
                      guide = FALSE) +
  scale_fill_manual(values = c("#CA3542", "#FEBC38", "#849FAD")) + 
  coord_flip() +
  labs(y = "Departure date", 
       x = "", 
       fill = "Year") +
  theme_bw() +
  theme(panel.grid.minor = element_blank())

编辑：

重复问题中提供的“hacky”解决方案不适用于我更大的数据框。

编辑2：

根据要求，这是我的数据框的一个子集。我试图让它尽可能具有代表性。

dput(lastDet.sub)
structure(list(speciesEN = c("Bank Swallow", "Bank Swallow", 
"Bank Swallow", "Bank Swallow", "Bank Swallow", "Bank Swallow", 
"Bank Swallow", "Bank Swallow", "Bank Swallow", "Bank Swallow", 
"Bank Swallow", "Bank Swallow", "Bank Swallow", "Bank Swallow", 
"Bank Swallow", "Bank Swallow", "Bank Swallow", "Bank Swallow", 
"Bank Swallow", "Bank Swallow", "Bank Swallow", "Bank Swallow", 
"Bank Swallow", "Bank Swallow", "Bank Swallow", "Bank Swallow", 
"Bank Swallow", "Bank Swallow", "Bank Swallow", "Bank Swallow", 
"Bank Swallow", "Bank Swallow", "Bank Swallow", "Bank Swallow", 
"Bank Swallow", "Bank Swallow", "Bank Swallow", "Bank Swallow", 
"Bank Swallow", "Bank Swallow", "Bank Swallow", "Bank Swallow", 
"Bank Swallow", "Bank Swallow", "Bank Swallow", "Bank Swallow", 
"Bank Swallow", "Bank Swallow", "Bank Swallow", "Bank Swallow", 
"Bank Swallow", "Bank Swallow", "Bank Swallow", "Bank Swallow", 
"Bank Swallow", "Bank Swallow", "Bank Swallow", "Bank Swallow", 
"Bank Swallow", "Bank Swallow", "Bank Swallow", "Bank Swallow", 
"Bank Swallow", "Bank Swallow", "Bank Swallow", "Bank Swallow", 
"Bank Swallow", "Bank Swallow", "Bank Swallow", "Bank Swallow", 
"Bank Swallow", "Bank Swallow", "Bank Swallow", "Bank Swallow", 
"Bank Swallow", "Bank Swallow", "Bank Swallow", "Bank Swallow", 
"Bank Swallow", "Bank Swallow", "Bank Swallow", "Bank Swallow", 
"Bank Swallow", "Bank Swallow", "Bank Swallow", "Bank Swallow", 
"Bank Swallow", "Barn Swallow", "Barn Swallow", "Barn Swallow", 
"Barn Swallow", "Barn Swallow", "Barn Swallow", "Barn Swallow", 
"Barn Swallow", "Barn Swallow", "Barn Swallow", "Barn Swallow", 
"Barn Swallow", "Barn Swallow", "Barn Swallow", "Barn Swallow", 
"Barn Swallow", "Barn Swallow", "Barn Swallow", "Barn Swallow", 
"Barn Swallow", "Cliff Swallow", "Cliff Swallow", "Cliff Swallow", 
"Cliff Swallow", "Cliff Swallow", "Cliff Swallow", "Cliff Swallow", 
"Cliff Swallow", "Cliff Swallow", "Cliff Swallow", "Tree Swallow", 
"Tree Swallow", "Tree Swallow", "Tree Swallow", "Tree Swallow", 
"Tree Swallow", "Tree Swallow", "Tree Swallow", "Tree Swallow", 
"Tree Swallow"), year = c(2018, 2018, 2018, 2018, 2018, 2018, 
2018, 2018, 2018, 2018, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 
2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 
2014, 2014, 2014, 2014, 2014, 2014, 2015, 2015, 2015, 2015, 2015, 
2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 
2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 
2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 
2015, 2015, 2015, 2015, 2015, 2015, 2018, 2018, 2018, 2018, 2018, 
2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 
2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 
2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 
2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018
), depDate = structure(c(1531737145.3837, 1534093849.7991, 1530997725.9412, 
1531076069.5422, 1533041446.3001, 1531076076.231, 1533032604.2326, 
1534086023.11, 1531737149.7107, 1532882823.5637, 1406899801.4133, 
1406297348.1112, 1407276094.4158, 1405278154.7126, 1406330632.0613, 
1407490305.4993, 1406370738.3239, 1406655731.0996, 1406552025.8514, 
1406366734.892, 1405371083.9787, 1405935159.2899, 1406656817.3111, 
1405964739.2527, 1405935269.2718, 1407405240.0903, 1406416984.3628, 
1407078925.0925, 1406201767.0139, 1406285074.475, 1407362335.7969, 
1405886217.5548, 1406586545.9097, 1406123078.5834, 1439577132.3188, 
1439594526.7378, 1438097832.985, 1438097743.3089, 1438470481.0184, 
1438246572.18, 1438252727.6824, 1436190169.4567, 1438595642.3985, 
1438728341.4292, 1437298553.0341, 1437573409.4331, 1439402462.271, 
1437577437.0105, 1438209133.1853, 1438006270.5975, 1438424815.9509, 
1438260465.2748, 1439561952.8794, 1441068339.0791, 1437322842.1042, 
1438794640.5246, 1439673494.5053, 1439825890.7982, 1438173337.2322, 
1438805137.1318, 1438083434.1402, 1436372532.3594, 1435960025.2834, 
1439508786.8144, 1439668992.4789, 1439545490.7975, 1438962415.0014, 
1437768970.3123, 1438423416.3447, 1438251288.8178, 1439757591.1317, 
1437844819.4679, 1438247033.9429, 1439141690.47, 1438207292.6573, 
1438171703.2655, 1438277212.7584, 1439199695.1607, 1534507807.6186, 
1532702235.5266, 1533820579.7317, 1532957266.8756, 1531824345.5634, 
1532598380.2699, 1532098828.52, 1533568517.8915, 1533407138.0839, 
1535885104.009, 1533305719.4551, 1535042919.6962, 1533555209.5058, 
1535132109.2126, 1534526297.7543, 1535543329.7974, 1535797758.1752, 
1535538134.3428, 1535279656.0938, 1532184581.5469, 1534778864.0948, 
1534708212.9832, 1534862676.3394, 1535027042.7154, 1534936249.3542, 
1535211828.7767, 1534936232.9197, 1535227479.6166, 1534506480.411, 
1533161753.2014, 1533115007.6647, 1531570748.0769, 1533673583.6144, 
1533201700.8021, 1531239978.3688, 1531843656.4454, 1532604093.761, 
1530790685.643, 1531132089.8288, 1530533431.1395, 1530787169.1414, 
1530471991.9423, 1530643624.7047, 1530474331.461, 1531679979.9343, 
1531673724.9375, 1531579988.1816, 1531394352.5095, 1531831107.0235
), class = c("POSIXct", "POSIXt"), tzone = "UTC")), class = c("tbl_df", 
"tbl", "data.frame"), row.names = c(NA, -127L))

标签： rggplot2

解决方案

我不geom_dotplot经常使用，所以我不能说是最熟悉的。但是根据样本数据，似乎通过 x 进行刻面并将每个 x 值分配给不同的刻面面板可以解决对齐问题。看看这是否适用于您的大型数据框？

# original plot as per question, other than the data portion since lastDet has no ID to filter
p1 <- ggplot(data = lastDet,
            aes(x = speciesEN, y = yday(depDate))) + 
  geom_dotplot(aes(fill = factor(year), colour = factor(year)), 
               binaxis = 'y', stackdir = 'center', dotsize = 0.7,
               stackgroups = TRUE, 
               binpositions = "all", 
               method = "histodot") +
  stat_summary(fun.y = mean, geom = "point",
               colour = "black", shape = 4, size = 4) +
  scale_y_continuous(limits = c(181, max(yday(lastDet$depDate))),
                     breaks = c(181, 196, 212, 227, 243),
                     labels = c("1 Jul", "15 Jul", "1 Aug",
                                "15 Aug", "1 Sep")) + 
  scale_colour_manual(values = c("white", "white", "white"),
                      guide = FALSE) +
  scale_fill_manual(values = c("#CA3542", "#FEBC38", "#849FAD")) + 
  coord_flip() +
  labs(y = "Departure date", 
       x = "", 
       fill = "Year") +
  theme_bw() +
  theme(panel.grid.minor = element_blank())

# alignment fixed by facet
p2 <- p1 + 
  facet_grid(forcats::fct_rev(speciesEN) ~ .,     # use fct_rev to reverse factor levels & match
                                                  # x-axis order (can replace with simply
                                                  # `speciesEN ~ .`, if this isn't needed)
             scales = "free", space = "free") +   
  theme(strip.background = element_blank(),
        strip.text = element_blank(),
        panel.spacing = unit(0, "pt"))

p2

默认情况下，每个分面面板具有相同的大小。相同位置的点数不会影响比例限制，因此设置space = "free"不会facet_grid更改分配给每个方面的空间量。由于“Bank Swallow”构面面板具有更多具有相同出发日期的点，因此我在 p2 中使用了非常宽大的高宽比来为每个构面提供足够的空间。

但是，如果我们买不起这么大的面板尺寸，我们也可以手动计算最大点数：

rel.width <- layer_data(p2) %>%
  select(PANEL, y, fill, colour, count) %>% 
  unique() %>%
  group_by(PANEL, y) %>%
  summarise(count = sum(count)) %>%
  summarise(count = max(count),
            y = mean(y, na.rm = TRUE)) %>%
  rename(speciesEN = PANEL)
levels(rel.width$speciesEN) <- rev(sort(unique(lastDet$speciesEN)))

> rel.width
# A tibble: 4 x 3
  speciesEN     count     y
  <fct>         <dbl> <dbl>
1 Tree Swallow      2  192.
2 Cliff Swallow     3  200 
3 Barn Swallow      5  229.
4 Bank Swallow     12  210.

并将其作为不可见层添加到绘图中，以强制每个方面调整其空间：

p3 <- p2 +
  geom_tile(data = rel.width,
            aes(y = y, width = count, height = 1),
            alpha = 0)

p3

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