带有堆叠列而不是分组的 R ggplot2
R ggplot2 with stacked column instead of grouped
我想将下面显示的数据绘制成一个分组 bar_plot。
我尝试了 position = "dodge"
或 position = "dodge2"
但没有成功。我也试过 position = position_dodge()
如果我使用 geom_bar
而不是 geom_col
并删除 y=overlap_percent
:
p3 <- ggplot(data = comp_coors, aes(x = species_code, fill = mirna_form)) +
geom_bar(position = "dodge2") + theme_classic()
p3
但我希望 y_axis 有 overlap_percent
。
另一个以堆叠条形图结束的尝试是:
p2 <- ggplot(data = comp_coors, aes(x = species_code, y = overlap_percent, fill = mirna_form)) +
geom_bar(stat = "identity") + theme_classic()
p2
最后通过使用 geom_col
,它 returns 这没有意义,至少对我来说:
p4 <- ggplot(data = comp_coors, aes(x = species_code, y = overlap_percent, fill = mirna_form)) +
geom_col(position = "dodge") + theme_classic()
p4
我要绘制的数据:
comp_coors <- data.table( species = c("aae","cel", "dme","hsa", "mdo"),
mirna_form = c("mature", "precursor"),
overlap_percent = c(100.0, 100.0, 88.0, 95.5, 91.7, 100.0, 96.6, 98.4),
overlapping_attribute = c("ID=MIMAT0014285;Alias=MIMAT0014285", "ID=MI0000043;Alias=MI0000043;Name=cel-mir-72", "ID=MIMAT0000401;Alias=MIMAT0000401;Name=dme-miR-", "ID=MI0000791;Alias=MI0000791;Name=hsa-mir-383", "ID=MI0005331;Alias=MI0005331;Name=mdo-let-7g")
)
尝试使用 species
作为一个因素,然后像这样添加 stat = "identity"
:
ggplot(data = comp_coors, aes(x = factor(species), y = overlap_percent, fill = mirna_form)) +
geom_bar(position = "dodge", stat = "identity") + theme_classic() + labs(x = "Species", y = "Overlap percent")
输出:
y-axis 右侧 overlap_percent
的分组条形图。
我想将下面显示的数据绘制成一个分组 bar_plot。
我尝试了 position = "dodge"
或 position = "dodge2"
但没有成功。我也试过 position = position_dodge()
如果我使用 geom_bar
而不是 geom_col
并删除 y=overlap_percent
:
p3 <- ggplot(data = comp_coors, aes(x = species_code, fill = mirna_form)) +
geom_bar(position = "dodge2") + theme_classic()
p3
但我希望 y_axis 有 overlap_percent
。
另一个以堆叠条形图结束的尝试是:
p2 <- ggplot(data = comp_coors, aes(x = species_code, y = overlap_percent, fill = mirna_form)) +
geom_bar(stat = "identity") + theme_classic()
p2
最后通过使用 geom_col
,它 returns 这没有意义,至少对我来说:
p4 <- ggplot(data = comp_coors, aes(x = species_code, y = overlap_percent, fill = mirna_form)) +
geom_col(position = "dodge") + theme_classic()
p4
我要绘制的数据:
comp_coors <- data.table( species = c("aae","cel", "dme","hsa", "mdo"),
mirna_form = c("mature", "precursor"),
overlap_percent = c(100.0, 100.0, 88.0, 95.5, 91.7, 100.0, 96.6, 98.4),
overlapping_attribute = c("ID=MIMAT0014285;Alias=MIMAT0014285", "ID=MI0000043;Alias=MI0000043;Name=cel-mir-72", "ID=MIMAT0000401;Alias=MIMAT0000401;Name=dme-miR-", "ID=MI0000791;Alias=MI0000791;Name=hsa-mir-383", "ID=MI0005331;Alias=MI0005331;Name=mdo-let-7g")
)
尝试使用 species
作为一个因素,然后像这样添加 stat = "identity"
:
ggplot(data = comp_coors, aes(x = factor(species), y = overlap_percent, fill = mirna_form)) +
geom_bar(position = "dodge", stat = "identity") + theme_classic() + labs(x = "Species", y = "Overlap percent")
输出:
y-axis 右侧 overlap_percent
的分组条形图。