柱状图柱状图的底部有额外的线条

Question

我有两个主要的问题需要一些帮助来解决。1.)在我的列的底部有一些奇怪的线条，我不知道如何去掉它们。2.)当我绘制图表时，我遇到了与列重叠的情况。(我认为这与position_dodge(width= XXX)有关，但不完全确定)。

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附上了一个例子情节的图像，主要是因为我不确定如何描述在情节的基础上正在发生的事情。

正在使用以下代码。

where_2 <- where %>% 
  group_by_("gender", "radio") %>% 
  summarise(count = n()) %>% 
  mutate(perc = (perc = (count / sum(count) * 100)))

gg <- ggplot(where_2, aes_string(x = names(where_2[1]), y = where_2$perc, fill = "radio"))
gg <- gg + geom_bar(aes(y = (..count..) / sum(..count..))) 
gg <-gg + geom_bar(position = position_dodge(.5),stat = "identity", width = .75)

#gg <- gg + scale_y_continuous(labels = scales::percent)
gg <- gg + xlab(paste0(lab5[2, title]))
gg <- gg + scale_fill_discrete(labels = c("Yes", "No"))
print(gg)

在过去的4天里，我一直在为这个问题奔跑，如果有任何帮助，我将不胜感激。

place   gender  Radio
1   Male    No
1   Female  Yes
1   Male    No
1   Female  Yes
1   Male    Yes
1   Male    Yes
1   Female  Yes
1   Female  Yes
1   Male    Yes
1   Female  No
1   Male    Yes
1   Male    Yes
1   Male    No
1   Female  No
1   Female  Yes
1   Female  Yes
1   Female  No
1   Male    Yes
1   Female  No
1   Female  Yes
1   Female  No
1   Female  Yes
1   Male    No
1   Male    No
1   Female  No
1   Male    No
1   Female  No
1   Female  No
1   Female  No
1   Male    Yes
1   Female  No
1   Female  No
1   Female  Yes
1   Male    No
1   Male    Yes
1   Female  No
2   Male    Yes
2   Male    Yes
2   Female  No
2   Female  No
2   Male    Yes
2   Female  No
2   Male    No
2   Male    Yes
2   Female  No
2   Female  No
2   Female  No
2   Male    No
2   Female  No
2   Male    No
2   Female  Yes
2   Female  Yes
2   Male    Yes
2   Male    No
2   Male    Yes
3   Female  No
3   Male    Yes
3   Female  No
3   Male    No
3   Male    Yes
3   Female  No
3   Female  Yes
3   Male    No
3   Male    Yes
3   Female  Yes
3   Male    No
3   Female  No
3   Female  Yes
3   Female  No
3   Female  Yes
3   Female  No
3   Male    Yes
3   Female  No
3   Female  No
4   Male    Yes
4   Female  No
4   Female  Yes
4   Female  Yes
4   Male    Yes
4   Female  No
4   Female  No
4   Male    No
4   Female  No
4   Female  No
4   Female  No
4   Male    Yes
4   Male    Yes
4   Female  Yes
4   Female  No
4   Male    Yes
4   Male    Yes
4   Male    Yes
4   Female  No
4   Female  No
4   Female  No

Answer 1

试试这个：

gg <- ggplot(where2, 
             aes(x = gender, y = perc, fill = Radio)) + 
  geom_col(position = "dodge", width = .75)

print(gg)

解释如下：

你说的对，“脚”确实是由geom_bar(aes(y = (..count..) / sum(..count..)))引起的。我不知道你为什么要把它放在第一位，但这就是为什么它创造了“脚”：

Good chart

p <- ggplot(where2, aes(x = gender, y = perc, fill = Radio))

p + geom_col(position = position_dodge(0.5), width = 0.75)

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上面是你想要得到的图表(我假设)。geom_col()等同于geom_bar(stat = "identity")，但输入更少，所以我改用了它。

通常人们在position_dodge()和width =中设置相同的值，这将避免重叠的外观。我暂时保留了它，以便与下面的“脚”形成对比。

还要注意y轴上的值。它们的范围从0到60+。

坏图表

p + geom_bar(aes(y = (..count..) / sum(..count..)))

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上面是“脚”的图表，现在占据了整个地块的高度。在这里，..count..返回每种性别和广播组合的行数，而sum(..count..)返回数据框中的总行数。数据框where2有4行，每行对应一种组合，因此与每个条形关联的y值为0.25，每个性别的两个条形的堆叠高度为0.5。

我认为这是一个糟糕的图表，因为可视化是无用的。当您已经自己计算了数据集中的行数(从where到where2)时，ggplot就没有必要再计算一次。

好图表+坏图表=奇怪的图表

p + 
  geom_col(position = position_dodge(0.5), width = 0.75) +
  geom_bar(aes(y = (..count..) / sum(..count..)))

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上图是两个层的组合图表。现在，坏图表的条形一直被挤压到底部，因为它们的总高度只有0.5，而好图表的条形一直延伸到60+。

使用的数据：

> dput(where)
structure(list(place = 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, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L), gender = structure(c(2L, 1L, 2L, 1L, 
2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 
1L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 
2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 
2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 
1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 
1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L), .Label = c("Female", 
"Male"), class = "factor"), Radio = structure(c(1L, 2L, 1L, 2L, 
2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 
1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 
2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 
2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 
1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 
1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 1L), .Label = c("No", 
"Yes"), class = "factor")), .Names = c("place", "gender", "Radio"
), class = "data.frame", row.names = c(NA, -95L))

where2 <- where %>% 
  group_by(gender, Radio) %>% 
  summarise(count = n()) %>% 
  mutate(perc = (perc = (count / sum(count) * 100))) 

> where2
# A tibble: 4 x 4
# Groups: gender [2]
  gender Radio  count  perc
  <fctr> <fctr> <int> <dbl>
1 Female No        37  67.3
2 Female Yes       18  32.7
3 Male   No        15  37.5
4 Male   Yes       25  62.5