在一张图上添加多行(excel中的序列)；在RStudio中计数响应和平均值

Question

我试过这样的代码：

ggplot(data = Master_Data) +
  geom_line(mapping = aes(
    x = fct_inorder(Gate),
    y = c(Correct),
    group = 1),
  stat = 'identity') +
  facet_wrap( ~ Condition, nrow = 2)

但是，对于“门”，它没有计数和平均正确的响应；我无法得到两行(一条用于AO，一条用于AV)。

下面是我试图从excel复制到R的图表：

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下面是我在RStudio中上传的电子表格的一个小示例：

Participant Condition Gate Sound Target Response Correct
VS0005  Clean   POD AV  Baby    baby    1
VS0005  Clean   Gate 1  AV  Sandwich    sandal  0
VS0005  Clean   Gate 2  AV  Rooster ruby    0
VS0005  Clean   Gate 3  AV  Puppy   puppy   1
VS0005  Clean   Full    AV  Peacock pizza   0
VS0005  Clean   POD AO  Banjo   banjo   1
VS0005  Clean   Gate 1  AO  Ferret  fairy   0
VS0005  Clean   Gate 2  AO  Carriage    carrot  0
VS0005  Clean   Gate 3  AO  Marble  marble  1
VS0005  Clean   Full    AO  Pasta   puzzle  0
VS0006  Clean   POD AV  Baby    baby    1
VS0006  Clean   Gate 1  AV  Sandwich    sandal  0
VS0006  Clean   Gate 2  AV  Rooster ruby    0
VS0006  Clean   Gate 3  AV  Puppy   puppy   1
VS0006  Clean   Full    AV  Peacock pizza   0
VS0006  Clean   POD AO  Banjo   banjo   1
VS0006  Clean   Gate 1  AO  Ferret  fairy   0
VS0006  Clean   Gate 2  AO  Carriage    carrot  0
VS0006  Clean   Gate 3  AO  Marble  marble  1
VS0006  Clean   Full    AO  Pasta   puzzle  0
VS0007  Degraded    POD AV  Baby    baby    1
VS0007  Degraded    Gate 1  AV  Sandwich    sandal  0
VS0007  Degraded    Gate 2  AV  Rooster ruby    0
VS0007  Degraded    Gate 3  AV  Puppy   puppy   1
VS0007  Degraded    Full    AV  Peacock pizza   0
VS0007  Degraded    POD AO  Banjo   banjo   1
VS0007  Degraded    Gate 1  AO  Ferret  fairy   0
VS0007  Degraded    Gate 2  AO  Carriage    carrot  0
VS0007  Degraded    Gate 3  AO  Marble  marble  1
VS0007  Degraded    Full    AO  Pasta   puzzle  0
VS0008  Degraded    POD AV  Baby    baby    1
VS0008  Degraded    Gate 1  AV  Sandwich    sandal  0
VS0008  Degraded    Gate 2  AV  Rooster ruby    0
VS0008  Degraded    Gate 1  AV  Puppy   puppy   1
VS0008  Degraded    Full    AV  Peacock pizza   0
VS0008  Degraded    POD AO  Banjo   banjo   1
VS0008  Degraded    Gate 1  AO  Ferret  fairy   0
VS0008  Degraded    Gate 2  AO  Carriage    carrot  0
VS0008  Degraded    Gate 3  AO  Marble  marble  1
VS0008  Degraded    Full    AO  Pasta   puzzle  0

Answer 1

我想像这样的东西应该能起作用。

library(ggplot2); library(dplyr)
Master_Data %>%
  group_by(Condition, Gate = fct_inorder(Gate), Sound) %>%
  summarize(mean = mean(Correct),
            sd = sd(Correct), .groups = "drop") %>%
  ggplot(aes(x = Gate, y = mean, color = Sound, group = Sound)) +
  geom_line() +
  geom_errorbar(aes(ymin = mean - sd, ymax = mean + sd)) +
  facet_wrap(~Condition) +
  theme_minimal()

对于数据样本来说，它看起来非常糟糕，因为大多数情况下只有一个观察结果。应该看上去更像excel图表，有更多的数据。

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