我将使用ggplot中的钻石数据集来说明我的观点，我想为价格绘制直方图，但是我想为每个切割显示每个bin的计数这是我的代码
p> ggplot（aes（x = price），data = diamonds_df）+ geom_histogram（aes（fill = cut，binwidth = 1500））+ stat_bin（binwidth = 1500，geom =text，aes（label = .. count ..）， vjust = -1）+ scale_x_continuous（breaks = seq （0，max（stores_1_5 $ Weekly_Sales），1500），labels = comma）这里是我目前的情节
但是如您所看到的数字显示每个bin上所有剪辑的计数，我想显示每个bin上每个剪辑的计数。
也是一个奖励点，如果我可以配置Y轴而不是在步骤5000中显示数字，我可以手动配置
解决方案更新为 ggplot2 2.x
您现在可以居中不使用 position = position_stack（vjust = 0.5）预先汇总数据，而是使用堆叠条形图中的标签。例如：
ggplot（aes（x = price），data = diamonds）+ geom_histogram（aes（fill = cut），binwidth = 1500，color =grey20，lwd = 0.2）+ stat_bin（binwidth = 1500，geom =text，color =white，size = 3.5， aes （0，max（钻石$价格），1500））（标签= ..计数，组=切），位置= position_stack（vjust = 0.5））+ scale_x_continuous原始答案
您可以获得每个值的计数通过添加 cut 作为组
上面的代码有一个问题，我希望标签在每个小节内垂直居中部分，但我不知道如何在 stat_bin 内做到这一点，或者甚至可能。乘以0.8（或其他）将每个标签移动一个不同的相对量。所以，为了让标签居中，我在下面的代码中为标签创建了一个单独的数据框：
＃创建文本标签 dat = diamonds％>％ group_by（cut， price = cut（price，seq（0，max（diamonds $ price）+1500,1500）， labels = seq（0，max（diamonds $ price），1500），right = FALSE））％>％ summary（count = n（））％>％ group_by（price）％> ;％ mutate（ypos = cumsum（count） - 0.5 * count）％>％ ungroup（）％>％ mutate（price = as.numeric（as.character价格））+ 750） ggplot（aes（x = price），data = diamonds）+ geom_histogram（aes（fill = cut），binwidth = 1500，color =grey20 ，lwd = 0.2）+ geom_text（data = dat，aes（label = count，y = ypos），color =white，size = 3.5） pre>
要在y轴上配置中断，只需添加 scale_y_continuous（breaks = seq（0,20） 000,2000））或任何你想要的休息。
I'll use the diamond data set in ggplot to illustrate my point , I want to draw a histogram for price , but I want to show the count for each bin for each cut this is my code
ggplot(aes(x = price ) , data = diamonds_df) + geom_histogram(aes(fill = cut , binwidth = 1500)) + stat_bin(binwidth= 1500, geom="text", aes(label=..count..) , vjust = -1) + scale_x_continuous(breaks = seq(0 , max(stores_1_5$Weekly_Sales) , 1500 ) , labels = comma)here is my current plot
but as you see the number shows the count for all cuts at each bin , I want to display the count for each cut on each bin .
also a bonus point if if I would be able to configure Y axis instead of displaying numbers at step of 5000 to something else I can configure manually
解决方案Update for ggplot2 2.x
You can now center labels within stacked bars without pre-summarizing the data using position=position_stack(vjust=0.5). For example:
ggplot(aes(x = price ) , data = diamonds) + geom_histogram(aes(fill=cut), binwidth=1500, colour="grey20", lwd=0.2) + stat_bin(binwidth=1500, geom="text", colour="white", size=3.5, aes(label=..count.., group=cut), position=position_stack(vjust=0.5)) + scale_x_continuous(breaks=seq(0,max(diamonds$price), 1500))Original Answer
You can get the counts for each value of cut by adding cut as a group aesthetic to stat_bin. I also moved binwidth outside of aes, which was causing binwidth to be ignored in your original code:
ggplot(aes(x = price ), data = diamonds) + geom_histogram(aes(fill = cut ), binwidth=1500, colour="grey20", lwd=0.2) + stat_bin(binwidth=1500, geom="text", colour="white", size=3.5, aes(label=..count.., group=cut, y=0.8*(..count..))) + scale_x_continuous(breaks=seq(0,max(diamonds$price), 1500))One issue with the code above is that I'd like the labels to be vertically centered within each bar section, but I'm not sure how to do that within stat_bin, or if it's even possible. Multiplying by 0.8 (or whatever) moves each label by a different relative amount. So, to get the labels centered, I created a separate data frame for the labels in the code below:
# Create text labels dat = diamonds %>% group_by(cut, price=cut(price, seq(0,max(diamonds$price)+1500,1500), labels=seq(0,max(diamonds$price),1500), right=FALSE)) %>% summarise(count=n()) %>% group_by(price) %>% mutate(ypos = cumsum(count) - 0.5*count) %>% ungroup() %>% mutate(price = as.numeric(as.character(price)) + 750) ggplot(aes(x = price ) , data = diamonds) + geom_histogram(aes(fill = cut ), binwidth=1500, colour="grey20", lwd=0.2) + geom_text(data=dat, aes(label=count, y=ypos), colour="white", size=3.5)To configure the breaks on the y axis, just add scale_y_continuous(breaks=seq(0,20000,2000)) or whatever breaks you'd like.
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