我需要在一个图表中绘制一个显示计数的柱状图和一个显示率的折线图,我可以分别做这两个,但当我把它们放在一起时,我的第一层(即geom_bar)的比例被第二层(即geom_line)重叠。
我可以将geom_line的轴向右移动吗?
我需要在一个图表中绘制一个显示计数的柱状图和一个显示率的折线图,我可以分别做这两个,但当我把它们放在一起时,我的第一层(即geom_bar)的比例被第二层(即geom_line)重叠。
我可以将geom_line的轴向右移动吗?
当前回答
这是我对如何做二次轴变换的两种看法。首先,您希望将主数据和辅助数据的范围耦合起来。这通常是混乱的,因为您不想要的变量污染了全局环境。
为了简化这一点,我们将创建一个生成两个函数的函数工厂,其中scales::rescale()完成所有繁重的工作。因为这些是闭包,所以它们知道创建它们的环境,所以它们“有”创建之前生成的to和from参数的“内存”。
一个函数进行正向转换:将辅助数据转换为主要尺度。 第二个函数进行反向转换:将主要单位中的数据转换为次要单位。
library(ggplot2)
library(scales)
# Function factory for secondary axis transforms
train_sec <- function(primary, secondary, na.rm = TRUE) {
# Thanks Henry Holm for including the na.rm argument!
from <- range(secondary, na.rm = na.rm)
to <- range(primary, na.rm = na.rm)
# Forward transform for the data
forward <- function(x) {
rescale(x, from = from, to = to)
}
# Reverse transform for the secondary axis
reverse <- function(x) {
rescale(x, from = to, to = from)
}
list(fwd = forward, rev = reverse)
}
这看起来相当复杂,但是创建函数工厂会使其余的一切变得更简单。现在,在绘制图形之前,我们将通过向工厂显示主要和次要数据来生成相关函数。我们将使用经济学数据集,它的失业列和pasavert列的范围非常不同。
sec <- with(economics, train_sec(unemploy, psavert))
然后我们使用y = sec$fwd(psavert)将辅助数据重新缩放到主轴,并指定~ sec$rev(.)作为辅助轴的转换参数。这给了我们一个主要范围和次要范围在图上占据相同空间的图。
ggplot(economics, aes(date)) +
geom_line(aes(y = unemploy), colour = "blue") +
geom_line(aes(y = sec$fwd(psavert)), colour = "red") +
scale_y_continuous(sec.axis = sec_axis(~sec$rev(.), name = "psavert"))
工厂比这稍微灵活一些,因为如果您只是想重新调整最大值,您可以传入下限为0的数据。
# Rescaling the maximum
sec <- with(economics, train_sec(c(0, max(unemploy)),
c(0, max(psavert))))
ggplot(economics, aes(date)) +
geom_line(aes(y = unemploy), colour = "blue") +
geom_line(aes(y = sec$fwd(psavert)), colour = "red") +
scale_y_continuous(sec.axis = sec_axis(~sec$rev(.), name = "psavert"))
由reprex包于2021-02-05创建(v0.3.0)
我承认这个例子中的区别不是很明显,但如果你仔细观察,你会发现最大值是相同的,红线比蓝色的线低。
编辑:
这种方法现在已经在ggh4x包中的help_secondary()函数中被捕获和扩展。声明:我是ggh4x的作者。
其他回答
从ggplot2 2.2.0开始,您可以添加如下的辅助轴(取自ggplot2 2.2.0公告):
ggplot(mpg, aes(displ, hwy)) +
geom_point() +
scale_y_continuous(
"mpg (US)",
sec.axis = sec_axis(~ . * 1.20, name = "mpg (UK)")
)
It seemingly appears to be a simple question but it boggles around 2 fundamental questions. A) How to deal with a multi-scalar data while presenting in a comparative chart, and secondly, B) whether this can be done without some thumb rule practices of R programming such as i) melting data, ii) faceting, iii) adding another layer to existing one. The solution given below satisfies both the above conditions as it deals data without having to rescale it and secondly, the techniques mentioned are not used.
这是结果,
如果有兴趣了解更多关于此方法的信息,请点击下面的链接。 如何绘制一个2 y轴图表与条形并排而不重新缩放数据
这是我对如何做二次轴变换的两种看法。首先,您希望将主数据和辅助数据的范围耦合起来。这通常是混乱的,因为您不想要的变量污染了全局环境。
为了简化这一点,我们将创建一个生成两个函数的函数工厂,其中scales::rescale()完成所有繁重的工作。因为这些是闭包,所以它们知道创建它们的环境,所以它们“有”创建之前生成的to和from参数的“内存”。
一个函数进行正向转换:将辅助数据转换为主要尺度。 第二个函数进行反向转换:将主要单位中的数据转换为次要单位。
library(ggplot2)
library(scales)
# Function factory for secondary axis transforms
train_sec <- function(primary, secondary, na.rm = TRUE) {
# Thanks Henry Holm for including the na.rm argument!
from <- range(secondary, na.rm = na.rm)
to <- range(primary, na.rm = na.rm)
# Forward transform for the data
forward <- function(x) {
rescale(x, from = from, to = to)
}
# Reverse transform for the secondary axis
reverse <- function(x) {
rescale(x, from = to, to = from)
}
list(fwd = forward, rev = reverse)
}
这看起来相当复杂,但是创建函数工厂会使其余的一切变得更简单。现在,在绘制图形之前,我们将通过向工厂显示主要和次要数据来生成相关函数。我们将使用经济学数据集,它的失业列和pasavert列的范围非常不同。
sec <- with(economics, train_sec(unemploy, psavert))
然后我们使用y = sec$fwd(psavert)将辅助数据重新缩放到主轴,并指定~ sec$rev(.)作为辅助轴的转换参数。这给了我们一个主要范围和次要范围在图上占据相同空间的图。
ggplot(economics, aes(date)) +
geom_line(aes(y = unemploy), colour = "blue") +
geom_line(aes(y = sec$fwd(psavert)), colour = "red") +
scale_y_continuous(sec.axis = sec_axis(~sec$rev(.), name = "psavert"))
工厂比这稍微灵活一些,因为如果您只是想重新调整最大值,您可以传入下限为0的数据。
# Rescaling the maximum
sec <- with(economics, train_sec(c(0, max(unemploy)),
c(0, max(psavert))))
ggplot(economics, aes(date)) +
geom_line(aes(y = unemploy), colour = "blue") +
geom_line(aes(y = sec$fwd(psavert)), colour = "red") +
scale_y_continuous(sec.axis = sec_axis(~sec$rev(.), name = "psavert"))
由reprex包于2021-02-05创建(v0.3.0)
我承认这个例子中的区别不是很明显,但如果你仔细观察,你会发现最大值是相同的,红线比蓝色的线低。
编辑:
这种方法现在已经在ggh4x包中的help_secondary()函数中被捕获和扩展。声明:我是ggh4x的作者。
对我来说,棘手的部分是计算出两个轴之间的变换函数。我用的是我的curvefit。
> dput(combined_80_8192 %>% filter (time > 270, time < 280))
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-100.87000577258, -98.467607232407, -95.005311380324, -102.04157607608,
-99.724619517, -93.022927803442, -92.404017215549, -92.204561341714,
-93.813803344588, -95.015606885523, -102.0157405687, -98.556982278361,
-96.172566862738, -103.21871579865, -99.714687230796, -93.022787428238,
-92.404017215549, -92.204274688493, -93.813803344588, -95.015606885523,
-102.0157405687, -98.556982278361, -96.172566862738, -103.21784988098,
-99.714687230796, -93.021813165972, -92.409950613665, -92.20229160243,
-93.805838770576, -96.184419849593, -102.02042267497, -99.728735187547,
-96.163233028048, -99.768774335378, -99.706399753853, -93.022228914406,
-92.411048503835, -92.203136463155, -93.807357409082, -95.012865008237,
-102.00985717796, -99.730352912911, -96.165675535906, -100.92744056572,
-99.708301333236, -92.735781110993, -92.408137395049, -92.119533319039,
-94.982938427575, -96.181073124017, -102.03018610927, -99.721633629806,
-97.32940323644, -97.347613268692, -100.87007386786), snr = c(49.848348091678,
57.698190927109, 60.17669971462, 41.529809724535, 31.452202106925,
8.1976890851341, 14.240447804094, 24.122884195464, 6.2202875499406,
10.674183333671, 49.848348091678, 57.746270018264, 60.17669971462,
41.529809724535, 31.452202106925, 8.1976890851341, 14.242292077376,
24.122884195464, 6.2202875499406, 10.672962852322, 49.854827699773,
57.49079026127, 60.192705735317, 41.549715223147, 31.499301851462,
6.2853718719014, 13.937702343688, 24.133388256416, 6.2028757927148,
10.677815810561, 49.867624820879, 57.417115267867, 60.224172277442,
41.635752021705, 24.074540962859, 6.2847854917092, 10.644529778044,
24.19227425387, 10.537686730745, 10.699414795917, 49.84017267426,
53.139646558768, 60.160512118809, 41.509660845114, 31.42665220053,
8.1846370024428, 14.231126423354, 31.584125885363, 6.2494585568733,
10.654622041348, 49.854827699773, 57.49079026127, 60.192705735317,
41.55465351989, 31.509340361646, 6.2867464196657, 13.941251828322,
24.140336174865, 4.765718874642, 10.679016976694, 49.856439162736,
57.49079026127, 60.196678846453, 41.55465351989, 31.509340361646,
6.2867464196657, 13.941251828322, 24.140336174865, 4.7666691818074,
10.679016976694, 49.867624820879, 57.412299088098, 60.224172277442,
41.630930975211, 24.074540962859, 6.279972363168, 10.644529778044,
24.19227425387, 10.546845071479, 10.699414795917, 49.862851240855,
57.397787176282, 60.212457625018, 41.61637603957, 31.529239767749,
6.2952688513108, 10.640565481982, 24.178672145334, 8.0771089950663,
10.694731030907, 53.262541905639, 57.43627424514, 61.382796189332,
31.747253311549, 24.093100244121, 6.2658701281075, 10.661949889074,
18.495227442305, 18.417839037171, 8.1845086722809), frameId = c(15051,
15106, 15165, 15220, 15279, 15330, 15385, 15452, 15511, 15566,
15019, 15074, 15129, 15184, 15239, 15298, 15353, 15412, 15471,
15526, 14947, 14994, 15057, 15112, 15171, 15226, 15281, 15332,
15391, 15442, 14971, 15030, 15085, 15144, 15203, 15262, 15321,
15380, 15435, 15490, 14915, 14978, 15033, 15092, 15147, 15198,
15257, 15312, 15371, 15430, 14975, 15034, 15089, 15140, 15195,
15254, 15313, 15368, 15427, 15478, 14987, 15046, 15105, 15160,
15215, 15274, 15329, 15384, 15447, 15506, 14943, 15002, 15061,
15116, 15171, 15230, 15285, 15344, 15399, 15454, 14971, 15026,
15081, 15136, 15195, 15258, 15313, 15368, 15423, 15478, 15039,
15094, 15149, 15204, 15263, 15314, 15369, 15428, 15487, 15546
), packetOkSinr = c(0.99999999314881, 0.9999999998736, 0.99999999996428,
0.99999952114066, 0.99991568416005, 3.00628034688444e-08,
0.51497487795954, 0.99627877136019, 0, 0.011303253101957,
0.99999999314881, 0.99999999987726, 0.99999999996428, 0.99999952114066,
0.99991568416005, 3.00628034688444e-08, 0.51530974419663,
0.99627877136019, 0, 0.011269851265775, 0.9999999931708,
0.99999999985986, 0.99999999996428, 0.99999952599145, 0.99991770469509,
0, 0.45861812482641, 0.99629897628155, 0, 0.011403119534097,
0.99999999321568, 0.99999999985437, 0.99999999996519, 0.99999954639936,
0.99618434878558, 0, 0.010513119213425, 0.99641022914441,
0.00801687746446111, 0.012011103529927, 0.9999999931195,
0.99999999871861, 0.99999999996428, 0.99999951617905, 0.99991456738049,
2.6525298291169e-08, 0.51328066587104, 0.9999212220316, 0,
0.010777054258914, 0.9999999931708, 0.99999999985986, 0.99999999996428,
0.99999952718674, 0.99991812902805, 0, 0.45929307038653,
0.99631228046814, 0, 0.011436292559188, 0.99999999317629,
0.99999999985986, 0.99999999996428, 0.99999952718674, 0.99991812902805,
0, 0.45929307038653, 0.99631228046814, 0, 0.011436292559188,
0.99999999321568, 0.99999999985437, 0.99999999996519, 0.99999954527918,
0.99618434878558, 0, 0.010513119213425, 0.99641022914441,
0.00821047996950475, 0.012011103529927, 0.99999999319919,
0.99999999985345, 0.99999999996519, 0.99999954188106, 0.99991896371849,
0, 0.010410830482692, 0.996384831822, 9.12484388049251e-09,
0.011877185067536, 0.99999999879646, 0.9999999998562, 0.99999999998077,
0.99992756868677, 0.9962208785486, 0, 0.010971897073662,
0.93214999078663, 0.92943956665979, 2.64925478221656e-08),
snir = c(49.848348091678, 57.698190927109, 60.17669971462,
41.529809724535, 31.452202106925, 8.1976890851341, 14.240447804094,
24.122884195464, 6.2202875499406, 10.674183333671, 49.848348091678,
57.746270018264, 60.17669971462, 41.529809724535, 31.452202106925,
8.1976890851341, 14.242292077376, 24.122884195464, 6.2202875499406,
10.672962852322, 49.854827699773, 57.49079026127, 60.192705735317,
41.549715223147, 31.499301851462, 6.2853718719014, 13.937702343688,
24.133388256416, 6.2028757927148, 10.677815810561, 49.867624820879,
57.417115267867, 60.224172277442, 41.635752021705, 24.074540962859,
6.2847854917092, 10.644529778044, 24.19227425387, 10.537686730745,
10.699414795917, 49.84017267426, 53.139646558768, 60.160512118809,
41.509660845114, 31.42665220053, 8.1846370024428, 14.231126423354,
31.584125885363, 6.2494585568733, 10.654622041348, 49.854827699773,
57.49079026127, 60.192705735317, 41.55465351989, 31.509340361646,
6.2867464196657, 13.941251828322, 24.140336174865, 4.765718874642,
10.679016976694, 49.856439162736, 57.49079026127, 60.196678846453,
41.55465351989, 31.509340361646, 6.2867464196657, 13.941251828322,
24.140336174865, 4.7666691818074, 10.679016976694, 49.867624820879,
57.412299088098, 60.224172277442, 41.630930975211, 24.074540962859,
6.279972363168, 10.644529778044, 24.19227425387, 10.546845071479,
10.699414795917, 49.862851240855, 57.397787176282, 60.212457625018,
41.61637603957, 31.529239767749, 6.2952688513108, 10.640565481982,
24.178672145334, 8.0771089950663, 10.694731030907, 53.262541905639,
57.43627424514, 61.382796189332, 31.747253311549, 24.093100244121,
6.2658701281075, 10.661949889074, 18.495227442305, 18.417839037171,
8.1845086722809), ookSnirBer = c(8.8808636558081e-24, 3.2219795637026e-27,
2.6468895519653e-28, 3.9807779074715e-20, 1.0849324265615e-15,
2.5705217057696e-05, 4.7313805615763e-08, 1.8800438086075e-12,
0.00021005320203921, 1.9147343768384e-06, 8.8808636558081e-24,
3.0694773489537e-27, 2.6468895519653e-28, 3.9807779074715e-20,
1.0849324265615e-15, 2.5705217057696e-05, 4.7223753038869e-08,
1.8800438086075e-12, 0.00021005320203921, 1.9171738578051e-06,
8.8229427230445e-24, 3.9715925056443e-27, 2.6045198111088e-28,
3.9014083702734e-20, 1.0342658440386e-15, 0.00019591630514278,
6.4692014108683e-08, 1.8600094209271e-12, 0.0002140067535655,
1.9074922485477e-06, 8.7096574467175e-24, 4.2779443633862e-27,
2.5231916788231e-28, 3.5761615214425e-20, 1.9750692814982e-12,
0.0001960392878411, 1.9748966344895e-06, 1.7515881895994e-12,
2.2078334799411e-06, 1.8649940680806e-06, 8.954486301678e-24,
3.2021085732779e-25, 2.690441113724e-28, 4.0627628846548e-20,
1.1134484878561e-15, 2.6061691733331e-05, 4.777159157954e-08,
9.4891388749738e-16, 0.00020359398491544, 1.9542110660398e-06,
8.8229427230445e-24, 3.9715925056443e-27, 2.6045198111088e-28,
3.8819641115984e-20, 1.0237769828158e-15, 0.00019562832342849,
6.4455095380046e-08, 1.8468752030971e-12, 0.0010099091367628,
1.9051035165106e-06, 8.8085966897635e-24, 3.9715925056443e-27,
2.594108048185e-28, 3.8819641115984e-20, 1.0237769828158e-15,
0.00019562832342849, 6.4455095380046e-08, 1.8468752030971e-12,
0.0010088638355194, 1.9051035165106e-06, 8.7096574467175e-24,
4.2987746909572e-27, 2.5231916788231e-28, 3.593647329558e-20,
1.9750692814982e-12, 0.00019705170257492, 1.9748966344895e-06,
1.7515881895994e-12, 2.1868296425817e-06, 1.8649940680806e-06,
8.7517439682173e-24, 4.3621551072316e-27, 2.553168170837e-28,
3.6469582463164e-20, 1.0032983660212e-15, 0.00019385229409318,
1.9830820164805e-06, 1.7760568361323e-12, 2.919419915209e-05,
1.8741284335866e-06, 2.8285944348148e-25, 4.1960751547207e-27,
7.8468215407139e-29, 8.0407329049747e-16, 1.9380328071065e-12,
0.00020004849911333, 1.9393279417733e-06, 5.9354475879597e-10,
6.4258355913627e-10, 2.6065221215415e-05), ookSnrBer = c(8.8808636558081e-24,
3.2219795637026e-27, 2.6468895519653e-28, 3.9807779074715e-20,
1.0849324265615e-15, 2.5705217057696e-05, 4.7313805615763e-08,
1.8800438086075e-12, 0.00021005320203921, 1.9147343768384e-06,
8.8808636558081e-24, 3.0694773489537e-27, 2.6468895519653e-28,
3.9807779074715e-20, 1.0849324265615e-15, 2.5705217057696e-05,
4.7223753038869e-08, 1.8800438086075e-12, 0.00021005320203921,
1.9171738578051e-06, 8.8229427230445e-24, 3.9715925056443e-27,
2.6045198111088e-28, 3.9014083702734e-20, 1.0342658440386e-15,
0.00019591630514278, 6.4692014108683e-08, 1.8600094209271e-12,
0.0002140067535655, 1.9074922485477e-06, 8.7096574467175e-24,
4.2779443633862e-27, 2.5231916788231e-28, 3.5761615214425e-20,
1.9750692814982e-12, 0.0001960392878411, 1.9748966344895e-06,
1.7515881895994e-12, 2.2078334799411e-06, 1.8649940680806e-06,
8.954486301678e-24, 3.2021085732779e-25, 2.690441113724e-28,
4.0627628846548e-20, 1.1134484878561e-15, 2.6061691733331e-05,
4.777159157954e-08, 9.4891388749738e-16, 0.00020359398491544,
1.9542110660398e-06, 8.8229427230445e-24, 3.9715925056443e-27,
2.6045198111088e-28, 3.8819641115984e-20, 1.0237769828158e-15,
0.00019562832342849, 6.4455095380046e-08, 1.8468752030971e-12,
0.0010099091367628, 1.9051035165106e-06, 8.8085966897635e-24,
3.9715925056443e-27, 2.594108048185e-28, 3.8819641115984e-20,
1.0237769828158e-15, 0.00019562832342849, 6.4455095380046e-08,
1.8468752030971e-12, 0.0010088638355194, 1.9051035165106e-06,
8.7096574467175e-24, 4.2987746909572e-27, 2.5231916788231e-28,
3.593647329558e-20, 1.9750692814982e-12, 0.00019705170257492,
1.9748966344895e-06, 1.7515881895994e-12, 2.1868296425817e-06,
1.8649940680806e-06, 8.7517439682173e-24, 4.3621551072316e-27,
2.553168170837e-28, 3.6469582463164e-20, 1.0032983660212e-15,
0.00019385229409318, 1.9830820164805e-06, 1.7760568361323e-12,
2.919419915209e-05, 1.8741284335866e-06, 2.8285944348148e-25,
4.1960751547207e-27, 7.8468215407139e-29, 8.0407329049747e-16,
1.9380328071065e-12, 0.00020004849911333, 1.9393279417733e-06,
5.9354475879597e-10, 6.4258355913627e-10, 2.6065221215415e-05
)), class = "data.frame", row.names = c(NA, -100L), .Names = c("run",
"repetition", "module", "configname", "packetByteLength", "numVehicles",
"dDistance", "time", "distanceToTx", "headerNoError", "receivedPower_dbm",
"snr", "frameId", "packetOkSinr", "snir", "ookSnirBer", "ookSnrBer"
))
求变换函数
Y1 -> y2 该函数用于将次要y轴的数据按照第一个y轴进行“归一化”
变换函数:f(y1) = 0.025*x + 2.75
Y2 -> y1 该函数用于将第一个y轴的断点转换为第二个y轴的值。注意,现在坐标轴互换了。
变换函数:f(y1) = 40*x - 110
策划
注意如何在ggplot调用中使用转换函数来“动态地”转换数据
ggplot(data=combined_80_8192 %>% filter (time > 270, time < 280), aes(x=time) ) +
stat_summary(aes(y=receivedPower_dbm ), fun.y=mean, geom="line", colour="black") +
stat_summary(aes(y=packetOkSinr*40 - 110 ), fun.y=mean, geom="line", colour="black", position = position_dodge(width=10)) +
scale_x_continuous() +
scale_y_continuous(breaks = seq(-0,-110,-10), "y_first", sec.axis=sec_axis(~.*0.025+2.75, name="y_second") )
第一个stat_summary调用是为第一个y轴设置基数的调用。 第二个stat_summary调用用于转换数据。请记住,所有数据将以第一个y轴为基础。第一个y轴的数据需要标准化。为此,我使用数据上的转换函数:y=packetOkSinr*40 - 110
现在要转换第二个轴,我在scale_y_continuous调用中使用相反的函数:sec.axis=sec_axis(~.*0.025+2.75, name="y_second")。
我们当然可以用R函数图来建立一个双y轴的图。
# pseudo dataset
df <- data.frame(x = seq(1, 1000, 1), y1 = sample.int(100, 1000, replace=T), y2 = sample(50, 1000, replace = T))
# plot first plot
with(df, plot(y1 ~ x, col = "red"))
# set new plot
par(new = T)
# plot second plot, but without axis
with(df, plot(y2 ~ x, type = "l", xaxt = "n", yaxt = "n", xlab = "", ylab = ""))
# define y-axis and put y-labs
axis(4)
with(df, mtext("y2", side = 4))