如何在 R 中制作 2 轴条形图
How to make a 2-axis bar plot in R
我试图在 R 中多年来直观地比较单个地块上 2 个物种的数量。我在网上看到这个地块，希望在 R 中创建类似的东西，但在网上找不到太多有帮助。
我的数据：
> head(df2)
# A tibble: 6 x 4
# Groups: Zone, Year [6]
Year Zone weighted_den weighted_den_carid
<dbl> <fct> <dbl> <dbl>
1 2009 West 0.00109 0.485
2 2009 Rankin 0 0.0869
3 2009 Whipray 0 0.000176
4 2009 Crocodile 0 0.0213
5 2010 West 0.00245 2.26
6 2010 Rankin 0 0
我的尝试：
ggplot(df2, aes(x=Zone)) +
geom_bar(aes(y=weighted_den_carid), col = 'red') +
geom_bar(aes(y=weighted_den), col = 'blue') +
scale_y_continuous("Carid", sec.axis = sec_axis(~ . *100, name = "Cneb")) +
facet_wrap(~Year)
我的数据输入格式：
dput(df)
structure(list(Year = c(2009, 2009, 2009, 2009, 2009, 2009, 2009,
2009, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2011, 2011,
2011, 2011, 2011, 2011, 2011, 2011, 2012, 2012, 2012, 2012, 2012,
2012, 2012, 2012, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013,
2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2015, 2015, 2015,
2015, 2015, 2015, 2015, 2015, 2016, 2016, 2016, 2016, 2016, 2016,
2016, 2016, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2018,
2018, 2018, 2018, 2018, 2018, 2018, 2018, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2020, 2020, 2020, 2020, 2020, 2020, 2020,
2020, 2021, 2021, 2021, 2021, 2021, 2021, 2021, 2021), Zone = structure(c(3L,
3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L, 3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L,
3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L, 3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L,
3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L, 3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L,
3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L, 3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L,
3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L, 3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L,
3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L, 3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L,
3L, 2L, 2L, 4L, 4L, 1L, 1L), .Label = c("Crocodile", "Rankin",
"West", "Whipray"), class = "factor"), code = c("2009-West",
"2009-West", "2009-Rankin", "2009-Rankin", "2009-Whipray", "2009-Whipray",
"2009-Crocodile", "2009-Crocodile", "2010-West", "2010-West",
"2010-Rankin", "2010-Rankin", "2010-Whipray", "2010-Whipray",
"2010-Crocodile", "2010-Crocodile", "2011-West", "2011-West",
"2011-Rankin", "2011-Rankin", "2011-Whipray", "2011-Whipray",
"2011-Crocodile", "2011-Crocodile", "2012-West", "2012-West",
"2012-Rankin", "2012-Rankin", "2012-Whipray", "2012-Whipray",
"2012-Crocodile", "2012-Crocodile", "2013-West", "2013-West",
"2013-Rankin", "2013-Rankin", "2013-Whipray", "2013-Whipray",
"2013-Crocodile", "2013-Crocodile", "2014-West", "2014-West",
"2014-Rankin", "2014-Rankin", "2014-Whipray", "2014-Whipray",
"2014-Crocodile", "2014-Crocodile", "2015-West", "2015-West",
"2015-Rankin", "2015-Rankin", "2015-Whipray", "2015-Whipray",
"2015-Crocodile", "2015-Crocodile", "2016-West", "2016-West",
"2016-Rankin", "2016-Rankin", "2016-Whipray", "2016-Whipray",
"2016-Crocodile", "2016-Crocodile", "2017-West", "2017-West",
"2017-Rankin", "2017-Rankin", "2017-Whipray", "2017-Whipray",
"2017-Crocodile", "2017-Crocodile", "2018-West", "2018-West",
"2018-Rankin", "2018-Rankin", "2018-Whipray", "2018-Whipray",
"2018-Crocodile", "2018-Crocodile", "2019-West", "2019-West",
"2019-Rankin", "2019-Rankin", "2019-Whipray", "2019-Whipray",
"2019-Crocodile", "2019-Crocodile", "2020-West", "2020-West",
"2020-Rankin", "2020-Rankin", "2020-Whipray", "2020-Whipray",
"2020-Crocodile", "2020-Crocodile", "2021-West", "2021-West",
"2021-Rankin", "2021-Rankin", "2021-Whipray", "2021-Whipray",
"2021-Crocodile", "2021-Crocodile"), species = c("weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den",
"weighted_den_carid", "weighted_den", "weighted_den_carid"),
density = c(0.00109451560281117, 0.484952868327336, 0, 0.086948676470023,
0, 0.000175586458772299, 0, 0.0213370469869364, 0.00244750051380243,
2.25961874077752, 0, 0, 0, 0.00109652922201019, 0, 0, 0.00155162534766244,
1.87765191982742, 0, 0.0506693553371398, 0, 0.00888790576574783,
0, 0.000113921166552746, 0.00271835365647371, 1.43239056009749,
0, 0.000182039455286541, 0, 0, 0, 0.000561519490035231, 0.00225835591184498,
2.40719953239284, 0, 0.000388080206313915, 0, 0.00309583234733728,
0, 0.000815020765525142, 9.16873040427497e-05, 0.330946212564868,
0, 0.00121708105974097, 0, 0, 0, 0, 0.00120311020545607,
0.245785509346677, 0, 0, 0, 0, 0, 0.0170052902510473, 0.00331914172039662,
0.65236339593047, 0.0018818919255523, 0.00514144664157328,
0.00049840112185749, 0.00211954056631631, 0, 0.00202007130311886,
0.00419876411388295, 0.199634354821455, 0.000976084425739813,
0.104217100578605, 0.00017317664770464, 0.00103563821616542,
0.000231762069846282, 0.000115118681029652, 0.001688624458484,
0.112896098983775, 0.00221388120855345, 0.00851524454018168,
0.000145407848151758, 0.000434852081803272, 0, 0.000412676750124396,
0.00273638649319108, 0.267608818473059, 0.00332090562164444,
0.068723241681447, 0.000426749934946656, 0.00149987725304424,
0, 0.000192673737735322, 0.000951619776409427, 0.215338040060959,
0.000434586745104274, 0.0478934449975685, 0, 0.00150998374994783,
0, 0.00129010186017751, 0.00131030492673741, 0.300718374949211,
0.00110524705272365, 0.203148234839554, 0, 0.00205469524493215,
0, 0.00279004408491279)), row.names = c(NA, -104L), groups = structure(list(
Zone = structure(c(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, 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), .Label = c("Crocodile",
"Rankin", "West", "Whipray"), class = "factor"), Year = c(2009,
2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019,
2020, 2021, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016,
2017, 2018, 2019, 2020, 2021, 2009, 2010, 2011, 2012, 2013,
2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2009, 2010,
2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020,
2021), .rows = structure(list(7:8, 15:16, 23:24, 31:32, 39:40,
47:48, 55:56, 63:64, 71:72, 79:80, 87:88, 95:96, 103:104,
3:4, 11:12, 19:20, 27:28, 35:36, 43:44, 51:52, 59:60,
67:68, 75:76, 83:84, 91:92, 99:100, 1:2, 9:10, 17:18,
25:26, 33:34, 41:42, 49:50, 57:58, 65:66, 73:74, 81:82,
89:90, 97:98, 5:6, 13:14, 21:22, 29:30, 37:38, 45:46,
53:54, 61:62, 69:70, 77:78, 85:86, 93:94, 101:102), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), row.names = c(NA, -52L), class = c("tbl_df",
"tbl", "data.frame"), .drop = TRUE), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"))
首先我用随机数据创建了一个可重现的数据集：
df <- data.frame(Year = rep(c(2009, 2010, 2011, 2012), 5),
Zone = rep(c("West", "Rankin", "Whipray", "Crocodile"), 5),
weighted_den = runif(20, 0, 1),
weighted_den_carid = runif(20, 0, 3))
之后，您应该使用以下代码 melt 您的数据：
library(reshape)
library(tidyverse)
df2 <- melt(df, id = c("Zone", "Year"))
并使用以下代码绘制带有第二个 y-axis 的条形图：
df2 %>% ggplot(aes(x = Zone, y = value, fill = variable)) +
geom_bar(stat = "identity", position = "dodge") +
scale_y_continuous("Carid", sec.axis = sec_axis(~ . *100, name = "Cneb"))
输出：
根据您的输入，我们可以创建以下代码，它似乎可以满足您的要求，但我不确定它作为可视化效果如何：
tidyr::pivot_wider(df, names_from = species, values_from = density) %>%
ggplot(aes(x = as.numeric(Zone) - 0.125)) +
geom_col(aes(y = weighted_den, group = 1, fill = 'weighted_den'),
width = 0.25) +
geom_col(aes(x = as.numeric(Zone) + 0.125,
y = weighted_den_carid / 100,
fill = 'weighted_den_carid'), width =0.25) +
scale_x_continuous(breaks = 1:4, labels = levels(df$Zone)) +
scale_y_continuous(sec.axis = sec_axis(trans = ~.x * 100,
name = 'weighted_den_carid')) +
facet_wrap(~Year, scales = 'free_y') +
theme_minimal() +
theme(axis.text.x = element_text(angle = 90))
我试图在 R 中多年来直观地比较单个地块上 2 个物种的数量。我在网上看到这个地块，希望在 R 中创建类似的东西，但在网上找不到太多有帮助。
我的数据：
> head(df2)
# A tibble: 6 x 4
# Groups: Zone, Year [6]
Year Zone weighted_den weighted_den_carid
<dbl> <fct> <dbl> <dbl>
1 2009 West 0.00109 0.485
2 2009 Rankin 0 0.0869
3 2009 Whipray 0 0.000176
4 2009 Crocodile 0 0.0213
5 2010 West 0.00245 2.26
6 2010 Rankin 0 0
我的尝试：
ggplot(df2, aes(x=Zone)) +
geom_bar(aes(y=weighted_den_carid), col = 'red') +
geom_bar(aes(y=weighted_den), col = 'blue') +
scale_y_continuous("Carid", sec.axis = sec_axis(~ . *100, name = "Cneb")) +
facet_wrap(~Year)
我的数据输入格式：
dput(df) structure(list(Year = c(2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2011, 2011, 2011, 2011, 2011, 2011, 2011, 2011, 2012, 2012, 2012, 2012, 2012, 2012, 2012, 2012, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2016, 2016, 2016, 2016, 2016, 2016, 2016, 2016, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2021, 2021, 2021, 2021, 2021, 2021, 2021, 2021), Zone = structure(c(3L, 3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L, 3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L, 3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L, 3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L, 3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L, 3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L, 3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L, 3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L, 3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L, 3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L, 3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L, 3L, 2L, 2L, 4L, 4L, 1L, 1L, 3L, 3L, 2L, 2L, 4L, 4L, 1L, 1L), .Label = c("Crocodile", "Rankin", "West", "Whipray"), class = "factor"), code = c("2009-West", "2009-West", "2009-Rankin", "2009-Rankin", "2009-Whipray", "2009-Whipray", "2009-Crocodile", "2009-Crocodile", "2010-West", "2010-West", "2010-Rankin", "2010-Rankin", "2010-Whipray", "2010-Whipray", "2010-Crocodile", "2010-Crocodile", "2011-West", "2011-West", "2011-Rankin", "2011-Rankin", "2011-Whipray", "2011-Whipray", "2011-Crocodile", "2011-Crocodile", "2012-West", "2012-West", "2012-Rankin", "2012-Rankin", "2012-Whipray", "2012-Whipray", "2012-Crocodile", "2012-Crocodile", "2013-West", "2013-West", "2013-Rankin", "2013-Rankin", "2013-Whipray", "2013-Whipray", "2013-Crocodile", "2013-Crocodile", "2014-West", "2014-West", "2014-Rankin", "2014-Rankin", "2014-Whipray", "2014-Whipray", "2014-Crocodile", "2014-Crocodile", "2015-West", "2015-West", "2015-Rankin", "2015-Rankin", "2015-Whipray", "2015-Whipray", "2015-Crocodile", "2015-Crocodile", "2016-West", "2016-West", "2016-Rankin", "2016-Rankin", "2016-Whipray", "2016-Whipray", "2016-Crocodile", "2016-Crocodile", "2017-West", "2017-West", "2017-Rankin", "2017-Rankin", "2017-Whipray", "2017-Whipray", "2017-Crocodile", "2017-Crocodile", "2018-West", "2018-West", "2018-Rankin", "2018-Rankin", "2018-Whipray", "2018-Whipray", "2018-Crocodile", "2018-Crocodile", "2019-West", "2019-West", "2019-Rankin", "2019-Rankin", "2019-Whipray", "2019-Whipray", "2019-Crocodile", "2019-Crocodile", "2020-West", "2020-West", "2020-Rankin", "2020-Rankin", "2020-Whipray", "2020-Whipray", "2020-Crocodile", "2020-Crocodile", "2021-West", "2021-West", "2021-Rankin", "2021-Rankin", "2021-Whipray", "2021-Whipray", "2021-Crocodile", "2021-Crocodile"), species = c("weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid", "weighted_den", "weighted_den_carid"), density = c(0.00109451560281117, 0.484952868327336, 0, 0.086948676470023, 0, 0.000175586458772299, 0, 0.0213370469869364, 0.00244750051380243, 2.25961874077752, 0, 0, 0, 0.00109652922201019, 0, 0, 0.00155162534766244, 1.87765191982742, 0, 0.0506693553371398, 0, 0.00888790576574783, 0, 0.000113921166552746, 0.00271835365647371, 1.43239056009749, 0, 0.000182039455286541, 0, 0, 0, 0.000561519490035231, 0.00225835591184498, 2.40719953239284, 0, 0.000388080206313915, 0, 0.00309583234733728, 0, 0.000815020765525142, 9.16873040427497e-05, 0.330946212564868, 0, 0.00121708105974097, 0, 0, 0, 0, 0.00120311020545607, 0.245785509346677, 0, 0, 0, 0, 0, 0.0170052902510473, 0.00331914172039662, 0.65236339593047, 0.0018818919255523, 0.00514144664157328, 0.00049840112185749, 0.00211954056631631, 0, 0.00202007130311886, 0.00419876411388295, 0.199634354821455, 0.000976084425739813, 0.104217100578605, 0.00017317664770464, 0.00103563821616542, 0.000231762069846282, 0.000115118681029652, 0.001688624458484, 0.112896098983775, 0.00221388120855345, 0.00851524454018168, 0.000145407848151758, 0.000434852081803272, 0, 0.000412676750124396, 0.00273638649319108, 0.267608818473059, 0.00332090562164444, 0.068723241681447, 0.000426749934946656, 0.00149987725304424, 0, 0.000192673737735322, 0.000951619776409427, 0.215338040060959, 0.000434586745104274, 0.0478934449975685, 0, 0.00150998374994783, 0, 0.00129010186017751, 0.00131030492673741, 0.300718374949211, 0.00110524705272365, 0.203148234839554, 0, 0.00205469524493215, 0, 0.00279004408491279)), row.names = c(NA, -104L), groups = structure(list( Zone = structure(c(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, 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), .Label = c("Crocodile", "Rankin", "West", "Whipray"), class = "factor"), Year = c(2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021), .rows = structure(list(7:8, 15:16, 23:24, 31:32, 39:40, 47:48, 55:56, 63:64, 71:72, 79:80, 87:88, 95:96, 103:104, 3:4, 11:12, 19:20, 27:28, 35:36, 43:44, 51:52, 59:60, 67:68, 75:76, 83:84, 91:92, 99:100, 1:2, 9:10, 17:18, 25:26, 33:34, 41:42, 49:50, 57:58, 65:66, 73:74, 81:82, 89:90, 97:98, 5:6, 13:14, 21:22, 29:30, 37:38, 45:46, 53:54, 61:62, 69:70, 77:78, 85:86, 93:94, 101:102), ptype = integer(0), class = c("vctrs_list_of", "vctrs_vctr", "list"))), row.names = c(NA, -52L), class = c("tbl_df", "tbl", "data.frame"), .drop = TRUE), class = c("grouped_df", "tbl_df", "tbl", "data.frame"))
首先我用随机数据创建了一个可重现的数据集：
df <- data.frame(Year = rep(c(2009, 2010, 2011, 2012), 5),
Zone = rep(c("West", "Rankin", "Whipray", "Crocodile"), 5),
weighted_den = runif(20, 0, 1),
weighted_den_carid = runif(20, 0, 3))
之后，您应该使用以下代码 melt 您的数据：
library(reshape)
library(tidyverse)
df2 <- melt(df, id = c("Zone", "Year"))
并使用以下代码绘制带有第二个 y-axis 的条形图：
df2 %>% ggplot(aes(x = Zone, y = value, fill = variable)) +
geom_bar(stat = "identity", position = "dodge") +
scale_y_continuous("Carid", sec.axis = sec_axis(~ . *100, name = "Cneb"))
输出：
根据您的输入，我们可以创建以下代码，它似乎可以满足您的要求，但我不确定它作为可视化效果如何：
tidyr::pivot_wider(df, names_from = species, values_from = density) %>%
ggplot(aes(x = as.numeric(Zone) - 0.125)) +
geom_col(aes(y = weighted_den, group = 1, fill = 'weighted_den'),
width = 0.25) +
geom_col(aes(x = as.numeric(Zone) + 0.125,
y = weighted_den_carid / 100,
fill = 'weighted_den_carid'), width =0.25) +
scale_x_continuous(breaks = 1:4, labels = levels(df$Zone)) +
scale_y_continuous(sec.axis = sec_axis(trans = ~.x * 100,
name = 'weighted_den_carid')) +
facet_wrap(~Year, scales = 'free_y') +
theme_minimal() +
theme(axis.text.x = element_text(angle = 90))