R 根据分类因子将ggplot上的点更改为颜色

我正在尝试改进我的

ggplot

，它是用

dotwisker

包中的

small\u multiple

创建的。我很高兴看到这样的情节，但我想改变颜色，以显示效果大小的重要性，并提供一个图例

下面是我用来绘图的数据框的链接

以及

dput

输出

structure(list(term = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 
1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L, 
3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L, 7L), .Label = c("Age of householder", 
"Resident", "Household size", "Receives remitances", "External income", 
"Number of Dependents", "Wealth Quartile (linear)"), class = "factor"), 
    estimate = c(-0.000810532238065848, 0.0254269932291557, 0.00151239486806329, 
    -0.00195137580266825, 0.0241145273101975, 7.89713470909372e-05, 
    0.0431864414315616, -0.000352189998018801, 0.0807237065792145, 
    0.00350237566205939, 0.0824016056908091, 0.000428245312902082, 
    0.00100203882798397, -0.00373159468619221, -0.00849653886442907, 
    -0.373953842018999, -0.0609596475582067, -0.36695400544924, 
    -0.203483373342371, 0.0235518405167902, 0.597075641980254, 
    0.000909859014488281, 0.0319827360659694, 0.00403573196123029, 
    0.0804028888279925, 0.0176817124413346, -0.00582802408980782, 
    -0.0118019232578557, -0.00183146459363335, 0.0525149485157465, 
    0.00288980763951367, 0.114589339700339, -0.148808706655833, 
    0.0256886983033479, -0.0347089125407724), std.error = c(0.000810654234866564, 
    0.0252884817638327, 0.00495624457235766, 0.02865293313387, 
    0.024633101790692, 0.0075249698129155, 0.011074940767766, 
    0.0015232885358452, 0.0483657672257486, 0.0107841171733555, 
    0.0465110585212233, 0.0453369280370182, 0.0159322010498352, 
    0.0229851941101918, 0.00503353340127795, 0.160380043957635, 
    0.0336136390831826, 0.177927931390999, 0.157637829739609, 
    0.0502799707398752, 0.0734336375273297, 0.00155887187625948, 
    0.0506436749394975, 0.00906123485748438, 0.0593975064913416, 
    0.0512499791059356, 0.0149811592829444, 0.0215922521880395, 
    0.00519154572969568, 0.168543739122589, 0.0312059226076805, 
    0.181305323277894, 0.172221721744089, 0.048730984968198, 
    0.0723545683575288), statistic = c(-0.999849508217599, 1.00547725508461, 
    0.305149361776521, -0.0681038759121512, 0.978948064076507, 
    0.0104945732746189, 3.89947380642044, -0.231203734375501, 
    1.66902566028642, 0.324771662414126, 1.77165621060223, 0.00944583877744019, 
    0.0628939356746528, -0.162347756051257, -1.68798698390914, 
    -2.3316731482988, -1.81353906393032, -2.06237437023226, -1.29082830992085, 
    0.468413966241872, 8.13081936405562, 0.583665039022637, 0.631524787728739, 
    0.445384323958546, 1.35364081048946, 0.345009163902015, -0.389023571523124, 
    -0.54658139202325, -0.352778283962203, 0.311580535646894, 
    0.0926044608853327, 0.632024132709568, -0.864053065715796, 
    0.527153274659078, -0.479705889049931), p.value = c(0.317383342554256, 
    0.314667096264215, 0.760252397576013, 0.945702944991097, 
    0.327605641839857, 0.991626695712718, 9.64019651538276e-05, 
    0.817156528984679, 0.0951122945259745, 0.745353893046104, 
    0.0764516427435714, 0.992463423149573, 0.949850963916399, 
    0.871032009571373, 0.0914137275496443, 0.0197178924481877, 
    0.0697487192470644, 0.0391721074734652, 0.196763218800044, 
    0.639488582387532, 4.26398344685646e-16, 0.559445693078128, 
    0.527697446929629, 0.656042038835549, 0.175851000195762, 
    0.730087481451201, 0.697258709585814, 0.584666355951097, 
    0.724254665274968, 0.755359328643605, 0.926217799705955, 
    0.527371108047216, 0.387558740148672, 0.598087153395465, 
    0.631436539811527), model = c("Dietary diversity", "Dietary diversity", 
    "Dietary diversity", "Dietary diversity", "Dietary diversity", 
    "Dietary diversity", "Dietary diversity", "Food security \n(Cond)", 
    "Food security \n(Cond)", "Food security \n(Cond)", "Food security \n(Cond)", 
    "Food security \n(Cond)", "Food security \n(Cond)", "Food security \n(Cond)", 
    "Food security \n(Zinf)", "Food security \n(Zinf)", "Food security \n(Zinf)", 
    "Food security \n(Zinf)", "Food security \n(Zinf)", "Food security \n(Zinf)", 
    "Food security \n(Zinf)", "Vegetable consumption \n(Cond)", 
    "Vegetable consumption \n(Cond)", "Vegetable consumption \n(Cond)", 
    "Vegetable consumption \n(Cond)", "Vegetable consumption \n(Cond)", 
    "Vegetable consumption \n(Cond)", "Vegetable consumption \n(Cond)", 
    "Vegetable consumption \n(Zinf)", "Vegetable consumption \n(Zinf)", 
    "Vegetable consumption \n(Zinf)", "Vegetable consumption \n(Zinf)", 
    "Vegetable consumption \n(Zinf)", "Vegetable consumption \n(Zinf)", 
    "Vegetable consumption \n(Zinf)"), Significance = c("non-significant", 
    "non-significant", "non-significant", "non-significant", 
    "non-significant", "non-significant", "< 0.05", "non-significant", 
    "< 0.1", "non-significant", "< 0.1", "non-significant", "non-significant", 
    "non-significant", "< 0.1", "< 0.05", "< 0.1", "< 0.05", 
    "non-significant", "non-significant", "< 0.05", "non-significant", 
    "non-significant", "non-significant", "non-significant", 
    "non-significant", "non-significant", "non-significant", 
    "non-significant", "non-significant", "non-significant", 
    "non-significant", "non-significant", "non-significant", 
    "non-significant")), row.names = c(NA, -35L), class = "data.frame", .Names = c("term", 
"estimate", "std.error", "statistic", "p.value", "model", "Significance"
))  

基本上，我希望根据数据框中的变量

重要性

对点和胡须进行着色，并用图例显示三个因子级别

---

任何帮助都将不胜感激，因为我已经在这个问题上把头撞在墙上很长一段时间了，我相信一定有一个现成的解决方案

请将您的数据的代表性样本直接放在帖子中，最好是

dput

的输出，这样人们就不必从单独的站点下载文件source@camille，我添加了

dput

输出。我认为下载可能会更容易，但重点是从现在开始使用

dput

。

small_multiple(stack_mods_dummys)+
ylab("Coefficient Estimate") +
geom_hline(yintercept = 0, colour = "grey60", linetype = 2) +
theme(axis.text.x  = element_text(angle = 90, hjust = 1,vjust = 0.5))+
facet_wrap(~term,nrow = 5, scales = "free_y")