ggplot2 R空间中负值和​​正值的气泡图

Question

I would like to make a bubble plot using ggplot2 in R. My code and data are found below. Please leave the colors as they are. I am having difficulties in scaling positive and negative values equally. For example, -3 is scaled smaller than +3. I would like negatives and positives to be scaled proportionately irrespective of sign.

Identify negative from positive values using some kind of outline linetype for bubbles and include it in the legend.

Also remove the "Mean" part of the legend.

Thanks very much for your great help.

#=====================================================================

library(ggplot2) 
if (dev.cur() == 1) x11(width=8,height=6) 
par(mfcol=c(1,1)) 
p<-ggplot(site.resiudal, aes(x=Eastings, y=Northings, size=Mean,label=site.resiudal$Site,legend = FALSE))+ 
#theme(legend.position="none")+
geom_point(shape=21)+ 
geom_point(aes(colour = factor(Region)))+ 
scale_area(range=c(1,15))+ 
scale_alpha(guide = 'none')+
scale_x_continuous(name="Longitude", limits=c(-120,-95))+ 
scale_y_continuous(name="Latitude", limits=c(48,61))+ 
geom_text(size=4)+
scale_colour_manual(name="Region",labels = c("A", "B","C","D", "E"),values = c("1" =   "firebrick3","2" = "palegreen4","3" = "sandybrown","4" = "red","5" = "gray0"))+
theme(legend.title = element_text(colour="black", size=16, face="plain"))+
theme(legend.text = element_text(colour="black", size = 16, face = "plain"))

p

#Data[["sign"]] = ifelse(Data[["Mean"]] >= 0, "positive", "negative")

#=================================================

structure(list(Site = structure(c(101L, 102L, 105L, 107L, 108L, 
110L, 111L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 
13L, 14L, 16L, 20L, 47L, 52L, 53L, 55L, 91L, 92L, 93L, 94L, 95L, 
96L, 99L, 15L, 17L, 18L, 19L, 21L, 114L, 23L, 26L, 36L, 59L, 
60L, 61L, 62L, 63L, 64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 
73L, 74L, 75L, 76L, 77L, 78L, 79L, 80L, 81L, 82L, 83L, 84L, 85L, 
86L, 87L, 88L, 89L, 98L, 100L, 103L, 104L, 106L, 109L, 112L, 
113L, 115L, 116L, 117L, 119L, 42L, 44L, 46L, 48L, 49L, 50L, 51L, 
54L, 56L, 57L, 58L, 90L, 97L, 118L, 120L, 22L, 24L, 25L, 27L, 
28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 37L, 38L, 39L, 40L, 41L, 
43L, 45L), .Label = c("G100", "G101", "G102", "G103", "G104", 
"G105", "G106", "G107", "G108", "G109", "G110", "G111", "G112", 
"G113", "G114", "G115", "G116", "G117", "G118", "G119", "G120", 
"GG10", "GG11", "GG12", "GG13", "GG14", "GG15", "GG16", "GG17", 
"GG18", "GG19", "GG20", "GG21", "GG22", "GG23", "GG24", "GG25", 
"GG26", "GG27", "GG28", "GG29", "GG30", "GG31", "GG32", "GG33", 
"GG34", "GG35", "GG36", "GG37", "GG38", "GG39", "GG40", "GG41", 
"GG42", "GG43", "GG44", "GG45", "GG46", "GG47", "GG48", "GG49", 
"GG50", "GG51", "GG52", "GG53", "GG54", "GG55", "GG56", "GG57", 
"GG58", "GG59", "GG60", "GG61", "GG62", "GG63", "GG64", "GG65", 
"GG66", "GG67", "GG68", "GG69", "GG70", "GG71", "GG72", "GG73", 
"GG74", "GG75", "GG76", "GG77", "GG78", "GG79", "GG80", "GG81", 
"GG82", "GG83", "GG84", "GG85", "GG86", "GG87", "GG88", "GG89", 
"GG90", "GG91", "GG92", "GG93", "GG94", "GG95", "GG96", "GG97", 
"GG98", "GG99", "GGG1", "GGG2", "GGG3", "GGG4", "GGG5", "GGG6", 
"GGG7", "GGG8", "GGG9"), class = "factor"), Name = structure(c(53L, 
87L, 29L, 92L, 36L, 76L, 102L, 103L, 119L, 2L, 9L, 11L, 45L, 
47L, 49L, 54L, 90L, 30L, 105L, 66L, 78L, 107L, 81L, 42L, 41L, 
43L, 59L, 110L, 24L, 27L, 56L, 61L, 64L, 118L, 40L, 21L, 44L, 
70L, 108L, 25L, 58L, 98L, 83L, 5L, 19L, 26L, 31L, 38L, 55L, 60L, 
71L, 74L, 75L, 85L, 95L, 120L, 109L, 1L, 67L, 20L, 50L, 63L, 
106L, 111L, 116L, 62L, 6L, 99L, 114L, 73L, 84L, 89L, 93L, 97L, 
115L, 80L, 10L, 12L, 88L, 79L, 15L, 17L, 33L, 35L, 94L, 100L, 
3L, 16L, 37L, 101L, 117L, 8L, 39L, 48L, 86L, 113L, 23L, 13L, 
69L, 96L, 104L, 32L, 65L, 82L, 14L, 22L, 18L, 46L, 68L, 72L, 
77L, 91L, 112L, 4L, 7L, 28L, 51L, 57L, 52L, 34L), .Label = c("ANEROID", 
"ARBORG", "ATHABASCA", "BANFF", "BANGOR", "BATTLEFORD", "BEAVER MINES", 
"BEAVERLODGE", "BERENS RIVER", "BIRTLE", "BISSETT", "BRANDON", 
"BUFFALO NARROWS", "CALGARY", "CALMAR", "CAMPSIE", "CAMROSE", 
"CARWAY", "CEYLON", "CHAPLIN", "CHURCHILL", "CLARESHOLM", "COLD LAKE", 
"COLLINS BAY", "CORONATION", "COTE", "CREE LAKE", "CROWSNEST", 
"CYPRESS RIVER", "DAUPHIN", "DAVIDSON", "DRUMHELLER", "EDMONTON", 
"EDSON", "ELK POINT", "EMERSON AUT", "ENILDA-BERG", "ESTEVAN", 
"FAIRVIEW", "FLIN FLON", "FORT CHIPEWYAN", "FORT MCMURRAY", "FORT VERMILION", 
"GILLAM", "GIMLI", "GLEICHEN", "GRAND RAPIDS", "GRANDE PRAIRIE", 
"GREAT FALLS", "HIGH POINT", "HIGHWOOD", "HINTON VALLEY", "HUDSON BAY", 
"INDIAN BAY", "INDIAN HEAD", "ISLAND FALLS", "JASPER WARDEN", 
"JENNER", "KEG RIVER RS", "KELLIHER", "KEY LAKE", "KINDERSLEY", 
"KLINTONEL", "LA RONGE", "LACOMBE 2", "LANGRUTH WEST", "LEADER", 
"LETHBRIDGE", "LOON LAKE", "LYNN LAKE", "MANOR", "MEDICINE HAT", 
"MELFORT", "MOOSE JAW", "MOOSOMIN", "MORDEN", "MOUNTAIN VIEW", 
"NEEPAWA MURRAY", "NINETTE", "NIPAWIN", "NORWAY HOUSE", "OLDS", 
"ONEFOUR", "OUTLOOK", "PASWEGIN", "PEACE RIVER", "PELLY", "PIERSON", 
"PILGER", "PINAWA WNRE", "PINCHER CREEK ", "PORTAGE PRAIRIE", 
"PRINCE ALBERT", "RANFURLY", "REGINA", "ROCKY MT HOUSE ", "SASKATOON", 
"SCOTFIELD", "SCOTT", "SION", "SLAVE LAKE", "SPRAGUE", "STEINBACH", 
"STETTLER NORTH", "SWAN RIVER", "SWIFT CURRENT", "THE PAS", "THOMPSON", 
"TONKIN", "URANIUM CITY ", "VAL-MARIE", "VAUXHALL", "WABASCA RS", 
"WASECA", "WASKESIU LAKE", "WEST POPLAR", "WHITECOURT", "WHITESAND DAM", 
"WINNIPEG", "YELLOW GRASS"), class = "factor"), Mean = c(-0.020525899, 
0.333863493, 0.210353772, NA, NA, 0.093520458, 0.341295298, NA, 
-0.175074657, 0.09834825, 0.075610648, NA, -0.117503802, 0.18309367, 
0.25246942, 0.221329766, 0.072167004, -0.094766032, NA, NA, 0.19783711, 
-0.166351357, -0.0996169, -0.038555432, -0.028092042, 0.297855371, 
0.108263891, 0.002057761, 0.327731415, NA, 0.180100638, 0.193837736, 
-0.003306948, 0.178881894, 0.3655509, -0.235975798, -0.176154056, 
-0.080433735, -0.110955273, -0.228010105, 0.048103255, -0.116681527, 
-0.073042421, NA, NA, 0.035356012, 0.297171565, -0.197834719, 
0.036412958, 0.055218077, NA, -0.236229087, 0.265211081, 0.271625885, 
-0.293179359, 0.113744571, -0.207770026, 0.100471248, -0.071569464, 
NA, NA, NA, -0.052716493, 0.057385851, 0.090340517, -0.30456625, 
-0.234420722, 0.082287977, 0.009973663, NA, -0.06405062, 0.074703356, 
-0.208329196, -0.272401078, 0.217991554, -0.043619919, -0.208901155, 
-0.020022401, 0.111495318, NA, 0.38239749, 0.199136959, -0.177740258, 
NA, 0.147515615, 0.309306538, 0.298741467, 0.068170296, NA, -0.02102765, 
0.001754313, -0.010196512, 0.108254156, -0.228183063, -0.196261239, 
NA, -0.167054722, 0.039949534, 0.154337034, -0.020855461, 0.136010278, 
NA, 0.096997744, NA, -0.241963754, 0.660176529, 0.423554314, 
0.190305726, -0.210778787, -0.261148915, NA, 0.054264129, -0.098706619, 
-0.138776994, NA, NA, NA, -0.113823745, 0.373292721, -0.047060083 
), Eastings = c(-102.5800018, -101.8700027, -99.08000183, -98.26999664, 
-97.23000336, -98.08000183, -95.59999847, -96.76999664, -97.23000336, 
-97.08000183, -97.02999878, -95.69999695, -97.01999664, -99.27999878, 
-96, -95.19999695, -96.06999969, -100.0500031, -101.2300034, 
-98.80000305, -99.56999969, -101.0999985, -97.84999847, -111.2200012, 
-111.1200027, -116.0299988, -117.6200027, -108.4800034, -103.6999969, 
-107.1299973, -102.3499985, -105.6200027, -105.2699966, -103.1500015, 
-101.8799973, -94.06999969, -94.72000122, -101.0800018, -97.87000275, 
-111.4499969, -111.1999969, -111.3499985, -110.4700012, -102.2799988, 
-104.6500015, -101.7799988, -105.9800034, -102.9700012, -103.6500015, 
-103.75, -102.0999985, -105.5500031, -101.6699982, -103.9199982, 
-104.6699982, -104.1800003, -102.2300034, -107.3000031, -109.5, 
-106.6500015, -107.9300003, -108.9199982, -107.7300034, -107.8499985, 
-106.3799973, -109.1800003, -108.25, -108.8300018, -109.4000015, 
-104.5999985, -107.0500031, -105.1500015, -105.6699982, -106.7200012, 
-106.0699997, -104, -101.0500031, -99.94999695, -101.2699966, 
-99.65000153, -113.8499985, -112.8199997, -113.5800018, -111.0699997, 
-111.7300034, -114.1200027, -113.2799988, -114.6800003, -116.3000031, 
-114.7799988, -115.7799988, -119.4000015, -118.5299988, -118.8799973, 
-117.4499969, -113.8300018, -110.2799988, -108.4300003, -109.0999985, 
-114.9199982, -112.7200012, -112.8700027, -113.75, -114.0999985, 
-114.0199966, -113.7300034, -113.3799973, -113.0500031, -112.8000031, 
-110.7200012, -113.6299973, -113.9800034, -112.1299973, -115.5500031, 
-114.1800003, -114.4800034, -114.3700027, -118.0299988, -117.5299988, 
-116.4499969), Northings = c(52.88000107, 52.08000183, 49.54999924, 
49.95000076, 49, 49.18000031, 49.02000046, 49.52999878, 49.91999817, 
50.93000031, 52.34999847, 51.02999878, 50.63000107, 53.15000153, 
50.47000122, 49.61999893, 50.18000031, 51.09999847, 52.11999893, 
50.41999817, 50.15000153, 53.97000122, 53.97000122, 56.65000153, 
58.77000046, 58.38000107, 57.75, 59.56999969, 58.18000031, 57.34999847, 
55.52999878, 57.25, 55.15000153, 56.22999954, 54.77000046, 58.72999954, 
56.34999847, 56.86999893, 55.79999924, 52.06999969, 50.72000122, 
51.58000183, 49.11999893, 50.90000153, 49.38000107, 51.52000046, 
51.27000046, 49.22000122, 50.54999924, 51.25, 49.61999893, 50.33000183, 
50.13000107, 51.97999954, 50.43000031, 49.81999969, 51.20000076, 
49.72000122, 50.90000153, 50.47000122, 50.97999954, 49.68000031, 
50.27000046, 49.36999893, 49, 51.52000046, 52.77000046, 52.36999893, 
53.13000107, 52.81999969, 51.47999954, 52.41999817, 53.22000122, 
52.16999817, 53.91999817, 53.33000183, 50.43000031, 49.91999817, 
49.18000031, 49.41999817, 53.27999878, 53.02999878, 53.31999969, 
53.88000107, 53.41999817, 53.88000107, 54.72000122, 54.13000107, 
55.41999817, 55.27999878, 54.15000153, 55.20000076, 56.08000183, 
55.18000031, 56.22999954, 55.97000122, 54.41999817, 55.83000183, 
54.04999924, 52.41999817, 52.33000183, 51.47000122, 52.45000076, 
51.77999878, 51.11999893, 49.93000031, 49, 50.88000107, 49.63000107, 
50.02000046, 49.13000107, 49.52000046, 50.04999924, 51.20000076, 
49.47000122, 49.63000107, 50.54999924, 52.93000031, 53.40000153, 
53.58000183), Region = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 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, 2L, 2L, 2L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 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, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L)), .Names = c("Site", 
"Name", "Mean", "Eastings", "Northings", "Region"), class = "data.frame", row.names =      c(NA, 
-120L))


#============================================

Answer 1

use abs()

eg instead of size=Mean use size=abs(Mean)

Then, you can track the sign using shape (or some other aesthetic, but color and size are already taken)

replace:

 geom_point(shape=21)+ 
 geom_point(aes(colour = factor(Region))) + 

with the single line

geom_point(aes(shape=factor(sign(Mean)), colour = factor(Region))) + 

If you'd like, you can also add lines such as

    scale_shape_discrete(name="Mean Is", breaks=c(-1, 1), labels=c("Negative", "Positive"))

    guides(size=FALSE)