So, I'm trying to build a horizontal barplot on R, as follows:
influencers=c(rep(row.names(data),4))
networks=c(rep("Youtube",60),rep("Twitter",60),rep("Instagram",60),rep("Facebook",60))
followers=c(f.you,f.twi,f.ins,f.fac)/1000000
bars=data.frame(influencers,networks,followers)
ggplot(bars, aes(fill=networks, y=followers, x=reorder(influencers,followers)))
geom_bar(position="stack", stat="identity")
coord_flip()
ylab("Followers (millions)")
xlab("")
theme_bw()
But the resulting plot is totally messed up, there are some bars with entries that simply doesn't exist on my data. I guess the only data that's correct is the YouTube... Check this out:
I've used a "*" on some of the wrong data.
I don't know what to do. I've double checked the data frame (the data are paired correctly), the values seems to be right, I replace any NA with 0, now I'm trying to reorder like this:
ggplot(bars, aes(reorder(influencers,as.numeric(gsub('([0-9] ).*','\\1',influencers))),followers,fill=networks))
coord_flip()
geom_bar(position="stack", stat="identity")
theme_bw()
But still unsuccessfully, sadly... Someone help me, please.
The data frame:
influencers networks followers
1 Gene Youtube 0.102000
2 Yoonjoo Youtube 0.199000
3 Bruce Youtube 0.061000
4 Lauryn Youtube 0.069100
5 Eli Youtube 0.007280
6 Danielle Youtube 0.219000
7 Makayla Youtube 0.025000
8 Jacky Youtube 0.156000
9 Kelly Youtube 0.029300
10 Olivia Youtube 1.010000
11 Sahl Youtube 1.100000
12 Kiel Youtube 0.164000
13 Shantiana Youtube 0.324000
14 Belle Youtube 2.500000
15 Jeremy Youtube 0.045300
16 Jaasir Youtube 0.010900
17 Zuhaira Youtube 0.029700
18 Khaira Youtube 0.013000
19 Chelsea Youtube 3.150000
20 Viviana Youtube 0.097300
21 Muzammil Youtube 0.088300
22 Gabriela Youtube 0.474000
23 Isaiah Youtube 0.034800
24 Anjanetta Youtube 0.019200
25 Dimitri Youtube 0.024800
26 Abbigelle Youtube 0.007160
27 Hinna Youtube 0.025700
28 Ethan Youtube 0.397000
29 Ashante Youtube 15.800000
30 Heather Youtube 0.212000
31 Johney Youtube 0.043500
32 Falon Youtube 2.170000
33 Kylie Youtube 0.105000
34 Alicia Youtube 0.133000
35 Xochitl Youtube 0.731000
36 Jaasir Youtube 1.420000
37 Amber Youtube 0.005140
38 Brandon Youtube 0.152000
39 Rana Youtube 0.268000
40 Jameela Youtube 0.014300
41 Breanna Youtube 1.150000
42 Victor Youtube 0.048400
43 Mckenna Youtube 0.085700
44 Matthew Youtube 0.740000
45 Chelsea Youtube 0.084200
46 Blake Youtube 0.127000
47 Jordynne Youtube 0.098500
48 Sarah Youtube 0.065900
49 Desmond Youtube 0.024200
50 Alexandra Youtube 1.080000
51 Mahboob Youtube 0.045200
52 Xiao Youtube 0.104000
53 Julio Youtube 0.017300
54 Numa Youtube 0.013800
55 Daniel Youtube 0.304000
56 Keisha Youtube 0.010100
57 Shaquille Youtube 0.008310
58 Kara Youtube 0.020500
59 Lauren Youtube 0.015800
60 Kevin Youtube 0.184000
61 Gene Twitter 0.017600
62 Yoonjoo Twitter 0.005412
63 Bruce Twitter 0.014800
64 Lauryn Twitter 0.016200
65 Eli Twitter 0.000619
66 Danielle Twitter 0.010000
67 Makayla Twitter 0.000394
68 Jacky Twitter 0.044000
69 Kelly Twitter 0.004881
70 Olivia Twitter 0.220100
71 Sahl Twitter 0.066500
72 Kiel Twitter 0.038400
73 Shantiana Twitter 0.075900
74 Belle Twitter 0.171100
75 Jeremy Twitter 0.006399
76 Jaasir Twitter 0.000000
77 Zuhaira Twitter 0.005434
78 Khaira Twitter 0.024100
79 Chelsea Twitter 0.398300
80 Viviana Twitter 0.059900
81 Muzammil Twitter 0.009801
82 Gabriela Twitter 0.000926
83 Isaiah Twitter 0.000276
84 Anjanetta Twitter 0.000027
85 Dimitri Twitter 0.000405
86 Abbigelle Twitter 0.004262
87 Hinna Twitter 0.000048
88 Ethan Twitter 0.069400
89 Ashante Twitter 0.154200
90 Heather Twitter 0.027100
91 Johney Twitter 0.006558
92 Falon Twitter 0.009579
93 Kylie Twitter 0.010700
94 Alicia Twitter 0.016400
95 Xochitl Twitter 0.002992
96 Jaasir Twitter 0.008854
97 Amber Twitter 0.001494
98 Brandon Twitter 0.022600
99 Rana Twitter 0.104800
100 Jameela Twitter 0.000000
101 Breanna Twitter 0.014100
102 Victor Twitter 0.011600
103 Mckenna Twitter 0.016200
104 Matthew Twitter 0.015000
105 Chelsea Twitter 0.000467
106 Blake Twitter 0.007961
107 Jordynne Twitter 0.010400
108 Sarah Twitter 0.067400
109 Desmond Twitter 0.016100
110 Alexandra Twitter 0.196800
111 Mahboob Twitter 0.001396
112 Xiao Twitter 0.000423
113 Julio Twitter 0.004294
114 Numa Twitter 0.004294
115 Daniel Twitter 0.002621
116 Keisha Twitter 0.005747
117 Shaquille Twitter 0.013600
118 Kara Twitter 0.001728
119 Lauren Twitter 0.018700
120 Kevin Twitter 0.254200
121 Gene Instagram 0.023200
122 Yoonjoo Instagram 0.013500
123 Bruce Instagram 0.004958
124 Lauryn Instagram 0.006026
125 Eli Instagram 0.001726
126 Danielle Instagram 0.013700
127 Makayla Instagram 0.005150
128 Jacky Instagram 0.013200
129 Kelly Instagram 0.000932
130 Olivia Instagram 0.164000
131 Sahl Instagram 0.058100
132 Kiel Instagram 0.015000
133 Shantiana Instagram 0.250000
134 Belle Instagram 0.159000
135 Jeremy Instagram 0.005613
136 Jaasir Instagram 0.024100
137 Zuhaira Instagram 0.002463
138 Khaira Instagram 0.012100
139 Chelsea Instagram 1.100000
140 Viviana Instagram 0.012900
141 Muzammil Instagram 0.000000
142 Gabriela Instagram 0.123000
143 Isaiah Instagram 0.000000
144 Anjanetta Instagram 0.000000
145 Dimitri Instagram 0.007311
146 Abbigelle Instagram 0.000000
147 Hinna Instagram 0.000550
148 Ethan Instagram 0.037700
149 Ashante Instagram 1.300000
150 Heather Instagram 0.064500
151 Johney Instagram 0.002818
152 Falon Instagram 0.236000
153 Kylie Instagram 0.003012
154 Alicia Instagram 0.006570
155 Xochitl Instagram 0.002851
156 Jaasir Instagram 0.039800
157 Amber Instagram 0.000000
158 Brandon Instagram 0.122000
159 Rana Instagram 0.015900
160 Jameela Instagram 0.000459
161 Breanna Instagram 0.114000
162 Victor Instagram 0.001928
163 Mckenna Instagram 0.019200
164 Matthew Instagram 0.036600
165 Chelsea Instagram 0.000000
166 Blake Instagram 0.002878
167 Jordynne Instagram 0.001471
168 Sarah Instagram 0.056500
169 Desmond Instagram 0.006116
170 Alexandra Instagram 0.249000
171 Mahboob Instagram 0.084500
172 Xiao Instagram 0.019300
173 Julio Instagram 0.001462
174 Numa Instagram 0.000480
175 Daniel Instagram 0.054900
176 Keisha Instagram 0.038800
177 Shaquille Instagram 0.001876
178 Kara Instagram 0.001439
179 Lauren Instagram 0.149000
180 Kevin Instagram 0.000000
181 Gene Facebook 0.007575
182 Yoonjoo Facebook 1.100000
183 Bruce Facebook 0.001200
184 Lauryn Facebook 0.004528
185 Eli Facebook 0.009964
186 Danielle Facebook 0.009003
187 Makayla Facebook 0.021634
188 Jacky Facebook 0.000292
189 Kelly Facebook 0.000000
190 Olivia Facebook 0.156000
191 Sahl Facebook 0.078983
192 Kiel Facebook 0.017000
193 Shantiana Facebook 0.233374
194 Belle Facebook 0.161573
195 Jeremy Facebook 0.014684
196 Jaasir Facebook 0.001494
197 Zuhaira Facebook 0.009570
198 Khaira Facebook 0.028940
199 Chelsea Facebook 3.100000
200 Viviana Facebook 0.182149
201 Muzammil Facebook 0.007312
202 Gabriela Facebook 0.214692
203 Isaiah Facebook 0.002075
204 Anjanetta Facebook 0.002177
205 Dimitri Facebook 0.001302
206 Abbigelle Facebook 0.000000
207 Hinna Facebook 0.003285
208 Ethan Facebook 0.028915
209 Ashante Facebook 1.958553
210 Heather Facebook 0.100000
211 Johney Facebook 0.004370
212 Falon Facebook 2.900000
213 Kylie Facebook 0.037525
214 Alicia Facebook 0.002348
215 Xochitl Facebook 0.006795
216 Jaasir Facebook 0.043135
217 Amber Facebook 0.038273
218 Brandon Facebook 0.054236
219 Rana Facebook 0.001504
220 Jameela Facebook 0.000000
221 Breanna Facebook 0.018074
222 Victor Facebook 0.078139
223 Mckenna Facebook 0.000000
224 Matthew Facebook 0.004010
225 Chelsea Facebook 0.000000
226 Blake Facebook 0.016021
227 Jordynne Facebook 0.003817
228 Sarah Facebook 0.017835
229 Desmond Facebook 0.001974
230 Alexandra Facebook 0.098445
231 Mahboob Facebook 0.011106
232 Xiao Facebook 0.012203
233 Julio Facebook 0.010359
234 Numa Facebook 0.000000
235 Daniel Facebook 0.008060
236 Keisha Facebook 1.700276
237 Shaquille Facebook 0.001203
238 Kara Facebook 0.000000
239 Lauren Facebook 0.000000
240 Kevin Facebook 0.049425
CodePudding user response：
It is slightly unclear if this is what you were talking about especially as you have no labels on your y axis, but I think your problem is that you are ordering your x values within the aes call. So therefore your y values are already set but you are effectively assigning them a random x value as they were out of order.
You are better off to assign a level to the influencers based on the total number of followers to order your plot
library(dplyr)
#count total followers and arrange plot
bars <- bars %>% group_by(influencers) %>%
mutate(total =sum(followers)) %>% arrange(total)
#set influencers levels based on total followers
bars <- bars %>% mutate(influencers = factor(influencers, levels = unique(bars$influencers)))
#plot without reordering
ggplot(bars,
aes(fill=networks, y=followers, x=influencers))
geom_bar(position="stack", stat="identity")
coord_flip()
ylab("Followers (millions)")
xlab("")
theme_bw()`
CodePudding user response：
Soo... I'm kind of embarrassed right now. I've misunderstood the graph, I realized just now that they're, as the function says, stacked! I thought it was juxtaposed.
I'm sorry for the trouble and many thanks to those who helped me!