废话不多说，上数据：
<br />
#这是我数据<br />
> T1<br />
mn kind deal day variable value<br />
1 E01 w C 5 mCa 1408.55606<br />
2 E01 w C 6 mCa 203.12438<br />
3 E01 m C 5 mCa 516.09401<br />
4 E01 m C 6 mCa 957.42041<br />
5 E01 n C 5 mCa 340.32281<br />
6 E01 n C 6 mCa 1385.94913<br />
7 E01 w P 6 mCa 371.25402<br />
8 E01 w P 7 mCa 1061.31650<br />
9 E01 w P 8 mCa 312.29193<br />
10 E01 w P 9 mCa 323.15918<br />
11 E01 m P 6 mCa 717.85780<br />
12 E01 m P 7 mCa 422.85011<br />
13 E01 m P 8 mCa 916.49068<br />
14 E01 m P 9 mCa 1141.75571<br />
15 E01 n P 6 mCa 374.74239<br />
16 E01 n P 7 mCa 352.06901<br />
17 E01 n P 8 mCa 808.32529<br />
18 E01 n P 9 mCa 449.08840<br />
19 E01 w C 5 mCb 466.35246<br />
20 E01 w C 6 mCb 55.33785<br />
21 E01 m C 5 mCb 136.34537<br />
22 E01 m C 6 mCb 296.63670<br />
23 E01 n C 5 mCb 94.93097<br />
24 E01 n C 6 mCb 446.53574<br />
25 E01 w P 6 mCb 103.36843<br />
26 E01 w P 7 mCb 318.95689<br />
27 E01 w P 8 mCb 76.99478<br />
28 E01 w P 9 mCb 82.84571<br />
29 E01 m P 6 mCb 226.63040<br />
30 E01 m P 7 mCb 112.83889<br />
31 E01 m P 8 mCb 272.76592<br />
32 E01 m P 9 mCb 356.53358<br />
33 E01 n P 6 mCb 97.80123<br />
34 E01 n P 7 mCb 89.60026<br />
35 E01 n P 8 mCb 247.39115<br />
36 E01 n P 9 mCb 115.42748<br />
> P2 <- ggplot(T1,aes(day,value,fill=kind))+<br />
geom_bar(stat="identity",position="dodge",width=0.8)+<br />
facet_wrap(~variable+deal,ncol=2,scales="free",as.table=FALSE)+<br />
theme_bw() # 绘图命令<br />
我想让每副图的bar width都一样，该怎么弄？当然 bar width 一样之后左边图形也得相应缩小~~~
这是使用我的命令创建的图效果：
</p>
另外，我在STACK overflow遇到了相似问题，但实在看不太懂，并且图形方式不一样~~~而且如果分开来画不是变得更加复杂了~~~就想着一步就把它给画好了。。。但上图实在不美观。。。
附上其链接：
http://stackoverflow.com/questions/11606441/ggplot2-gridextra-how-to-ensure-geom-bar-in-different-size-plot-grobs-result
麻烦大家了。。。[s:11]
PS:
附上我的csv文件（可直接粘贴成CSV文件）：
"","mn","kind","deal","day","variable","value"
"1","E01","w","C","5","mCa",1408.55606060606
"2","E01","w","C","6","mCa",203.124378596532
"3","E01","m","C","5","mCa",516.094012345679
"4","E01","m","C","6","mCa",957.420405443322
"5","E01","n","C","5","mCa",340.322806637807
"6","E01","n","C","6","mCa",1385.94913265306
"7","E01","w","P","6","mCa",371.254019607843
"8","E01","w","P","7","mCa",1061.31649590164
"9","E01","w","P","8","mCa",312.291926587302
"10","E01","w","P","9","mCa",323.159176470588
"11","E01","m","P","6","mCa",717.85780441447
"12","E01","m","P","7","mCa",422.850107142857
"13","E01","m","P","8","mCa",916.490676121949
"14","E01","m","P","9","mCa",1141.75571079294
"15","E01","n","P","6","mCa",374.742388888889
"16","E01","n","P","7","mCa",352.069013157895
"17","E01","n","P","8","mCa",808.325288614157
"18","E01","n","P","9","mCa",449.088395061728
"19","E01","w","C","5","mCb",466.352462121212
"20","E01","w","C","6","mCb",55.3378513497857
"21","E01","m","C","5","mCb",136.34537037037
"22","E01","m","C","6","mCb",296.636697530864
"23","E01","n","C","5","mCb",94.9309668109668
"24","E01","n","C","6","mCb",446.535739795918
"25","E01","w","P","6","mCb",103.368433952528
"26","E01","w","P","7","mCb",318.956885245902
"27","E01","w","P","8","mCb",76.9947757936508
"28","E01","w","P","9","mCb",82.8457058823529
"29","E01","m","P","6","mCb",226.630402820356
"30","E01","m","P","7","mCb",112.838892857143
"31","E01","m","P","8","mCb",272.765922054064
"32","E01","m","P","9","mCb",356.533577446704
"33","E01","n","P","6","mCb",97.8012323232323
"34","E01","n","P","7","mCb",89.6002631578947
"35","E01","n","P","8","mCb",247.391152758392
"36","E01","n","P","9","mCb",115.427478882391
