這裏是作爲一個data.frame
數據的轉儲稱爲test
:
test <- structure(list(cluster = structure(c(6L, 7L, 17L, 1L, 8L, 11L,
15L, 2L, 4L, 5L, 16L, 12L, 9L, 14L, 13L, 10L, 3L), .Label = c("Cluster_10141",
"Cluster_10883", "Cluster_1419", "Cluster_16641", "Cluster_20143",
"Cluster_20637", "Cluster_20919", "Cluster_21451", "Cluster_26249",
"Cluster_28603", "Cluster_30198", "Cluster_32878", "Cluster_41908",
"Cluster_46928", "Cluster_55982", "Cluster_57942", "Cluster_9642"
), class = "factor"), value = c(0.02, 0.02, 0.147, 0.148, 0.148,
0.148, 0.498, 0.5, 0.5, 0.5, 0.867, 0.868, 0.87, 0.87, 0.871,
0.872, 0.873)), .Names = c("cluster", "value"), row.names = c(NA,
-17L), class = "data.frame")
它看起來像:
cluster value
1 Cluster_20637 0.020
2 Cluster_20919 0.020
3 Cluster_9642 0.147
<<snip>>
16 Cluster_28603 0.872
17 Cluster_1419 0.873
生成累積百分比變量
> test$cumperc <- (1:nrow(test))/nrow(test)
> test
cluster value cumperc
1 Cluster_20637 0.020 0.05882353
2 Cluster_20919 0.020 0.11764706
3 Cluster_9642 0.147 0.17647059
<<snip>>
14 Cluster_46928 0.870 0.82352941
15 Cluster_41908 0.871 0.88235294
16 Cluster_28603 0.872 0.94117647
17 Cluster_1419 0.873 1.00000000
然後繪製數據
圖(試驗$值,測試$ cumperc,類型= 「L」,XLIM = C(0,1))
![enter image description here](https://i.stack.imgur.com/iuoBH.png)
編輯解決下面的評論:
嘗試這組集羣第一:
tabvals <- table(test$value)
plot(names(tabvals),(1:length(tabvals))/length(tabvals),xlim=c(0,1),type="l")
哪個給出了這樣的情節:
![enter image description here](https://i.stack.imgur.com/OfnQR.png)
感謝joran的編輯 - 我無法弄清楚如何做格式化! – psaima
可能的重複:http://stackoverflow.com/questions/10030547/frequency-and-cumulative-frequency-curve-on-the-same-graph-in-r/10031056#10031056 –