R 水彩画

我正在处理一个相当大的数据集（2000列，11行）。下面是其中的一个子集

     Col1      Col2       Col3      Col4       Col5      Col6         Col7        Col8      Col9       Col10
1  2509.60840 650.44520 1208.00000 1795.00000 2889.000000 2158.00000 1827.25070 1482.000000 1858.00000 2544.39450
2    58.03994 -23.13326  -15.49636   12.09075   86.300341   34.46581   13.94546   -4.533958   15.89606   60.50394
3    94.15235  48.95360   80.27238  120.64317   62.791467  309.90168  175.94835  175.427179   83.94264  173.50097
4   245.69264  55.18302  137.75501  200.89969  -26.608255  161.46379  237.20321   84.304826  178.47248   97.40814
5    48.63110  70.49905  111.77759  181.52456 -107.426908  278.38505  116.95109  151.338578  218.93919   57.89194
6   264.90391  71.18622  129.02855  116.35842  -49.956152  147.17100  147.19528  229.756718   98.92684  193.43460
7   208.02697  75.31583   70.26002  136.39284    4.383722  150.74978  156.59314  162.983479   87.34028  358.01097
8   168.77588  71.57783  156.26653  132.90093   46.189138  254.28341  131.49356  211.540117   69.87448  312.34010
9   212.42247  53.04903  165.36475   49.42609  -14.050163   75.35783  160.37957  150.106290   96.19735  170.49562
10  175.34079  56.51675  148.31084  150.04976   32.373020  120.79866  147.48743  126.595648   84.46121  142.00257
11  249.20497  60.53568  139.56612  145.09104    6.308908  127.05724  141.34019  134.092717  103.45419  294.44998
12   67.80644  46.36427  101.25284  128.60477  -33.661878  361.66227   81.30154   88.232663  138.95064   83.37984

如何从该数据集创建瀑布线图？像这样的东西

请注意，第一行

{2509.60840650.44520 1208.000001795.000002889.0000002158.000001827.250701482.0000001858.000002544.39450}

中的值是我的x值，其余是对应于每个x值的y值。比如说

---

{58.03994，94.15235，245.69264，48.63110264.90391…..67.80644}

是我的

y

值，与

x=2509.60840

等相关。

从

将数据帧更改为可行的数据帧

library(tidyverse)
    structure(list(Col1 = c(2509.6084, 58.03994, 94.15235, 245.69264, 
48.6311, 264.90391, 208.02697, 168.77588, 212.42247, 175.34079, 
249.20497, 67.80644), Col2 = c(650.4452, -23.13326, 48.9536, 
55.18302, 70.49905, 71.18622, 75.31583, 71.57783, 53.04903, 56.51675, 
60.53568, 46.36427), Col3 = c(1208, -15.49636, 80.27238, 137.75501, 
111.77759, 129.02855, 70.26002, 156.26653, 165.36475, 148.31084, 
139.56612, 101.25284), Col4 = c(1795, 12.09075, 120.64317, 200.89969, 
181.52456, 116.35842, 136.39284, 132.90093, 49.42609, 150.04976, 
145.09104, 128.60477), Col5 = c(2889, 86.300341, 62.791467, -26.608255, 
-107.426908, -49.956152, 4.383722, 46.189138, -14.050163, 32.37302, 
6.308908, -33.661878), Col6 = c(2158, 34.46581, 309.90168, 161.46379, 
278.38505, 147.171, 150.74978, 254.28341, 75.35783, 120.79866, 
127.05724, 361.66227), Col7 = c(1827.2507, 13.94546, 175.94835, 
237.20321, 116.95109, 147.19528, 156.59314, 131.49356, 160.37957, 
147.48743, 141.34019, 81.30154), Col8 = c(1482, -4.533958, 175.427179, 
84.304826, 151.338578, 229.756718, 162.983479, 211.540117, 150.10629, 
126.595648, 134.092717, 88.232663), Col9 = c(1858, 15.89606, 
83.94264, 178.47248, 218.93919, 98.92684, 87.34028, 69.87448, 
96.19735, 84.46121, 103.45419, 138.95064), Col10 = c(2544.3945, 
60.50394, 173.50097, 97.40814, 57.89194, 193.4346, 358.01097, 
312.3401, 170.49562, 142.00257, 294.44998, 83.37984)), class = "data.frame", row.names = c(NA, 
-12L)) -> df

t(df) %>% 
  data.frame() %>% 
  gather(variable, y, -X1) -> new_df

塑造你的身材

vwReg(y ~ X1, new_df)

---

多谢各位。这很有趣，vwReg函数产生了如此多的引导，让您对数据有了有趣的了解。这太棒了。