功能的一个for循环以产生具有值1的列：N由另一列匹配间隔

我有如下所示功能的一个for循环以产生具有值1的列：N由另一列匹配间隔

my_df=data.frame(x=runif(100, min = 0,max = 60), 
      y=runif(100, min = 0,max = 60)) #x and y in cm

有了这个，我需要从1值的新列的数据帧调节至36，匹配x和y每10厘米。例如，如果0<=x<=10 & 0<=y<=10，放1，那么如果10<=x<=20 & 0<=y<=10，把2等等放到6，然后0<=x<=10 & 10<=y<=20开始7到12，等我试图做一个if函数重复的x 6倍的时间间隔，并在每次迭代中增加y的时间间隔。下面是函数

#my miscarried function 'zones' 

>zones= function(x,y) { 
    i=vector(length = 6) 
    n=vector(length = 6) 
    z=vector(length = 36) 
    i[1]=0 
    z[1]=0 
    n[1]=1 

for (t in 1:6) { 

    if (0<=x & x<10 & i[t]<=y & y<i[t]+10) { z[t] = n[t]} else 

     if (10<=x & x<20 & i[t]<=y & y<i[t]+10) {z[t]=n[t]+1} else 
       if (20<=x & x<30 & i[t]<=y & y<i[t]+10) {z[t]=n[t]+2} else 
         if (30<=x & x<40 & i[t]<=y & y<i[t]+10) {z[t]=n[t]+3} else 
          if (40<=x & x<50 & i[t]<=y & y<i[t]+10) {z[t]=n[t]+4}else 
            if (50<=x & x<=60 & i[t]<=y & y<i[t]+10) {z[t]=n[t]+5} 
else {i[t+1]=i[t]+10 
     n[t+1]=n[t]+6} 
         } 

return(z) 

} 


>xy$z=zones(x=xy$x,y=xy$y)

和我

There were 31 warnings (use warnings() to see them) 
>xy$z 
[1] 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

请帮助我之前，我孤独终老！

来源

2017-10-18 jealcalat

既然你不会独自死亡，你应该接受其中一个答案。 :) – Suren

@ Headpoint对不起！我正在一家酒吧里死去，但我看到了灯光。谢谢你，你提供的解决方案工作得很好。 – jealcalat

我认为这是一个窍门。

a <- cut(my_df$x, (0:6) * 10) 
b <- cut(my_df$y, (0:6) * 10) 
z <- interaction(a, b) 

levels(z) 
[1] "(0,10].(0,10]" "(10,20].(0,10]" "(20,30].(0,10]" "(30,40].(0,10]" 
[5] "(40,50].(0,10]" "(50,60].(0,10]" "(0,10].(10,20]" "(10,20].(10,20]" 
[9] "(20,30].(10,20]" "(30,40].(10,20]" "(40,50].(10,20]" "(50,60].(10,20]" 
[13] "(0,10].(20,30]" "(10,20].(20,30]" "(20,30].(20,30]" "(30,40].(20,30]" 
[17] "(40,50].(20,30]" "(50,60].(20,30]" "(0,10].(30,40]" "(10,20].(30,40]" 
[21] "(20,30].(30,40]" "(30,40].(30,40]" "(40,50].(30,40]" "(50,60].(30,40]" 
[25] "(0,10].(40,50]" "(10,20].(40,50]" "(20,30].(40,50]" "(30,40].(40,50]" 
[29] "(40,50].(40,50]" "(50,60].(40,50]" "(0,10].(50,60]" "(10,20].(50,60]" 
[33] "(20,30].(50,60]" "(30,40].(50,60]" "(40,50].(50,60]" "(50,60].(50,60]"

如果这类型的级别不适合您的口味，然后如下更改：

levels(z) <- 1:36

来源

2017-10-18 05:52:27 Suren

这是你所追求的？所得到的数字是res列：

# Get bin index for x values and y values 
my_df$bin1 <- as.numeric(cut(my_df$x, breaks = seq(0, max(my_df$x) + 10, by = 10))); 
my_df$bin2 <- as.numeric(cut(my_df$y, breaks = seq(0, max(my_df$x) + 10, by = 10))); 

# Multiply bin indices 
my_df$res <- my_df$bin1 * my_df$bin2; 

> head(my_df) 
      x   y bin1 bin2 res 
1 49.887499 47.302849 5 5 25 
2 43.169773 50.931357 5 6 30 
3 10.626466 43.673533 2 5 10 
4 43.401454 3.397009 5 1 5 
5 7.080386 22.870539 1 3 3 
6 39.094724 24.672907 4 3 12

我打破用于说明目的的步骤;您可能不想保留中间栏bin1和bin2。

来源

2017-10-18 05:43:51

我认为最多应该有36个类别。我不确定这是否会给出它：例如1,2和2,1（分别在'bin1'和'bin2'中）将与您的方法处于相同的类别。不是吗？ – Suren

是的，你是对的。我不完全确定OP想要什么。你的解决方案做的是正确的工作井井有条。 –

我认为它可以工作，如果你将两个切割映射到两个不相交的素数（如拳头12个素数），那么...很高兴你喜欢我的。 – Suren

我们可能需要显示X，Y和Z之间的关系的表。之后，我们可以定义一个函数来进行连接。

该解决方案与此帖相关并受到启发（R dplyr join by range or virtual column）。您也可能会发现其他解决方案很有用。

# Set seed for reproducibility 
set.seed(1) 

# Create example data frame 
my_df <- data.frame(x=runif(100, min = 0,max = 60), 
        y=runif(100, min = 0,max = 60)) 

# Load the dplyr package 
library(dplyr) 

# Create a table to show the relationship between x, y, and z 
r <- expand.grid(x_from = seq(0, 50, 10), y_from = seq(0, 50, 10)) %>% 
    mutate(x_to = x_from + 10, y_to = y_from + 10, z = 1:n()) 

# Define a function for dynamic join 
dynamic_join <- function(d, r){ 

    if (!("z" %in% colnames(d))){ 
    d[["z"]] <- NA_integer_ 
    } 

    d <- d %>% 
    mutate(z = ifelse(x >= r$x_from & x < r$x_to & y >= r$y_from & y < r$y_to, 
         r$z, z)) 
    return(d) 
} 

re_dynamic_join <- function(d, r){ 
    r_list <- split(r, r$z) 
    for (i in 1:length(r_list)){ 
    d <- dynamic_join(d, r_list[[i]]) 
    } 
    return(d) 
} 

# Apply the function 
re_dynamic_join(my_df, r) 
      x   y z 
1 15.930520 39.2834357 20 
2 22.327434 21.1918363 15 
3 34.371202 16.2156088 10 
4 54.492467 59.5610437 36 
5 12.100916 38.0095959 20 
6 53.903381 12.7924881 12 
7 56.680516 7.7623409 6 
8 39.647868 28.6870821 16 
9 37.746843 55.4444682 34 
10 3.707176 35.9256580 19 
11 12.358474 58.5702417 32 
12 10.593405 43.9075507 26 
13 41.221371 21.4036147 17 
14 23.046223 25.8884214 15 
15 46.190485 8.8926936 5 
16 29.861955 0.7846545 3 
17 43.057110 42.9339640 29 
18 59.514366 6.1910541 6 
19 22.802111 26.7770609 15 
20 46.646713 38.4060627 23 
21 56.082314 59.5103172 36 
22 12.728551 29.7356147 14 
23 39.100426 29.0609715 16 
24 7.533306 10.4065401 7 
25 16.033240 45.2892567 26 
26 23.166846 27.2337294 15 
27 0.803420 30.6701870 19 
28 22.943277 12.4527068 9 
29 52.181451 13.7194886 12 
30 20.420940 35.7427198 21 
31 28.924807 34.4923319 21 
32 35.973950 4.6238628 4 
33 29.612478 2.1324348 3 
34 11.173056 38.5677295 20 
35 49.642399 55.7169120 35 
36 40.108004 35.8855453 23 
37 47.654392 33.6540449 23 
38 6.476618 31.5616634 19 
39 43.422657 59.1057134 35 
40 24.676466 30.4585093 21 
41 49.256778 40.9672847 29 
42 38.823612 36.0924731 22 
43 46.975966 14.3321207 11 
44 33.182179 15.4899556 10 
45 31.783175 43.7585774 28 
46 47.361374 27.1542499 17 
47 1.399872 10.5076061 7 
48 28.633804 44.8018962 27 
49 43.938824 6.2992584 5 
50 41.563893 51.8726969 35 
51 28.657177 36.8786983 21 
52 51.672569 33.4295723 24 
53 26.285826 19.7266391 9 
54 14.687837 27.1878867 14 
55 4.240743 30.0264584 19 
56 5.967970 10.8519817 7 
57 18.976302 31.7778362 20 
58 31.118056 4.5165447 4 
59 39.720305 16.6653560 10 
60 24.409811 12.7619712 9 
61 54.772555 17.0874289 12 
62 17.616202 53.7056462 32 
63 27.543944 26.7741194 15 
64 19.943680 46.7990934 26 
65 39.052228 52.8371421 34 
66 15.481007 24.7874526 14 
67 28.712715 3.8285088 3 
68 45.978640 20.1292495 17 
69 5.054815 43.4235568 25 
70 52.519280 20.2569200 18 
71 20.344376 37.8248473 21 
72 50.366421 50.4368732 36 
73 20.801009 51.3678999 33 
74 20.026496 23.4815569 15 
75 28.581075 22.8296331 15 
76 53.531900 53.7267256 36 
77 51.860368 38.6589458 24 
78 23.399373 44.4647189 27 
79 46.639242 36.3182068 23 
80 57.637080 54.1848967 36 
81 26.079569 17.6238093 9 
82 42.750881 11.4756066 11 
83 23.999662 53.1870566 33 
84 19.521129 30.2003691 20 
85 45.425229 52.6234526 35 
86 12.161535 11.3516173 8 
87 42.667273 45.4861831 29 
88 7.301515 43.4699336 25 
89 14.729311 56.6234891 32 
90 8.598263 32.8587952 19 
91 14.377765 42.7046321 26 
92 3.536063 23.3343060 13 
93 38.537296 6.0523876 4 
94 52.576153 55.6381253 36 
95 46.734881 16.9939500 11 
96 47.838530 35.4343895 23 
97 27.316467 6.6216363 3 
98 24.605045 50.4304219 33 
99 48.652215 19.0778211 11 
100 36.295997 46.9710802 28

来源

2017-10-18 06:03:06 www

功能的一个for循环以产生具有值1的列：N由另一列匹配间隔

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