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r - 在一次 `mutate` 调用中创建的列是否有限制？

问题描述

我目前正在重组一个应用程序，它为某个主题提供数据。目前我正在为闪亮的应用程序设计新脚本的结构，它运行良好。在我继续完成工作之前，我想问一下是否有人在创建包含许多mutate语句的新列时遇到问题？最后，我可能会有100多个，我不确定是否应该拆分它。

感谢您的一些答案！

标签： rtidyversedplyr

解决方案

我怀疑有限制。它适用于创建至少 1000 个新列：

# Attach the dplyr package for tibble() and mutate()
library(dplyr)
# Create a dummy tibble
example_data <- tibble(x = 1:100)
# We'll do the mutate call by creating a text string and using eval()
# (saves some typing)
call_text <- paste(paste0("x", 1:1000, " = x * ", 1:1000), collapse = ", ")
call_text <- paste0("example_data %>% mutate(", call_text, ")")
# Sanity check on the call:
substr(call_text, 1, 60)
# [1] "example_data %>% mutate(x1 = x * 1, x2 = x * 2, x3 = x * 3, " # looks OK
example_data <- eval(parse(text = call_text))
# Examine the result
example_data

# A tibble: 100 x 1,001
       x    x1    x2    x3    x4    x5    x6    x7    x8    x9   x10   x11   x12
   <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
 1     1     1     2     3     4     5     6     7     8     9    10    11    12
 2     2     2     4     6     8    10    12    14    16    18    20    22    24
 3     3     3     6     9    12    15    18    21    24    27    30    33    36
 4     4     4     8    12    16    20    24    28    32    36    40    44    48
 5     5     5    10    15    20    25    30    35    40    45    50    55    60
 6     6     6    12    18    24    30    36    42    48    54    60    66    72
 7     7     7    14    21    28    35    42    49    56    63    70    77    84
 8     8     8    16    24    32    40    48    56    64    72    80    88    96
 9     9     9    18    27    36    45    54    63    72    81    90    99   108
10    10    10    20    30    40    50    60    70    80    90   100   110   120
# … with 90 more rows, and 988 more variables: x13 <dbl>, x14 <dbl>, x15 <dbl>,
#   x16 <dbl>, x17 <dbl>, x18 <dbl>, x19 <dbl>, x20 <dbl>, x21 <dbl>, x22 <dbl>,
#   x23 <dbl>, x24 <dbl>, x25 <dbl>, x26 <dbl>, x27 <dbl>, x28 <dbl>, x29 <dbl>,
#   x30 <dbl>, x31 <dbl>, x32 <dbl>, x33 <dbl>, x34 <dbl>, x35 <dbl>, x36 <dbl>,
#   x37 <dbl>, x38 <dbl>, x39 <dbl>, x40 <dbl>, x41 <dbl>, x42 <dbl>, x43 <dbl>,
#   x44 <dbl>, x45 <dbl>, x46 <dbl>, x47 <dbl>, x48 <dbl>, x49 <dbl>, x50 <dbl>,
#   x51 <dbl>, x52 <dbl>, x53 <dbl>, x54 <dbl>, x55 <dbl>, x56 <dbl>, x57 <dbl>,
#   x58 <dbl>, x59 <dbl>, x60 <dbl>, x61 <dbl>, x62 <dbl>, x63 <dbl>, x64 <dbl>,
#   x65 <dbl>, x66 <dbl>, x67 <dbl>, x68 <dbl>, x69 <dbl>, x70 <dbl>, x71 <dbl>,
#   x72 <dbl>, x73 <dbl>, x74 <dbl>, x75 <dbl>, x76 <dbl>, x77 <dbl>, x78 <dbl>,
#   x79 <dbl>, x80 <dbl>, x81 <dbl>, x82 <dbl>, x83 <dbl>, x84 <dbl>, x85 <dbl>,
#   x86 <dbl>, x87 <dbl>, x88 <dbl>, x89 <dbl>, x90 <dbl>, x91 <dbl>, x92 <dbl>,
#   x93 <dbl>, x94 <dbl>, x95 <dbl>, x96 <dbl>, x97 <dbl>, x98 <dbl>, x99 <dbl>,
#   x100 <dbl>, x101 <dbl>, x102 <dbl>, x103 <dbl>, x104 <dbl>, x105 <dbl>,
#   x106 <dbl>, x107 <dbl>, x108 <dbl>, x109 <dbl>, x110 <dbl>, x111 <dbl>,
#   x112 <dbl>, …

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