我正在尝试为 R 找到一个函数，它可以data.frame像这样以 MySQL 样式的 ascii 表输出对象
+----+------+------+
| id | var1 | var2 |
+----+------+------+
| 1 | asdf | g |
| 2 | asdf | h |
| 3 | asdf | j |
+----+------+------+
有这样的功能吗？至少有两个工具可以做到这一点
但是有没有办法直接从 R 中做到这一点？
使用您的数据：
d <- data.frame(id = 1:3, va1 = rep("asdf", 3), var2 = c("g","h","j"),
stringsAsFactors = FALSE)
这里有一些可以帮助您入门的东西，至少对于简单的表格来说可能就足够了。
asciify <- function(df, pad = 1, ...) {
## error checking
stopifnot(is.data.frame(df))
## internal functions
SepLine <- function(n, pad = 1) {
tmp <- lapply(n, function(x, pad) paste(rep("-", x + (2* pad)),
collapse = ""),
pad = pad)
paste0("+", paste(tmp, collapse = "+"), "+")
}
Row <- function(x, n, pad = 1) {
foo <- function(i, x, n) {
fmt <- paste0("%", n[i], "s")
sprintf(fmt, as.character(x[i]))
}
rowc <- sapply(seq_along(x), foo, x = x, n = n)
paste0("|", paste(paste0(rep(" ", pad), rowc, rep(" ", pad)),
collapse = "|"),
"|")
}
## convert everything to characters
df <- as.matrix(df)
## nchar in data
mdf <- apply(df, 2, function(x) max(nchar(x)))
## nchar in names
cnames <- nchar(colnames(df))
## max nchar of name+data per elements
M <- pmax(mdf, cnames)
## write the header
sep <- SepLine(M, pad = pad)
writeLines(sep)
writeLines(Row(colnames(df), M, pad = pad))
writeLines(sep)
## write the rows
for(i in seq_len(nrow(df))) {
## write a row
writeLines(Row(df[i,], M, pad = pad))
## write separator
writeLines(sep)
}
invisible(df)
}
在使用中我们得到：
> asciify(d)
+----+------+------+
| id | va1 | var2 |
+----+------+------+
| 1 | asdf | g |
+----+------+------+
| 2 | asdf | h |
+----+------+------+
| 3 | asdf | j |
+----+------+------+
在一些更复杂的事情上，我们得到
> asciify(mtcars)
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| mpg | cyl | disp | hp | drat | wt | qsec | vs | am | gear | carb |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 21 | 6 | 160 | 110 | 3.9 | 2.62 | 16.46 | 0 | 1 | 4 | 4 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 21 | 6 | 160 | 110 | 3.9 | 2.875 | 17.02 | 0 | 1 | 4 | 4 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 22.8 | 4 | 108 | 93 | 3.85 | 2.32 | 18.61 | 1 | 1 | 4 | 1 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 21.4 | 6 | 258 | 110 | 3.08 | 3.215 | 19.44 | 1 | 0 | 3 | 1 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 18.7 | 8 | 360 | 175 | 3.15 | 3.44 | 17.02 | 0 | 0 | 3 | 2 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 18.1 | 6 | 225 | 105 | 2.76 | 3.46 | 20.22 | 1 | 0 | 3 | 1 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 14.3 | 8 | 360 | 245 | 3.21 | 3.57 | 15.84 | 0 | 0 | 3 | 4 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 24.4 | 4 | 146.7 | 62 | 3.69 | 3.19 | 20 | 1 | 0 | 4 | 2 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 22.8 | 4 | 140.8 | 95 | 3.92 | 3.15 | 22.9 | 1 | 0 | 4 | 2 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 19.2 | 6 | 167.6 | 123 | 3.92 | 3.44 | 18.3 | 1 | 0 | 4 | 4 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 17.8 | 6 | 167.6 | 123 | 3.92 | 3.44 | 18.9 | 1 | 0 | 4 | 4 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 16.4 | 8 | 275.8 | 180 | 3.07 | 4.07 | 17.4 | 0 | 0 | 3 | 3 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 17.3 | 8 | 275.8 | 180 | 3.07 | 3.73 | 17.6 | 0 | 0 | 3 | 3 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 15.2 | 8 | 275.8 | 180 | 3.07 | 3.78 | 18 | 0 | 0 | 3 | 3 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 10.4 | 8 | 472 | 205 | 2.93 | 5.25 | 17.98 | 0 | 0 | 3 | 4 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 10.4 | 8 | 460 | 215 | 3 | 5.424 | 17.82 | 0 | 0 | 3 | 4 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 14.7 | 8 | 440 | 230 | 3.23 | 5.345 | 17.42 | 0 | 0 | 3 | 4 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 32.4 | 4 | 78.7 | 66 | 4.08 | 2.2 | 19.47 | 1 | 1 | 4 | 1 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 30.4 | 4 | 75.7 | 52 | 4.93 | 1.615 | 18.52 | 1 | 1 | 4 | 2 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 33.9 | 4 | 71.1 | 65 | 4.22 | 1.835 | 19.9 | 1 | 1 | 4 | 1 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 21.5 | 4 | 120.1 | 97 | 3.7 | 2.465 | 20.01 | 1 | 0 | 3 | 1 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 15.5 | 8 | 318 | 150 | 2.76 | 3.52 | 16.87 | 0 | 0 | 3 | 2 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 15.2 | 8 | 304 | 150 | 3.15 | 3.435 | 17.3 | 0 | 0 | 3 | 2 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 13.3 | 8 | 350 | 245 | 3.73 | 3.84 | 15.41 | 0 | 0 | 3 | 4 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 19.2 | 8 | 400 | 175 | 3.08 | 3.845 | 17.05 | 0 | 0 | 3 | 2 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 27.3 | 4 | 79 | 66 | 4.08 | 1.935 | 18.9 | 1 | 1 | 4 | 1 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 26 | 4 | 120.3 | 91 | 4.43 | 2.14 | 16.7 | 0 | 1 | 5 | 2 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 30.4 | 4 | 95.1 | 113 | 3.77 | 1.513 | 16.9 | 1 | 1 | 5 | 2 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 15.8 | 8 | 351 | 264 | 4.22 | 3.17 | 14.5 | 0 | 1 | 5 | 4 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 19.7 | 6 | 145 | 175 | 3.62 | 2.77 | 15.5 | 0 | 1 | 5 | 6 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 15 | 8 | 301 | 335 | 3.54 | 3.57 | 14.6 | 0 | 1 | 5 | 8 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
| 21.4 | 4 | 121 | 109 | 4.11 | 2.78 | 18.6 | 1 | 1 | 4 | 2 |
+------+-----+-------+-----+------+-------+-------+----+----+------+------+
请注意，代码不处理在小数点上对齐数字数据，但Row()可以修改内部函数的代码以适应所有需要的sprintf()调用略有不同。另外，我意识到我已将字符串右对齐，这不是您在示例表中显示的内容，但不是终端故障！
要在文件中获取输出，请asciify()使用以下命令捕获输出capture.output()：
> capture.output(asciify(d), file = "asciified_d.txt")
> readLines("asciified_d.txt")
[1] "+----+------+------+" "| id | va1 | var2 |" "+----+------+------+"
[4] "| 1 | asdf | g |" "+----+------+------+" "| 2 | asdf | h |"
[7] "+----+------+------+" "| 3 | asdf | j |" "+----+------+------+"
（注意上面显示的输出只是一个字符串向量，每个字符串在捕获的文件中占一行。文件在磁盘上看起来像这样：
$ cat asciified_d.txt
+----+------+------+
| id | va1 | var2 |
+----+------+------+
| 1 | asdf | g |
+----+------+------+
| 2 | asdf | h |
+----+------+------+
| 3 | asdf | j |
+----+------+------+
.)
我没有检查过这么多，在很多情况下它很可能会失败，但它适用于基本数据帧。
Update asciify()现在处理带有因子的数据帧以及字符和数字数据：
> require(ggplot2)
> asciify(head(diamonds))
+-------+-----------+-------+---------+-------+-------+-------+------+------+------+
| carat | cut | color | clarity | depth | table | price | x | y | z |
+-------+-----------+-------+---------+-------+-------+-------+------+------+------+
| 0.23 | Ideal | E | SI2 | 61.5 | 55 | 326 | 3.95 | 3.98 | 2.43 |
+-------+-----------+-------+---------+-------+-------+-------+------+------+------+
| 0.21 | Premium | E | SI1 | 59.8 | 61 | 326 | 3.89 | 3.84 | 2.31 |
+-------+-----------+-------+---------+-------+-------+-------+------+------+------+
| 0.23 | Good | E | VS1 | 56.9 | 65 | 327 | 4.05 | 4.07 | 2.31 |
+-------+-----------+-------+---------+-------+-------+-------+------+------+------+
| 0.29 | Premium | I | VS2 | 62.4 | 58 | 334 | 4.20 | 4.23 | 2.63 |
+-------+-----------+-------+---------+-------+-------+-------+------+------+------+
| 0.31 | Good | J | SI2 | 63.3 | 58 | 335 | 4.34 | 4.35 | 2.75 |
+-------+-----------+-------+---------+-------+-------+-------+------+------+------+
| 0.24 | Very Good | J | VVS2 | 62.8 | 57 | 336 | 3.94 | 3.96 | 2.48 |
+-------+-----------+-------+---------+-------+-------+-------+------+------+------+
另一个已经比我在午餐时写的代码更先进的解决方案是pander包，它在 Pandoc markdown 中呈现 R 对象，以便随后转换为一系列其他格式。
标记与显示的 MySQL 不太相同，但最相似的是：
> pandoc.table(m, style = "grid")
+---------------------+-------+-------+--------+
| | mpg | cyl | disp |
+=====================+=======+=======+========+
| **Mazda RX4** | 21 | 6 | 160 |
+---------------------+-------+-------+--------+
| **Mazda RX4 Wag** | 21 | 6 | 160 |
+---------------------+-------+-------+--------+
如您所见，这具有对行名称的内置处理（我的没有），并且随着时间的推移可能会获得更多的糖。
在这个 StackOverflow question中有一些相关的讨论和进一步的例子。
如果您追求的是 HTML 结果，也许您可以收获googleVis包的力量。您在包中有更多示例demo()。
library(googleVis)
x <- data.frame(matrix(runif(9), nrow = 3))
xg <- gvisTable(x, options=list(page='enable', height=300))
plot(xg)
上面的块将生成一个看起来像这样的网页。
如果您正在寻找报告工具，可以Markdown在 RStudio 中查看。