最小的可重现的示例 (RE)下面是我尝试弄清楚如何使用knitr
用于生成复杂的动态文档,这里的“复杂”不是指文档的元素及其布局,而是指非线性逻辑底层 R 代码块。虽然提供的 RE 及其结果表明solution,基于这种方法可能效果很好,我会喜欢知道: 1) 这是一个correct使用方法knitr
对于此类情况; 2)有没有优化可以用来改进方法; 3)什么是替代方法,这可能会减少粒度代码块。
EDA源代码(文件“reEDA.R”):
## @knitr CleanEnv
rm(list = ls(all.names = TRUE))
## @knitr LoadPackages
library(psych)
library(ggplot2)
## @knitr PrepareData
set.seed(100) # for reproducibility
data(diamonds, package='ggplot2') # use built-in data
## @knitr PerformEDA
generatePlot <- function (df, colName) {
df <- df
df$var <- df[[colName]]
g <- ggplot(data.frame(df)) +
scale_fill_continuous("Density", low="#56B1F7", high="#132B43") +
scale_x_log10("Diamond Price [log10]") +
scale_y_continuous("Density") +
geom_histogram(aes(x = var, y = ..density..,
fill = ..density..),
binwidth = 0.01)
return (g)
}
performEDA <- function (data) {
d_var <- paste0("d_", deparse(substitute(data)))
assign(d_var, describe(data), envir = .GlobalEnv)
for (colName in names(data)) {
if (is.numeric(data[[colName]]) || is.factor(data[[colName]])) {
t_var <- paste0("t_", colName)
assign(t_var, summary(data[[colName]]), envir = .GlobalEnv)
g_var <- paste0("g_", colName)
assign(g_var, generatePlot(data, colName), envir = .GlobalEnv)
}
}
}
performEDA(diamonds)
EDA 报告 R Markdown 文档(文件“reEDA.Rmd”):
```{r KnitrSetup, echo=FALSE, include=FALSE}
library(knitr)
opts_knit$set(progress = TRUE, verbose = TRUE)
opts_chunk$set(
echo = FALSE,
include = FALSE,
tidy = FALSE,
warning = FALSE,
comment=NA
)
```
```{r ReadChunksEDA, cache=FALSE}
read_chunk('reEDA.R')
```
```{r CleanEnv}
```
```{r LoadPackages}
```
```{r PrepareData}
```
Narrative: Data description
```{r PerformEDA}
```
Narrative: Intro to EDA results
Let's look at summary descriptive statistics for our dataset
```{r DescriptiveDataset, include=TRUE}
print(d_diamonds)
```
Now, let's examine each variable of interest individually.
Varible Price is ... Decriptive statistics for 'Price':
```{r DescriptivePrice, include=TRUE}
print(t_price)
```
Finally, let's examine price distribution across the dataset visually:
```{r VisualPrice, include=TRUE, fig.align='center'}
print(g_price)
```
结果可以在这里找到:
http://rpubs.com/abrpubs/eda1 http://rpubs.com/abrpubs/eda1