【问题标题】:Dynamically switch to next tab in flexdashboard动态切换到 flexdashboard 中的下一个选项卡
【发布时间】:2022-01-14 09:54:37
【问题描述】:

我有大约 20 个样本,我需要为这些样本绘制图形,例如直方图、箱线图等……我想将所有这些图组织在一个 flexdashboard 中,每个样本都有一个选项卡。所以每个选项卡都有一个直方图、一个箱线图等。

以下模板仅生成一个选项卡。我将数据集翻了一番并添加了一列,因此它有两个 type、“first_sample”和“second_sample”(第一块代码)。

有没有一种简单的方法可以循环这些类型,以便在每个样本的单独选项卡上生成图?

谢谢!

编辑:我也找到了这篇文章,但我无法让它工作:Dynamicly increasing amount of tabs and pages in flexdashboards

---
title: "ggplotly geoms"
author: "Carson Sievert"
output: 
  flexdashboard::flex_dashboard:
  orientation: rows
social: menu
source_code: embed
---
  
```{r setup, include=FALSE}
library(ggplot2)
library(plotly)
library(plyr)
library(flexdashboard)

# Make some noisily increasing data
set.seed(955)
dat1 <- data.frame(cond = rep(c("A", "B"), each=10),
                  xvar = 1:20 + rnorm(20,sd=3),
                  yvar = 1:20 + rnorm(20,sd=3))

dat1$type <- "first_sample"

dat2 <- data.frame(cond = rep(c("A", "B"), each=10),
                  xvar = 1:20 + rnorm(20,sd=3),
                  yvar = 1:20 + rnorm(20,sd=3))

dat2$type <- "second_sample"

dat <- rbind(dat1, dat2)

```

geom_point
=======================================================================
  
Row
-----------------------------------------------------------------------
  
### Scatter Chart with geom_point
  
```{r}
p <- ggplot(dat, aes(x=xvar, y=yvar)) +
  geom_point(shape=1)      # Use hollow circles
ggplotly(p)
```


### geom_smooth Linear Regression

```{r}
p <- ggplot(dat, aes(x=xvar, y=yvar)) +
  geom_point(shape=1) +    # Use hollow circles
  geom_smooth(method=lm)   # Add linear regression line
ggplotly(p)
```

Row
-----------------------------------------------------------------------
  
### geom_smooth with Loess Smoothed Fit
  
```{r}
p <- ggplot(dat, aes(x=xvar, y=yvar)) +
  geom_point(shape=1) +    # Use hollow circles
  geom_smooth()            # Add a loess smoothed fit curve with confidence region
ggplotly(p)
```

### Constraining Slope with stat_smooth

```{r}
n <- 20
x1 <- rnorm(n); x2 <- rnorm(n)
y1 <- 2 * x1 + rnorm(n)
y2 <- 3 * x2 + (2 + rnorm(n))
A <- as.factor(rep(c(1, 2), each = n))
df <- data.frame(x = c(x1, x2), y = c(y1, y2), A = A)
fm <- lm(y ~ x + A, data = df)

p <- ggplot(data = cbind(df, pred = predict(fm)), aes(x = x, y = y, color = A))
p <- p + geom_point() + geom_line(aes(y = pred))
ggplotly(p)

```

【问题讨论】:

    标签: r r-markdown flexdashboard


    【解决方案1】:

    要做到这一点,我必须结合起来(我引用了这篇文章的一些内容):

    Use loop to generate section of text in rmarkdown

    • sprintf 通过数据的types 准备模板文本和名称选项卡
    • results = "asis",rmarkdown 块参数“防止 knitr 向输出添加格式”
    • cat 防止 R 添加额外的东西,如引号和元素编号”
    • print 在for 循环中绘图

    以下代码为dat 中的每个样本生成一个带有两个选项卡和两个绘图的 flexdashboard

    ---
    title: "test"
    author: "Paul Endymion"
    output: 
      flexdashboard::flex_dashboard:
      orientation: rows
    social: menu
    source_code: embed
    ---
    
      
    ```{r setup, include=FALSE}
    library(ggplot2)
    library(flexdashboard)
    library(data.table)
    
    # Make some noisily increasing data
    set.seed(955)
    dat1 <- data.frame(cond = rep(c("A", "B"), each=10),
                      xvar = 1:20 + rnorm(20,sd=3),
                      yvar = 1:20 + rnorm(20,sd=3))
    
    dat1$type <- "first_sample"
        
    dat2 <- data.frame(cond = rep(c("A", "B"), each=10),
                          xvar = 1:20 + rnorm(20,sd=3),
                          yvar = 1:20 + rnorm(20,sd=3))
        
    dat2$type <- "second_sample"
        
    dat <- rbind(dat1, dat2)
    
    setDT(dat)
    ```
    
    ```{r echo = FALSE, results = "asis"}
    
    template <- "
    
    %s
    =======================================================================
      
    ### Scatter Chart with geom_point
    
    " # dont't forget the newline
    
    template2 <- "
    
    Row
    -----------------------------------------------------------------------
    
    ### geom_smooth Linear Regression
    
    "
    
    for (i in unique(dat$type)) {
      cat(sprintf(template, i))
      
      p<-ggplot(dat[type == i], aes(x=xvar, y=yvar)) +
        geom_point(shape=1)      # Use hollow circles
      print(p)
      
      cat(template2)
      
      p2 <- ggplot(dat[type == i], aes(x=xvar, y=yvar)) +
      geom_point(shape=1) +    # Use hollow circles
      geom_smooth(method=lm)   # Add linear regression line
      print(p2)
    }
    ```
    

    它仍然需要调整,但它做了我想做的事情。

    【讨论】:

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