> For the complete documentation index, see [llms.txt](https://zpliu.gitbook.io/booknote/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://zpliu.gitbook.io/booknote/ggplot2/untitled-folder-1/zhi-fang-tu-hui-zhi.md).

# 直方图绘制

## 1.频数直方图

### 数据准备

```bash
> head(pacBioData)
               V1 V2
1 Ghir_A01G000010  1
2 Ghir_A01G000030  1
3 Ghir_A01G000040  3
4 Ghir_A01G000070  3
5 Ghir_A01G000080  1
6 Ghir_A01G000100  2
```

如果你同时含有两个样本的频数信息，需要针对不同的样本画不同的的柱子；只需要在数据框中添加一个字段即可。例如我的数据中含有PacBio测序数据和参考基因组数据两个文件

* PacBio
* regerence

```r
pacBioData<- read.table("PacBio文件")
referenceData <- read.table("reference文件")
##添加分类信息
pacBioData$type <- "PacBio"
referenceData$type <- "reference"
## 合并两个数据框
mergeData <- rbind(pacBioData, referenceData)
```

### 绘制直方图

* `x=V2`表示x轴数据使用V2字段进行映射
* `fill = type`针对type字段使用不同颜色进行填充
* `stat = "count"`统计x轴中每个值出现的次数，用作柱子的高度

```r
library(ggplot2)
ggplot(data = mergeData, aes(x = V2, fill = type)) +
  geom_bar(stat = "count")
```

![堆积直方图](https://s1.ax1x.com/2020/04/12/GO7SiV.png)

#### 调整

* `position = "dodge"`将柱子调整为不堆积状态
* `width = 0.5`调整柱子宽度&#x20;

这里由于x轴的坐标轴范围比较大，柱子缩放了看不清

```r
ggplot(data = mergeData, aes(x = V2, fill = type)) +
  geom_bar(stat = "count", position = "dodge", width = 0.5)
```

![不堆积](https://s1.ax1x.com/2020/04/12/GOH6nH.png)

## 2.频率直方图

### 数据准备

使用R中的`table`函数和`prop.table`函数计算频率

```r
PacBioFrequent <- as.data.frame(prop.table(table(pacBioData$V2)))[1:10, ]
referenceFrequent <- as.data.frame(prop.table(table(referenceData$V2)))[1:10, ]
## 样本分类
PacBioFrequent$type <- "PacBio"
referenceFrequent$type <- "reference"
## 合并数据
mergeData <- rbind(PacBioFrequent, referenceFrequent)
```

处理后的数据

```r
Var1       Freq   type
1    1 0.28121310 PacBio
2    2 0.21962588 PacBio
3    3 0.15747934 PacBio
4    4 0.10686098 PacBio
5    5 0.07342614 PacBio
```

### 绘制图形

参数和之前的都是一样的

```r
ggplot(data = mergeData, aes(x =Var1, y=Freq,fill = type)) +
  geom_bar(stat = "identity", position = "dodge", width = 0.5)
```

![频率直方图](https://s1.ax1x.com/2020/04/12/GOqkLQ.png)

## 3.美化图片

### 不涉及数据层的美化

* 图片背景色
* 图片网格
* 坐标轴刻度线
* 坐标轴刻度文字
* 坐标轴label文字
* 图例标题
* 图例位置

```r
p=ggplot(data = mergeData, aes(x =Var1, y=Freq,fill = type)) +
  geom_bar(stat = "identity", position = "dodge", width = 0.5)  

p+theme_bw() +
  theme(
    panel.grid = element_blank(), #图片网格线
    panel.background = element_blank(), #图片背景色为空
    axis.line = element_line(size = 0.5, color = "black"),#坐标轴线条
    axis.text.x = element_text(size = "15"), #x坐标轴刻度文字
    axis.text.y = element_text(size = "10"), #y坐标轴刻度文字
    axis.title.y = element_text(size = "15"), #x坐标轴label文字
    legend.title = element_blank(), #图例标题
    legend.position = c(0.8, 0.8), #图例位置
  )
```

![美化1](https://s1.ax1x.com/2020/04/12/GOLE6O.png)

### 自定义填充色

```r
p+  scale_fill_manual(values = c(
    "#f6e58d", "#ffbe76", "#686de0", "#4834d4"
  ))
```

![美化2](https://s1.ax1x.com/2020/04/12/GOLYng.png)

### 调整柱子离坐标轴位置

这里我将柱子与x轴进行贴近，其他的可以类似

* `expand`贴近坐标轴的位置
* `limits`设置显示的范围

```r
p+  scale_y_continuous(expand = c(0, 0), limits = c(0, 1))
```

![美化3](https://s1.ax1x.com/2020/04/12/GOOFEj.png)

### 添加自定义文字

通过使用`geom_text`函数，并且选择不继承原有的图片数据

* `data = labelData`要显示的注释信息
* `mapping`指定显示的位置和字段
* `inherit.aes`是否继承图形数据，如果是使用自定义数据，这里一定要`FALSE`

```r
#将要展示的注释文字
labelData <- data.frame(text1 = "3.39", text2 = "/", text3 = "2.01")
p+geom_text(
    data = labelData,
    mapping = aes(x = 8, y = 0.5, label = text1),
    inherit.aes = FALSE,
    show.legend = NA,
    color = "#ffbe76"
  ) +
  geom_text(
    data = labelData,
    mapping = aes(x = 8.5, y = 0.5, label = text2),
    inherit.aes = FALSE,
    show.legend = NA,
    color = "black"
  ) +
  geom_text(
    data = labelData,
    mapping = aes(x = 9, y = 0.5, label = text3),
    inherit.aes = FALSE,
    show.legend = NA,
    color = "#4834d4"
  )
```

![美化4](https://s1.ax1x.com/2020/04/12/GOzsjx.png)

### 参考

1. CDSN[博客](https://blog.csdn.net/Bone_ACE/article/details/47427453)


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