group by 保留哪一条数据_使用R语言绘制一维数据统计图总结

加载数据绘制茎叶图绘制直方图绘制概率密度曲线绘制小提琴图绘制箱线图绘制小提琴图箱线图集中趋势统计分散程度 apply的使用

加载数据

模拟数据下载

library(tidyverse)
cjb <- read.csv("/home/wy/Downloads/cjb.csv",header = TRUE,stringsAsFactors = FALSE,fileEncoding = "UTF-8")

绘制茎叶图

cjb %>% filter(bj == '1101') %>%select(sx) %>%as_vector() %>%stem()
5 | 57996 | 00146 | 557897 | 0000111223344447 | 7888998 | 1112223344448 | 5899 | 224

绘制直方图

sx_hist_result = hist(cjb$sx,plot = FALSE)
typeof(sx_hist_result)
names(sx_hist_result)
# 使用ggplot绘制与hist相同的直方图
ggplot(data = cjb,mapping = aes(sx))+geom_histogram(breaks = sx_hist_result$breaks,color = "darkgray",fill = "white")+stat_bin(breaks = sx_hist_result$breaks,geom = "text",aes(label = ..count..))+coord_flip()

绘制概率密度曲线

ggplot(data = cjb,mapping = aes(sx))+geom_histogram(breaks = sx_hist_result$breaks,color = "darkgray",fill = "white",aes(y = ..density.. ))+geom_density(color = 'blue')

绘制小提琴图

ggplot(cjb,aes(x=factor(0),y=sx))+geom_violin(fill="orange",alpha=0.2)+coord_flip()

绘制箱线图

cjb %>%ggplot(aes(x=factor(0),y=sx))+geom_boxplot(width=0.25,fill = "#E69F00",outlier.colour = "red",outlier.shape = 1,outlier.size = .2)+geom_rug(position = "jitter",size=0.1,sides = "l")+coord_flip()

boxplot.stats(cjb$sx)
# $stats 下边界 一分位距 中位数 三分位距 上边界
# [1]  60  81  89  95 100
# $n 数据记录数
# [1] 775
# $conf
# [1] 88.20543 89.79457
# $out 异常点
# [1] 55 59 57 59 58 51 56 55 59 26 58 46  0 59 59

绘制小提琴图+箱线图

cjb %>%ggplot(aes(x=factor(0),y=sx)) +geom_violin(fill="#56B4E9",width=0.75) +geom_boxplot(width=0.25,fill = "#E69F00",outlier.colour = "red",outlier.shape = 1,outlier.size = 2)+geom_rug(position = "jitter",size=0.1,sides = "l")+coord_flip()

集中趋势统计

cjb %>%group_by(wlfk) %>% # 按文理分科分组统计summarise(count = n(), # 各组人数sx_median = median(sx), # 中位数sx_mean = mean(sx) # 均值)
# A tibble: 2 x 4
# wlfk  count sx_median sx_mean
# <chr> <int>     <dbl>   <dbl>
# 1 文科    394        84    82.7
# 2 理科    381        93    89.5

分散程度

cjb %>%group_by(wlfk) %>% # 按文理分科分组统计summarise(sx_max = max(sx), # 最大值sx_min = min(sx), # 最小值sx_range = max(sx) - min(sx) # 极差)# A tibble: 2 x 4
# wlfk  sx_max sx_min sx_range
# <chr>  <int>  <int>    <int>
# 1 文科     100     26       74
# 2 理科     100      0      100
cjb %>%group_by(wlfk) %>% # 按文理分科分组统计summarise(sx_O3 = quantile(sx,3/4), # 第三分位数sx_min = quantile(sx,1/4), # 第一分位数sx_iqr = IQR(sx) # 四分位距)
# A tibble: 2 x 4
# wlfk  sx_O3 sx_min sx_iqr
# <chr> <dbl>  <dbl>  <dbl>
# 1 文科     92     75     17
# 2 理科     96     86     10

apply的使用

round(apply(cjb[,4:12], 2, function(x){c(mean = mean(x),median = median(x),range = diff(range(x)),IQR = IQR(x))
}))
# yw  sx wy  zz  ls  dl  wl  hx  sw
# mean   87  86 87  92  89  93  81  92  86
# median 88  89 88  93  90  94  83  94  88
# range  96 100 99 100 100 100 100 100 100
# IQR     6  14  8   5  10   6  17  10  12

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