#{getwd()} 获取当前工作目录
library(readxl)
library(tidyverse)
library(knitr)
library(ggplot2)
library(ggthemes)
library(here)
library(showtext)
library(ggblanket)
set_blanket(
mode = dark_mode_r(),
font_family = "wqy-microhei",
theme = light_mode_r() + mode_orientation_to_x()
)
library(plotly)
showtext_auto()
path <- getwd() #设置工作目录
file <- here(path, "scores.xlsx")
file[1] "/Users/alex/Rlearning/score_test/score_test/scores.xlsx"data <- read_excel(file,skip = 1) |>
select(-starts_with (c("主管领导",'备注'))) |>
filter(!姓名 %in% c("张集锋","李瑞娟",'龙湘珍')) |>
rename(name=姓名,
score = 总分,
department= 部门,
score_A1 =评分表A1,
score_B1 =评分表B1,
score_A2 =评分表A2,
score_B2 =评分表B2,
plus = 加减分,
leader= 部门负责人,
vice_general = 分管领导,)1.3.1 概览
anly_data <- data |>
select(-c(序号,职务)) |>
group_by(department) |>
mutate(mean_score=round(mean(score),2),.before = 3) |>
arrange(department)
anly_data# A tibble: 44 × 11
# Groups: department [3]
name department mean_score score_A1 score_A2 score_B1 score_B2 plus leader
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <dbl>
1 方琦 BIM中心 93.6 92 92 88 88 NA 90
2 张凯 BIM中心 93.6 95 95 91 91 NA 93
3 刘志强 BIM中心 93.6 97 97 97 97 NA 97
4 段晓莉 BIM中心 93.6 95 95 96 96 NA 95.5
5 马海珍 BIM中心 93.6 92 92 94 94 NA 93
6 胡亚丽 BIM中心 93.6 94 94 88 88 NA 91
7 宋彩娟 BIM中心 93.6 92 92 95 95 NA 93.5
8 姜艳萍 BIM中心 93.6 95 95 89 89 NA 92
9 陈望 BIM中心 93.6 95 95 91 91 NA 93
10 赵新光 BIM中心 93.6 97 97 96 96 NA 96.5
# ℹ 34 more rows
# ℹ 2 more variables: vice_general <dbl>, score <dbl>1.3.2 部门汇总
suminfo <- anly_data |>
group_by(department) |>
summarise(counts=n(),Leader_score=round(mean(leader),2),Vice_socre=round(mean(vice_general),2)) |>
rename(Department=department,
Counts=counts)
kable(suminfo)| Department | Counts | Leader_score | Vice_socre |
|---|---|---|---|
| BIM中心 | 20 | 93.55 | 93.55 |
| 创作一室 | 9 | 94.06 | 93.78 |
| 创作二室 | 15 | 92.10 | 91.77 |
p <- anly_data |>
ggplot(mapping = aes(x=score,fill=department,color=department))+
geom_histogram(binwidth = 1)+
facet_wrap(~department)
ggplotly(p)P <- anly_data |>
ggplot(aes(x = department, y = score, fill = department)) +
geom_violin() +
geom_jitter(width = 0.2) +
theme_minimal()
ggplotly(P)anly_data |>
ggplot(aes(x=department,y=score,fill=department,color=department)) +
geom_boxplot() +
geom_jitter(width = 0.2) +
theme_minimal()
library(ggridges)
vice <- anly_data |>
ggplot(aes(x = vice_general,y=department, fill = department, colour = department)) +
geom_density_ridges(alpha = 0.5, show.legend = FALSE) +
labs(title = "分管评分密度", x = "分管领导评分") +
# facet_grid(department~.) +
theme_minimal()
vice
library(ggridges)
leader <- anly_data |>
ggplot(aes(x = leader, y=department, fill = department, colour = department)) +
geom_density_ridges(alpha = 0.5, show.legend = FALSE) +
labs(title = "部门评分密度", x = "部门负责人评分") +
theme_minimal()
leader
anly_data |>
ggplot(aes(x = score_A1, y = score_A2, color = department,pch=department,lty=department)) +
geom_jitter() +
geom_smooth(method = "lm", se = FALSE) +
labs(title = "评分表A1与评分表A2的关系", x = "评分表A1", y = "评分表A2") +
theme_minimal()
anly_data |>
ggplot(aes(x = score_B1, y = score_B2, color = department,pch=department,lty=department)) +
geom_jitter() +
geom_smooth(method = "lm", se = FALSE) +
labs(title = "评分表B1与评分表B2的关系", x = "评分表B1", y = "评分表B2") +
theme_minimal()
anly_data |>
ggplot(aes(x = leader, y = vice_general, color = department,pch=department,lty=department)) +
geom_jitter() +
geom_smooth(method = "lm", se = FALSE) +
labs(title = "部门负责人 与 分管领导评分关系", x = "部门负责人", y = "分管领导") +
theme_minimal()
anly_data |>
ggplot(aes(x = department, color = department)) +
geom_point(aes(y = vice_general,shape = 'Vice'),color='orange',size=4,position = position_jitterdodge()) +
geom_point(aes(y = leader,shape = "Leader"),color='lightblue',size=4,position = position_jitterdodge()) +
theme_minimal() 
top3 <- anly_data |>
select(name,department,score) |>
group_by(department) |>
top_n(3, score) |>
mutate(rank=row_number()) |>
arrange(department, desc(score))
top3 |>
kable()| name | department | score | rank |
|---|---|---|---|
| 刘志强 | BIM中心 | 97 | 1 |
| 刘俊超 | BIM中心 | 97 | 2 |
| 杨曾光 | BIM中心 | 97 | 3 |
| 胡龙 | 创作一室 | 98 | 2 |
| 朱宇 | 创作一室 | 97 | 3 |
| 张继源 | 创作一室 | 96 | 1 |
| 程笑雨 | 创作二室 | 96 | 1 |
| 王燕皓 | 创作二室 | 96 | 2 |
| 郑有池 | 创作二室 | 96 | 3 |
top3_leader <- anly_data |>
select(name,department,leader) |>
group_by(department) |>
arrange(desc(leader)) |>
top_n(3, leader) |>
mutate(rank=row_number()) |>
arrange(department, desc(leader))
top3_leader |>
kable()| name | department | leader | rank |
|---|---|---|---|
| 刘志强 | BIM中心 | 97 | 1 |
| 刘俊超 | BIM中心 | 97 | 2 |
| 杨曾光 | BIM中心 | 97 | 3 |
| 胡龙 | 创作一室 | 98 | 1 |
| 朱宇 | 创作一室 | 97 | 2 |
| 张继源 | 创作一室 | 96 | 3 |
| 程笑雨 | 创作二室 | 97 | 1 |
| 王燕皓 | 创作二室 | 96 | 2 |
| 郑有池 | 创作二室 | 96 | 3 |
top3_vice <- anly_data |>
select(name,department,vice_general) |>
group_by(department) |>
arrange(desc(vice_general)) |>
top_n(3, vice_general) |>
mutate(rank=row_number()) |>
arrange(department, desc(vice_general))
top3_vice |>
kable()| name | department | vice_general | rank |
|---|---|---|---|
| 刘志强 | BIM中心 | 97.0 | 1 |
| 刘俊超 | BIM中心 | 97.0 | 2 |
| 杨曾光 | BIM中心 | 97.0 | 3 |
| 胡龙 | 创作一室 | 98.0 | 1 |
| 朱宇 | 创作一室 | 97.0 | 2 |
| 张继源 | 创作一室 | 96.0 | 3 |
| 王燕皓 | 创作二室 | 96.0 | 1 |
| 郑有池 | 创作二室 | 96.0 | 2 |
| 孙祎璐 | 创作二室 | 95.5 | 3 |
通过数据分析，可以看出各部门员工的评分分布情况，以及部门负责人和分管领导的评分情况。
通过相关性分析，可以看出评分表A1与评分表A2的关系，评分表B1与评分表B2的关系，部门负责人与分管领导的评分关系。
通过TOP3的分析，可以看出各部门的TOP3员工，以及部门负责人和分管领导的TOP3员工。
通过数据分析，可以为公司的人事管理提供参考依据。
本次分析结果仅供参考，具体情况具体分析。
根据评分规律发现，不同的leader和vice对部门员工的评分标准尺度很难横向对比，需要进一步优化评分标准。