数据分析岗位招聘分析


本次有360个数据分析岗位在招聘,用工地点涉及全国,各行业都有这个岗位需求。其中,北上广深的需求最多,北京和上海偏好拥有3-5年相关工作经验者,广州和深圳偏好拥有1-3年相关工作经验者,深圳也偏好5-10年相关工作经验者。薪酬在各行业分布范围比较大,从月薪下限3000元到上限80000元不等,主要看技能(如Python,SQL,SPSS,SAS等)和知识(如计算机编程,数学,统计学等),以及工作经验是否符合岗位需求。


1. 岗位说明

da[11:15,c(1,11,6:10,2)] %>% rename('岗位'="jobs","行业"="Industry","工作地点"="location","学历要求"="education","工作经验"="experience","工资下限"="salaryMin","工资上限"="salaryMax","岗位说明"="JD")

2. 岗位数量分布

da %>% select_at(c(6:12)) %>% group_by(location,education,experience) %>% 
    summarize(n=n()) %>% ggplot(aes(experience,n,fill=education))+
    geom_bar(stat='identity')+facet_wrap(~location,scales='free')+
    coord_flip()+theme(text=element_text(size=7))+
    labs(title='招聘数据分析岗位分布按地区、学历、经验',x='工作经验',y='岗位数量',caption='PLOT01_20210924')

3. 岗位薪酬分布

da %>% mutate(Industry01=as.factor(Industry01)) %>% group_by(Industry01) %>%
    summarize(工资下限=mean(salaryMin),工资上限=mean(salaryMax)) %>% 
    filter(Industry01!='2') %>% melt() %>% ggplot(aes(variable,value,fill=variable))+
    geom_col(show.legend = FALSE)+facet_wrap(~Industry01,scales='free')+
    labs(title='招聘数据分析岗位薪酬_按行业',caption='PLOT02_20210924')+
    theme(text=element_text(size=8))

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