Python-based employment big data analysis in higher vocational colleges

Ping Du
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Abstract

In recent years, with the increase of graduates and the economic slowdown caused by the impact of the novel coronavirus pneumonia epidemic, the problem of difficult employment has attracted wide attention from all walks of life. Taking the employment data of graduates of a vocational college as an example, this paper displays the employment rate of graduates, employment industry, matching degree between employment unit and profession, salary level, geographical distribution and other information through data collection, data cleaning, data analysis and data visualization, so as to provide reference for students' career planning and employment choice. Finally, countermeasures and suggestions are put forward to help students better plan their career development, and job market data support for universities and government departments are also provided.
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基于Python的高职院校就业大数据分析
近年来,随着毕业生的增多和新型冠状病毒肺炎疫情影响导致的经济增速放缓,就业难问题引起了社会各界的广泛关注。本文以某职业院校毕业生就业数据为例,通过数据采集、数据清洗、数据分析、数据可视化等过程,展示了该校毕业生就业率、就业行业、就业单位与专业匹配度、薪资水平、地域分布等信息,为学生职业规划和就业选择提供参考。最后,提出帮助学生更好地规划职业发展的对策建议,为高校和政府部门提供就业市场数据支持。
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