首页|基于Python的数据分析在水环境评价中的应用

基于Python的数据分析在水环境评价中的应用

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为优化水环境监测数据利用效率、深入揭示水污染特征及变化规律,为水环境科学评价与管理提供有力支撑,创造性地运用Python编程语言,对江苏省某水质自动监测站近三年内累计的25517条水质监测数据进行探索性分析,研究的核心内容涵盖了不同时间颗粒度下的单因子水质评价、水质变化趋势的量化分析、主要污染物的特征识别,以及监测指标间相关性的探索。结果表明:Python凭借强大的数据处理能力、灵活的编程方式以及丰富的可视化手段,显著提高了水质分析评价的效率,深化了对水污染特征及变化规律的理解,为水资源保护和水污染治理提供了更加精准、高效的技术支持。
Application of Python-Based Data Analysis in Water Environment Assessment
To optimize the utilization efficiency of water environment monitoring data,deeply reveal the character-istics and changing patterns of water pollution,and provide robust support for scientific evaluation and manage-ment of the water environment,this paper creatively employs the Python programming language to conduct an ex-ploratory analysis of 25517 water quality monitoring data records accumulated over the past three years from a water quality automatic monitoring station in Jiangsu Province.The core content of this research encompasses sin-gle-factor water quality assessments at different temporal granularities,quantitative analysis of water quality trends,characteristic identification of major pollutants,and exploration of correlations among monitoring indica-tors.The research findings indicate that Python,with its formidable data processing capabilities,flexible program-ming approaches,and abundant visualization tools,has significantly enhanced the efficiency of water quality anal-ysis and evaluation,deepened the understanding of water pollution characteristics and changing patterns,and pro-vided more precise and efficient technical support for water resource protection and pollution control.

Pythonwater quality assessmenttime-series datatrend analysiscorrelation analysis

聂慧君、蔡颖、朱晓晓、张淼、吴天祺、王苑

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江苏省环境工程技术有限公司,江苏南京 210019

江苏省环保集团有限公司,江苏 南京 210019

江苏省重点行业减污降碳协同控制工程研究中心,江苏南京 210019

Python 水质评价 时间序列数据 变化趋势分析 相关性

2024

绿色科技
花木盆景杂志社

绿色科技

影响因子:0.365
ISSN:1674-9944
年,卷(期):2024.26(20)