使用Python语言分析巴西东北部伯南布哥州首府累西腓的登革热数据,并使用机器学习定义趋势线

Angélica Félix de Castro, Amanda Gondim de Oliveira, George Felipe Fernandes Vieira, Daiane Emanuele Fernandes Da Silva
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引用次数: 1

摘要

目前的工作包括在巴西东北部伯南布哥州首府累西腓进行登革热案例研究,使用数据科学工具、Python语言及其库。首先,从累西腓市公共实体的官方来源提取了2020年登革热病例的数据。在此提取之后,应用Python命令来了解累西腓的登革热疫情在该特定年份是如何发生的。可以得出结论,登革热不是死亡原因之一,也不会导致患者住院。还可以绘制热图,显示2020年疫情最严重的社区(突出显示Ibura和Cohab社区)。在这项工作的第二阶段,应用机器学习(使用线性回归)来分析2013年至2020年累西腓登革热的时间序列:预测了这7年的历史,并验证了疫情下降的趋势线。未来几年累西腓的登革热
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Use of Python language in the analysis of dengue data in Recife, capital of the state of Pernambuco, Northeast of Brazil and definition of trend line using Machine Learning
The present work consists of a case study of dengue in Recife, capital of the state of Pernambuco, Northeast Brazil, using data science tools, Python language and its libraries. Firstly, data were extracted from official sources of public entities in the city of Recife about dengue cases in the year 2020. After this extraction, Python commands were applied to understand how the dengue outbreak in Recife happened in that specific year. It was possible to conclude that dengue is not one of the reasons for death and doesn´t cause hospitalization for patients. It was also possible to draw heat maps showing the neighborhoods that had the biggest outbreaks in 2020 (highlighting the Ibura and Cohab neighborhoods). In the second stage of this work, Machine Learning (using Linear Regression) was applied to analyze the time series of dengue in Recife between the years 2013 to 2020: a history was projected over these 7 years and a decreasing trend line of outbreaks was verified. dengue fever in Recife for the next few years.
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