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【原创】R语言案例数据分析可视化报告 (附代码数据)

来源:网络收集 时间:2026-05-19
导读: 【原创】R语言案例数据分析报告论文(附代码数据) 有问题到淘宝找“大数据部落”就可以了 A study of the impact of storms and weather events in the United States Deborah 5 de novembro de 2017 Synopsis: In this report we aim to identify the stor

【原创】R语言案例数据分析报告论文(附代码数据)

有问题到淘宝找“大数据部落”就可以了

A study of the impact of storms and weather events in the United States

Deborah

5 de novembro de 2017

Synopsis:

In this report we aim to identify the storm and weather events more harmful to population health and with greate impacct on economy in the United States. The report analyses data from US. National Oceanic and Atmospheric Administration’s (NOAA) storm database since 1950 to 2011. Our overall hypothesis is that Tsunami is the most harmful event to population health and hurricane has the greatest impact on economy. To investigate this hypothesis, we had to adjust the events names and aggregate the data to calculate average impacts for each event. From these data, we confirmed our hypothesis.

Data Processing

From the U.S. National Oceanic and Atmo spheric Administration’s (NOAA) we obtained database on major storms and weather events in the United States, including when and where they occur, as well as estimates of any fatalities, injuries, and property damage. The data is from 1950 and end in November 2011.

Reading in database

We first read in the data from the raw text file included in the zip archive. The data is a comma separated file (csv).

After reading in the data we check the first few rows (there are 902,297) rows in this dataset.

【原创】R语言案例数据分析报告论文(附代码数据)有问题到淘宝找“大数据部落”就可以了

【原创】R语言案例数据分析报告论文(附代码数据)

有问题到淘宝找“大数据部落”就可以了

As we can see that are more unique events than permitted by National Weather Service Instruction (NWSI). For the rest of the analysis, we will reclassify some of the events so that most events perfectly matches the 48 permitted Storm Data Events. The following steps will be taken: - Replace “s” at the end of the event by “” - Replace “TSTM” by “THUNDERSTORM” - Replace “ING” at the end of a line by “” - Look for some part of the events name and replace it by the real event name - for example, there are many occurances of “THUNDERSTORM W” with many different continuations. So everytime there is this matche it will be replaced by “THUNDERSTORM WIND”.

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