[英]How do find correlation between time events and time series data in python?
I have two different excel files.我有两个不同的excel文件。 One of them is including time series data (268943 accident time rows) as below其中之一是包括时间序列数据(268943 事故时间行)如下
The other file is value of 14 workers measured daily from 8 to 17 and during 4 months(all data merged in one file)另一个文件是每天从 8 到 17 和在 4 个月内测量的 14 名工人的值(所有数据合并在一个文件中)
I am trying to understand correlation between accident times and values (hourly from 8 to 17 per one hour and daily from Monday to Friday and monthly)我试图了解事故时间和价值之间的相关性(每小时从 8 到 17 每小时,每天从周一到周五和每月)
Which statistical method is fit(Normalized Auto or cross correlation) and how can I do that?哪种统计方法适合(归一化自动或互相关),我该怎么做? Generally, in the questions, the correlation analysis are performed between two time series based values, but I think this is a little bit different.一般来说,在问题中,相关分析是在两个基于时间序列的值之间进行的,但我认为这有点不同。 Also, here times are different.此外,这里的时间不同。
Thank your advance..谢谢你的提前..
I think the accident times and the bloodsugar levels are not coming from the same source, and so I think it is not possible to draw a correlation between these two separate datasets.我认为事故次数和血糖水平并非来自同一来源,因此我认为不可能在这两个独立的数据集之间建立相关性。 If you would like to assume that the blood sugar levels of all 14 workers reflect that of the workers accident dataset, that is a different story.如果您想假设所有 14 名工人的血糖水平都反映了工人事故数据集的血糖水平,那就是另一回事了。 But what if those who had accidents had a significantly different blood sugar level profile than the rest, and what if your tiny dataset of 14 workers does not comprise such examples?但是,如果发生事故的人的血糖水平与其他人明显不同,并且您的 14 名工人的小数据集不包含此类示例,该怎么办? I think the best you may do is to graph the blood sugar level of your 14 worker dataset and also similarly analyze the accident dataset separately, and try to see visually whether there is any correlation here.我认为你可能做的最好的事情是绘制你的 14 名工人数据集的血糖水平,并类似地分别分析事故数据集,并尝试直观地查看这里是否存在任何相关性。
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