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This repository has been archived by the owner on May 19, 2021. It is now read-only.
There have been ubiquitous in seeing large collections of time series in the practice, but it seems to me that there doesn't exist an R package aiming to provide efficient and straightforward tools for visualising sufficiently long time series, a handful of multivariate time series and even big time series. Many issues are worth giving a look/thought. For example,
What's the best data structure for time series data? A data frame with multiple keys (Year, Quarter, Month, Day, Hour, and etc.) and other variables?
It's kind of a pain to switch between a time series object (ts and mts in R) for analysing time series and a data frame for plotting such series in ggplot2. Is there other way around that we can make these two objects transform more seamlessly?
Rob's anomalous package provides a few useful cognostics to summarize time series characteristics, which makes big time series visualization accessible. Can we add more insightful and interesting cognostics to give a comprehensive picture of big time series?
The text was updated successfully, but these errors were encountered:
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There have been ubiquitous in seeing large collections of time series in the practice, but it seems to me that there doesn't exist an R package aiming to provide efficient and straightforward tools for visualising sufficiently long time series, a handful of multivariate time series and even big time series. Many issues are worth giving a look/thought. For example,
ts
andmts
in R) for analysing time series and a data frame for plotting such series inggplot2
. Is there other way around that we can make these two objects transform more seamlessly?The text was updated successfully, but these errors were encountered: