A data processing framework used to convert time series data into standardized format.
Project description
Time Series Data Library
This library provides general utility methods for working with time series datasets, which are stored as Xarray Dataset objects. In particular, it will provide declarative methods for being able standardize, apply Q/C checks, correct, and transform datastreams as a whole, reducing the amount of coding required for data processing.
Installation
This library depends on the ARM ACT library which will be used for plotting and data standardization. You can install it via pip, but it has problems on Windows because some of the dependencies require C code to be built. It's way easier to install the environment via Anaconda, which is described below. If you do not want to use Anaconda, you can install the tsdat requirements via:
pip3 install -r requirements.txt
1) Install Anaconda
We recommend using Anaconda to install the required Python environment. because some of our plotting dependencies require libraries that are difficult to set up on windows machines.
https://www.anaconda.com/download/#
2) Create Anaconda Environment
conda create -n tsdat_env -c conda-forge python=3.8 act-atmos cfunits yamllint
Note that Windows users should open the anaconda prompt and run this there.
3) OR Activate Existing Anaconda Environment
conda activate tsdat_env
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