This repository contains the raw data and examples of how to process it for selected entries from the STAMP project. Any mention of commercial products is for information only; it does not imply recommendation or endorsement by NIST.
The procedure below uses conda to install package dependencies, which we recommend doing in a separate virtual environment, assumed below to be called "myenv". The python packages in requirements.txt can be installed via other methods as well.
$ git clone https://github.com/mahynski/stamp-dataset-1999-2010
$ cd stamp-dataset-1999-2010
$ conda activate myenv
$ conda install --file requirements.txtYou can recreate plots found in Ref. [1] using the visualize_stamp.ipynb Jupyter notebook. The required libraries are included in the requirements.txt and should be installed in the above step.
Otherwise, the included X.csv and y.csv contain the processed chemometric information described in Ref. [1]. The raw data is available at https://dx.doi.org/10.18434/mds2-2431.
This data can be easily read, for example, with pandas in python:
>>> import pandas as pd
>>> X = pd.read_csv('X.csv')
>>> y = pd.read_csv('y.csv')- X.csv : CSV file with the processed chemical information that should be used for analysis.
- y.csv : CSV file with the target properties of each sample, corresponding to X.csv.
[1] Mahynski NA, Ragland JM, Schuur SS, Pugh R, Shen VK, "Seabird Tissue Archival and Monitoring Project (STAMP) Data from 1999-2010," Journal of Research of the National Institute of Standards and Technology, Volume 126, Article No. 126028, https://dx.doi.org/10.6028/jres.126.028