Removing redundant samples

Sometimes we accumulate huge amounts of spectra in a CAL file, and most of them is redundant and maybe that not helps to improve the calibration. One thing important when we have a lot of spectra is that we have more when we can select and to fill our hypercube in the best way. The option "Select Samples from a Spectra File" in Win ISI help us to select samples which fill the hypercube  with the samples at similar distances between them, so all of them are important in the calculation in the centroid, and there are not groups which makes that the centroid is more closer to them. The number of PCs is also reduced and as we can see comparing these two plots (left: without redundant samples, right: with redundant samples) and maybe we increase the variance explained for the PC terms respect to some constituents in the case we want to develop PC regression. So no discard to use this option to improve the calibrations.

 

Comtrade Webpage

These days I am doing an Online Course of  Python and we are practicing extracting data,  to work with, from a very interesting web page that I want to share with the readers of this blog.
http://comtrade.un.org/data/
From this web page you can extract very interesting information about your country, about from or to where, we import  or exports commodities.
For example in this case I want to see from which countries we imported computers and to which countries we exported computers in 2015:

You can preview or download the csv file and to work with it  R or Python for grouping and practice statistics.
The first row is the result for all the countries in the World. So we have to look to the next rows to see from which countries we import or to which countries we export computers:
In the case of imports:

and in the case of exports:

Hope you find it interesting, and share things that have surprise you from your Country.