Tools for data organising and processing Suppose we perform experiments with input parameters (temperature, humidity, processing time...) and collect resulting data (thickness, structure, mech. properties...).

Is there a tool (or set of tools) to organize, process and export data from such experiments?

Key features are:


Structured files decomposition (raw text files).
Basic math operations.
Filter and sort by given parameters (show/export data from samples treated at given temperature and humidity for various times).
Generating tables with given parameters and list of "constants" (table of times, mech. properties and thicknesses and list containing temperature, humidity...).
Vector graphics output and/or output suitable for MATLAB (graph of thickness as function of time).
Automated (or easy-to-create) LaTeX output (report sheet).


If not, any idea, hint or recommendation how to create it is appreciated. Right now I'm thinking of a spreadsheet (Excel) as core database and MATLAB as the processor (filters, sorting, graphics).
I would store data in CSV (i.e. text file with a table, with values separated by commas) rather than XLS files (the first is easier to import from and export to anything). Otherwise many tools will do the job (if you are familiar with MATLAB - why not using it)?

For general data processing and manipulation, Python (with SciPy stack) is capable of everything you mentioned. In particular IPython Notebook is great for data exploration and presentation (you can use code, comments and LaTeX in such notebook - also for reports). For tabular data, use Pandas (R-like DataFrames).

For reports also you can create files in Markdown (with LaTeX), and then convert them to pdf with Pandoc - may be much easier than generation of LaTeX code. (To get you some taste what is Markdown - look at StackEdit.)

And alternative to Python is R, with knitr for report generation. If you are not sure, if to choose R or Python, then for your task R seems to be an easier and better way to start (especially with RStudio as an interface).

For a bigger list and links to tutorials, take a look at a list of software for scientists.