Search Results for "basic-miktex-2.9.6"

pandas-profiling generates profile reports from a pandas DataFrame. The pandas df.describe() function is handy yet a little basic for exploratory data analysis. pandas-profiling extends pandas DataFrame with df.profile_report(), which automatically generates a standardized univariate and multivariate report for data understanding. High correlation warnings, based on different correlation metrics (Spearman, Pearson, Kendall, Cramér’s V, Phik). Most common categories (uppercase, lowercase, separator), scripts (Latin, Cyrillic) and blocks (ASCII, Cyrilic). ...

PyNanoLab contains a variety of tools to complete the data analysis, statistics, curve fitting, and basic machine learning application. Visualization in pynanolab is based on matplotlib. The setup tools is desinged to control and set-up all the details of the figure with a GUI.

Crystalsim is a simple freeware program with a neat graphical user interface for X-ray diffraction (XRD) data analysis . It can simulates all possible {hkl} planes data for the selected crystal. Crystallographic Information File (.cif) can also be used. Analyze both powder diffraction and single crystal data . Indexed at International Union of Crystallography (IUCR). Crystalline lattice parameters such as ‘a’, ‘b’, ‘c’ as well as interfacial angles such as alpha, beta,...

Larch is a scientific data processing language that is designed to be easy to use for novices and complete enough for advanced data processing and analysis. Larch provides a wide range of functionality for dealing with arrays of scientific data, and basic tools to make it easy to use and organize complex data. Larch has been primarily developed for dealing with x-ray spectroscopic and scattering data, especially the kind of data collected at modern synchrotrons and x-ray sources. Larch is written in Python and relies heavily on the standard tools for scientific computing with Python (numpy, scipy, matplotlib, and h5py).

Set of tools for basic analysis of electrophysiological data. The Python classes show how to call OpenElectrophy functions and save data. The R library applies circular statistics to spike phase data and saves the best von Mises fit and the Rayleigh statistics on the disk. The wavelet coherence analysis is done in R by the package "sowas". Check the module R_coherence to see how we solved that problem.

A GPR processer and viewer written in Python!