Search Results for "common"

...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). File sizes, creation dates, dimensions, indication of truncated images and existance of EXIF metadata. Mostly global details about the dataset (number of records, number of variables, overall missigness and duplicates, memory footprint). ...

The POCO C++ Libraries are powerful cross-platform C++ libraries for building network- and internet-based applications that run on desktop, server, mobile, IoT, and embedded systems. Whether building automation systems, industrial automation, IoT platforms, air traffic management systems, enterprise IT application and infrastructure management, security and network analytics, automotive infotainment and telematics, financial or healthcare, C++ developers have been trusting the POCO C++...

...With these .NET APIs, you can access the most popular Dataframe and SparkSQL aspects of Apache Spark, for working with structured data, and Spark Structured Streaming, for working with streaming data. .NET for Apache Spark is compliant with .NET Standard - a formal specification of .NET APIs that are common across .NET implementations. This means you can use .NET for Apache Spark anywhere you write .NET code allowing you to reuse all the knowledge, skills, code, and libraries you already have as a .NET developer. .NET for Apache Spark runs on Windows, Linux, and macOS using .NET Core, or Windows using .NET Framework. It also runs on all major cloud providers including Azure HDInsight Spark, Amazon EMR Spark, AWS & Azure Databricks.

xrayutilities is a python package used to analyze x-ray diffraction data. It can support with performing diffraction experiments and used for common steps in the data analysis. It can read experimental data from several data formats (spec, edf, xrdml, ...); convert them to reciprocal space for arbitrary goniometer geometries and different detector systems (point, linear as well as area detectors); for further processing the data can be gridded (transformed to a regular grid). ...

log4jscanner is a filesystem scanner and Go package that helps organizations quickly identify vulnerable Log4j components inside JARs and shaded dependencies. Instead of probing networks, it walks directories and archives, including nested JARs, to find version fingerprints and risky classes associated with the Log4Shell family of issues. The focus on static analysis makes it suitable for container images, build artifacts, and offline systems where active scanning isn’t feasible. Clear,...

RadiationHelper is a data analysis tool for : 1. gross alpha and beta radiation measurement and detector calibration using experimental data (counts acquired by alpha-beta devices). 2. gamma spectroscopy measurements and detector calibration using experimental data (spectra acquired by acquisition software such as Assayer, Gamma Vision, Maestro) 3. gross alpha,beta, gamma detector efficiencies and gamma peak efficiency can be theoretical computed using Monte-Carlo simulation technique for radiation transport (based on EGSnrc toolkit) 4.dose assessment in human body exposed to radiations from nuclides in several common scenarios such as air exposure, water submersion, ground surface, internal ingestion or inhalation. 5. quick dosimetry and shielding computations. It is platform independent (written entirely in Java). Source code included in jar files! Also, available on GitHub: https://github.com/ZiliasTheSaint/RadiationHelper.git Checkout for dependent modules!

...It was created to build binding profiles between proteins and loci in the genome. In addition it computes statistics of the number of loci/positions containing specified amount of tags. jChIP is able to load data in several common formats (SAM, BAM, WIG, BED, Bowtie) and download loci definitions directly from the Ensembl database. http://www.biomedcentral.com/1756-0500/7/676

MolBioLib is a compact, portable, and extensively tested C++11 software framework and set of applications tailored to the demands of next-generation sequencing data and applicable to many other applications. MolBioLib is designed to work with common file formats and data types used both in genomic analysis and general data analysis. A central relational-database-like Table class is a flexible and powerful object to intuitively represent and work with a wide variety of tabular datasets, ranging from alignment data to annotations. MolBioLib includes programs to perform a wide variety of analysis tasks such as computing read coverage, annotating genomic intervals, and novel peak calling with a wavelet algorithm. ...

This is the beta-version of a shape-based peak calling tool for ChIP-Seq data analysis. It is built using Generalized Linear Model with Negative binomial distribution. This tool accounts for the common peak shape, local variability of peak shifting distance and negative binomial background noise.

A collection of tools for working with the comparative data analysis ontology including import/export facilities for common phylogenetic file formats, and also a triple-store framework.

JNeuron is an analysis tool for multi-neuronal spike train analysis. The tool will allow scientists to organize their spike train data analysis into projects. The tool will implement standard spike train analysis algorithms and also datamining algorithms