Search Results for "python data analysis" - Page 10
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609 projects for "python data analysis" with 2 filters applied:
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PixieDust
Python Helper library for Jupyter Notebooks
PixieDust is an open source Python helper library that works as an add-on to Jupyter notebooks to improve the user experience of working with data. It also fills a gap for users who have no access to configuration files when a notebook is hosted on the cloud. -
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RecNN
Reinforced Recommendation toolkit built around pytorch 1.7
This is my school project. It focuses on Reinforcement Learning for personalized news recommendation. The main distinction is that it tries to solve online off-policy learning with dynamically generated item embeddings. I want to create a library with SOTA algorithms for reinforcement learning recommendation, providing the level of abstraction you like. -
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Twint
An advanced Twitter scraping & OSINT tool written in Python
Twint is an advanced open-source Twitter scraping and OSINT tool written in Python that extracts tweets, user data, followers, likes, and more—without relying on Twitter’s API—making it highly useful for researchers, analysts, and hobbyists who want to bypass rate limits and access public Twitter data. -
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pysourceinfo
RTTI for Python Source and Binary Files
The 'pysourceinfo' package provides source information on Python runtime objects based on 'inspect', 'sys', 'os', and 'imp'. The covered objects include packages, modules, functions, methods, scripts, and classes by two views: - File System View - packages, modules, and linenumbers - based on files and paths - Runtime Object View - callables, classes, and containers - based on in-memory RTTI / introspection The supported platforms are: - Linux, BSD, Unix, OS-X, Cygwin, and... -
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yapydata
Lower-Layer unified data - JSON, XML, YAML + INI, CFG, properties
The yapydata - Yet Another Python Data - provides a unified interface for the access to various data syntaxes. Therefore it encapsulates the libraries by offering a common API with the canonical internal data as JSON compatible Python in-memory structure. The application is foreseen in particular for the lower layer of the software stack including setup-tools. -
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setuplib
Extensions for setuptools - detailed information on entry points
The *setuplib* package provides core functions for the query of meta information and installation repositories of *Python* packages. It provides query and filter options on the installed packages and the available information, while displaying the result data in various formats, e.g. as table, list, or JSON, XML, YAML, CSV, etc. The provided commands and extension points integrate seamless into the standard *setuptools* and/or *distutils*. The *setuplib* is member of the group *setuplib* of extension components for the common *setup.py* installer. ... -
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yapyutils
Utilities for platform indepentent low-level system APIs.
The 'yapyutils' - Yet Another Python Utils - package provides miscellaneous *Python* utilities for the adaptation of platform independent APIs of the low-level part of the software stack. These are e.g. used for extensions of the *setuptools* and *distutils*, thus reduce the package dependency and avoid circular dependencies whenever possible by using standard packages and classes only. -
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platformids
OS and Distribution Release Enumeration
The ‘platformids‘ package provides the categorization and enumeration of OS platforms and distributions. This enables the development of portable generic code for arbitrary platforms in IT and IoT landscapes consisting of heterogeneous physical and virtual runtime environments. The introduced hierarchical bitmask vectors enable for fast and efficient platform specific code and data selection for OS and distributions with routines for specific platform releases. The supported... -
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AES Everywhere
Cross Language AES 256 Encryption Library
AES Everywhere is Cross Language Encryption Library that provides the ability to encrypt and decrypt data using a single algorithm in different programming languages and on different platforms. This is an implementation of the AES algorithm, specifically CBC mode, with 256-bit key length and PKCS7 padding. It implements OpenSSL-compatible cryptography with randomly generated salt. -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Olex2 is visualisation software for small-molecule crystallography developed at Durham University/EPSRC. It provides comprehensive tools for crystallographic model manipulation for the end user and an extensible development framework for programmers. The project has been supported by Olexsys Ltd since 2010.
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Patlac--Xml2cpp is a totally customizable code generator that generates classes (c++ for now) automatically from a xsd schema. Classes are described in google-ctemplate files and a xml options file allow precise definition of projects.
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RobotsDisallowed
A curated list of the most common and most interesting robots.txt
RobotsDisallowed is a public catalog that tracks websites and organizations explicitly blocking AI and web-scraping crawlers in their robots.txt or related mechanisms. It focuses on documenting the growing trend of content owners asserting control over how their data is used for model training and automated harvesting. The project aggregates domains, notes the targeted bots or user agents, and surfaces patterns for researchers, policymakers, and tool builders. It serves both as a... -
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Open|SpeedShop
Open|SpeedShop is an open source multi platform Linux performance tool
Open|SpeedShop is an open source multi platform Linux performance tool which is targeted to support performance analysis of applications running on both single node and large scale IA64, IA32, EM64T, AMD64, PPC, Blue Gene, ARM and Cray platforms. -
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Personal Blog
One article per week, the content is concise, neither salty nor light
Personal Blog holds the source structure and article index for the author’s personal technical blog, which is closely tied to the “芋道源码” WeChat public account. It uses Markdown files and a static-site setup (with configuration like _config.yml) to organize posts about Java back-end engineering, distributed systems, and source-code deep dives. The README and index emphasize that the blog (in this repo) is paused and that new content is primarily delivered via the WeChat channel, but the... -
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data-science-ipython-notebooks
Data science Python notebooks: Deep learning
Data Science IPython Notebooks is a broad, curated set of Jupyter notebooks covering Python, data wrangling, visualization, machine learning, deep learning, and big data tools. It aims to be a practical map of the ecosystem, showing hands-on examples with libraries such as NumPy, pandas, matplotlib, scikit-learn, and others. Many notebooks introduce concepts step by step, then apply them to real datasets so readers can see techniques in action. -
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porttree
Show dependences of a FreeBSD port as a pseudo graphic tree
For a given FreeBSD port, determine its dependences using any combination of the FETCH_, EXTRACT_, PATCH_, BUILD_, LIB_, RUN_ and TEST_DEPENDS, and show them as a pseudo graphical tree. Use back references for cross-connections. -
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Invenio
Invenio digital library framework
Invenio is a highly customizable open-source framework for building large-scale digital repositories and research data platforms. Developed by CERN, it is designed to manage, index, and provide access to metadata-rich content such as publications, datasets, and multimedia files. Invenio provides a modular architecture, making it suitable for libraries, archives, and research institutions. -
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Kalibr Allan
IMU Allan standard deviation charts
...While manufacturers typically provide “white noise” values in IMU datasheets, the bias instability and random walk parameters must be determined experimentally. This project enables users to compute those values using Allan variance analysis from recorded IMU data. The workflow involves recording IMU measurements with the device stationary, converting ROS bag files into MATLAB-compatible formats, and then running MATLAB scripts to generate Allan deviation plots. These plots are analyzed to determine noise density and random walk parameters for both gyroscopes and accelerometers. ... -
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Functional, Data Science Intro To Python
[tutorial]A functional, Data Science focused introduction to Python
The first section is an intentionally brief, functional, data science-centric introduction to Python. The assumption is a someone with zero experience in programming can follow this tutorial and learn Python with the smallest amount of information possible. The sections after that, involve varying levels of difficulty and cover topics as diverse as Machine Learning, Linear Optimization, build systems, command line tools, recommendation engines, Sentiment Analysis and Cloud Computing. -
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concordia
Powerful search library, best suited for computer-aided translation
Concordia - Roman goddess of agreement. Concordance searcher - tool for translators who need their translations to "agree" with one standard. Concordia is a C++ library for fast text lookup in large corpora. It uses a RAM stored index, which takes up approximately 600MB of memory for a corpus of 2 million sentences. It is based on the idea of a suffix array, enhanced by the presence of other auxiliary data structures. The effects are stunning - Concordia is able to do simple substring... -
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Autologging
Easier logging and tracing of Python functions and class methods.
Autologging eliminates boilerplate logging setup code and tracing code, and provides a means to separate application logging from program flow and data tracing. Autologging provides two decorators and a custom log level: "autologging.logged" decorates a class to create a __log member. By default, the logger is named for the class's containing module and name (e.g. "my.module.ClassName"). "autologging.traced" decorates a class to provide automatic CALL/RETURN tracing for all class, static, and instance methods, as well as the special __init__ method (by default) "autologging.TRACE" is a custom log level (lower than logging.DEBUG) that is registered with the Python logging module when autologging is imported -
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Dr0p1t-Framework
A framework that create an advanced stealthy dropper
Dr0p1t-Framework is a penetration testing tool designed to generate advanced and stealthy droppers capable of delivering and executing payloads on target systems while evading detection mechanisms. A dropper is a type of malware used to download and install additional malicious software, and this framework focuses on making that process more flexible and difficult to detect. It provides a wide range of modules that allow users to customize payload delivery, persistence mechanisms, and... -
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ansvif
An advanced cross platform fuzzing framework suited to find code bugs.
ansvif, or A Not So Very Intelligent Fuzzer, suited to find bugs in code by throwing garbage arguments, files, and environment variables at the target program, that you may or may not have the source code to. It supports many features, such as buffer size, randomization of the buffer size, random data injection, templates, and much more. The purpose of this project is to identify bugs in software, specifically bugs that can induce a segmentation fault under various conditions. This aids... -
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Ponder
C++ reflection library with Lua binding, and JSON and XML
...It provides an abstraction for most of the high-level concepts of C++ like classes, enumerations, properties, functions, and objects. By wrapping all these concepts into abstract structures, Ponder provides an extra layer of flexibility to programs and allows them to expose and manipulate their data structures at runtime. Many applications can take advantage of Ponder, in order to automate tasks that would otherwise require a huge amount of work. For example, Ponder can be used to expose and edit objects' attributes in a graphical user interface. It can also be used to do automatic binding of C++ classes to script languages such as Python or Lua. ... -
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BinCoMerge
Compare binary files in hexadecimal view
BinCoMerge is a binary files diff at byte resolution. It shows hexadecimal and raw ASCII data. BinCoMerge is seeking for common blocks from the bigger ones to the lower ones. It works by levels of minimum block sizes which are powers of 2. For example, with a file sizing between 16 KiB and 32 KiB, Bincomerge will firstly seek for all common blocks bigger than 16 KiB. Then, it will seek for all common bigger than 8 KiB, then 4KiB, 2KiB, 1024 Bytes... Because it works by levels, BinCoMerge...
