30 projects for "matplotlib" with 1 filter applied:

  • Track time for payroll, billing and productivity Icon
    Track time for payroll, billing and productivity

    Flexible time and billing software that enables teams to easily track time and expenses for payroll, projects, and client billing.

    Because time is money, and we understand how challenging it can be to keep track of employee hours. The constant reminder to log timesheets so your business can increase billables, run an accurate payroll and remove the guesswork from project estimates – we get it.
    Learn More
  • Teradata VantageCloud Enterprise is a data analytics platform for performing advanced analytics on AWS, Azure, and Google Cloud. Icon
    Teradata VantageCloud Enterprise is a data analytics platform for performing advanced analytics on AWS, Azure, and Google Cloud.

    Power faster innovation with Teradata VantageCloud

    VantageCloud is the complete cloud analytics and data platform, delivering harmonized data and Trusted AI for all. Built for performance, flexibility, and openness, VantageCloud enables organizations to unify diverse data sources, run complex analytics, and deploy AI models—all within a single, scalable platform.
    Learn More
  • 1
    Zero to Mastery Machine Learning

    Zero to Mastery Machine Learning

    All course materials for the Zero to Mastery Machine Learning

    ...The repository includes datasets, Jupyter notebooks, documentation, and example code that walk learners through the entire machine learning workflow from problem definition to model deployment. The course introduces essential tools such as NumPy, pandas, Matplotlib, and scikit-learn before moving on to deep learning with frameworks like TensorFlow and Keras. It also includes milestone projects that demonstrate how to build end-to-end machine learning systems using real datasets, including classification and regression tasks.
    Downloads: 7 This Week
    Last Update:
    See Project
  • 2
    Complete-Python-3-Bootcamp

    Complete-Python-3-Bootcamp

    Course Files for Complete Python 3 Bootcamp Course on Udemy

    ...The repository covers a wide range of Python topics, including data types, control flow, functions, object-oriented programming, error handling, modules, and advanced concepts like decorators and generators. In addition, it includes applied exercises in areas such as web scraping, working with APIs, and using Python libraries like NumPy, pandas, Matplotlib, and Seaborn for data analysis and visualization. Learners can progress from beginner-friendly basics to more advanced programming skills while reinforcing their knowledge with practice problems and projects. Because it mirrors the course content, this repository is widely used by students taking the Udemy course.
    Downloads: 4 This Week
    Last Update:
    See Project
  • 3
    spider_collection

    spider_collection

    Collection of Python web scraping scripts for data extraction tasks

    ...Several scripts also incorporate multi-threading and proxy usage to improve scraping efficiency and help avoid common anti-scraping limitations. In addition to raw data collection, some spiders include basic data processing and analysis using tools such as pandas and simple visualization with matplotlib. It also contains examples of proxy pool integration and encapsulation to support more reliable crawling when working with sites that enforce request limits.
    Downloads: 2 This Week
    Last Update:
    See Project
  • 4
    Scientific Visualization

    Scientific Visualization

    An open access book on scientific visualization using python

    The Scientific Visualization book is a freely available open-access textbook that introduces how to produce effective scientific visualizations using Python, focusing especially on leveraging the popular plotting library Matplotlib (and related tools). It goes beyond simple plotting tutorials and emphasizes design principles: how to choose colors, layout subplots, annotate graphs, and present data in a way that is both accurate and visually compelling. As such, it serves as a guide for researchers, data scientists, and academic authors who need to create publication-quality figures or explanatory graphics, rather than quick exploratory plots. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Jscrambler: Pioneering Client-Side Protection Platform Icon
    Jscrambler: Pioneering Client-Side Protection Platform

    Jscrambler offers an exclusive blend of cutting-edge first-party JavaScript obfuscation and state-of-the-art third-party tag protection.

    Jscrambler is the leader in Client-Side Protection and Compliance. We were the first to merge advanced polymorphic JavaScript obfuscation with fine-grained third-party tag protection in a unified Client-Side Protection and Compliance Platform. Our integrated solution ensures a robust defense against current and emerging client-side cyber threats, data leaks, and IP theft, empowering software development and digital teams to innovate securely. With Jscrambler, businesses adopt a unified, future-proof client-side security policy all while achieving compliance with emerging security standards including PCI DSS v4.0. Trusted by digital leaders worldwide, Jscrambler gives businesses the freedom to innovate securely.
    Learn More
  • 5
    Peroxide

    Peroxide

    Rust numeric library with high performance and friendly syntax

    Rust numeric library contains linear algebra, numerical analysis, statistics and machine learning tools with R, MATLAB, Python-like macros. Peroxide uses a 1D data structure to represent matrices, making it straightforward to integrate with BLAS (Basic Linear Algebra Subprograms). This means that Peroxide can guarantee excellent performance for linear algebraic computations by leveraging the optimized routines provided by BLAS. For users familiar with numerical computing libraries like...
    Downloads: 2 This Week
    Last Update:
    See Project
  • 6
    Python 100 Days

    Python 100 Days

    Python - From Novice to Master in 100 Days

    ...The curriculum expands into databases and SQL, Linux essentials, web fundamentals, and a substantial Practical Django track that covers ORM, sessions, RESTful APIs, caching with Redis, asynchronous tasks with Celery, authentication, testing, and deployment. Data analysis and visualization receive dedicated coverage via NumPy, pandas, matplotlib, seaborn, and pyecharts, followed by an applied machine learning track with kNN, trees, Bayes, regression, clustering, ensembles, and neural networks.
    Downloads: 4 This Week
    Last Update:
    See Project
  • 7
    Kedro

    Kedro

    A Python framework for creating reproducible, maintainable code

    Kedro is an open sourced Python framework for creating maintainable and modular data science code. Provides the scaffolding to build more complex data and machine-learning pipelines. In addition, there's a focus on spending less time on the tedious "plumbing" required to maintain data science code; this means that you have more time to solve new problems. Standardises team workflows; the modular structure of Kedro facilitates a higher level of collaboration when teams solve problems...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 8
    Data Preprocessing Automate

    Data Preprocessing Automate

    Data Preprocessing Automation: A GUI for easy data cleaning & visualiz

    ...The application provides data visualization tools, including box plots for distribution analysis and scatter plots for exploring relationships between variables. Users can download the processed data for further analysis. Built with Tkinter, Pandas, Matplotlib, and Seaborn, it ensures an intuitive interface and efficient performance. Additionally, it features a custom logo, a clean UI with a green-blue theme, and options for licensing and public release. This tool is ideal for data analysts, researchers, and professionals looking to automate preprocessing without coding. 🚀
    Downloads: 0 This Week
    Last Update:
    See Project
  • 9
    Python Data Science Handbook

    Python Data Science Handbook

    Python Data Science Handbook: full text in Jupyter Notebooks

    The Python Data Science Handbook is a comprehensive collection of Jupyter notebooks written by Jake VanderPlas covering fundamental Python libraries for data science, including IPython, NumPy, Pandas, Matplotlib, Scikit-Learn and more. The project is designed for data scientists, researchers, and anyone transitioning into Python-based data work; it assumes you already know basic Python and focuses more on how to use the ecosystem effectively. Each chapter is a standalone Jupyter notebook, with runnable code, explanatory prose, visuals, and examples showing how to handle data-wrangling, exploratory data analysis, machine learning workflows, and visualization. ...
    Downloads: 10 This Week
    Last Update:
    See Project
  • Silverware is an enterprise-grade hospitality platform built for hotels, resorts, and complex multi-venue operations. Icon
    Silverware is an enterprise-grade hospitality platform built for hotels, resorts, and complex multi-venue operations.

    Silverware powers high-end hospitality environments

    Silverware is built for hotel, resort, and multi-venue hospitality operators who need enterprise-grade control, deep integrations, and always-on reliability to run complex operations at scale.
    Learn More
  • 10
    vim-jukit

    vim-jukit

    Jupyter-Notebook inspired Neovim/Vim Plugin

    REPL plugin and Jupyter-Notebook alternative for (Neo)Vim. This plugin is aimed at users in search for a REPL plugin with lots of additional features.
    Downloads: 6 This Week
    Last Update:
    See Project
  • 11
    Python ML Jupyter Notebooks

    Python ML Jupyter Notebooks

    Practice and tutorial-style notebooks

    ...The project provides numerous examples and tutorials covering classical machine learning techniques such as regression, classification, clustering, and dimensionality reduction. It includes code implementations that show how to build models using popular libraries like scikit-learn, NumPy, pandas, and Matplotlib. The repository is designed to help learners understand both the theory and practical implementation of machine learning algorithms through step-by-step code examples. Many notebooks include explanations of algorithm behavior, data preparation techniques, and evaluation methods for machine learning models. The project also includes examples that demonstrate how to apply machine learning to real-world datasets and practical business problems.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 12
    IdleX - IDLE Extensions for Python
    A collection of extensions for Python's IDLE, the Python IDE built with the tkinter GUI toolkit.
    Downloads: 42 This Week
    Last Update:
    See Project
  • 13
    Brand new cheatsheets and handouts

    Brand new cheatsheets and handouts

    Matplotlib 3.1 cheat sheet

    ...For practitioners working on data-heavy projects, dashboards, or research code where plotting is frequent, it helps speed up development by reducing context-switching and documentation navigation overhead. It is especially useful when you know roughly what you want (e.g. “I need a scatter + histogram marginal plot”) but don’t remember the exact Matplotlib call.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 14
    The Neural Process Family

    The Neural Process Family

    This repository contains notebook implementations

    ...Each notebook includes theoretical explanations, key building blocks, and executable code that runs directly in Google Colab, requiring no local setup. Implementations rely only on standard dependencies such as NumPy, TensorFlow, and Matplotlib, and provide visualizations of model performance.
    Downloads: 2 This Week
    Last Update:
    See Project
  • 15
    Scikit-learn Tutorial

    Scikit-learn Tutorial

    An introductory tutorial for scikit-learn

    ...The tutorial covers data preparation, model fitting, evaluation, and common algorithms such as classification, regression, clustering, and dimensionality reduction. It is designed for people who already have a working Python environment and some familiarity with NumPy, SciPy, and Matplotlib. The repository specifies a clear list of dependencies so that participants can reproduce the environment used in the tutorial, and many downstream forks keep the content updated for newer versions of scikit-learn. Although the GitHub repository has been archived and is read-only, it is still a valuable snapshot of early, hands-on teaching material for scikit-learn and machine learning in Python.
    Downloads: 2 This Week
    Last Update:
    See Project
  • 16
    AI Cheatsheets

    AI Cheatsheets

    Essential Cheat Sheets for deep learning and machine learning research

    ...The project aims to provide quick-reference materials that help engineers, researchers, and students review key techniques and frameworks without reading extensive documentation. It compiles cheat sheets for widely used libraries and technologies such as TensorFlow, Keras, NumPy, Pandas, Scikit-learn, Matplotlib, and PySpark. These materials summarize common functions, workflows, and best practices in a concise visual format that makes them easy to consult during development or study sessions. The repository functions as a centralized library where users can quickly access reference materials for both machine learning theory and practical programming tools. ...
    Downloads: 1 This Week
    Last Update:
    See Project
  • 17
    data-science-ipython-notebooks

    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. Advanced sections touch on neural networks and distributed computing topics, helping you bridge from basics to production-adjacent workflows. The collection is suitable for self-paced study, quick reference, or as teaching materials in workshops. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 18

    MerDAQ

    A DAQ solution in Python 2 for your Ardruino

    MerDAQ is a data acquisition GUI and other tools for collecting and storing time dependent. Originally designed to collect 4 temperature data vs. time and plot one of the temperatures in real time with matplotlib. Ideal for use with Arduino.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 19
    Matplotlib tutorial

    Matplotlib tutorial

    Matplotlib tutorial for beginner

    The Matplotlib tutorial repository is designed as a hands-on learning resource to help users — especially Python beginners — get started with Matplotlib for creating plots and charts. It provides a sequence of example scripts and notebooks that cover fundamental plotting tasks: line graphs, histograms, scatter plots, bar charts, customizing axes, labels, legends, and styling.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 20
    RoiView
    Explore InSAR data and more
    Downloads: 0 This Week
    Last Update:
    See Project
  • 21
    pyisocalc

    pyisocalc

    Isotopic pattern calculator in python 2.x

    This is an isotopic pattern calculator written in python. It depends on re, sys, numpy, operator, itertools, and matplotlib.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 22

    pyShotDetect

    (Auto-)Detect Video Scene Changes, output an edit list

    ...Given a .dv file automatically detect scene changes within that file (best performance on cuts and fade through/to black). Write a .kino file with each of the scenes for post-processing. Dependencies: (Python) openCV matplotlib Tkinter
    Downloads: 0 This Week
    Last Update:
    See Project
  • 23
    HOPSA
    ...Although written for this specific task it is easy to adopt for any experimental task which changes hardware parameters and waits for a specific condition before proceeding. The graphical interface (QT4) includes plotting (matplotlib), instrument configuration/monitoring and a program step creator. The communication with the hardware is independent of the GUI and any number of devices can be selected. To modify the code for any other task only the hardware interface needs to be redefined.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 24

    pygolem

    Python API for the GOLEM Tokamak discharge database

    This simple Python API aims to provide a simple and easy to understand access to the discharge database of the GOLEM Tokamak. The scipy, numpy and matplotlib Python libraries are used for data analysis and plotting.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 25
    Echoproc is a piece of scientific analysis software used to extract physical ice sheet characteristics from radio echograms from experiments like the Center for the Remote sensing of ice sheets (https://www.cresis.ku.edu/)
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • 2
  • Next
MongoDB Logo MongoDB