Search Results for "python data analysis"
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Showing 541 open source projects for "python data analysis"
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Create and manage the email signature you needWith WiseStamp it’s easy to unify your brand and turn your emails into a powerful marketing tool. Get the most out of your emails with a professionally designed custom email signature.
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JS7 JobScheduler is an open source workload automation solution.JS7 JobScheduler is an open source workload automation solution. It is used to run executable files, shell scripts etc. and database procedures.
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Orange Data Mining
Orange: Interactive data analysis
...Interactive data exploration for rapid qualitative analysis with clean visualizations. Graphic user interface allows you to focus on exploratory data analysis instead of coding, while clever defaults make fast prototyping of a data analysis workflow extremely easy. Place widgets on the canvas, connect them, load your datasets and harvest the insight! -
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Cookiecutter Data Science
Project structure for doing and sharing data science work
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work. When we think about data analysis, we often think just about the resulting reports, insights, or visualizations. While these end products are generally the main event, it's easy to focus on making the products look nice and ignore the quality of the code that generates them. Because these end products are created programmatically, code quality is still important! ... -
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pandas
Fast, flexible and powerful Python data analysis toolkit
pandas is a Python data analysis library that provides high-performance, user friendly data structures and data analysis tools for the Python programming language. It enables you to carry out entire data analysis workflows in Python without having to switch to a more domain specific language. With pandas, performance, productivity and collaboration in doing data analysis in Python can significantly increase. ... -
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AI Data Science Team
An AI-powered data science team of agents
AI Data Science Team is a Python library and agent ecosystem designed to accelerate and automate common data science workflows by modeling them as specialized AI “agents” that can be orchestrated to perform tasks like data cleaning, transformation, analysis, visualization, and machine learning. It provides a modular agent framework where each agent focuses on a step in the typical data science pipeline — for example, loading data from CSV/Excel files, cleaning and wrangling messy datasets, engineering predictive features, building models with AutoML, connecting to SQL databases, and producing visual outputs — all driven by natural language or programmatic instructions. ... -
GoAnywhere Managed File Transfer (MFT)GoAnywhere MFT provides secure managed file transfer for enterprises. Deployable on-premise, in the cloud, or in hybrid environments, GoAnywhere MFT software enables organizations to exchange data among employees, customers, and trading partners, as well as between systems, securely. GoAnywhere MFT was a recipient of the Cybersecurity Excellence Award for Secure File Transfer.
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scikit-learn
Machine learning in Python
scikit-learn is an open source Python module for machine learning built on NumPy, SciPy and matplotlib. It offers simple and efficient tools for predictive data analysis and is reusable in various contexts. -
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geemap
A Python package for interactive geospaital analysis and visualization
A Python package for interactive geospatial analysis and visualization with Google Earth Engine. Geemap is a Python package for geospatial analysis and visualization with Google Earth Engine (GEE), which is a cloud computing platform with a multi-petabyte catalog of satellite imagery and geospatial datasets. During the past few years, GEE has become very popular in the geospatial community and it has empowered numerous environmental applications at local, regional, and global scales. ... -
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airda
airda(Air Data Agent
airda(Air Data Agent) is a multi-smart body for data analysis, capable of understanding data development and data analysis needs, understanding data, generating data-oriented queries, data visualization, machine learning and other tasks of SQL and Python codes. -
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ydata-profiling
Create HTML profiling reports from pandas DataFrame objects
ydata-profiling primary goal is to provide a one-line Exploratory Data Analysis (EDA) experience in a consistent and fast solution. Like pandas df.describe() function, that is so handy, ydata-profiling delivers an extended analysis of a DataFrame while allowing the data analysis to be exported in different formats such as html and json. -
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AWS Data Wrangler
Pandas on AWS, easy integration with Athena, Glue, Redshift, etc.
An AWS Professional Service open-source python initiative that extends the power of Pandas library to AWS connecting DataFrames and AWS data-related services. Easy integration with Athena, Glue, Redshift, Timestream, OpenSearch, Neptune, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON, and EXCEL). Built on top of other open-source projects like Pandas, Apache Arrow and Boto3, it offers abstracted functions to execute usual ETL tasks like load/unload data from Data Lakes, Data Warehouses, and Databases. ... -
Easy-to-use online form builder for every business.Easy-to-use online form builder for every business. Create online forms and publish them. Get an email for each response. Collect data. Design professional looking forms with JotForm Online Form Builder. Customize with advanced styling options to match your branding. Speed up and simplify your daily work by automating complex tasks with JotForm’s industry leading features. Securely and easily sell products. Collect subscription fees and donations. Being away from your computer shouldn’t stop you from getting the information you need. No matter where you work, JotForm Mobile Forms lets you collect data offline with powerful forms you can manage from your phone or tablet. Get the full power of JotForm at your fingertips. JotForm PDF Editor automatically turns collected form responses into professional, secure PDF documents that you can share with colleagues and customers. Easily generate custom PDF files online!
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Sweetviz
Visualize and compare datasets, target values and associations
Sweetviz is an open-source Python library that generates beautiful, high-density visualizations to kickstart EDA (Exploratory Data Analysis) with just two lines of code. Output is a fully self-contained HTML application. The system is built around quickly visualizing target values and comparing datasets. Its goal is to help quick analysis of target characteristics, training vs testing data, and other such data characterization tasks. ... -
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Positron
Positron, a next-generation data science IDE
Positron is a next-generation integrated development environment (IDE) created by Posit PBC (formerly RStudio Inc) specifically tailored for data science workflows in Python, R, and multi-language ecosystems. It aims to unify exploratory data analysis, production code, and data-app authoring in a single environment so that data scientists move from “question → insight → application” without switching tools. Built on the open-source Code-OSS foundation, Positron provides a familiar coding experience along with specialized panes and tooling for variable inspection, data-frame viewing, plotting previews, and interactive consoles designed for analytical work. ... -
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PyVista
3D plotting and mesh analysis through a streamlined interface
...This module can be used for scientific plotting for presentations and research papers as well as a supporting module for other mesh-dependent Python modules. Easily integrate with NumPy and create a variety of geometries and plot them. You could use any geometry to create your glyphs, or even plot the points directly. Direct access to mesh analysis and transformation routines. Intuitive plotting routines with matplotlib similar syntax. -
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leafmap
A Python package for interactive mapping and geospatial analysis
A Python package for geospatial analysis and interactive mapping in a Jupyter environment. Leafmap is a Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment. It is a spin-off project of the geemap Python package, which was designed specifically to work with Google Earth Engine (GEE). -
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Astropy
Repository for the Astropy core package
...The Anaconda Python Distribution includes Astropy and is the recommended way to install both Python and the Astropy package. The astropy package contains key functionality and common tools needed for performing astronomy and astrophysics with Python. It is at the core of the Astropy Project, which aims to enable the community to develop a robust ecosystem of affiliated packages covering a broad range of needs for astronomical research, data processing, and data analysis. -
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Panda-Helper
Panda-Helper: Data profiling utility for Pandas DataFrames and Series
Panda-Helper is a simple data-profiling utility for Pandas DataFrames and Series. Assess data quality and usefulness with minimal effort. Quickly perform initial data exploration, so you can move on to more in-depth analysis. -
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Timesketch
Collaborative forensic timeline analysis
Timesketch is a collaborative forensic timeline analysis platform used to investigate security incidents by turning diverse evidence into a single, searchable chronology. Analysts ingest logs and artifacts from many sources—endpoints, servers, cloud services—and Timesketch normalizes them into events on a unified timeline. Powerful search, aggregations, and saved views help you pivot quickly, highlight anomalies, and preserve investigative steps for later review. -
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JS Analyzer
Burp Suite extension for JavaScript static analysis
...It also includes UI features such as live search, result filtering, and the ability to export findings in JSON format for further processing. The underlying engine can be used independently in Python, enabling integration into custom workflows or automated pipelines outside Burp Suite. -
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VisPy
Main repository for Vispy
Vispy is an open-source, high-performance interactive visualization library in Python, designed for creating scientific visualizations and interactive plots. It leverages the power of modern Graphics Processing Units (GPUs) through OpenGL to render large datasets efficiently. Vispy supports a wide range of visualization types, including 2D plots, 3D visualizations, volume rendering, and more, making it suitable for scientific research, data analysis, and educational purposes. -
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Pandas Profiling
Create HTML profiling reports from pandas DataFrame objects
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). ... -
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whylogs
The open standard for data logging
whylogs is an open-source library for logging any kind of data. With whylogs, users are able to generate summaries of their datasets (called whylogs profiles) which they can use to track changes in their dataset Create data constraints to know whether their data looks the way it should. Quickly visualize key summary statistics about their datasets. whylogs profiles are the core of the whylogs library. They capture key statistical properties of data, such as the distribution (far beyond... -
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atpbar
Progress bars for threading and multiprocessing tasks on terminal
Progress bars for threading and multiprocessing tasks on the terminal and Jupyter Notebook. atpbar can display multiple progress bars simultaneously growing to show the progresses of iterations of loops in threading or multiprocessing tasks. atpbar can display progress bars on the terminal and Jupyter Notebook. atpbar can be used with Mantichora. atpbar started its development in 2015 as part of Alphatwirl. atpbar prevented physicists from terminating their running analysis codes, which... -
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Datasette
An open source multi-tool for exploring and publishing data
Datasette is a tool for exploring and publishing data. It helps people take data of any shape or size, analyze and explore it, and publish it as an interactive website and accompanying API. Datasette is aimed at data journalists, museum curators, archivists, local governments, scientists, researchers and anyone else who has data that they wish to share with the world. It is part of a wider ecosystem of tools and plugins dedicated to making working with structured data as productive as... -
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F1 Race Replay
An interactive Formula 1 race visualisation and data analysis tool
F1 Race Replay is an interactive replay viewer that lets users watch and analyze recorded Formula 1 race sessions with precise control over camera angles, timing, and telemetry overlay, offering a rich experience beyond standard broadcast replays. It ingests official timing and positional data, then renders vehicle movements through track maps and 3D visualizations so fans, analysts, and engineers can review strategy, overtakes, tire degradation effects, and pit stop impacts in detail. Users... -
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folium
Python data, Leaflet.js maps
folium builds on the data wrangling strengths of the Python ecosystem and the mapping strengths of the leaflet.js library. Manipulate your data in Python, then visualize it in on a Leaflet map via folium. folium makes it easy to visualize data that’s been manipulated in Python on an interactive leaflet map. It enables both the binding of data to a map for choropleth visualizations as well as passing rich vector/raster/HTML visualizations as markers on the map. ... -
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SageMaker Spark Container
Docker image used to run data processing workloads
Apache Spark™ is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing.
