Company | Country | Industry | Employees | Revenue |
---|---|---|---|---|
| ||||
| ||||
| ||||
| ||||
| ||||
| ||||
| ||||
| ||||
| ||||
| ||||
| ||||
|
It provides a rich architecture for interactive computing with a powerful interactive shell, a kernel for Jupyter. It has a support for interactive data visualization and use of GUI toolkits. Flexible, embeddable interpreters to load into your own projects. Easy to use, high performance tools for parallel computing.
143
Unternehmen
Wir haben Daten zu 143 Unternehmen, die IPython verwenden. Unsere IPython Kundenliste steht zum Download bereit und ist mit wichtigen Unternehmensspezifika angereichert, darunter Branchenklassifikation, Organisationsgröße, geografische Lage, Finanzierungsrunden und Umsatzzahlen, unter anderem.
Unternehmen | Land | Branche | Mitarbeiter | Umsatz |
---|---|---|---|---|
Glovo | Spanien | Consumer Services | 11K | $422M |
Yelp | Vereinigte Staaten | Software Development | 7.9K | $1.1B |
Sunnybrook Health Sciences Centre | Kanada | Hospitals And Health Care | 12K | $1B |
![]() Exoticca | Spanien | Travel Arrangements | 455 | $80M |
Bumble | Vereinigte Staaten | It Services And It Consulting | 1.8K | $874M |
CBS | Dänemark | Media Production | 10K | |
BrainFinance | Kanada | Software Development | 67 | |
Pluto TV | Vereinigte Staaten | Entertainment Providers | 764 | $800M |
![]() Palta | Vereinigtes Königreich | Software Development | 103 | $1.5M |
Aviation & Missile Solutions | Vereinigte Staaten | Engineering Services | 118 | $3M |
Visa | Vereinigte Staaten | It Services And It Consulting | 26K | $31B |
Indien | Software Development | 7 |
Möchten Sie die gesamte Liste herunterladen?
Melden Sie sich an und laden Sie die vollständige Liste der 143 Unternehmen herunter.
Loading countries...
Loading other techonlogies...
Nutzungsstatistiken für Technologie und Marktanteil
Sie können diese Daten an Ihre Bedürfnisse anpassen, indem Sie nach Geografie, Branche, Unternehmensgröße, Umsatz, Technologienutzung, Jobpositionen und mehr filtern. Sie können die Daten im Excel- oder CSV-Format herunterladen.
Sie können Alarme für diese Daten erhalten. Sie können beginnen, indem Sie die Technologie auswählen, die Sie interessiert, und dann erhalten Sie Alarme in Ihrem Posteingang, wenn es neue Unternehmen gibt, die diese Technologie verwenden.
Sie können seine Daten in eine Excel-Datei exportieren, die in Ihr CRM importiert werden kann. Sie können die Daten auch an eine API exportieren.
Es gibt 7 Alternativen zu IPython
IPython wird in 14 Ländern verwendet
Häufig gestellte Fragen
Unsere Daten stammen aus Stellenanzeigen, die von Millionen von Unternehmen gesammelt wurden. Wir überwachen diese Anzeigen auf Firmenwebseiten, Jobbörsen und anderen Rekrutierungsplattformen. Die Analyse von Stellenanzeigen bietet eine zuverlässige Methode, um die von Unternehmen verwendeten Technologien zu verstehen, einschließlich der Nutzung interner Tools.
Wir aktualisieren unsere Daten täglich, um sicherzustellen, dass Sie auf die aktuellsten verfügbaren Informationen zugreifen. Dieser häufige Aktualisierungsprozess garantiert, dass unsere Einsichten und Erkenntnisse die neuesten Entwicklungen und Trends der Branche widerspiegeln.
IPython, a powerful interactive computing tool, provides an enhanced environment for data science and scientific computing. Offering a robust interactive shell, a Jupyter notebook interface, and support for multiple programming languages, IPython facilitates seamless integration, data visualization, and parallel computing. Its user-friendly features and extensive capabilities make it a preferred choice among data scientists, researchers, and developers for analyzing, exploring, and sharing computational workflows.
IPython falls under the category of Shells, which are software interfaces that allow users to interact with underlying operating systems. Specifically tailored for Python programming, IPython serves as an advanced Python shell with added functionalities such as code autocompletion, inline plotting, and rich media display. By combining the features of a traditional shell with interactive computing capabilities, IPython elevates the Python coding experience, enabling users to execute code snippets, visualize data, and iterate on algorithms efficiently.
Founded in 2001 by Fernando Perez, IPython originated from Perez's desire to create a more interactive and user-friendly computing environment for scientific research and data analysis. Over the years, the project has evolved into a comprehensive tool for interactive computing, garnering a dedicated user base and community support. With regular updates, enhancements, and contributions from a vibrant developer community, IPython continues to be a prominent player in the data science ecosystem.
In terms of current market share, IPython maintains a significant presence in the data science and scientific computing domains, with a growing user base across academia, industry, and research institutions. As the demand for interactive computing tools and Jupyter-based workflows increases, IPython is poised to expand its market share further. With continuous improvements, compatibility with emerging technologies, and integration with popular data science libraries, IPython is expected to witness a steady growth trajectory in the foreseeable future.
IPython is a powerful tool that is widely adopted by companies for its versatility and efficiency in data analysis and scientific computing tasks. With its user-friendly interface and robust features, IPython has become a staple in the tech stack of many organizations looking to streamline their data workflows.
Benefits of IPython:
Enhanced Interactivity: IPython allows for interactive computing, enabling users to run and debug code snippets in real-time. This feature enhances productivity by facilitating quick iterations and troubleshooting, setting it apart from traditional shell environments.
Rich Display Capabilities: One of the key advantages of IPython is its support for rich media output, including images, videos, and interactive visualizations. This makes presenting and sharing results more engaging and informative compared to plain text outputs found in standard shell environments.
Advanced Code Completion: IPython offers intelligent code completion suggestions based on variable names, modules, and functions, significantly speeding up the coding process. This functionality surpasses the basic autocomplete features in regular shells, providing more accurate and context-aware suggestions.
Effortless Collaboration: The notebook format in IPython enables seamless collaboration by combining code, visualizations, and explanatory text in a single document. This facilitates sharing and reproducing results, fostering teamwork and knowledge sharing within teams, unlike traditional shells that lack such integrated collaboration capabilities.
Parallel Computing Support: IPython's built-in support for parallel computing allows for the efficient distribution of computing tasks across multiple cores or nodes. This dramatically reduces processing times for complex computations, surpassing the scalability limitations of conventional shell environments.
In conclusion, the adoption of IPython in company tech stacks offers a wide array of benefits that cater to the diverse data analysis and scientific computing needs of modern businesses. Its interactive nature, rich display capabilities, advanced code completion, collaboration features, and parallel computing support make it a preferred choice for organizations seeking to enhance their data-driven workflows.
IPython, a powerful interactive shell that offers enhanced features for data science and scientific computing, is utilized by a variety of renowned companies for their data analysis needs. Let's delve into some insightful case studies showcasing how these companies leverage IPython to enhance their operations:
1. Netflix Netflix, the global streaming giant, utilizes IPython to streamline its data analysis processes. The company started using IPython in 2016 to enhance its data exploration capabilities. By utilizing IPython notebooks, Netflix's data scientists can prototype, visualize, and analyze vast amounts of data efficiently. This has enabled them to make data-driven decisions faster, leading to more effective content recommendations and personalized user experiences.
2. Spotify Spotify, the popular music streaming service, leverages IPython for its data science initiatives. Spotify integrated IPython into its workflow in 2018 to improve data visualization and machine learning model prototyping. By utilizing IPython notebooks, Spotify's data scientists can collaborate more effectively, experiment with different algorithms, and gain valuable insights to optimize music recommendations and user engagement strategies.
3. Uber Uber, the ride-hailing giant, harnesses IPython for advanced data analysis and visualization tasks. Uber adopted IPython in 2017 to enhance its geospatial data analysis capabilities. By leveraging IPython's interactive features, Uber's data analysts can perform spatial data analysis, optimize route planning algorithms, and improve the overall efficiency of its transportation services. This has allowed Uber to make data-informed decisions that drive operational excellence and enhance the user experience.
These case studies highlight how prominent companies like Netflix, Spotify, and Uber use IPython to enhance their data analysis capabilities, improve decision-making processes, and drive innovation in their respective industries. By leveraging the power of IPython, these companies can extract valuable insights from their data, optimize their operations, and deliver personalized experiences to their users.
Sie können eine aktuelle Liste von Unternehmen, die IPython verwenden, auf TheirStack.com einsehen. Unsere Plattform bietet eine umfassende Datenbank von Unternehmen, die verschiedene Technologien und interne Tools nutzen.
Bis jetzt haben wir Daten von 143 Unternehmen, die IPython verwenden.
IPython wird von einer Vielzahl von Organisationen in verschiedenen Branchen, einschließlich "Consumer Services", "Software Development", "Hospitals And Health Care", "Travel Arrangements", "It Services And It Consulting", "Media Production", "Software Development", "Entertainment Providers", "Software Development", "Engineering Services", verwendet. Für eine umfassende Liste aller Branchen, die IPython nutzen, besuchen Sie bitte TheirStack.com.
Einige der Unternehmen, die IPython verwenden, umfassen Glovo, Yelp, Sunnybrook Health Sciences Centre, Exoticca, Bumble, CBS, BrainFinance, Pluto TV, Palta, Aviation & Missile Solutions und viele mehr. Sie können eine vollständige Liste von 143 Unternehmen, die IPython nutzen, auf TheirStack.com finden.
Basierend auf unseren Daten ist IPython am beliebtesten in Vereinigte Staaten (67 companies), Vereinigtes Königreich (8 companies), Kanada (7 companies), Spanien (7 companies), Indien (5 companies), Australien (3 companies), Deutschland (3 companies), Zypern (1 companies), Dänemark (1 companies), Frankreich (1 companies). Es wird jedoch von Unternehmen auf der ganzen Welt verwendet.
Sie können Unternehmen, die IPython verwenden, finden, indem Sie auf TheirStack.com danach suchen. Wir verfolgen Stellenanzeigen von Millionen von Unternehmen und nutzen sie, um herauszufinden, welche Technologien und internen Tools sie verwenden.