使用Matplotlib的公司
It is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. It can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application servers, and four graphical user interface toolkits.
使用Matplotlib的公司列表
curl --request POST \
--url "https://api.theirstack.com/v1/companies/search" \
--header "Accept: application/json" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer <api_key>" \
-d "{
\"company_technology_slug_or\": [
\"matplotlib\"
]
}"Technology
is any of
Matplotlib
员工数346k收入$61BIT Services and IT ConsultingMatplotlib高置信度
员工数2.3M收入$611BRetailMatplotlib高置信度
员工数93k收入$75BMotor Vehicle ManufacturingMatplotlib高置信度
员工数7Technology, Information and InternetMatplotlib高置信度
E-Learning ProvidersMatplotlib高置信度
员工数166kSoftware DevelopmentMatplotlib高置信度
员工数3.1k收入$14MFinancial ServicesMatplotlib高置信度
员工数46k收入$13BBusiness Consulting and ServicesMatplotlib高置信度
员工数30k收入$4.8BSoftware DevelopmentMatplotlib高置信度
员工数201Business Consulting and ServicesMatplotlib高置信度
我们拥有关于17,288家公司和用户使用Matplotlib的数据。我们的Matplotlib用户和客户列表可供下载，并附有重要的公司信息，包括行业分类、组织规模、地理位置、融资轮次和收入数据等。
技术使用统计和市场份额
如何定位 Matplotlib 用户
- 如何自定义此列表？
您可以根据地理位置、行业、公司规模、收入、技术使用、职位发布等需求自定义此数据。您可以将数据下载为Excel或CSV格式。
- 如何在公司采用此技术时收到通知？
您可以为此数据设置提醒。您可以通过选择您感兴趣的技术开始，当有新公司使用该技术时，您将收到收件箱中的提醒。
- 如何将此数据导入我的CRM？
您可以将此数据导出为Excel文件，然后导入到您的CRM中。您也可以将数据导出到API。
常见问题
我们的数据来源于从数百万家公司收集的职位发布。我们监控公司网站、招聘网站和其他招聘平台上的这些发布。分析职位发布提供了一种可靠的方法来了解公司正在使用的技术，包括他们使用的内部工具。
我们每天刷新数据，以确保您访问的是最新的信息。这一频繁的更新过程保证了我们的洞察和情报反映行业的最新发展和趋势。
Matplotlib is a popular data visualization library in the Python programming language. It provides a wide variety of high-quality 2D plotting capabilities, making it an essential tool for data scientists, analysts, and researchers. With Matplotlib, users can create line plots, bar plots, histograms, scatter plots, and much more, allowing them to effectively communicate insights and trends within their data.
Charting Libraries like Matplotlib belong to the broader category of data visualization tools. These tools are crucial for transforming raw data into visual representations, enabling easier interpretation and analysis. Matplotlib, specifically, stands out for its flexibility and customization options, allowing users to fine-tune every aspect of their plots to meet specific requirements. Whether it's creating simple visualizations or complex, publication-quality figures, Matplotlib excels in catering to a wide range of user needs within the data visualization domain.
Founded in 2003 by John D. Hunter, Matplotlib initially stemmed from the desire to replicate the plotting capabilities of MATLAB in Python. Hunter, a neurobiologist, recognized the gap in Python's data visualization offerings and sought to create a robust plotting library that would facilitate interactive and publication-ready visualizations. Since its inception, Matplotlib has evolved into a cornerstone tool within the Python ecosystem.
Currently, Matplotlib holds a significant market share within the Charting Libraries category, owing to its extensive functionality, active community support, and seamless integration with other data analysis libraries like NumPy and Pandas. As the demand for data-driven insights continues to grow across industries, Matplotlib is poised to maintain and potentially expand its market share in the future. Its adaptability, reliability, and continuous development make it a go-to choice for professionals looking to visualize their data effectively.