List of the Top 6 Data Science Software for PyCharm in 2025

Jupyter Notebook is a versatile, web-based open-source application that allows individuals to generate and share documents that include live code, visualizations, mathematical equations, and textual descriptions. Its wide-ranging applications include data cleaning, statistical modeling, numerical simulations, data visualization, and machine learning, highlighting its adaptability across different domains. Furthermore, it acts as a superb medium for collaboration and the exchange of ideas among professionals within the data science community, fostering innovation and collective learning. This collaborative aspect enhances its value, making it an essential tool for both beginners and experts alike.

The Domino Enterprise MLOps Platform enhances the efficiency, quality, and influence of data science on a large scale, providing data science teams with the tools they need for success. With its open and adaptable framework, Domino allows experienced data scientists to utilize their favorite tools and infrastructures seamlessly. Models developed within the platform transition to production swiftly and maintain optimal performance through cohesive workflows that integrate various processes. Additionally, Domino prioritizes essential security, governance, and compliance features that are critical for enterprise standards. The Self-Service Infrastructure Portal further boosts the productivity of data science teams by granting them straightforward access to preferred tools, scalable computing resources, and a variety of data sets. By streamlining labor-intensive DevOps responsibilities, data scientists can dedicate more time to their core analytical tasks, enhancing overall efficiency. The Integrated Model Factory offers a comprehensive workbench alongside model and application deployment capabilities, as well as integrated monitoring, enabling teams to swiftly experiment and deploy top-performing models while ensuring high performance and fostering collaboration throughout the entire data science process. Finally, the System of Record is equipped with a robust reproducibility engine, search and knowledge management tools, and integrated project management features that allow teams to easily locate, reuse, reproduce, and build upon existing data science projects, thereby accelerating innovation and fostering a culture of continuous improvement. As a result, this comprehensive ecosystem not only streamlines workflows but also enhances collaboration among team members.

Deepnote is creating an exceptional data science notebook designed specifically for collaborative teams. You can seamlessly connect to your data, delve into analysis, and collaborate in real time while benefiting from version control. Additionally, you can easily share project links with fellow analysts and data scientists or showcase your refined notebooks to stakeholders and end users. This entire experience is facilitated through a robust, cloud-based user interface that operates directly in your browser, making it accessible and efficient for all. Ultimately, Deepnote aims to enhance productivity and streamline the data science workflow within teams.

Stata delivers everything you need for reproducible data analysis—powerful statistics, visualization, data manipulation, and automated reporting—all in one intuitive platform. Known for its speed and precision, Stata features an extensive graphical interface that simplifies usability while allowing for full programmability. The software combines the convenience of menus, dialogs, and buttons, giving users a flexible approach to data management. Its drag-and-drop functionality and point-and-click capabilities make accessing Stata's vast array of statistical and graphical tools straightforward. Additionally, users can quickly execute commands using Stata's user-friendly command syntax, which enhances efficiency. Furthermore, Stata logs every action and result, ensuring that all analyses maintain reproducibility and integrity, regardless of whether menu options or dialog boxes are used. Complete command-line programming and capabilities, including a robust matrix language, are also part of Stata's offerings. This versatility allows users to utilize all pre-installed commands, facilitating the creation of new commands or the scripting of complex analyses, thereby broadening the scope of what can be achieved within the software.

Datalore serves as a collaborative data science and analytics platform designed to enhance the analytics workflow, making data interaction more enjoyable for both data scientists and business teams with analytical skills. This platform prioritizes the efficiency of data teams, enabling technically skilled business users to engage with data teams through no-code and low-code solutions alongside the robust capabilities of Jupyter Notebooks. With Datalore, business users can enjoy analytic self-service by utilizing SQL or no-code cells, generating reports, and exploring data in depth. This functionality also allows core data teams to concentrate on more complex tasks, thus streamlining their workflow. Moreover, Datalore facilitates seamless collaboration between data scientists and analysts, enabling them to share their findings with ML Engineers. Users can effortlessly share their code with ML Engineers who have access to powerful CPUs and GPUs, all while collaborating in real time with colleagues for improved productivity and creativity. Ultimately, Datalore seeks to bridge the gap between technical and non-technical users, fostering a truly collaborative environment in the data science field.

Coder provides self-hosted cloud development environments that are ready for immediate use by developers and provisioned as code. This solution is especially popular among enterprises, as it is open source and can be deployed either on-premise or in the cloud, maintaining robust infrastructure access while ensuring compliance with governance requirements. By centralizing development and source code management, Coder allows developers to connect to their remote environments using their favorite desktop or web-based integrated development environments (IDEs). This method significantly improves the overall developer experience, boosts productivity, and enhances security measures. Additionally, Coder features ephemeral development environments created from pre-defined templates, enabling developers to set up new workspaces in an instant. This efficiency minimizes the challenges associated with local dependency versioning and lengthy security approval processes, allowing developers to switch projects or onboard new ones within minutes. Furthermore, organizations can benefit from reduced setup times and increased flexibility in managing their development workflows.