Deep Talk vs PyXLL
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Integrate Python into Microsoft Excel. Use Excel as your user-facing front-end with calculations, business logic and data access powered by Python. Works with all 3rd party and open source Python packages. No need to write any VBA! | It is the fastest way to transform text from chats, emails, surveys, reviews, social networks into real business intelligence. Experience the power of data science without being a data scientist |
User Defined Functions: Write Excel worksheet functions in Python - no VBA required;Ribbon Customization: Give your users a rich Excel native experience;Macros: No need for VBA, access to the full Excel Object Model in Python;Menu Functions: Call Python functions from Excel menus, and give common tasks keyboard shortcuts;Real Time Data: Stream data to Excel in real-time using Python;Array Functions: Return tables of data to Excel that resize automatically;IntelliSense: Auto-complete worksheet functions as you type them;NumPy and Pandas Integration: Use NumPy and Pandas types in Excel | Unsupervised deep learning models to analyze your unstructured text data;
Deepers are pre trained deep learning models to get custom detections inside your data;
Real time tagging;
Conversation analysis;
Easy integrations |
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Stacks 8 | Stacks 0 |
Followers 104 | Followers 0 |
Votes 8 | Votes 0 |
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What are some alternatives to PyXLL, Deep Talk?
Metabase
It is an easy way to generate charts and dashboards, ask simple ad hoc queries without using SQL, and see detailed information about rows in your Database. You can set it up in under 5 minutes, and then give yourself and others a place to ask simple questions and understand the data your application is generating.
Superset
Superset's main goal is to make it easy to slice, dice and visualize data. It empowers users to perform analytics at the speed of thought.
Cube
Cube: the universal semantic layer that makes it easy to connect BI silos, embed analytics, and power your data apps and AI with context.
Power BI
It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards.
Pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.
Mode
Created by analysts, for analysts, Mode is a SQL-based analytics tool that connects directly to your database. Mode is designed to alleviate the bottlenecks in today's analytical workflow and drive collaboration around data projects.
Google Datastudio
It lets you create reports and data visualizations. Data Sources are reusable components that connect a report to your data, such as Google Analytics, Google Sheets, Google AdWords and so forth. You can unlock the power of your data with interactive dashboards and engaging reports that inspire smarter business decisions.
NumPy
Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
AskNed
AskNed is an analytics platform where enterprise users can get answers from their data by simply typing questions in plain English.
Shiny
It is an open source R package that provides an elegant and powerful web framework for building web applications using R. It helps you turn your analyses into interactive web applications without requiring HTML, CSS, or JavaScript knowledge.
