Tag: python

Feed: AWS Big Data Blog. As the most widely used cloud data warehouse, Amazon Redshift makes it simple and cost-effective to analyze your data using standard SQL and your existing ETL (extract, transform, and load), business intelligence (BI), and reporting tools. Tens of thousands of customers use Amazon Redshift to analyze exabytes of data per day and power analytics workloads such as BI, predictive analytics, and real-time streaming analytics without having to manage the data warehouse infrastructure. It natively integrates with other AWS services, facilitating the process of building enterprise-grade analytics applications in a manner that is not only cost-effective, ... Read More

Feed: Neo4j Graph Data Platform. Author: Yolande Poirier. Graph Data Science features are now available in Bloom 2.3! Just select the Graph Data Science icon and choose from the available algorithms. The GDS plugin needs to be installed on the database for self-managed users, or you can use AuraDS. To get an idea of what Bloom and Graph Data Science are capable of, read Zach Blumenfeld ’s blog on using graph technology on a freight forwarding logistics network. In this first blog in the series, he gets us started with experimentation and visualization of supply chain data using ... Read More

Feed: Neo4j Graph Data Platform. Author: Enzo. It’s been such an eventful week for the Neo4j community, especially for those who went to GraphConnect 2022 in Austin, Texas. If you were there in person earlier this week (lucky you), you probably saw all of the exciting new tools and features announced during the keynote. For the rest of us who couldn’t make it, this newsletter is here to catch you up to speed. PRODUCT ANNOUNCEMENT: What’s New in UserTools, Graph Database, and GDS At GraphConnect 2022, Emil and team announced the new Neo4j Workspace in UserTools and Neo4j Data Warehouse ... Read More

Feed: AWS Big Data Blog. Data engineers use various Python packages to meet their data processing requirements while building data pipelines with AWS Glue PySpark Jobs. Languages like Python and Scala are commonly used in data pipeline development. Developers can take advantage of their open-source packages or even customize their own to make it easier and faster to perform use cases, such as data manipulation and analysis. However, managing standardized packages can be cumbersome with multiple teams using different versions of packages, installing non-approved packages, and causing duplicate development effort due to the lack of visibility of what is available ... Read More

Feed: Recent Announcements. You can now run graph analytics and machine learning tasks on graph data stored in Amazon Neptune using an open-source Python integration that simplifies data science and ML workflows. With this integration, you can read and write graph data stored in Neptune using Pandas DataFrames in any Python environment, such as a local Jupyter notebook instance, Amazon SageMaker Studio, AWS Lambda, or other compute resources. From there, you can run graph algorithms, such as PageRank and Connected Components, using open-source libraries like iGraph, Network, and cuGraph. Today’s launch helps customers to build and innovate faster by simplifying ... Read More

Feed: R-bloggers. Author: R on Amit Levinson. A few months ago Tal Mizrachi (The famous Analysis Paralysis) & I live streamed an R vs Python data analysis session (in Hebrew). We took the dogs of Zurich dataset, formatted it a bit, added a random DOB column and wrote down a few questions we answered during the live stream, each with his own tool.Besides it being a great experience collaborating with Tal, I think the questions overall touched on various aspects of our day-to-day data analysis flow. I initially hosted the questions and answers on a GitHub page but realized they ... Read More

Feed: R-bloggers. Author: RStudio | Open source & professional software for data science teams on RStudio. We’re excited to announce the release of pins for Python! pins removes the hassle of managing data across projects, colleagues, and teams by providing a central place for people to store, version and retrieve data. If you’ve ever chased a CSV through a series of email exchanges, or had to decide between data-final.csv and data-final-final.csv, then pins is for you. pins stores data on a board, which can be a local folder, or on RStudio Connect or a cloud provider like Amazon S3. Each ... Read More

Feed: R-bloggers. Author: R Views. [This article was first published on R Views, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. This post on R Views is about… Python! Surprising, I know. Python has several well-written packages for statistics and data science, but CRAN, R’s central repository, contains thousands of packages implementing sophisticated statistical algorithms that have been field-tested over many years. Thanks to the rpy2 package, Pythonistas can take advantage of the ... Read More

Feed: O'Reilly Media, Inc. Upcoming Titles. Author: O'Reilly Media, Inc.. Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.9 and pandas 1.2, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You'll learn the latest versions of pandas, NumPy, and Jupyter in the process.Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It's ideal for analysts new to Python ... Read More

Feed: SAS Blogs. Author: Sundaresh Sankaran. By Sundaresh Sankaran & Ali Aiello, Global Technology Practice, SAS Institute Many analytics developers prefer Python for its ease of use, versatility and community support. Acknowledging this from an early stage of Viya’s evolution, SAS has progressively provided access to Python from within its applications, the latest being SAS Studio. The Proc Python procedure, Python code editor & Python code step facilitate low-code analytics calling Python and SAS from a common interface. Data scientists also appreciate the connection to Python & R through the Model Studio Open-source Code node. Older methods of interaction include the swat and ... Read More