Tag: Library

Feed: Neo4j Graph Database Platform. Author: Enzo. We have added a new certification exam for Neo4j Graph Data Science on Neo4j GraphAcademy.There is a growing community of developers and data scientists who are using the Neo4j Graph Data Science Library to perform analysis of their graph data. The Neo4j Graph Data Science Library contains many graph algorithms that Neo4j provides full support for, as well as algorithms that are implemented, but not fully-supported (alpha/beta).You can become certified in Neo4j Graph Data Science to demonstrate to your colleagues you have this high-in-demand skill.About the ExamThe Neo4j Graph Data Science Certification exam ... Read More

Feed: R-bloggers. Author: Rstats on Jakub Nowosad's website. TLTR: Clustering similar spatial patterns requires one or more raster datasets for the same area. Input data is divided into many sub-areas, and spatial signatures are derived for each sub-area. Next, distances between signatures for each sub-area are calculated and stored in a distance matrix. The distance matrix can be used to create clusters of similar spatial patterns. Quality of clusters can be assessed visually using a pattern mosaic or with dedicated quality metrics. To reproduce the calculations in the following post, you need to download all of relevant datasets using the ... Read More

Feed: AWS Big Data Blog. Thousands of customers are building their data lakes on Amazon Simple Storage Service (Amazon S3). You can use AWS Lake Formation to build your data lakes easily—in a matter of days as opposed to months. However, there are still some difficult challenges to address with your data lakes: Supporting streaming updates and deletes in your data lakes, for example, database replication, and supporting privacy regulations such as GDPR and CCPA Achieving fine-grained secure sharing not only with table-level or column-level access control, but with row-level access control Optimizing the layout of various tables and files on ... Read More

Feed: R-bloggers. Author: Gary Hutson. I will take you through step by step how to use the data.table package, and compare it with base R operations, to see the performance gains you get when using this optimised package. Load in data.table To load the package in you can follow the below instructions: #install.packages(data.table) library(data.table) You should now have everything you need to start the tutorial. Reading in a data.table csv To read files in data.table you use the fread syntax to bring files in. I will load the NHSRDatasets package and export this out and then I will use the ... Read More

Feed: Microsoft Azure Blog. Author: Roanne Sones. In today’s fast-paced world, there is often a need for instantaneous, real-time responses. Companies are finding the computing needed to support this 24/7 mentality generates staggering amounts of data, often from devices out in the physical world. This influences a shift in priorities as companies look for technology that gives them the flexibility to innovate anywhere in their environment. The biggest trend: the evolution of cloud strategies to include edge and hybrid investments. This hybrid cloud journey gives companies the flexibility to easily handle future growth and technology needs. Add in the movement ... Read More

Feed: Planet PostgreSQL. 03 Mar 2021 Are you tired of this syntax in PostgreSQL? SELECT jsonb_column->'key' FROM table; UPDATE table SET jsonb_column = jsonb_set(jsonb_column, '{"key"}', '"value"'); The select part is actually fine. But for updates, especially for complex updates, it could be pretty verbose and far from being ergonomic. What would you say to this syntax instead? SELECT jsonb_column['key'] FROM table; UPDATE table SET jsonb_column['key'] = '"value"'; With subscripting it looks more concise and probably even familiar for developers due to its “pythonic” style. If you like this syntax more I have good news for you, recently a patch implementing ... Read More

Feed: R-bloggers. Author: Keith Goldfeld. [This article was first published on ouR data generation, 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. I’m preparing a lecture on simulation for a statistical modeling class, and I plan on describing a couple of cases where simulation is intrinsic to the analytic method rather than as a tool for exploration and planning. MCMC methods used for Bayesian estimation, bootstrapping, and randomization tests all come to mind ... Read More

Feed: R-bloggers. Author: Econometrics and Free Software. In this blog post, I want to discuss something that I, personally, have never seen discussed; how to create a “serverless” (or “shinyless” you could say) dashboard using R. I made one dashboard like that, which you can find here. This dashboard is running on a simple, standard web server. No Shiny involved! The idea is to create a dashboard with simple tables, graphs, and filters, to communicate results without the need for a Shiny server. The “dashboard” will be a simple html file that only needs a good old web server. Or ... Read More

Feed: R-bloggers. Author: R on Dominic Royé. [This article was first published on R on Dominic Royé, 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. A disadvantage of choropleth maps is that they tend to distort the relationship between the true underlying geography and the represented variable. It is because the administrative divisions do not usually coincide with the geographical reality where people live. Besides, large areas appear to have a weight that ... Read More

Feed: R-bloggers. Author: Andrew Treadway. Data exploration is an important part of the modeling process. It can also take up a fair amount of time. The awesome DataExplorer package in R aims to make this process easier. To get started with DataExplorer, you’ll need to install it like below: install.packages("DataExplorer") Let’s use DataExplorer to explore a dataset on diabetes. # load DataExplorer library(DataExplorer) # read in dataset diabetes_data Running the create_report line of code above will generate an HTML report file containing a collection of useful information about the data. This includes: Basic statistics, such as number of rows and ... Read More