Pandas vs. dplyr It’s difficult to find the ultimate go-to library for data analysis. Both R and Python provide excellent options, so the question quickly becomes “which data analysis library...continue reading.
Exploratory Data Analysis With dplyr When it comes to data analysis in R, you should look no further than the dplyr package. It’s an excellent all-rounder – providing you with...continue reading.
Must-Have Skills for Data Science Everybody and their mother wants to learn data science. And there’s no reason not to – the job you do is interesting 95% of the...continue reading.
REST APIs with R and Plumber REST APIs are everywhere around us. Software engineers use them to develop backend logic, and data scientists use them to deploy machine learning models....continue reading.
Logistic Regression with R Logistic regression is one of the most fundamental algorithms from statistics, commonly used in machine learning. It’s not used to produce SOTA models but can serve...continue reading.
Datasets often require many work hours to understand fully. R makes this process as easy as possible through the dplyr package – the easiest solution for code-based data analysis. You’ll...continue reading.
Geo maps with R and Leaflet Data visualization can be tough to get right, and geospatial data is not an exception. Today you’ll learn how to build aesthetically pleasing interactive...continue reading.
Linear Regression with R Chances are you had some prior exposure to machine learning and statistics. Basically, that’s all linear regression is – a simple statistics problem. Need help with...continue reading.
Scatter Plots with R Do you want to make stunning visualizations, but they always end up looking like a potato? It’s a tough place to be. Luckily, R makes it...continue reading.
Line Charts with R Are your visualizations an eyesore? The 1990s are over, pal. Terrible-looking visualizations are no longer acceptable, no matter how useful they might otherwise be. Luckily, there’s...continue reading.
Python and Dash vs. R and Shiny Developing dashboards is no small task. You have to think about a vast amount of technical details and at the same time build...continue reading.
Bar Charts with R The language of data visualization is universal. Not everyone will recognize a great visualization, but everyone will remember a terrible one. If you use tools and...continue reading.
Introducing semantic.dashboard Dashboards allow you to structure reports intuitively and break them down into easy-to-read chunks. As a result, end-users can navigate and explore data much easier than with traditional...continue reading.
R is a programming language created by Ross Ihaka and Robert Gentleman in 1993. It was designed for analytics, statistics, and data visualizations. Nowadays, R can handle anything from basic...continue reading.
Business Intelligence (BI) is used to transform data into actionable insights that provide value to an organization and help achieve its business goals. Reports and dashboards are go-to approaches for...continue reading.
Basic Routing for Shiny Web Applications Web applications couldn’t exist without routing. Think about it in terms of the Appsilon website – you’ve visited our home page, navigated to the...continue reading.
tl;dr Choosing the appropriate dashboarding/reporting/BI tool has never harder than it is now, as there are plenty of genuinely great options such as R Shiny, PowerBI, and Tableau. Today we’ll...continue reading.
Rapid Multi-Language Support for Shiny Apps Have you ever created a multilingual Shiny application? Chances are the answer is yes, if you are a big fan of Appsilon‘s blog and have...continue reading.
tl;dr As of late 2020 there are many dashboarding/reporting/BI tools out there, with the most popular ones being Tableau, PowerBI, and R Shiny. The question quickly becomes – “How can I determine...continue reading.
Streamlit Tutorial: How to Deploy Streamlit Apps on RStudio Connect
February 25, 2022
