Well Suited for Data Visualization and Modeling
Updated September 02, 2021
Well Suited for Data Visualization and Modeling
Score 10 out of 10
Vetted Review
Verified User
Overall Satisfaction with RStudio
We use RStudio as an GUI interface for R, which we use to visualize and model data. For modeling data, we use lots of machine learning techniques like Regression, and R provides an excellent package to implement various flavors of regression like lasso and ridge regression. For data visualization we also use Shiny apps.
- Debugging
- Front-end interface to R
- Provide shortcuts to some R commands
- RStudio connect experience was not very smooth
- Web service configuration for the RStudio server is not very intuitive
- Some Visual DataGrid GUI would be beneficial
- Web service configuration
- RStudio connect interface is not easily configurable
- No widows server option for R Connect server, so IT department needs to be familiar with Linux server administration
JMP is more customizable. It also has very good drag and drop graphing capabilities, which are not present in RStudio. Data exploration is much more convenient with JMP. However, the analysis work is better with RStudio since it is a bit hard to tweak the JMP built-in models.
Using RStudio
7 - Write R scripts for machine learning and data visualization . Data visualization is used for control charting and monitor production yield. It is also used to follow up on debugging other manufacturing issues by using data visualization. Machine learning is used to create statistical models for the products that are used to convert raw data to a format understood by the relevant clients.
2 - R syntax knowledge is the most important skill needed to use RStudio. In addition these people are also capable with configuring the R compiler in a Windows environment. One of them is also knowledgeable with RStudio web version which is available with the Pro version of R studio. Network configuartion knowledge is helpful in this area.
- Statistical modeling
- Data visualization
- Yield monitoring
- Use RStudio to create web based reports.
- Write script in RStudio and call it from JMP software environment.
- Use RStudio for Python integration
- Develop shiny apps using R studio to create interactive apps.
- Use RStudio debug functionalities to root out bugs.
- Use Rstudio as as IDE.