Skills data join requirements
Development Environment Setup
For performing data joins and analyses, this tutorial covers example scripts in both the R and Python analysis environments. Here are the pre-requisites for them respectively:
Option 1: R Environment
To run the R code in this tutorial, you must have R and ideally a code editor installed:
- Install R: Download from https://cran.r-project.org/
- Install RStudio (recommended): Download from https://www.rstudio.com/. Alternatively, you may choose to use Visual Studio Code as your IDE.
Required R Packages:
The next step is to install the required R packages:
- vivainsights: Microsoft’s R package for Viva Insights analysis
- tidyverse: Collection of R packages for data science
- here: Easy file path management
If these are not already installed, you can install them in R with:
install.packages(c("vivainsights", "tidyverse", "here"))
Option 2: Python Environment
To run the Python code in this tutorial, you must have Python and ideally a code editor installed:
- Install Python: Download from https://www.python.org/downloads/ or use Anaconda
- Install Jupyter (recommended): Comes with Anaconda or install via
pip install jupyter. Alternatively, you may choose to use Visual Studio Code as your IDE.
Required Python Packages:
Ensure that you have the following python packages installed:
- vivainsights: Microsoft’s Python package for Viva Insights analysis
- pandas: Data manipulation and analysis library
- numpy: Fundamental package for scientific computing
- plotly: Interactive visualization library
- scipy: Scientific computing tools
If not, you can install them in the Command Prompt with:
pip install vivainsights pandas numpy plotly scipy
Once the developer pre-requisites are satisfied, see how to load and join data.