Installing Additional Packages
Cloudera Data Science Workbench engines are preloaded with a few common packages and libraries for R, Python, and Scala. However, a key feature of Cloudera Data Science Workbench is the ability of different projects to install and use libraries pinned to specific versions, just as you would on your local computer.
You can install additional libraries and packages from the workbench, using either the command prompt or the terminal. Alternatively, you might choose to use a package manager such as Conda to install and maintain packages and their dependencies. For some basic usage guidelines for Conda, see Using Conda with Cloudera Data Science Workbench.
- Navigate to your project's Overview page. Click New Session and start a session.
At the command prompt in the bottom right, enter the command to install the
package. Some examples using Python and R have been provided.
# Install from CRAN install.packages("ggplot2") # Install using devtools install.packages('devtools') library(devtools) install_github("hadley/ggplot2")Python 2
# Installing from console using ! shell operator and pip: !pip install beautifulsoup # Installing from terminal pip install beautifulsoupPython 3
# Installing from console using ! shell operator and pip3: !pip3 install beautifulsoup4 # Installing from terminal pip3 install beautifulsoup4