Tech | Use Different Languages in One Jupyter Notebook: Python, R and Julia
date
Sep 25, 2024
slug
all-languages-for-data-analysis-in-one-notebook-python-r-and-julia
status
Published
summary
Integrate Python, R, and Julia in a single Jupyter Notebook for efficient data analysis by using Julia for fast data preparation, Python for machine learning, and R for visualization with ggplot2. Ensure all necessary kernels and libraries are installed for seamless operation.
tags
Data Analysis
Python
ML
type
Post
I recently faced an efficiency challenge in my data analysis pipeline: Python and R were too slow, even with parallelization. To address this, I began learning Julia.
Surprisingly, I discovered a method to integrate all major data analysis languages in a single notebook. Now we can seamlessly combine machine learning (in Python), fast data preparation (using Julia), and result visualization with
ggplot2 (supported in R).Prerequisites
- Python, R, Julia installed
- Jupyter Notebook installed
- Install Julia kernel:
- Enter Julia REPL
- For example, we want to add a Julia kernel in Jupyter using multi-threads:
installkernel("Julia (4 threads)", env=Dict("JULIA_NUM_THREADS"=>"4"))
- Install
PyCallandRCallin Julia
Usage
- Then write jupyter notebooks as
Result
Alternative
- 2Sigma, BeakerX, https://github.com/twosigma/beakerx