Creating Seaborn Plots With R

Abdul Majed Raja shows how to call Python from R and build plots using the Seaborn Python package:

The reticulate package provides a comprehensive set of tools for interoperability between Python and R. The package includes facilities for:

  • Calling Python from R in a variety of ways including R Markdown, sourcing Python scripts, importing Python modules, and using Python interactively within an R session.
  • Translation between R and Python objects (for example, between R and Pandas data frames, or between R matrices and NumPy arrays).
  • Flexible binding to different versions of Python including virtual environments and Conda environments.

Reticulate embeds a Python session within your R session, enabling seamless, high-performance interoperability.

The more common use of reticulate I’ve seen is running TensorFlow neural networks from R.

Related Posts

Combining Keras With Apache MXNet

Lai Wei, et al, show how to build a neural network in Keras 2 using MXNet as the engine: Distributed training with Keras 2 and MXNet This article shows how to install Keras-MXNet and demonstrates how to train a CNN and an RNN. If you tried distributed training with other deep learning engines before, you […]

Read More

Principal Component Analysis With Stack Overflow Data

Julia Silge explains Principal Component Analysis and shows us an example using Stack Overflow data: We have tidy data, both because that’s what I get when querying our databases and because it is useful for exploratory data analysis when preparing for a machine learning algorithm like PCA. To implement PCA, we need a matrix, and […]

Read More

Categories

April 2018
MTWTFSS
« Mar May »
 1
2345678
9101112131415
16171819202122
23242526272829
30