JuICe: A Large Scale Distantly Supervised Datasetfor Open Domain Context-based Code Generation
Table 4: JuICe includes code for various real world applications, primarily for data science/machine learning.
['Code Type', '%']
Majority of code cells are geared towards data science applications. The Data Exploration category covers scenarios for computing statistics or queries to gain new insights about the data, and the Machine Learning category covers training models, as well as tensor operations. 13% of code cells are used for plotting figures and the Miscellaneous category covers a broad range of utility functions.