Generators and data science

Question

How I can use generators in Data science, any examples?))

Answer 1

Great question! Generators are one of the most efficient ways you can manage resources. Generators "yield" results, which means the program will wait for the "next" command, and it will allow the processor and other resources to be used by other programs, until the "next" is called.
I wrote this a few days ago...Check Cell-15, its where I have the main function. The generator I wrote displays Covid data for each state.

https://www.kaggle.com/n3v375/covid-deadliest-states-and-counties

Answer 2

@Abdulkarim: Just putting this here for reference

https://docs.scipy.org/doc/scipy/reference/stats.html
https://docs.scipy.org/doc/numpy-1.13.0/reference/routines.random.html

Answer 3

@Steven: Great example and thanks for introducing kaggle!

Answer 4

Ockert van Schalkwyk Kaggle is great, lots of datasets to play with and learn Data Science & Machine Learning 👍👍