Steven, A more practical answer about splitting a data frame is to import modules such as for machine learning.
Import sklearn.model_selection Then use train_test_split() to return 4 parts. Not sure what answers you need and why here. Plenty of ways and tools exist to specify choosing percentages to partition by or other ways. Sent from AOL Mobile Mail On Saturday, December 29, 2018 Avi Gross <avigr...@verizon.net> wrote: Steven, As I head out the door, I will sketch it. Given a data.frame populated with N rows and columns you want to break it into training and test data sets. In a data.frame, you can refer to a row by using an index like 5 or 2019. You can ask for the number of rows currently in existence. You can also create an array/vector of length N consisting of instructions that can tell which random rows of the N you want and which you don't. For the purposes of this task, you choose random numbers in the range of N and either keep the numbers as indices or as a way to mark True/False in the vector. You then ask for a new data.frame made by indexing the existing one using the vector. You can then negate the vector and ask for a second new data.frame indexing it. Something close to that. Or, you can simply add the vector as a new column in the data.frame in some form. It would then mark which rows are to be used for which purpose. Later, when using the data, you include a CONDITION that row X is true, or whatever. -----Original Message----- From: Tutor <tutor-bounces+avigross=verizon....@python.org> On Behalf Of Steven D'Aprano Sent: Friday, December 28, 2018 11:12 PM To: tutor@python.org Subject: Re: [Tutor] decomposing a problem On Fri, Dec 28, 2018 at 10:39:53PM -0500, Avi Gross wrote: > I will answer this question then head off on vacation. You wrote about 140 or more lines, but didn't come close to answering the question: how to randomly split data from a dictionary into training data and reserved data. -- Steve _______________________________________________ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor _______________________________________________ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor _______________________________________________ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
