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Exercise

Random row selection

In this exercise, you will compare the two methods described for selecting random rows (entries) with replacement in a pandas DataFrame:

  • The built-in pandas function .random()
  • The NumPy random integer number generator np.random.randint()

Generally, in the fields of statistics and machine learning, when we need to train an algorithm, we train the algorithm on the 75% of the available data and then test the performance on the remaining 25% of the data.

For this exercise, we will randomly sample the 75% percent of all the played poker hands available, using each of the above methods, and check which method is more efficient in terms of speed.

Instructions 1/3
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  • Randomly select 75% of the rows of the poker dataset using the np.random.randint() method.
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