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

**undefined XP**

- Randomly select 75% of the rows of the poker dataset using the
`np.random.randint()`

method.