The simplest way to implement hard voting in Python is to use scikit-learn to create base learners, train them on some data, and combine their predictions on test data. In order to do so, we will go through the following steps:

1. Load the data and split it into train and test sets
2. Create some base learners
3. Train them on the train data
4. Produce predictions for the test data
5. Combine predictions using hard voting
6. Compare the individual learner's predictions as well as the combined predictions with the ground truth (actual correct classes)

Although scikit-learn has implementations for voting, by creating a custom implementation, it will be easier to understand how the algorithm works. Furthermore, it will enable us to better understand how to process and analyze a base learner's outputs.