Codecademy export

script.py

import codecademylib3_seaborn
import matplotlib.pyplot as plt
from sklearn.svm import SVC
from sklearn.model_selection import train_test_split
from svm_visualization import draw_boundary
from players import aaron_judge, jose_altuve, david_ortiz

fig, ax = plt.subplots()
def find_strike_zone(data_set):
  data_set['type'] = data_set['type'].map({'S':1, 'B':2})
  
  data_set = data_set.dropna(subset = ['plate_x', 'plate_z', 'type'])

  #print(aaron_judge.columns)
  #print(aaron_judge.description.unique())
  #print(aaron_judge.type.unique())
  #print(aaron_judge['plate_x'])
  #print(aaron_judge['plate_z'])

  plt.scatter(x = data_set['plate_x'], 
              y = data_set['plate_z'], 
              c = data_set.type, 
              cmap = plt.cm.coolwarm, 
              alpha = 0.25)

  training_set, validation_set = train_test_split(data_set, random_state=1)

  classifier = SVC(kernel = 'rbf', gamma=3, C=1)
  classifier.fit(training_set[['plate_x', 'plate_z']],
training_set.type
) 
  score = classifier.score(validation_set[['plate_x', 'plate_z']], validation_set.type)

  print(score)

  draw_boundary(ax, classifier)
  ax.set_ylim(-2, 6)
  ax.set_xlim(-3, 3)
  plt.show()

find_strike_zone(aaron_judge)
find_strike_zone(jose_altuve)
find_strike_zone(david_ortiz)