# Import the necessary modules import numpy as np import pandas as pd from sklearn.linear_model import LogisticRegression # Read in the file fg_attempt.csv field_goal = pd.read_csv('fg_attempt.csv') # Create a dataframe X containing 'Distance' and 'ScoreDiffPreKick' X = # Your code here # Create a dataframe y containing 'Outcome' y = # Your code here # Flatten y into an array # Your code here # Initialize a LogisticRegression() model logisticModel = # Your code here # Fit the model # Your code here # Input feature values for a sample instance Distance = float(input()) ScoreDiffPreKick = float(input()) # Create a new dataframe with user-input Distance and ScoreDiffPreKick XNew = # Your code here # Predict the outcome from the new data pred = # Your code here print(pred) # Determine the accuracy of the model logisticModel score = # Your code here print(score)