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for i in range ( size ) : bs _ inds = np . random.choice ( inds , size = len ( inds ) )

for i in range(size):
bs_inds = np.random.choice(inds, size=len(inds))
bs_genre = gross['genre'][bs_inds]
bs_gross = gross['inflation_adjusted_gross'][bs_inds]
bs_dummies = pd.get_dummies(bs_genre)
regr = LinearRegression().fit(bs_dummies, bs_gross)
bs_action_reps[i]= regr.intercept_
bs_adventure_reps[i]= regr.coef_[[0]][0]
# Given the above code, compute 95% confidence intervals for intercept and coefficient values
confidence_interval_action = #CODE HERE
confidence_interval_adventure =. #CODE HERE
# Inspect the confidence intervals
print(confidence_interval_action)
print(confidence_interval_adventure)

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