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from xgboost import XGBRegressor

from xgboost import plot_importance

from xgboost import plot_importance, plot_tree

import matplotlib.pyplot as plt

model2 = XGBRegressor(n_estimators=1000)
model2.fit(X_train, y_train[:, 1])

from xgboost import plot_importance
import matplotlib.pyplot as plt

def plot_features(booster, figsize):    
    fig, ax = plt.subplots(1,1,figsize=figsize)
    return plot_importance(booster=booster, ax=ax)

plot_features(model2, (10, 14))