Names features importance plot after preprocessing

Question

Before building a model I make scaling like this

X = StandardScaler(with_mean = 0, with_std = 1).fit_transform(X)

and after build a features importance plot

xgb.plot_importance(bst, color='red')
plt.title('importance', fontsize = 20)
plt.yticks(fontsize = 10)
plt.ylabel('features', fontsize = 20)

The problem is that instead of feature's names we get f0, f1, f2, f3 etc..... How to return feature's names?

thanks

Answer 1

first we get list of feature names before preprocessing

dtrain = xgb.DMatrix( X, label=y)
dtrain.feature_names

Then

bst.get_fscore()
mapper = {'f{0}'.format(i): v for i, v in enumerate(dtrain.feature_names)}
mapped = {mapper[k]: v for k, v in bst.get_fscore().items()}
mapped
xgb.plot_importance(mapped, color='red')

that's all