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import os
import pandas as pd
import numpy as np
from scipy.interpolate import Rbf
from scipy.optimize import curve_fit
from scipy.stats import linregress
from datetime import timedelta
from sklearn.metrics import mean_squared_log_error
from sklearn.impute import SimpleImputer
from sklearn.ensemble import RandomForestRegressor
from sklearn.linear_model import ElasticNet
from sklearn.model_selection import GridSearchCV, KFold
from sklearn.preprocessing import OrdinalEncoder
import category_encoders as ce
import xgboost
from catboost import Pool, CatBoostRegressor
import matplotlib.pyplot as plt
plt.style.use('ggplot')
for dirname, _, filenames in os.walk('/kaggle/input'):
    for filename in filenames:
        print(os.path.join(dirname, filename))