import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
from plotly.offline import init_notebook_mode, iplot
import plotly.graph_objs as go
from plotly import tools
import plotly.plotly as py
from datetime import date
import random
import warnings
import gc
import math
import xgboost as xgb
from catboost import CatBoostRegressor
from sklearn.model_selection import train_test_split
warnings.filterwarnings("ignore")
init_notebook_mode()
train_df = pd.read_csv("input/train.csv", parse_dates=["activation_date"])
pr_train = pd.read_csv("input/periods_train.csv",
parse_dates=["activation_date", "date_from", "date_to"])
pr_test = pd.read_csv("input/periods_test.csv",
parse_dates=["activation_date", "date_from", "date_to"])
test_df = pd.read_csv('input/test.csv', parse_dates=["activation_date"])