import numpy as np # linear algebra import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv) import seaborn as sns from matplotlib import pyplot as plt from matplotlib import rcParams
import missingno as msno
#import ggplot import matplotlib.pyplot as plt %matplotlib inline
from sklearn.preprocessing import LabelEncoder import lightgbm as lgb from tqdm import tqdm from subprocess import check_output from time import gmtime, strftime import gc from sklearn.model_selection import (train_test_split, GridSearchCV) from sklearn.metrics import (roc_curve, auc, accuracy_score) from subprocess import check_output
library(reshape) library(reshape2) library(xgboost) library(caret) library(jsonlite) library(dplyr) library(Matrix) library(doParallel) library(lubridate)