text_plain_output_1.png
import os
import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)
warnings.filterwarnings('ignore')
def ignore_warn(*args, **kwargs):
    pass
warnings.warn = ignore_warn
import pandas as pd
import datetime
import math
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
import matplotlib.cm as cm
from pandasql import sqldf
pysqldf = lambda q: sqldf(q, globals())
import seaborn as sns
sns.set(style='ticks', color_codes=True, font_scale=1.5)
color = sns.color_palette()
sns.set_style('darkgrid')
from mpl_toolkits.mplot3d import Axes3D
import plotly as py
import plotly.graph_objs as go
py.offline.init_notebook_mode()
from scipy import stats
from scipy.stats import skew, norm, probplot, boxcox
from sklearn import preprocessing
import math
from sklearn.cluster import KMeans
from sklearn.metrics import silhouette_samples, silhouette_score
from sklearn.model_selection import train_test_split
from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import OneHotEncoder, StandardScaler
from sklearn.metrics import mean_squared_error
from sklearn.linear_model import LinearRegression
from sklearn.compose import make_column_transformer
from sklearn import set_config
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import classification_report
import seaborn as dg