Last edited : 4:20pm 5/18/2020
"""
from GetData import GetData
from Utility import Util
from Transform import Transform
import numpy as np
import seaborn as sn
import matplotlib.pyplot as plt
from sklearn import linear_model
from sklearn.model_selection import cross_val_score
#read config
config = Util.read_config()
#get data
df = GetData.read_csv(GetData, config['data']['FuelConsumption']['filepath'])
#get all numeric columns
cols_numeric = df.select_dtypes([np.number]).columns
#remove non-numeric columns
df = df[cols_numeric]
#find correlations between variables
corrMatrix = df.corr()
mask = np.zeros_like(corrMatrix)
mask[np.triu_indices_from(mask)] = True
with sn.axes_style("white"):
f, ax = plt.subplots(figsize=(7, 5))
sn.heatmap(corrMatrix,
vmin=-1,
vmax=1,
mask=mask,
annot=True,
