!pip install seaborn==0.11.0
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sn
def load_dataset(path):
dataset = pd.read_csv(path, header=0, delimiter=',')
return dataset
train_dataset = load_dataset("train.csv")
test_dataset = load_dataset('test.csv')
x_train = train_dataset.drop("price_range", axis="columns").to_numpy()
y_train = train_dataset["price_range"].to_numpy()
train_dataset
test_dataset
for i,j in zip(train_dataset.columns,train_dataset.dtypes):
print(i,":",j)
print("Number of attributes = %d" %train_dataset.columns.size)
corrMatrix = train_dataset.corr()
sn.heatmap(corrMatrix, annot=True)
plt.show()
