application_vnd.jupyter.stderr_output_1.png
import matplotlib.pyplot as plt

import pandas as pd

import seaborn as sb

df = pd.read_csv('../input/kc_house_data.csv')

#df correlation matrix
f,ax = plt.subplots(figsize=(12, 9))
sb.heatmap(df.corr(), annot=True, linewidths=.5, fmt='.1f', ax=ax)

var = 'sqft_living'
data = pd.concat([df['price'], df[var]], axis=1)

var1 = 'grade'
data = pd.concat([df['price'], df[var1]], axis=1)
f, ax = plt.subplots(figsize=(8, 6))
fig = sb.boxplot(x=var1, y='price', data=data)
fig.axis(ymin=0, ymax=8000000)