# %load q03_regression_plot/build.py
# Default imports

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt


data = pd.read_csv('data/house_prices_multivariate.csv')
var1=data['GrLivArea']
var2=data['SalePrice']

# Write your code here
def regression_plot (var1,var2):
    sns.lmplot(var1,var2,data=data,fit_reg=True)
    plt.tight_layout()
    plt.show()
    return regression_plot

#regression_plot ('GrLivArea','SalePrice')

02d308611bc6fad6e0b7df5ef1e3965d9cf9902e
<mask token>

<mask token>


def regression_plot(var1, var2):
    sns.lmplot(var1, var2, data=data, fit_reg=True)
    plt.tight_layout()
    plt.show()
    return regression_plot

<mask token>
data = pd.read_csv('data/house_prices_multivariate.csv')
var1 = data['GrLivArea']
var2 = data['SalePrice']


def regression_plot(var1, var2):
    sns.lmplot(var1, var2, data=data, fit_reg=True)
    plt.tight_layout()
    plt.show()
    return regression_plot

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
data = pd.read_csv('data/house_prices_multivariate.csv')
var1 = data['GrLivArea']
var2 = data['SalePrice']


def regression_plot(var1, var2):
    sns.lmplot(var1, var2, data=data, fit_reg=True)
    plt.tight_layout()
    plt.show()
    return regression_plot

# %load q03_regression_plot/build.py
# Default imports

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt


data = pd.read_csv('data/house_prices_multivariate.csv')
var1=data['GrLivArea']
var2=data['SalePrice']

# Write your code here
def regression_plot (var1,var2):
    sns.lmplot(var1,var2,data=data,fit_reg=True)
    plt.tight_layout()
    plt.show()
    return regression_plot

#regression_plot ('GrLivArea','SalePrice')
