# Relationship between correlations and model coefficients

I have done a machine learning regression task. I am confused by the correlations and regression coefficient. The correlations of the datasets are depicted using seaborn library heatmap:

sns.heatmap(usa_housing_price.corr(), annot=True, cmap='coolwarm')


The result is:

The regression coefficients are as follows:

coef = pd.DataFrame(linear_model.coef_, X.columns)
coef.columns = ['Coefficients']
coef


The coefficients are:

My question is despite the "Avg. Area Income" is the most correlated feature with the "Price", it has less impact on "Price" in compare of other features?
How this tow parameter related to each other?

• DId you scale the predictor variables before fitting? – user0 Aug 6 '18 at 10:56
• No, I didn't scale them. – Ali Majed HA Aug 6 '18 at 12:26