diff --git a/q01_plot/build.py b/q01_plot/build.py
index 0425964..3d59649 100644
--- a/q01_plot/build.py
+++ b/q01_plot/build.py
@@ -1,8 +1,17 @@
+# %load q01_plot/build.py
+# Default imports
 import matplotlib.pyplot as plt
 import seaborn as sns
 import pandas as pd
 
 data = pd.read_csv('data/house_prices_multivariate.csv')
+
 plt.switch_backend('agg')
+def plot(num_cols):
+    for col in num_cols:
+        sns.distplot(data[col], kde=True)
+        plt.show()
+num_cols = ['LotArea', 'GarageArea', 'OpenPorchSF', 'SalePrice']
+plot(num_cols)
+
 
-# Write your code here :
diff --git a/q02_plot/build.py b/q02_plot/build.py
index 67b4924..68ee5b0 100644
--- a/q02_plot/build.py
+++ b/q02_plot/build.py
@@ -1,11 +1,20 @@
+# %load q02_plot/build.py
 # Default imports
 import pandas as pd
 import matplotlib.pyplot as plt
 import seaborn as sns
 
 data = pd.read_csv('data/house_prices_multivariate.csv')
-plt.switch_backend('agg')
 
 
 # Write your code here:
+plt.switch_backend('agg')
+def plot(num_cols):
+    for col in num_cols:
+        sns.boxplot(x=data[col])
+        plt.show()
+num_cols = ['LotArea', 'GarageArea', 'OpenPorchSF', 'SalePrice']
+plot(num_cols)
+
+
 
diff --git a/q03_regression_plot/build.py b/q03_regression_plot/build.py
index 2aaf8f6..bc5d932 100644
--- a/q03_regression_plot/build.py
+++ b/q03_regression_plot/build.py
@@ -1,3 +1,4 @@
+# %load q03_regression_plot/build.py
 # Default imports
 
 import pandas as pd
@@ -6,10 +7,16 @@
 
 
 data = pd.read_csv('data/house_prices_multivariate.csv')
-plt.switch_backend('agg')
 
 
 # Write your code here
+plt.switch_backend('agg')
+def regression_plot(variable1, variable2):
+    plot = sns.lmplot(variable1, variable2, data, fit_reg=True)
+    return plot
+regression_plot('SalePrice', 'GrLivArea')
+
+
 
 
 
diff --git a/q04_cor/build.py b/q04_cor/build.py
index f3fae50..ac413b0 100644
--- a/q04_cor/build.py
+++ b/q04_cor/build.py
@@ -1,10 +1,16 @@
+# %load q04_cor/build.py
 # Default imports
 import pandas as pd
 import matplotlib.pyplot as plt
 import seaborn as sns
 
 data = pd.read_csv('data/house_prices_multivariate.csv')
+
+
 plt.switch_backend('agg')
+def cor(data):
+    return sns.heatmap(data.corr())
+cor(data)
+
 
 
-# Write your code here