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q01_plot/build.py

@@ -1,8 +1,23 @@
 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')
 
-# Write your code here :
+def plot(num_cols):
+    for i in range(0,len(num_cols),2):
+        if len(num_cols) > i+1:
+            plt.figure(figsize=(10,4))
+            plt.subplot(121)
+            sns.distplot(data[num_cols[i]], kde=False)
+            plt.subplot(122)
+            sns.distplot(data[num_cols[i+1]], kde=False)
+            plt.tight_layout()
+            plt.show()
+
+        else:
+            sns.distplot(data[num_cols[i]], kde=False)  
+
+
+

q02_plot/build.py

@@ -1,11 +1,29 @@
+# %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:
+def plot(num_cols):
+    num_cols = ['LotArea', 'GarageArea', 'OpenPorchSF', 'SalePrice']
+    facet = None
+    for i in range(0,len(num_cols),2):
+        if len(num_cols) > i+1:
+            plt.figure(figsize=(10,4))
+            plt.subplot(121)
+            sns.boxplot(facet, num_cols[i],data = data)
+            plt.subplot(122)            
+            sns.boxplot(facet, num_cols[i+1],data = data)
+            plt.tight_layout()
+            plt.show()
+
+        else:
+            sns.boxplot(facet, num_cols[i],data = data)
+
+
+
 

q03_regression_plot/build.py

@@ -1,3 +1,4 @@
+# %load q03_regression_plot/build.py
 # Default imports
 
 import pandas as pd
@@ -6,10 +7,15 @@
 
 
 data = pd.read_csv('data/house_prices_multivariate.csv')
-plt.switch_backend('agg')
-
+variable1 = data['GrLivArea']
+variable2 = data['SalePrice']
 
 # Write your code here
+def regression_plot(variable1, variable2):
+    sns.scatterplot(variable1, variable2, data = data)
+    sns.lmplot(variable1, variable2, data= data, fit_reg=True)
+
+
 
 
 

q04_cor/build.py

@@ -1,10 +1,18 @@
+# %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')
 
 
 # Write your code here
+def cor(data):
+    cm = data.corr()
+    plt.figure(figsize=(10,6))
+    sns.heatmap(cm, annot=True)
+
+
+
+