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q01_plot/build.py

@@ -1,8 +1,25 @@
+# %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')
+num_cols=['LotArea','GarageArea','OpenPorchSF','SalePrice']
 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()
+
+plot(num_cols)
+
+

q02_plot/build.py

@@ -1,11 +1,24 @@
+# %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')
+data = pd.read_csv('data/house_prices_multivariate.csv')
+num_cols = ['LotArea', 'GarageArea', 'OpenPorchSF', 'SalePrice']
+facet = None
+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.boxplot(facet, num_cols[i],data = data)
+            plt.subplot(122)            
+            sns.boxplot(facet, num_cols[i+1],data = data)
+            plt.tight_layout()
+            plt.show()
+plot(num_cols)
 
 
-# Write your code here:
 

q03_regression_plot/build.py

@@ -1,16 +1,18 @@
+# %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')
 plt.switch_backend('agg')
+data = pd.read_csv('data/house_prices_multivariate.csv')
 
 
-# Write your code here
-
+def regression_plot(variable1,variable2):
+    sns.lmplot(variable1, variable2, data=data, fit_reg=True)
+    plt.show()
 
+regression_plot('GrLivArea','SalePrice')
 
 

q04_cor/build.py

@@ -1,10 +1,15 @@
+# %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):
+    plt.figure(figsize = (8,5))
+    sns.heatmap(data.corr(),cmap='viridis')
+    plt.show()
 
 
-# Write your code here