Commit Live PR

q01_plot/build.py

@@ -1,8 +1,26 @@
+# %load q01_plot/build.py
+
 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:
+num_cols = ['LotArea', 'GarageArea', 'OpenPorchSF', 'SalePrice']
+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)
+
+
+
 
-# Write your code here :

q02_plot/build.py

@@ -1,11 +1,23 @@
+# %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')
-
 
+num_cols = ['LotArea','GarageArea','OpenPorchSF','SalePrice']
 # Write your code here:
+# %matplotlib inline
+
+def plot(num_cols):
+
+    f, axs = plt.subplots(2, 2, figsize=(7, 7), sharex=False)
+    sns.boxplot(data['LotArea'],ax= axs[0,0])
+    sns.boxplot(data['GarageArea'],ax=axs[0,1])
+    sns.boxplot(data['OpenPorchSF'],ax=axs[1,0])
+    sns.boxplot(data['SalePrice'],ax=axs[1,1])
+
+
+
 

q03_regression_plot/build.py

@@ -1,3 +1,4 @@
+# %load q03_regression_plot/build.py
 # Default imports
 
 import pandas as pd
@@ -6,10 +7,13 @@
 
 
 data = pd.read_csv('data/house_prices_multivariate.csv')
-plt.switch_backend('agg')
 
 
 # Write your code here
+def regression_plot(variable1,variable2):
+    return sns.lmplot(variable1, variable2, data=data, fit_reg=True)
+
+
 
 
 

q04_cor/build.py

@@ -1,10 +1,17 @@
+# %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):
+    return sns.heatmap(data.corr(), cmap='viridis')
+
+
+
+
+