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q01_plot/build.py

@@ -1,8 +1,21 @@
+# %load q01_plot/build.py
+# Default imports
 import matplotlib.pyplot as plt
 import seaborn as sns
 import pandas as pd
-
+import numpy as np
 data = pd.read_csv('data/house_prices_multivariate.csv')
-plt.switch_backend('agg')
 
-# Write your code here :
+# Write your code here:
+def plot(num_cols):
+    num_cols=[data['LotArea'],data['GarageArea'],data['OpenPorchSF'],data['SalePrice']]
+    Plot=plt.hist(num_cols, bins=50, alpha=0.5, label=['LotArea','GarageArea','OpenPorchSF','SalePrice'])
+
+    plt.legend(loc='upper right')
+
+
+    return Plot
+
+
+
+

q02_plot/build.py

@@ -1,11 +1,17 @@
+# %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=[data['LotArea'],data['GarageArea'],data['OpenPorchSF'],data['SalePrice']]
+    Plot=plt.boxplot(num_cols)
+    return Plot
+
+
 

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
+def regression_plot(variable1,variable2):
+    variable1=data.loc[:,'SalePrice']
+
+    variable2=data.loc[:,'GrLivArea']
+    Plot=plt.scatter(variable1,variable2)
+    return Plot
+
 
 
 

q04_cor/build.py

@@ -1,10 +1,19 @@
+# %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):
+    corr = data.corr()
+
+
+    Plot=sns.heatmap(corr,xticklabels=corr.columns,yticklabels=corr.columns)
+    return Plot
+
+
+