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q01_plot/build.py

@@ -1,8 +1,18 @@
+# %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')
 
-# Write your code here :
+# Write your code here:
+
+listie = [data.LotArea,data.GarageArea,data.OpenPorchSF, data.SalePrice]
+def plot(num_cols):
+    sns.set()
+    ax = sns.displot(num_cols)
+return ax
+
+
+

q02_plot/build.py

@@ -1,11 +1,18 @@
+# %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:
+listie = [data.LotArea, data.GarageArea, data.OpenPorchSF, data.SalePrice]
+def plot(num_cols):
+    plt.rcParams['figure.figsize'] = (23,10)
+    bx = sns.boxplot(x = num_cols , y = 'SalePrice', data = data)
+    return bx
+
+
 

q03_regression_plot/build.py

@@ -1,3 +1,4 @@
+# %load q03_regression_plot/build.py
 # Default imports
 
 import pandas as pd
@@ -6,11 +7,21 @@
 
 
 data = pd.read_csv('data/house_prices_multivariate.csv')
-plt.switch_backend('agg')
 
 
 # Write your code here
 
+X = data.GrLivArea
+Y = data.SalePrice
+def regression_plot(X, Y):
+    sns.set(color_codes=True)
+    tips = sns.load_dataset(data)
+    ax = sns.regplot(x=X, y=Y, data=tips)
+    return ax
+
+
+
+
 
 
 

q04_cor/build.py

@@ -1,10 +1,20 @@
+# %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.values,
+            yticklabels=corr.columns.values)
+    return plot
+
+
+
+