Update dynamic_pricing.py

dynamic_pricing.py

@@ -13,8 +13,8 @@ import joblib
 import numpy as np
 import pandas as pd
 
-import matplotlib.pyplot as plt
-import seaborn as sns
+# import matplotlib.pyplot as plt
+# import seaborn as sns
 # %matplotlib inline
 
 from sklearn.model_selection import train_test_split
@@ -44,21 +44,21 @@ X_test = X_test.iloc[:, 3:]
 
 X_train.info
 
-plt.figure(figsize = (12, 8))
-plot = sns.countplot(x = 'day_of_week', data = X_train)
-plt.xticks(rotation = 90)
-for p in plot.patches:
-    plot.annotate(p.get_height(),
-                        (p.get_x() + p.get_width() / 2.0,
-                         p.get_height()),
-                        ha = 'center',
-                        va = 'center',
-                        xytext = (0, 5),
-                        textcoords = 'offset points')
-
-plt.title("Price changes based on day")
-plt.xlabel("Day")
-plt.ylabel("Price")
+# plt.figure(figsize = (12, 8))
+# plot = sns.countplot(x = 'day_of_week', data = X_train)
+# plt.xticks(rotation = 90)
+# for p in plot.patches:
+#     plot.annotate(p.get_height(),
+#                         (p.get_x() + p.get_width() / 2.0,
+#                          p.get_height()),
+#                         ha = 'center',
+#                         va = 'center',
+#                         xytext = (0, 5),
+#                         textcoords = 'offset points')
+
+# plt.title("Price changes based on day")
+# plt.xlabel("Day")
+# plt.ylabel("Price")
 
 print(sum(X_train["day_of_week"].isnull()))
 print(sum(X_test["day_of_week"].isnull()))