From e8c7e239d8238b18c9ab3461a2e18cb81befafb4 Mon Sep 17 00:00:00 2001
From: Yanchong Xu <60683403+yx-xyc@users.noreply.github.com>
Date: Wed, 13 Jan 2021 16:10:05 +0800
Subject: [PATCH] Update Day 1_Data_Preprocessing.py

On line 20, the input of missing_value should be np.nan. This is the default of this function in the newest version of sklearn.
---
 Code/Day 1_Data_Preprocessing.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Code/Day 1_Data_Preprocessing.py b/Code/Day 1_Data_Preprocessing.py
index d81deb2..a6c8ed3 100644
--- a/Code/Day 1_Data_Preprocessing.py	
+++ b/Code/Day 1_Data_Preprocessing.py	
@@ -17,7 +17,7 @@ print(Y)
 #Step 3: Handling the missing data
 # If you use the newest version of sklearn, use the lines of code commented out
 # from sklearn.impute import SimpleImputer
-# imputer = SimpleImputer(missing_values="NaN", strategy="mean")
+# imputer = SimpleImputer(missing_values=np.nan, strategy="mean")
 from sklearn.preprocessing import Imputer
 imputer = Imputer(missing_values = "NaN", strategy = "mean", axis = 0)
 imputer = imputer.fit(X[ : , 1:3])