From 5680d2dc40fb45a7fba54b24e043e8827e2f4071 Mon Sep 17 00:00:00 2001
From: preetiail <ailpreeti@ymail.com>
Date: Tue, 20 Nov 2018 03:23:08 +0000
Subject: [PATCH 1/5] Done

---
 __pycache__/__init__.cpython-36.pyc              | Bin 0 -> 153 bytes
 .../__pycache__/__init__.cpython-36.pyc          | Bin 0 -> 171 bytes
 .../__pycache__/build.cpython-36.pyc             | Bin 0 -> 660 bytes
 q01_missing_value/build.py                       |  10 +++++++++-
 .../tests/__pycache__/__init__.cpython-36.pyc    | Bin 0 -> 177 bytes
 .../test_q01_imputation.cpython-36.pyc           | Bin 0 -> 2326 bytes
 6 files changed, 9 insertions(+), 1 deletion(-)
 create mode 100644 __pycache__/__init__.cpython-36.pyc
 create mode 100644 q01_missing_value/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q01_missing_value/__pycache__/build.cpython-36.pyc
 create mode 100644 q01_missing_value/tests/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q01_missing_value/tests/__pycache__/test_q01_imputation.cpython-36.pyc

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diff --git a/q01_missing_value/build.py b/q01_missing_value/build.py
index 7dc4d18..0caeecf 100644
--- a/q01_missing_value/build.py
+++ b/q01_missing_value/build.py
@@ -1,3 +1,4 @@
+# %load q01_missing_value/build.py
 # Default imports
 import pandas as pd
 
@@ -5,6 +6,13 @@
 ny_housing = pd.read_csv('data/train.csv')
 # Selecting 4 most relevant variables along with target variable from the dataset fot the Cleaning and Preprocessing.
 housing_data = ny_housing[['MasVnrArea', 'GrLivArea', 'LotShape', 'GarageType', 'SalePrice']]
+def imputation(housing_data):
+    housing_data1=housing_data.loc[:,['MasVnrArea', 'GrLivArea']]
+    total =housing_data1.loc[:,['MasVnrArea','GrLivArea']].notnull()
+    total1 =total.notna()
+    housing_data2=housing_data.loc[:,['LotShape', 'GarageType']]
+    total2=housing_data2.loc[:,['LotShape', 'GarageType']].notnull()
+    total3 =total2.notna()
+    return(total1,total3)
 
 
-# Write your code here:
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From 4ea7419b247323a9d15636ce35ed8b4345c33051 Mon Sep 17 00:00:00 2001
From: preetiail <ailpreeti@ymail.com>
Date: Sun, 25 Nov 2018 18:09:59 +0000
Subject: [PATCH 2/5] Done

---
 .../__pycache__/__init__.cpython-36.pyc          | Bin 0 -> 173 bytes
 .../__pycache__/build.cpython-36.pyc             | Bin 0 -> 770 bytes
 q02_outlier_removal/build.py                     |  15 +++++++++++++--
 .../tests/__pycache__/__init__.cpython-36.pyc    | Bin 0 -> 179 bytes
 .../test_q02_outlier_removal.cpython-36.pyc      | Bin 0 -> 1789 bytes
 5 files changed, 13 insertions(+), 2 deletions(-)
 create mode 100644 q02_outlier_removal/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q02_outlier_removal/__pycache__/build.cpython-36.pyc
 create mode 100644 q02_outlier_removal/tests/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q02_outlier_removal/tests/__pycache__/test_q02_outlier_removal.cpython-36.pyc

diff --git a/q02_outlier_removal/__pycache__/__init__.cpython-36.pyc b/q02_outlier_removal/__pycache__/__init__.cpython-36.pyc
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diff --git a/q02_outlier_removal/__pycache__/build.cpython-36.pyc b/q02_outlier_removal/__pycache__/build.cpython-36.pyc
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diff --git a/q02_outlier_removal/build.py b/q02_outlier_removal/build.py
index 74df5f2..b8a9301 100644
--- a/q02_outlier_removal/build.py
+++ b/q02_outlier_removal/build.py
@@ -1,10 +1,21 @@
+# %load q02_outlier_removal/build.py
 # Default imports
+import matplotlib.pyplot as plt
+import seaborn as sns
 import pandas as pd
-
+import numpy as np
 # Data
 ny_housing = pd.read_csv('data/train.csv')
 # Selecting 4 most relevant variables from the dataset fot the Cleaning and Preprocessing.
 housing_data = ny_housing[['MasVnrArea', 'GrLivArea', 'LotShape', 'GarageType', 'SalePrice']]
+#housing_data.describe()
+def outlier_removal(housing_data):
+    housing_data1=housing_data[housing_data.loc[:,['MasVnrArea','GrLivArea','LotShape','GarageType','SalePrice']].notnull()]
+    housing_data1=housing_data1.dropna()
+    housing_data2=housing_data1.sort_values(['MasVnrArea', 'GrLivArea','SalePrice'])
+    upper_quartile = np.percentile(housing_data2['SalePrice'],95)
+    h2=(housing_data2[housing_data2['SalePrice']<upper_quartile])
+    return(h2)
 
+outlier_removal(housing_data)
 
-# Write your code here:
diff --git a/q02_outlier_removal/tests/__pycache__/__init__.cpython-36.pyc b/q02_outlier_removal/tests/__pycache__/__init__.cpython-36.pyc
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From 292a1d5670dcffaa93d653227978e2b60d333e94 Mon Sep 17 00:00:00 2001
From: preetiail <ailpreeti@ymail.com>
Date: Tue, 27 Nov 2018 16:49:12 +0000
Subject: [PATCH 3/5] Done

---
 .../__pycache__/__init__.cpython-36.pyc          | Bin 0 -> 170 bytes
 .../__pycache__/build.cpython-36.pyc             | Bin 0 -> 531 bytes
 q03_skewness_log/build.py                        |   9 +++++++--
 .../tests/__pycache__/__init__.cpython-36.pyc    | Bin 0 -> 176 bytes
 .../test_q03_skewness_log.cpython-36.pyc         | Bin 0 -> 2201 bytes
 5 files changed, 7 insertions(+), 2 deletions(-)
 create mode 100644 q03_skewness_log/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q03_skewness_log/__pycache__/build.cpython-36.pyc
 create mode 100644 q03_skewness_log/tests/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q03_skewness_log/tests/__pycache__/test_q03_skewness_log.cpython-36.pyc

diff --git a/q03_skewness_log/__pycache__/__init__.cpython-36.pyc b/q03_skewness_log/__pycache__/__init__.cpython-36.pyc
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diff --git a/q03_skewness_log/__pycache__/build.cpython-36.pyc b/q03_skewness_log/__pycache__/build.cpython-36.pyc
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diff --git a/q03_skewness_log/build.py b/q03_skewness_log/build.py
index f008d0f..aa1f074 100644
--- a/q03_skewness_log/build.py
+++ b/q03_skewness_log/build.py
@@ -1,8 +1,13 @@
+# %load q03_skewness_log/build.py
 from scipy.stats import skew
 import pandas as pd
 import numpy as np
 
 data = pd.read_csv('data/train.csv')
+def skewness_log(data): 
+    data_trans=data.copy()
+    data_trans['GrLivArea']=np.log(data_trans['GrLivArea'])
+    data_trans['SalePrice']=np.log(data_trans['SalePrice'])
+    return(skew(data_trans['GrLivArea']),skew(data_trans['SalePrice']))
+skewness_log(data)
 
-
-# Write code here:
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From 1bea9d109bd014e5ba182874dbb34254522d3513 Mon Sep 17 00:00:00 2001
From: preetiail <ailpreeti@ymail.com>
Date: Tue, 27 Nov 2018 16:53:10 +0000
Subject: [PATCH 4/5] Done

---
 .../__pycache__/__init__.cpython-36.pyc          | Bin 0 -> 171 bytes
 .../__pycache__/build.cpython-36.pyc             | Bin 0 -> 558 bytes
 q03_skewness_sqrt/build.py                       |   9 ++++++++-
 .../tests/__pycache__/__init__.cpython-36.pyc    | Bin 0 -> 177 bytes
 .../test-q03_skewness_sqrt.cpython-36.pyc        | Bin 0 -> 2072 bytes
 5 files changed, 8 insertions(+), 1 deletion(-)
 create mode 100644 q03_skewness_sqrt/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q03_skewness_sqrt/__pycache__/build.cpython-36.pyc
 create mode 100644 q03_skewness_sqrt/tests/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q03_skewness_sqrt/tests/__pycache__/test-q03_skewness_sqrt.cpython-36.pyc

diff --git a/q03_skewness_sqrt/__pycache__/__init__.cpython-36.pyc b/q03_skewness_sqrt/__pycache__/__init__.cpython-36.pyc
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diff --git a/q03_skewness_sqrt/build.py b/q03_skewness_sqrt/build.py
index 4bdb0e4..3e29976 100644
--- a/q03_skewness_sqrt/build.py
+++ b/q03_skewness_sqrt/build.py
@@ -1,3 +1,4 @@
+# %load q03_skewness_sqrt/build.py
 # Default imports
 from scipy.stats import skew
 import pandas as pd
@@ -5,6 +6,12 @@
 
 ny_housing = pd.read_csv('data/train.csv')
 
+data = pd.read_csv('data/train.csv')
+def skewness_sqrt(data): 
+    data_trans=data.copy()
+    data_trans['GrLivArea']=np.sqrt(data_trans['GrLivArea'])
+    data_trans['SalePrice']=np.sqrt(data_trans['SalePrice'])
+    return(skew(data_trans['GrLivArea']),skew(data_trans['SalePrice']))
+skewness_sqrt(data)
 
-# Write your Solution Here:
 
diff --git a/q03_skewness_sqrt/tests/__pycache__/__init__.cpython-36.pyc b/q03_skewness_sqrt/tests/__pycache__/__init__.cpython-36.pyc
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From 1a975df4e22e3d6d1152128b064aabc8b2fd16c3 Mon Sep 17 00:00:00 2001
From: preetiail <ailpreeti@ymail.com>
Date: Sun, 2 Dec 2018 06:05:50 +0000
Subject: [PATCH 5/5] Done

---
 q04_encoding/__pycache__/__init__.cpython-36.pyc | Bin 0 -> 166 bytes
 q04_encoding/__pycache__/build.cpython-36.pyc    | Bin 0 -> 745 bytes
 q04_encoding/build.py                            |  11 +++++++++--
 .../tests/__pycache__/__init__.cpython-36.pyc    | Bin 0 -> 172 bytes
 .../__pycache__/test_q04_encoding.cpython-36.pyc | Bin 0 -> 1730 bytes
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 create mode 100644 q04_encoding/__pycache__/build.cpython-36.pyc
 create mode 100644 q04_encoding/tests/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q04_encoding/tests/__pycache__/test_q04_encoding.cpython-36.pyc

diff --git a/q04_encoding/__pycache__/__init__.cpython-36.pyc b/q04_encoding/__pycache__/__init__.cpython-36.pyc
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diff --git a/q04_encoding/build.py b/q04_encoding/build.py
index a52c57f..6eb1f96 100644
--- a/q04_encoding/build.py
+++ b/q04_encoding/build.py
@@ -1,3 +1,4 @@
+# %load q04_encoding/build.py
 # Default imports
 import pandas as pd
 from sklearn.preprocessing import LabelEncoder
@@ -5,6 +6,12 @@
 ny_housing = pd.read_csv('data/train.csv')
 housing_data = ny_housing[['MasVnrArea', 'GrLivArea', 'LotShape', 'GarageType', 'SalePrice']]
 
-
-# Write your code here:
+def encoding(housing_data):
+    total12=housing_data[housing_data.notnull()]
+    le = LabelEncoder()
+    #total12['GarageType_label']=total12['GarageType'].fillna('null')
+    total12=pd.concat([total12,pd.get_dummies(total12['GarageType'],prefix=['GarageType_Label'],dummy_na=False,drop_first=False)],axis=1).drop('GarageType',1)
+    total12['LotShape_label']=le.fit_transform(total12['LotShape'])
+    return(total12)
+encoding(housing_data)
 
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