From 730305151f047376f3ec26ab3f9dada26cf43ab8 Mon Sep 17 00:00:00 2001
From: sannidh <soniknitr@gmail.com>
Date: Sat, 3 Nov 2018 01:05:52 +0000
Subject: [PATCH 1/5] Done

---
 __pycache__/__init__.cpython-36.pyc           | Bin 0 -> 151 bytes
 .../__pycache__/__init__.cpython-36.pyc       | Bin 0 -> 169 bytes
 .../__pycache__/build.cpython-36.pyc          | Bin 0 -> 1101 bytes
 q01_missing_value/build.py                    |  19 ++++++++++++++++--
 .../tests/__pycache__/__init__.cpython-36.pyc | Bin 0 -> 175 bytes
 .../test_q01_imputation.cpython-36.pyc        | Bin 0 -> 2324 bytes
 6 files changed, 17 insertions(+), 2 deletions(-)
 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..6100490 100644
--- a/q01_missing_value/build.py
+++ b/q01_missing_value/build.py
@@ -1,10 +1,25 @@
+# %load q01_missing_value/build.py
 # Default imports
 import pandas as pd
-
+from sklearn.preprocessing import Imputer
 # Data loading
 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(df):
+    numeric_features = [a for a in range(len(df.dtypes)) if df.dtypes[a] in ['int64','float64']]
+    numeric_df = df.iloc[:, numeric_features]
+    cat_features = df.columns.difference(df.columns[numeric_features])
+    cat_df = df.loc[:,cat_features]
+    numeric_imputer = Imputer(missing_values = 'NaN', strategy='mean')
+    numeric_imputed_df = pd.DataFrame(numeric_imputer.fit_transform(numeric_df))
+    numeric_imputed_df.columns = numeric_df.columns
+    numeric_imputed_df.index = numeric_df.index
+    for feature in cat_features:
+        cat_df[feature] = cat_df[feature].fillna(cat_df[feature].mode()[0])
+    return numeric_imputed_df, cat_df
+
+
+
 
-# Write your code here:
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From 3f50e1ff4363b74fbd41400642963d2bcbcd8945 Mon Sep 17 00:00:00 2001
From: sannidh <soniknitr@gmail.com>
Date: Sat, 3 Nov 2018 04:20:10 +0000
Subject: [PATCH 2/5] Done

---
 .../__pycache__/__init__.cpython-36.pyc          | Bin 0 -> 171 bytes
 .../__pycache__/build.cpython-36.pyc             | Bin 0 -> 910 bytes
 q02_outlier_removal/build.py                     |  14 +++++++++++++-
 .../tests/__pycache__/__init__.cpython-36.pyc    | Bin 0 -> 177 bytes
 .../test_q02_outlier_removal.cpython-36.pyc      | Bin 0 -> 1787 bytes
 5 files changed, 13 insertions(+), 1 deletion(-)
 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..8140ac5 100644
--- a/q02_outlier_removal/build.py
+++ b/q02_outlier_removal/build.py
@@ -1,3 +1,4 @@
+# %load q02_outlier_removal/build.py
 # Default imports
 import pandas as pd
 
@@ -6,5 +7,16 @@
 # Selecting 4 most relevant variables from the dataset fot the Cleaning and Preprocessing.
 housing_data = ny_housing[['MasVnrArea', 'GrLivArea', 'LotShape', 'GarageType', 'SalePrice']]
 
+def outlier_removal(df):
+    qv = 0.95
+    df_qv = df.quantile(q=qv, axis=0, numeric_only=True, interpolation='linear')
+    numeric_features = [a for a in range(len(df.dtypes)) if df.dtypes[a] in ['int64','float64']]
+    numeric_df = df.iloc[:, numeric_features]
+    for feature in numeric_df.columns:
+        df=df.drop(df[df[feature]>df_qv[feature]].index)
+    return df
+
+
+
+
 
-# 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 5d33248754bcc0ac6624273d7b8c47d91c101a6f Mon Sep 17 00:00:00 2001
From: sannidh <soniknitr@gmail.com>
Date: Sat, 3 Nov 2018 06:31:47 +0000
Subject: [PATCH 3/5] Done

---
 .../__pycache__/__init__.cpython-36.pyc          | Bin 0 -> 168 bytes
 .../__pycache__/build.cpython-36.pyc             | Bin 0 -> 516 bytes
 q03_skewness_log/build.py                        |   9 ++++++++-
 .../tests/__pycache__/__init__.cpython-36.pyc    | Bin 0 -> 174 bytes
 .../test_q03_skewness_log.cpython-36.pyc         | Bin 0 -> 2199 bytes
 5 files changed, 8 insertions(+), 1 deletion(-)
 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..c2ecbc9 100644
--- a/q03_skewness_log/build.py
+++ b/q03_skewness_log/build.py
@@ -1,8 +1,15 @@
+# %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(df):
+    df_trans = df.copy()
+    df_trans['SalePrice'] = np.log(df_trans['SalePrice'])
+    df_trans['GrLivArea'] = np.log(df_trans['GrLivArea'])
+    return skew(df_trans['GrLivArea']), skew(df_trans['SalePrice'])
+
+
 
-# Write code here:
diff --git a/q03_skewness_log/tests/__pycache__/__init__.cpython-36.pyc b/q03_skewness_log/tests/__pycache__/__init__.cpython-36.pyc
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From e7a7a2581c0ef67cf19b5500e0e0ab8dec3fd15c Mon Sep 17 00:00:00 2001
From: sannidh <soniknitr@gmail.com>
Date: Sat, 3 Nov 2018 06:37:38 +0000
Subject: [PATCH 4/5] Done

---
 .../__pycache__/__init__.cpython-36.pyc          | Bin 0 -> 169 bytes
 .../__pycache__/build.cpython-36.pyc             | Bin 0 -> 525 bytes
 q03_skewness_sqrt/build.py                       |   8 +++++++-
 .../tests/__pycache__/__init__.cpython-36.pyc    | Bin 0 -> 175 bytes
 .../test-q03_skewness_sqrt.cpython-36.pyc        | Bin 0 -> 2070 bytes
 5 files changed, 7 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
new file mode 100644
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diff --git a/q03_skewness_sqrt/__pycache__/build.cpython-36.pyc b/q03_skewness_sqrt/__pycache__/build.cpython-36.pyc
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diff --git a/q03_skewness_sqrt/build.py b/q03_skewness_sqrt/build.py
index 4bdb0e4..ba215a4 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 +6,11 @@
 
 ny_housing = pd.read_csv('data/train.csv')
 
+def skewness_sqrt(df):
+    df_trans = df.copy()
+    df_trans['SalePrice'] = np.sqrt(df_trans['SalePrice'])
+    df_trans['GrLivArea'] = np.sqrt(df_trans['GrLivArea'])
+    return skew(df_trans['GrLivArea']), skew(df_trans['SalePrice'])
+
 
-# 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 4517aa7af96e2d2448a3caa319b1b1be768075aa Mon Sep 17 00:00:00 2001
From: sannidh <soniknitr@gmail.com>
Date: Sat, 3 Nov 2018 08:57:48 +0000
Subject: [PATCH 5/5] Done

---
 q04_encoding/__pycache__/__init__.cpython-36.pyc | Bin 0 -> 164 bytes
 q04_encoding/__pycache__/build.cpython-36.pyc    | Bin 0 -> 621 bytes
 q04_encoding/build.py                            |   9 ++++++++-
 .../tests/__pycache__/__init__.cpython-36.pyc    | Bin 0 -> 170 bytes
 .../__pycache__/test_q04_encoding.cpython-36.pyc | Bin 0 -> 1728 bytes
 5 files changed, 8 insertions(+), 1 deletion(-)
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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..c291f38 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']]
 
+def encoding(df):
+    le = LabelEncoder()
+    df['LotShape_Label'] = le.fit_transform(df['LotShape'])
+    df=df.join(pd.get_dummies(df['GarageType'], drop_first=True))
+    return df
+
+
 
-# Write your code here:
 
diff --git a/q04_encoding/tests/__pycache__/__init__.cpython-36.pyc b/q04_encoding/tests/__pycache__/__init__.cpython-36.pyc
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