import numpy as np
import scipy.stats as stats
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
from sklearn import linear_model
from sklearn.metrics import mean_squared_error
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import PolynomialFeatures
from sklearn.linear_model import Ridge, Lasso, ElasticNet, LinearRegression, RidgeCV, LassoCV, ElasticNetCV
from sklearn.model_selection import cross_val_score, cross_val_predict, train_test_split
import warnings
warnings.simplefilter("ignore")

sns.set_style('darkgrid')

%config InlineBackend.figure_format = 'retina'
%matplotlib inline

train_csv = '/Users/evanjacobs/dsi/DSI-US-4/project-2/train.csv'
test_csv = '/Users/evanjacobs/dsi/DSI-US-4/project-2/test.csv'

df = pd.read_csv(train_csv)
finaltest = pd.read_csv(test_csv)

X = df.drop(['SalePrice'], axis=1)
y = df.SalePrice.values
X_full = df.drop(['SalePrice'], axis=1)
X_train, X_test, y_train, y_test = train_test_split(X, y)

X_train.head()

X_train.describe()

X_train.info()

X_train.columns

def colclean(column_list): 
    columns=[]
    for n in column_list:
        n = n.lower().replace(' ','')
        columns.append(n)
    return columns
colclean(df.columns)
X_train.columns = colclean(X_train.columns)
X_test.columns = colclean(X_test.columns)
X_train.columns
X_full.columns = colclean(X_full.columns)
finaltest.columns = colclean(finaltest.columns)

X_train.duplicated(subset='pid', keep='first').sum()

X_train.isnull().sum()

X_train.isna().sum()[X_train.isna().sum() !=0]

X_train.poolqc.unique()

X_train = X_train.fillna(X_train.mean())
X_test = X_test.fillna(X_test.mean())
X_full = X_full.fillna(X_full.mean())
finaltest = finaltest.fillna(finaltest.mean())

X_train.info()

X_tr_obj = X_train.select_dtypes(exclude=[np.number])
X_tr_num = X_train.select_dtypes(include=[np.number])
X_ts_obj = X_test.select_dtypes(exclude=[np.number])
X_ts_num = X_test.select_dtypes(include=[np.number])
X_full_obj = X_full.select_dtypes(exclude=[np.number])
X_full_num = X_full.select_dtypes(include=[np.number])
finaltest_obj = finaltest.select_dtypes(exclude=[np.number])
finaltest_num = finaltest.select_dtypes(include=[np.number])

X_ts_num.head()

print(X_train.shape)
print(X_tr_obj.shape)
print(X_tr_num.shape)

X_tr_num.describe().T

X_tr_num['sp']=y_train

abs(X_tr_num.corr().sp)

vals = abs(X_tr_num.corr().sp).drop('sp').sort_values(ascending=False)
corr_cols = list(vals[vals >= 0.3].index)

X_tr_mod1 = X_tr_num[corr_cols]
X_ts_mod1 = X_ts_num[corr_cols]
X_full_mod1 = X_full_num[corr_cols]
finaltest_num = finaltest_num[corr_cols]

corr_cols

from sklearn.preprocessing import PolynomialFeatures
pf = PolynomialFeatures(degree=2, interaction_only=False, 
                         include_bias=True)
pf.fit(X_tr_mod1)
X_tr_mod1 = pf.transform(X_tr_mod1)
X_ts_mod1 = pf.transform(X_ts_mod1)
X_full_mod1 = pf.transform(X_full_mod1)
finaltest_num = pf.transform(finaltest_num)

from sklearn.preprocessing import StandardScaler
ss = StandardScaler()
X_tr_mod1 = ss.fit_transform(X_tr_mod1)
X_ts_mod1 = ss.transform(X_ts_mod1)
X_full_mod1 = ss.fit_transform(X_full_mod1)
finaltest_num = ss.transform(finaltest_num)

l_alphas = np.arange(.001, .15, .0025)
lasso_model = LassoCV(alphas=l_alphas, max_iter=2000, cv=5)
# lasso_model = LassoCV(max_iter=10000, cv=5)

model_1 = lasso_model.fit(X_tr_mod1, y_train)

print(model_1.score(X_ts_mod1, y_test))

ridge_alphas = np.logspace(0, 5, 200)

ridge_model = RidgeCV(alphas=ridge_alphas, cv=10)
# ridge_model = RidgeCV(cv=10)
ridge_model.fit(X_tr_mod1, y_train)

ridge = Ridge(alpha=ridge_model.alpha_)

ridge_scores = cross_val_score(ridge, X_ts_mod1, y_test, cv=15)

print(ridge_scores)
print(np.mean(ridge_scores))

l1_ratios = np.linspace(0.01, 1.0, 25)

enet = ElasticNetCV(l1_ratio=l1_ratios, n_alphas=100, cv=10,
                            verbose=0)
# enet = ElasticNetCV(cv=10, verbose=0)
enet.fit(X_tr_mod1, y_train)

print(enet.alpha_)
print(enet.l1_ratio_)

enet = ElasticNet(alpha=enet.alpha_, l1_ratio=enet.l1_ratio_)

enet_scores = cross_val_score(enet, X_ts_mod1, y_test, cv=10)

print(enet_scores)
print(np.mean(enet_scores))

# l_alphas = np.arange(.001, .15, .0025)
# lasso_model_final = LassoCV(alphas=l_alphas, cv=5)
# model_1_final = lasso_model.fit(X_full_mod1, y)

enet = ElasticNetCV(l1_ratio=l1_ratios, n_alphas=100, cv=10,
                            verbose=0)
model_1_final = enet.fit(X_full_mod1, y)

evansubmission1 = pd.DataFrame(data = model_1_final.predict(finaltest_num), columns = ['SalePrice'], index=finaltest['id'])
evansubmission1.to_csv('./evansubmission1.csv')

predictions = model_1_final.predict(X_ts_mod1)
y = y_test

# Plot the model
plt.figure(figsize=(8,8))
plt.scatter(predictions, y, s=30, c='g', marker='*', zorder=10)
plt.xlabel("Predicted Values of Price From My Horrible Model")
plt.ylabel("Actual Values of Price")

plt.plot([0, np.max(y)], [0, np.max(y)], c = 'k')

plt.show()
score = cross_val_score(model_1_final, X_ts_mod1, y_test, cv=10)
print("score: ", score.mean())

# evansubmission1 = pd.DataFrame(data = model_1.predict(X_ts_mod1), columns = ['SalePrice'], index=y_test['Id'])
# evansubmission1.to_csv('./evansubmission1.csv')

# There are three files:

# train.csv -- this data contains all of the training data for your model.
# The target variable (SalePrice) is removed from the test set!
# test.csv -- this data contains the test data for your model. You will feed this data into your regression model to make predictions.
# sample_sub_reg.csv -- An example of a correctly formatted submission for this challenge (with a random number provided as predictions for SalePrice. Please ensure that your submission to Kaggle matches this format.
# Codebook / Data Dictionary:

# SalePrice - the property's sale price in dollars. This is the target variable that you're trying to predict for this challenge.
# MSSubClass: The building class
#     20 1-STORY 1946 & NEWER ALL STYLES
#     30 1-STORY 1945 & OLDER
#     40 1-STORY W/FINISHED ATTIC ALL AGES
#     45 1-1/2 STORY - UNFINISHED ALL AGES
#     50 1-1/2 STORY FINISHED ALL AGES
#     60 2-STORY 1946 & NEWER
#     70 2-STORY 1945 & OLDER
#     75 2-1/2 STORY ALL AGES
#     80 SPLIT OR MULTI-LEVEL
#     85 SPLIT FOYER
#     90 DUPLEX - ALL STYLES AND AGES
#     120 1-STORY PUD (Planned Unit Development) - 1946 & NEWER
#     150 1-1/2 STORY PUD - ALL AGES
#     160 2-STORY PUD - 1946 & NEWER
#     180 PUD - MULTILEVEL - INCL SPLIT LEV/FOYER
#     190 2 FAMILY CONVERSION - ALL STYLES AND AGES
# MSZoning: Identifies the general zoning classification of the sale.
#     A Agriculture
#     C Commercial
#     FV Floating Village Residential
#     I Industrial
#     RH Residential High Density
#     RL Residential Low Density
#     RP Residential Low Density Park
#     RM Residential Medium Density
# LotFrontage: Linear feet of street connected to property
# LotArea: Lot size in square feet
# Street: Type of road access to property
#     Grvl Gravel
#     Pave Paved
# Alley: Type of alley access to property
#     Grvl Gravel
#     Pave Paved
#     NA No alley access
# LotShape: General shape of property
#     Reg Regular
#     IR1 Slightly irregular
#     IR2 Moderately Irregular
#     IR3 Irregular
# LandContour: Flatness of the property
#     Lvl Near Flat/Level
#     Bnk Banked - Quick and significant rise from street grade to building
#     HLS Hillside - Significant slope from side to side
#     Low Depression
# Utilities: Type of utilities available
#     AllPub All public Utilities (E,G,W,& S)
#     NoSewr Electricity, Gas, and Water (Septic Tank)
#     NoSeWa Electricity and Gas Only
#     ELO Electricity only
# LotConfig: Lot configuration
#     Inside Inside lot
#     Corner Corner lot
#     CulDSac Cul-de-sac
#     FR2 Frontage on 2 sides of property
#     FR3 Frontage on 3 sides of property
# LandSlope: Slope of property
#     Gtl Gentle slope
#     Mod Moderate Slope
#     Sev Severe Slope
# Neighborhood: Physical locations within Ames city limits
#     Blmngtn Bloomington Heights
#     Blueste Bluestem
#     BrDale Briardale
#     BrkSide Brookside
#     ClearCr Clear Creek
#     CollgCr College Creek
#     Crawfor Crawford
#     Edwards Edwards
#     Gilbert Gilbert
#     IDOTRR Iowa DOT and Rail Road
#     MeadowV Meadow Village
#     Mitchel Mitchell
#     Names North Ames
#     NoRidge Northridge
#     NPkVill Northpark Villa
#     NridgHt Northridge Heights
#     NWAmes Northwest Ames
#     OldTown Old Town
#     SWISU South & West of Iowa State University
#     Sawyer Sawyer
#     SawyerW Sawyer West
#     Somerst Somerset
#     StoneBr Stone Brook
#     Timber Timberland
#     Veenker Veenker
# Condition1: Proximity to main road or railroad
#     Artery Adjacent to arterial street
#     Feedr Adjacent to feeder street
#     Norm Normal
#     RRNn Within 200' of North-South Railroad
#     RRAn Adjacent to North-South Railroad
#     PosN Near positive off-site feature--park, greenbelt, etc.
#     PosA Adjacent to postive off-site feature
#     RRNe Within 200' of East-West Railroad
#     RRAe Adjacent to East-West Railroad
# Condition2: Proximity to main road or railroad (if a second is present)
#     Artery Adjacent to arterial street
#     Feedr Adjacent to feeder street
#     Norm Normal
#     RRNn Within 200' of North-South Railroad
#     RRAn Adjacent to North-South Railroad
#     PosN Near positive off-site feature--park, greenbelt, etc.
#     PosA Adjacent to postive off-site feature
#     RRNe Within 200' of East-West Railroad
#     RRAe Adjacent to East-West Railroad
# BldgType: Type of dwelling
#     1Fam Single-family Detached
#     2FmCon Two-family Conversion; originally built as one-family dwelling
#     Duplx Duplex
#     TwnhsE Townhouse End Unit
#     TwnhsI Townhouse Inside Unit
# HouseStyle: Style of dwelling
#     1Story One story
#     1.5Fin One and one-half story: 2nd level finished
#     1.5Unf One and one-half story: 2nd level unfinished
#     2Story Two story
#     2.5Fin Two and one-half story: 2nd level finished
#     2.5Unf Two and one-half story: 2nd level unfinished
#     SFoyer Split Foyer
#     SLvl Split Level
# OverallQual: Overall material and finish quality
#     10 Very Excellent
#     9 Excellent
#     8 Very Good
#     7 Good
#     6 Above Average
#     5 Average
#     4 Below Average
#     3 Fair
#     2 Poor
#     1 Very Poor
# OverallCond: Overall condition rating
#     10 Very Excellent
#     9 Excellent
#     8 Very Good
#     7 Good
#     6 Above Average
#     5 Average
#     4 Below Average
#     3 Fair
#     2 Poor
#     1 Very Poor
# YearBuilt: Original construction date
# YearRemodAdd: Remodel date (same as construction date if no remodeling or additions)
# RoofStyle: Type of roof
#     Flat Flat
#     Gable Gable
#     Gambrel Gabrel (Barn)
#     Hip Hip
#     Mansard Mansard
#     Shed Shed
# RoofMatl: Roof material
#     ClyTile Clay or Tile
#     CompShg Standard (Composite) Shingle
#     Membran Membrane
#     Metal Metal
#     Roll Roll
#     Tar&Grv Gravel & Tar
#     WdShake Wood Shakes
#     WdShngl Wood Shingles
# Exterior1st: Exterior covering on house
#     AsbShng Asbestos Shingles
#     AsphShn Asphalt Shingles
#     BrkComm Brick Common
#     BrkFace Brick Face
#     CBlock Cinder Block
#     CemntBd Cement Board
#     HdBoard Hard Board
#     ImStucc Imitation Stucco
#     MetalSd Metal Siding
#     Other Other
#     Plywood Plywood
#     PreCast PreCast
#     Stone Stone
#     Stucco Stucco
#     VinylSd Vinyl Siding
#     Wd Sdng Wood Siding
#     WdShing Wood Shingles
# Exterior2nd: Exterior covering on house (if more than one material)
#     AsbShng Asbestos Shingles
#     AsphShn Asphalt Shingles
#     BrkComm Brick Common
#     BrkFace Brick Face
#     CBlock Cinder Block
#     CemntBd Cement Board
#     HdBoard Hard Board
#     ImStucc Imitation Stucco
#     MetalSd Metal Siding
#     Other Other
#     Plywood Plywood
#     PreCast PreCast
#     Stone Stone
#     Stucco Stucco
#     VinylSd Vinyl Siding
#     Wd Sdng Wood Siding
#     WdShing Wood Shingles
# MasVnrType: Masonry veneer type
#     BrkCmn Brick Common
#     BrkFace Brick Face
#     CBlock Cinder Block
#     None None
#     Stone Stone
# MasVnrArea: Masonry veneer area in square feet
# ExterQual: Exterior material quality
#     Ex Excellent
#     Gd Good
#     TA Average/Typical
#     Fa Fair
#     Po Poor
# ExterCond: Present condition of the material on the exterior
#     Ex Excellent
#     Gd Good
#     TA Average/Typical
#     Fa Fair
#     Po Poor
# Foundation: Type of foundation
#     BrkTil Brick & Tile
#     CBlock Cinder Block
#     PConc Poured Contrete
#     Slab Slab
#     Stone Stone
#     Wood Wood
# BsmtQual: Height of the basement
#     Ex Excellent (100+ inches)
#     Gd Good (90-99 inches)
#     TA Typical (80-89 inches)
#     Fa Fair (70-79 inches)
#     Po Poor (<70 inches)
#     NA No Basement
# BsmtCond: General condition of the basement
#     Ex Excellent
#     Gd Good
#     TA Typical - slight dampness allowed
#     Fa Fair - dampness or some cracking or settling
#     Po Poor - Severe cracking, settling, or wetness
#     NA No Basement
# BsmtExposure: Walkout or garden level basement walls
#     Gd Good Exposure
#     Av Average Exposure (split levels or foyers typically score average or above)
#     Mn Mimimum Exposure
#     No No Exposure
#     NA No Basement
# BsmtFinType1: Quality of basement finished area
#     GLQ Good Living Quarters
#     ALQ Average Living Quarters
#     BLQ Below Average Living Quarters
#     Rec Average Rec Room
#     LwQ Low Quality
#     Unf Unfinshed
#     NA No Basement
# BsmtFinSF1: Type 1 finished square feet
# BsmtFinType2: Quality of second finished area (if present)
#     GLQ Good Living Quarters
#     ALQ Average Living Quarters
#     BLQ Below Average Living Quarters
#     Rec Average Rec Room
#     LwQ Low Quality
#     Unf Unfinshed
#     NA No Basement
# BsmtFinSF2: Type 2 finished square feet
# BsmtUnfSF: Unfinished square feet of basement area
# TotalBsmtSF: Total square feet of basement area
# Heating: Type of heating
#     Floor Floor Furnace
#     GasA Gas forced warm air furnace
#     GasW Gas hot water or steam heat
#     Grav Gravity furnace
#     OthW Hot water or steam heat other than gas
#     Wall Wall furnace
# HeatingQC: Heating quality and condition
#     Ex Excellent
#     Gd Good
#     TA Average/Typical
#     Fa Fair
#     Po Poor
# CentralAir: Central air conditioning
#     N No
#     Y Yes
# Electrical: Electrical system
#     SBrkr Standard Circuit Breakers & Romex
#     FuseA Fuse Box over 60 AMP and all Romex wiring (Average)
#     FuseF 60 AMP Fuse Box and mostly Romex wiring (Fair)
#     FuseP 60 AMP Fuse Box and mostly knob & tube wiring (poor)
#     Mix Mixed
# 1stFlrSF: First Floor square feet
# 2ndFlrSF: Second floor square feet
# LowQualFinSF: Low quality finished square feet (all floors)
# GrLivArea: Above grade (ground) living area square feet
# BsmtFullBath: Basement full bathrooms
# BsmtHalfBath: Basement half bathrooms
# FullBath: Full bathrooms above grade
# HalfBath: Half baths above grade
# Bedroom: Number of bedrooms above basement level
# Kitchen: Number of kitchens
# KitchenQual: Kitchen quality
#     Ex Excellent
#     Gd Good
#     TA Typical/Average
#     Fa Fair
#     Po Poor
# TotRmsAbvGrd: Total rooms above grade (does not include bathrooms)
# Functional: Home functionality rating
#     Typ Typical Functionality
#     Min1 Minor Deductions 1
#     Min2 Minor Deductions 2
#     Mod Moderate Deductions
#     Maj1 Major Deductions 1
#     Maj2 Major Deductions 2
#     Sev Severely Damaged
#     Sal Salvage only
# Fireplaces: Number of fireplaces
# FireplaceQu: Fireplace quality
#     Ex Excellent - Exceptional Masonry Fireplace
#     Gd Good - Masonry Fireplace in main level
#     TA Average - Prefabricated Fireplace in main living area or Masonry Fireplace in basement
#     Fa Fair - Prefabricated Fireplace in basement
#     Po Poor - Ben Franklin Stove
#     NA No Fireplace
# GarageType: Garage location
#     2Types More than one type of garage
#     Attchd Attached to home
#     Basment Basement Garage
#     BuiltIn Built-In (Garage part of house - typically has room above garage)
#     CarPort Car Port
#     Detchd Detached from home
#     NA No Garage
# GarageYrBlt: Year garage was built
# GarageFinish: Interior finish of the garage
#     Fin Finished
#     RFn Rough Finished
#     Unf Unfinished
#     NA No Garage
# GarageCars: Size of garage in car capacity
# GarageArea: Size of garage in square feet
# GarageQual: Garage quality
#     Ex Excellent
#     Gd Good
#     TA Typical/Average
#     Fa Fair
#     Po Poor
#     NA No Garage
#     GarageCond: Garage condition
#     Ex Excellent
#     Gd Good
#     TA Typical/Average
#     Fa Fair
#     Po Poor
#     NA No Garage
# PavedDrive: Paved driveway
#     Y Paved
#     P Partial Pavement
#     N Dirt/Gravel
# WoodDeckSF: Wood deck area in square feet
# OpenPorchSF: Open porch area in square feet
# EnclosedPorch: Enclosed porch area in square feet
# 3SsnPorch: Three season porch area in square feet
# ScreenPorch: Screen porch area in square feet
# PoolArea: Pool area in square feet
# PoolQC: Pool quality
#     Ex Excellent
#     Gd Good
#     TA Average/Typical
#     Fa Fair
#     NA No Pool
# Fence: Fence quality
#     GdPrv Good Privacy
#     MnPrv Minimum Privacy
#     GdWo Good Wood
#     MnWw Minimum Wood/Wire
#     NA No Fence
# MiscFeature: Miscellaneous feature not covered in other categories
#     Elev Elevator
#     Gar2 2nd Garage (if not described in garage section)
#     Othr Other
#     Shed Shed (over 100 SF)
#     TenC Tennis Court
#     NA None
# MiscVal: $Value of miscellaneous feature
# MoSold: Month Sold
# YrSold: Year Sold
# SaleType: Type of sale
#     WD Warranty Deed - Conventional
#     CWD Warranty Deed - Cash
#     VWD Warranty Deed - VA Loan
#     New Home just constructed and sold
#     COD Court Officer Deed/Estate
#     Con Contract 15% Down payment regular terms
#     ConLw Contract Low Down payment and low interest
#     ConLI Contract Low Interest
#     ConLD Contract Low Down
#     Oth Other