Added application file

app.py

@@ -0,0 +1,206 @@
+import streamlit as st
+import shap
+import xgboost
+from sklearn.ensemble import RandomForestRegressor
+from sklearn.model_selection import train_test_split
+import datetime
+import pandas as pd
+import numpy as np
+import seaborn as sns
+import matplotlib.pyplot as plt
+import plotly.express as px
+import pickle as pk
+import os
+
+# ml related
+from sklearn import ensemble, tree, linear_model
+from sklearn.model_selection import train_test_split, cross_val_score
+from sklearn.metrics import r2_score, mean_squared_error
+from sklearn.utils import shuffle
+import warnings
+from scipy import stats
+from scipy.stats import norm, skew
+
+warnings.filterwarnings('ignore')
+
+train_path = "train.csv"
+test_path = "test.csv"
+train_encode_path = "train_encode.csv"
+real = "RealEstate.csv"
+head = "head.jpg"
+
+@st.cache_data
+def load_train_data(train_path):
+    return pd.read_csv(train_path)
+
+@st.cache_data
+def load_train_encode_data(train_encode_path):
+    return pd.read_csv(train_encode_path)
+
+@st.cache_data
+def load_test_data(test_path):
+    return pd.read_csv(test_path)
+
+@st.cache_data
+def load_data(real):
+    return pd.read_csv(real)
+
+
+def save_data(value,res):
+    file = 'db.csv'
+    if not os.path.exists(file):
+        with open(file,'w') as f:
+            f.write("OverallQual,GrLivArea,GarageCars,GarageArea,TotalBsmtSF,fstFlrSF,FullBath,TotRmsAbvGrd,YearBuilt,YearRemodAdd,GarageYrBlt,MasVnrArea,Fireplaces,BsmtFinSF1,Result\n")
+    with open(file,'a') as f:
+        data = f"{OverallQual},{GrLivArea},{GarageCars},{GarageArea},{TotalBsmtSF},{fstFlrSF},{FullBath},{TotRmsAbvGrd},{YearBuilt},{YearRemodAdd},{GarageYrBlt},{MasVnrArea},{Fireplaces},{BsmtFinSF1},{res}\n"
+        f.write(data)
+
+st.sidebar.image(head, caption="project on Artificial intelligence",use_column_width=True)
+
+
+
+
+st.title("House Pricing Analysis")
+
+menu=["House Prediction","Predicted House","About","Visual"]
+choices=st.sidebar.selectbox("Menu Bar",menu)
+
+if choices=='House Prediction':
+    st.subheader("House Prediction")
+    OverallQual=st.selectbox("Select the overall quality(10 being 'Very Excellent' and 1 being 'very poor')",(10,9,8,7,6,5,4,3,2,1))
+    GrLivArea= st.number_input("Enter Ground Floor Living Area (in Sqft)",value=0,min_value=0,format='%d')
+    GarageArea=st.number_input("Enter area of Garage (in Sqft)",value=0.0,format='%f',step=1.0)
+    GarageCars=st.number_input("Number of Cars to be accomodated in garage",min_value=1.0,max_value=10.0,step=1.0,format='%f')
+    TotalBsmtSF=st.number_input("Enter area of Basement (in Sqft)",value=0.0,format='%f',step=1.0)
+    fstFlrSF=st.number_input("Enter area of First Floor (in Sqft)",value=0,format='%d')
+    FullBath=st.number_input("Enter number of Bathrooms",min_value=1,max_value=10,format='%d')
+    TotRmsAbvGrd=st.number_input("Enter number of Rooms",min_value=1,max_value=10,format='%d')
+    years=tuple([i for i in range(1872,2011)])
+    YearBuilt=st.selectbox("Select the overall quality(10 being 'Very Excellent' and 1 being 'very poor')",years)
+    remyears=tuple([i for i in range(1950,2011)])
+    YearRemodAdd=st.selectbox("Select Remodel date (same as construction date if no remodeling or additions)",remyears)
+    garyears=tuple([i for i in range(1872,2011)])
+    garyears=tuple(map(float,garyears))
+    GarageYrBlt=st.selectbox("Select year in which Garage was built)",garyears)
+    MasVnrArea=st.number_input("Masonry veneer area (in Sqft)",value=0.0,format='%f',step=1.0)
+    Fireplaces=st.number_input("Select number of FirePlaces",min_value=1,max_value=10,format='%d')
+    BsmtFinSF1=st.number_input("Enter Basement Finished Area(in Sqft)",value=0,format='%d')
+    submit = st.button('Predict')
+    if submit:
+        st.success("Prediction Done")
+        value=[OverallQual,GrLivArea,GarageCars,GarageArea,TotalBsmtSF,fstFlrSF,FullBath,TotRmsAbvGrd,YearBuilt,YearRemodAdd,GarageYrBlt,MasVnrArea,Fireplaces,BsmtFinSF1]
+        df=pd.DataFrame(value).transpose()
+        # st.dataframe(df)
+        model=pk.load(open('rfrmodel.pkl','rb'))
+        scaler=pk.load(open('scale.pkl','rb'))
+        #xgboostmodel=pk.load(open('xgboostmodel.pkl','rb'))
+        scaler.transform(df)
+        ans=int(model.predict(df))
+        st.subheader(f"The price is {ans} ($) ")
+        save_data(value,ans)
+
+if choices=='Predicted House':
+    st.subheader("Predicted House")
+    st.info("expand to see data clearly")
+    if os.path.exists("db.csv"):
+        data = pd.read_csv('db.csv')
+        st.write(data)
+    else:
+        st.error("please try some prediction, then the data will be available here")
+if choices=='About':
+    st.subheader("About Us")
+    info='''
+        A house value is simply more than location and square footage. Like the features that make up a person, an educated party would want to know all aspects that give a house its value.
+
+        We are going to take advantage of all of the feature variables available to use and use it to analyze and predict house prices.
+
+        We are going to break everything into logical steps that allow us to ensure the cleanest, most realistic data for our model to make accurate predictions from.
+
+        - Load Data and Packages
+        - Analyzing the Test Variable (Sale Price)
+        - Multivariable Analysis
+        - Impute Missing Data and Clean Data
+        - Feature Transformation/Engineering
+        - Modeling and Predictions
+    '''
+    st.markdown(info,unsafe_allow_html=True)
+
+if choices=='Visual':
+    st.subheader("Data Visualization")
+
+    train_data = load_train_data(train_path)
+    train_encode_data = load_train_encode_data(train_encode_path)
+    test_data = load_test_data(test_path)
+
+    X=train_encode_data.drop(['SalePrice'],axis=1)
+    y=train_encode_data['SalePrice']
+    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42, shuffle=True)
+
+
+    if st.checkbox("view dataset colum description"):
+        st.subheader('displaying the column wise stats for the dataset')
+        st.write(train_data.columns)
+        st.write(train_data.describe())
+
+    st.subheader('Correlation b/w dataset columns')
+    corrmatrix = train_data.corr()
+    f,ax = plt.subplots(figsize=(20,9))
+    sns.heatmap(corrmatrix,vmax = .8, annot=True)
+    #st.set_option('deprecation.showPyplotGlobalUse', False)
+    st.pyplot()
+
+    st.subheader("most correlated features")
+    top_corr = train_data.corr()
+    top_corr_feat = corrmatrix.index[abs(corrmatrix['SalePrice'])>.5]
+    plt.figure(figsize=(10,10))
+    sns.heatmap(train_data[top_corr_feat].corr(), annot=True, cmap="RdYlGn")
+    #st.set_option('deprecation.showPyplotGlobalUse', False)
+    st.pyplot()
+
+    st.subheader("Comparing Overall Quality vs Sale Price")
+    sns.barplot(x=train_data.OverallQual, y=train_data.SalePrice, alpha=0.8)
+    #st.set_option('deprecation.showPyplotGlobalUse', False)
+    st.pyplot()
+
+    st.subheader("Pairplot visualization to describe correlation easily")
+    sns.set()
+    cols = ['SalePrice', 'OverallQual', 'GrLivArea', 'GarageCars', 'TotalBsmtSF', 'FullBath', 'YearBuilt']
+    sns.pairplot(train_data[cols], size=2.5)
+    #st.set_option('deprecation.showPyplotGlobalUse', False)
+    st.pyplot()
+
+    st.subheader("Analyis of Sale Price column in dataset")
+    sns.distplot(train_data['SalePrice'] , fit=norm)# Get the fitted parameters used by the function
+    (mu, sigma) = norm.fit(train_data['SalePrice'])
+    st.write( '\n mu = {:.2f} and sigma = {:.2f}\n'.format(mu, sigma))
+
+    plt.legend(['Normal dist. ($\mu=$ {:.2f} and $\sigma=$ {:.2f} )'.format(mu, sigma)], loc='best')
+    plt.ylabel('Frequency')
+    plt.title('SalePrice distribution')
+    #st.set_option('deprecation.showPyplotGlobalUse', False)
+    st.pyplot()
+
+    fig = plt.figure(figsize=(10,10))
+    res = stats.probplot(train_data['SalePrice'], plot=plt,)
+    #st.set_option('deprecation.showPyplotGlobalUse', False)
+    st.pyplot()
+
+
+    #Explaning the model's predictions using SHAP values
+    xgboostmodel = xgboost.XGBRegressor().fit(X_train, y_train)
+    explainer = shap.Explainer(xgboostmodel)
+    shap_values = explainer(X_train)
+
+    # visualize the first prediction's explanation
+    shap.plots.waterfall(shap_values[0])
+
+    st.header('SHAP Feature importances')
+    plt.title('Feature importances based on SHAP values')
+    shap.summary_plot(shap_values,X_train)
+    st.pyplot(bbox_inches='tight')
+    st.write('---')
+
+    plt.title('Feature importances based on SHAP values (Bar plot)')
+    shap.summary_plot(shap_values,X_train, plot_type="bar", show=False)
+    st.pyplot(bbox_inches='tight')
+

data_description.txt

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+MSSubClass: Identifies the type of dwelling involved in the sale.	
+
+        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 various conditions
+	
+       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 various conditions (if more than one 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: Rates the overall material and finish of the house
+
+       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: Rates the overall condition of the house
+
+       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: Evaluates the quality of the material on the exterior 
+		
+       Ex	Excellent
+       Gd	Good
+       TA	Average/Typical
+       Fa	Fair
+       Po	Poor
+		
+ExterCond: Evaluates the 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: Evaluates the 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: Evaluates the 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: Refers to walkout or garden level 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: Rating 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: Rating of basement finished area (if multiple types)
+
+       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: Bedrooms above grade (does NOT include basement bedrooms)
+
+Kitchen: Kitchens above grade
+
+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 (Assume typical unless deductions are warranted)
+
+       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 (MM)
+
+YrSold: Year Sold (YYYY)
+
+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
+		
+SaleCondition: Condition of sale
+
+       Normal	Normal Sale
+       Abnorml	Abnormal Sale -  trade, foreclosure, short sale
+       AdjLand	Adjoining Land Purchase
+       Alloca	Allocation - two linked properties with separate deeds, typically condo with a garage unit	
+       Family	Sale between family members
+       Partial	Home was not completed when last assessed (associated with New Homes)

db.csv

@@ -0,0 +1,2 @@
+OverallQual,GrLivArea,GarageCars,GarageArea,TotalBsmtSF,fstFlrSF,FullBath,TotRmsAbvGrd,YearBuilt,YearRemodAdd,GarageYrBlt,MasVnrArea,Fireplaces,BsmtFinSF1,Result
+10,0,1.0,0.0,0.0,0,1,1,1872,1950,1872.0,0.0,1,0,263695

requirements.txt

@@ -0,0 +1,16 @@
+streamlit==1.25.0
+streamlit-shap==1.0.2
+shap==0.42.1
+xgboost==1.7.6
+sklearn-pandas==2.2.0
+pandas==1.5.3
+pandas-datareader==0.10.0
+pandas-gbq==0.17.9
+numpy==1.22.4
+seaborn==0.12.2
+matplotlib==3.7.1
+matplotlib-inline==0.1.6
+matplotlib-venn==0.11.9
+plotly==5.13.1
+pickleshare==0.7.5
+scipy==1.10.1

rfrmodel.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:875bb05bc9b1969a3b2f77d7dcd0bb2a9b99eb594bb4e8c911d5f3bb7e4d9266
+size 13885067

sample_submission.csv

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