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读取数据

import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
from sklearn.preprocessing import StandardScaler # Used for scaling of data
from sklearn.model_selection import train_test_split
from keras.models import Sequential
from keras.layers import Dense, Dropout
from keras import metrics
import seaborn as sns
import matplotlib.pyplot as plt
from keras import backend as K
from keras.wrappers.scikit_learn import KerasRegressor
Using TensorFlow backend. 
# Read in train data
df_train = pd.read_csv('/home/kesci/work/house/train.csv')
df_train.info()
<class 'pandas.core.frame.DataFrame'> RangeIndex: 1460 entries, 0 to 1459 Data columns (total 81 columns): Id 1460 non-null int64 MSSubClass 1460 non-null int64 MSZoning 1460 non-null object LotFrontage 1201 non-null float64 LotArea 1460 non-null int64 Street 1460 non-null object Alley 91 non-null object LotShape 1460 non-null object LandContour 1460 non-null object Utilities 1460 non-null object LotConfig 1460 non-null object LandSlope 1460 non-null object Neighborhood 1460 non-null object Condition1 1460 non-null object Condition2 1460 non-null object BldgType 1460 non-null object HouseStyle 1460 non-null object OverallQual 1460 non-null int64 OverallCond 1460 non-null int64 YearBuilt 1460 non-null int64 YearRemodAdd 1460 non-null int64 RoofStyle 1460 non-null object RoofMatl 1460 non-null object Exterior1st 1460 non-null object Exterior2nd 1460 non-null object MasVnrType 1452 non-null object MasVnrArea 1452 non-null float64 ExterQual 1460 non-null object ExterCond 1460 non-null object Foundation 1460 non-null object BsmtQual 1423 non-null object BsmtCond 1423 non-null object BsmtExposure 1422 non-null object BsmtFinType1 1423 non-null object BsmtFinSF1 1460 non-null int64 BsmtFinType2 1422 non-null object BsmtFinSF2 1460 non-null int64 BsmtUnfSF 1460 non-null int64 TotalBsmtSF 1460 non-null int64 Heating 1460 non-null object HeatingQC 1460 non-null object CentralAir 1460 non-null object Electrical 1459 non-null object 1stFlrSF 1460 non-null int64 2ndFlrSF 1460 non-null int64 LowQualFinSF 1460 non-null int64 GrLivArea 1460 non-null int64 BsmtFullBath 1460 non-null int64 BsmtHalfBath 1460 non-null int64 FullBath 1460 non-null int64 HalfBath 1460 non-null int64 BedroomAbvGr 1460 non-null int64 KitchenAbvGr 1460 non-null int64 KitchenQual 1460 non-null object TotRmsAbvGrd 1460 non-null int64 Functional 1460 non-null object Fireplaces 1460 non-null int64 FireplaceQu 770 non-null object GarageType 1379 non-null object GarageYrBlt 1379 non-null float64 GarageFinish 1379 non-null object GarageCars 1460 non-null int64 GarageArea 1460 non-null int64 GarageQual 1379 non-null object GarageCond 1379 non-null object PavedDrive 1460 non-null object WoodDeckSF 1460 non-null int64 OpenPorchSF 1460 non-null int64 EnclosedPorch 1460 non-null int64 3SsnPorch 1460 non-null int64 ScreenPorch 1460 non-null int64 PoolArea 1460 non-null int64 PoolQC 7 non-null object Fence 281 non-null object MiscFeature 54 non-null object MiscVal 1460 non-null int64 MoSold 1460 non-null int64 YrSold 1460 non-null int64 SaleType 1460 non-null object SaleCondition 1460 non-null object SalePrice 1460 non-null int64 dtypes: float64(3), int64(35), object(43) memory usage: 924.0+ KB 
df_train.head()