Pick one of the quantitative independent variables from the training data set (train.csv) , and define that variable as X. Pick SalePrice as the dependent variable, and define it as Y for the next analysis.

train.data <- read.csv("https://raw.githubusercontent.com/komotunde/DATA605/master/train.csv", header  = TRUE)
head(train.data)
##   Id MSSubClass MSZoning LotFrontage LotArea Street Alley LotShape
## 1  1         60       RL          65    8450   Pave  <NA>      Reg
## 2  2         20       RL          80    9600   Pave  <NA>      Reg
## 3  3         60       RL          68   11250   Pave  <NA>      IR1
## 4  4         70       RL          60    9550   Pave  <NA>      IR1
## 5  5         60       RL          84   14260   Pave  <NA>      IR1
## 6  6         50       RL          85   14115   Pave  <NA>      IR1
##   LandContour Utilities LotConfig LandSlope Neighborhood Condition1
## 1         Lvl    AllPub    Inside       Gtl      CollgCr       Norm
## 2         Lvl    AllPub       FR2       Gtl      Veenker      Feedr
## 3         Lvl    AllPub    Inside       Gtl      CollgCr       Norm
## 4         Lvl    AllPub    Corner       Gtl      Crawfor       Norm
## 5         Lvl    AllPub       FR2       Gtl      NoRidge       Norm
## 6         Lvl    AllPub    Inside       Gtl      Mitchel       Norm
##   Condition2 BldgType HouseStyle OverallQual OverallCond YearBuilt
## 1       Norm     1Fam     2Story           7           5      2003
## 2       Norm     1Fam     1Story           6           8      1976
## 3       Norm     1Fam     2Story           7           5      2001
## 4       Norm     1Fam     2Story           7           5      1915
## 5       Norm     1Fam     2Story           8           5      2000
## 6       Norm     1Fam     1.5Fin           5           5      1993
##   YearRemodAdd RoofStyle RoofMatl Exterior1st Exterior2nd MasVnrType
## 1         2003     Gable  CompShg     VinylSd     VinylSd    BrkFace
## 2         1976     Gable  CompShg     MetalSd     MetalSd       None
## 3         2002     Gable  CompShg     VinylSd     VinylSd    BrkFace
## 4         1970     Gable  CompShg     Wd Sdng     Wd Shng       None
## 5         2000     Gable  CompShg     VinylSd     VinylSd    BrkFace
## 6         1995     Gable  CompShg     VinylSd     VinylSd       None
##   MasVnrArea ExterQual ExterCond Foundation BsmtQual BsmtCond BsmtExposure
## 1        196        Gd        TA      PConc       Gd       TA           No
## 2          0        TA        TA     CBlock       Gd       TA           Gd
## 3        162        Gd        TA      PConc       Gd       TA           Mn
## 4          0        TA        TA     BrkTil       TA       Gd           No
## 5        350        Gd        TA      PConc       Gd       TA           Av
## 6          0        TA        TA       Wood       Gd       TA           No
##   BsmtFinType1 BsmtFinSF1 BsmtFinType2 BsmtFinSF2 BsmtUnfSF TotalBsmtSF
## 1          GLQ        706          Unf          0       150         856
## 2          ALQ        978          Unf          0       284        1262
## 3          GLQ        486          Unf          0       434         920
## 4          ALQ        216          Unf          0       540         756
## 5          GLQ        655          Unf          0       490        1145
## 6          GLQ        732          Unf          0        64         796
##   Heating HeatingQC CentralAir Electrical X1stFlrSF X2ndFlrSF LowQualFinSF
## 1    GasA        Ex          Y      SBrkr       856       854            0
## 2    GasA        Ex          Y      SBrkr      1262         0            0
## 3    GasA        Ex          Y      SBrkr       920       866            0
## 4    GasA        Gd          Y      SBrkr       961       756            0
## 5    GasA        Ex          Y      SBrkr      1145      1053            0
## 6    GasA        Ex          Y      SBrkr       796       566            0
##   GrLivArea BsmtFullBath BsmtHalfBath FullBath HalfBath BedroomAbvGr
## 1      1710            1            0        2        1            3
## 2      1262            0            1        2        0            3
## 3      1786            1            0        2        1            3
## 4      1717            1            0        1        0            3
## 5      2198            1            0        2        1            4
## 6      1362            1            0        1        1            1
##   KitchenAbvGr KitchenQual TotRmsAbvGrd Functional Fireplaces FireplaceQu
## 1            1          Gd            8        Typ          0        <NA>
## 2            1          TA            6        Typ          1          TA
## 3            1          Gd            6        Typ          1          TA
## 4            1          Gd            7        Typ          1          Gd
## 5            1          Gd            9        Typ          1          TA
## 6            1          TA            5        Typ          0        <NA>
##   GarageType GarageYrBlt GarageFinish GarageCars GarageArea GarageQual
## 1     Attchd        2003          RFn          2        548         TA
## 2     Attchd        1976          RFn          2        460         TA
## 3     Attchd        2001          RFn          2        608         TA
## 4     Detchd        1998          Unf          3        642         TA
## 5     Attchd        2000          RFn          3        836         TA
## 6     Attchd        1993          Unf          2        480         TA
##   GarageCond PavedDrive WoodDeckSF OpenPorchSF EnclosedPorch X3SsnPorch
## 1         TA          Y          0          61             0          0
## 2         TA          Y        298           0             0          0
## 3         TA          Y          0          42             0          0
## 4         TA          Y          0          35           272          0
## 5         TA          Y        192          84             0          0
## 6         TA          Y         40          30             0        320
##   ScreenPorch PoolArea PoolQC Fence MiscFeature MiscVal MoSold YrSold
## 1           0        0   <NA>  <NA>        <NA>       0      2   2008
## 2           0        0   <NA>  <NA>        <NA>       0      5   2007
## 3           0        0   <NA>  <NA>        <NA>       0      9   2008
## 4           0        0   <NA>  <NA>        <NA>       0      2   2006
## 5           0        0   <NA>  <NA>        <NA>       0     12   2008
## 6           0        0   <NA> MnPrv        Shed     700     10   2009
##   SaleType SaleCondition SalePrice
## 1       WD        Normal    208500
## 2       WD        Normal    181500
## 3       WD        Normal    223500
## 4       WD       Abnorml    140000
## 5       WD        Normal    250000
## 6       WD        Normal    143000
#I will go ahead and use Sale Price as my dependent variable, as requested so it'll be my Y. For my X variable (independent), I will use Total Basement Square Footage.

X <- train.data$TotalBsmtSF
Y <- train.data$SalePrice

Probability. Calculate as a minimum the below probabilities a through c. Assume the small letter “x” is estimated as the 4th quartile of the X variable, and the small letter “y” is estimated as the 2nd quartile of the Y variable. Interpret the meaning of all probabilities.

  1. P(X > x |Y > y) = .4519231
require(dplyr)
## Loading required package: dplyr
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
x <- quantile(X, .75) #x is the estimated 4th quartile of X
y <- quantile(Y, .5) #y is the estimated 2nd quartile of Y 

num <- filter(train.data, SalePrice > y & TotalBsmtSF > x) %>% tally()/nrow(train.data)
den <- filter(train.data, SalePrice > y) %>% tally()/nrow(train.data)
p1 <- num/den
p1 
##           n
## 1 0.4519231

Below is how I arrived at the above code.

\[P(X > x |Y > y) = P(X > .75 |Y > .50)\] \[P(A|B) = P(B and A)/P(B)\] b. P(X>x, Y>y) = 0.1246575

num.b <- filter(train.data, TotalBsmtSF > x) %>% tally()/nrow(train.data)
den.b <- filter(train.data, SalePrice > y) %>% tally()/nrow(train.data)
p2 <- num.b * den.b
p2
##           n
## 1 0.1246575
  1. P(Xy) = 0.5480769
num.c <- filter(train.data, SalePrice > y & TotalBsmtSF < x) %>% tally()/nrow(train.data)
den.c <- filter(train.data, SalePrice > y) %>% tally()/nrow(train.data)
p3 <- num.c/den.c
p3
##           n
## 1 0.5480769

Does splitting the training data in this fashion make them independent? In other words, does P(X|Y)=P(X)P(Y))? Check mathematically, and then evaluate by running a Chi Square test for association. You might have to research this.

filter(train.data, SalePrice <= y & TotalBsmtSF <=x) %>% tally() #696
##     n
## 1 696
filter(train.data, SalePrice > y & TotalBsmtSF <=x) %>% tally() #399
##     n
## 1 399
filter(train.data, TotalBsmtSF <=x) %>% tally() #1095
##      n
## 1 1095
filter(train.data, SalePrice <= y & TotalBsmtSF > x) %>% tally() #36
##    n
## 1 36
filter(train.data, SalePrice > y & TotalBsmtSF > x) %>% tally() #329
##     n
## 1 329
filter(train.data, TotalBsmtSF > x) %>% tally()#365
##     n
## 1 365
filter(train.data, SalePrice <= y) %>% tally() #732
##     n
## 1 732
filter(train.data, SalePrice > y) %>% tally() #728
##     n
## 1 728
nrow(train.data)#1460
## [1] 1460
P.A = 365/1460  #.25
P.A
## [1] 0.25
P.B = 728/1460 #.5
P.B
## [1] 0.4986301
P.AB = P.A * P.B
P.AB
## [1] 0.1246575
#P(X > x |Y > y) = .4519231

#We can see mathematically that these two variables are dependent.

It does not appear that splitting up the data makes them independent. We will perform th Chi Square test to verify our mathematical findings

chi.test <- table(train.data$SalePrice, train.data$TotalBsmtSF)
#now we will do the chi test to find our signifance level

chisq.test(chi.test)
## Warning in chisq.test(chi.test): Chi-squared approximation may be incorrect
## 
##  Pearson's Chi-squared test
## 
## data:  chi.test
## X-squared = 509710, df = 476640, p-value < 2.2e-16
#Since our p-value is significantly less than .05, we can reject the null hypothesis stating that X and Y are independent. That is to say that there is dependence between the Sale Price and the Total Basement Square Foot.

Descriptive and Inferential Statistics. Provide univariate descriptive statistics and appropriate plots for both variables(SalePrice and TotalBsmtSF). * TotalBsmtSF: Total square feet of basement area * SalePrice: Price house sold for + I assumed on this description as it was not on the data description list.

require(ggplot2)
## Loading required package: ggplot2
summary(train.data$SalePrice)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   34900  129975  163000  180921  214000  755000
summary(train.data$TotalBsmtSF)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##     0.0   795.8   991.5  1057.4  1298.2  6110.0
ggplot(data=train.data, aes(SalePrice)) + geom_histogram(binwidth = 1000) 

#This plot looks slightly skewed to the right.

ggplot(data=train.data, aes(TotalBsmtSF)) + geom_histogram(binwidth = 100) 

#This plot also looks slightly skewed to the right.

Provide a scatterplot of X and Y.

ggplot(train.data, aes(x = TotalBsmtSF, y = SalePrice)) + geom_point(shape = 1) + geom_smooth(method = lm) + labs(x = "Basement Total Sq. Footage", y = "Total Sale Price", title = "Basement Square Footage vs. Sale Price")

#I used geom_smooth to add a linear regression line which is by default a 95% confidence interval region

Transform both variables simultaneously using Box-Cox transformations.You might have to research this.

#I found a lot of useful information on the following website:  http://rstudio-pubs-static.s3.amazonaws.com/63893_9f6bc9cd73ad47aab3aa85d0193244d9.html

require(MASS)
## Loading required package: MASS
## 
## Attaching package: 'MASS'
## The following object is masked from 'package:dplyr':
## 
##     select
bc <- lm(train.data$SalePrice ~ train.data$TotalBsmtSF)
trans <- boxcox(bc, lambda=seq(-2,2,.1), plotit = FALSE, interp = TRUE)
trans.test.data <- as.data.frame(trans)
lamda <- trans.test.data[which.max(trans$y),1]
lamda #0.02020202
## [1] 0.02020202
new.data <- cbind(X, Y, train.data$SalePrice^lamda, train.data$TotalBsmtSF^lamda)
colnames(new.data) <- c("TotalBsmtSF", "SalePrice", "Trans.SalePrice", "Trans.TB")
head(new.data)
##      TotalBsmtSF SalePrice Trans.SalePrice Trans.TB
## [1,]         856    208500        1.280727 1.146151
## [2,]        1262    181500        1.277144 1.155175
## [3,]         920    223500        1.282526 1.147822
## [4,]         756    140000        1.270463 1.143278
## [5,]        1145    250000        1.285433 1.152906
## [6,]         796    143000        1.271008 1.144470

Using the transformed variables, run a correlation analysis and interpret. Test the hypothesis that the correlation between these variables is 0 and provide a 99% confidence interval.Discuss the meaning of your analysis.

#For some odd reason, it was not easy for me to subset the data frame for just the columns I need. I used this site for assistance: https://stackoverflow.com/questions/10085806/extracting-specific-columns-from-a-data-frame

trans.data <- new.data[,c("Trans.SalePrice", "Trans.TB")]
head(trans.data)
##      Trans.SalePrice Trans.TB
## [1,]        1.280727 1.146151
## [2,]        1.277144 1.155175
## [3,]        1.282526 1.147822
## [4,]        1.270463 1.143278
## [5,]        1.285433 1.152906
## [6,]        1.271008 1.144470
require(corrplot)
## Loading required package: corrplot
require(stats)
corr. <- cor(trans.data)
corrplot(corr., method = "ellipse")

corrplot(corr., method = "number")

#https://cran.r-project.org/web/packages/corrplot/vignettes/corrplot-intro.html
TSP <- new.data[,"Trans.SalePrice"]
TTB <- new.data[,"Trans.TB"]
TBSF <- new.data[,"TotalBsmtSF"]
SP <- new.data[,"SalePrice"]

c.test <- cor.test(TSP,TTB,  method = "pearson", conf.level = .99)
c.test
## 
##  Pearson's product-moment correlation
## 
## data:  TSP and TTB
## t = 8.844, df = 1458, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 99 percent confidence interval:
##  0.1607066 0.2886342
## sample estimates:
##       cor 
## 0.2256429
#https://stat.ethz.ch/R-manual/R-devel/library/stats/html/cor.test.html

From both the numerical and ellipse correlation plot, we see that there is a correlation betweeen the two variables. The confidence interval is [0.1607066, 0.2886342]. From this, we reject our null hypothesis, which we proved is incorrect when we showed that there is a strong correlation between Total Basement SF and Total Sale Price.

prec <- solve(corr.)

ans <- corr. * prec
ans2 <- prec * corr.

ans
##                 Trans.SalePrice    Trans.TB
## Trans.SalePrice      1.05364608 -0.05364608
## Trans.TB            -0.05364608  1.05364608
ans2
##                 Trans.SalePrice    Trans.TB
## Trans.SalePrice      1.05364608 -0.05364608
## Trans.TB            -0.05364608  1.05364608

Many times, it makes sense to fit a closed form distribution to data. For your non-transformed independent variable, location shift it so that the minimum value is above zero. Then load the MASS package and run fitdistr to fit a density function of your choice. (See https://stat.ethz.ch/R-manual/R-devel/library/MASS/html/fitdistr.html ). Find the optimal value of the parameters for this distribution, and then take 1000 samples from this distribution (e.g., rexp(1000, ???) for an exponential). Plot a histogram and compare it with a histogram of your non-transformed original variable.

min(train.data$TotalBsmtSF)
## [1] 0
fit.data <- cbind(SP, TBSF)
zero_sub = apply(fit.data, 1, function(row) all(row !=0 ))

FD <- fit.data[zero_sub,]
FD
##             SP TBSF
##    [1,] 208500  856
##    [2,] 181500 1262
##    [3,] 223500  920
##    [4,] 140000  756
##    [5,] 250000 1145
##    [6,] 143000  796
##    [7,] 307000 1686
##    [8,] 200000 1107
##    [9,] 129900  952
##   [10,] 118000  991
##   [11,] 129500 1040
##   [12,] 345000 1175
##   [13,] 144000  912
##   [14,] 279500 1494
##   [15,] 157000 1253
##   [16,] 132000  832
##   [17,] 149000 1004
##   [18,] 159000 1114
##   [19,] 139000 1029
##   [20,] 325300 1158
##   [21,] 139400  637
##   [22,] 230000 1777
##   [23,] 129900 1040
##   [24,] 154000 1060
##   [25,] 256300 1566
##   [26,] 134800  900
##   [27,] 306000 1704
##   [28,] 207500 1484
##   [29,]  68500  520
##   [30,]  40000  649
##   [31,] 149350 1228
##   [32,] 179900 1234
##   [33,] 165500 1398
##   [34,] 277500 1561
##   [35,] 309000 1117
##   [36,] 145000 1097
##   [37,] 153000 1297
##   [38,] 109000 1057
##   [39,] 160000 1088
##   [40,] 170000 1350
##   [41,] 144000  840
##   [42,] 130250  938
##   [43,] 141000 1150
##   [44,] 319900 1752
##   [45,] 239686 1434
##   [46,] 249700 1656
##   [47,] 113000  736
##   [48,] 127000  955
##   [49,] 177000  794
##   [50,] 114500  816
##   [51,] 110000  816
##   [52,] 385000 1842
##   [53,] 130000  384
##   [54,] 180500 1425
##   [55,] 172500  970
##   [56,] 196500  860
##   [57,] 438780 1410
##   [58,] 124900  780
##   [59,] 158000 1158
##   [60,] 101000  530
##   [61,] 202500 1370
##   [62,] 140000  576
##   [63,] 219500 1057
##   [64,] 317000 1143
##   [65,] 180000 1947
##   [66,] 226000 1453
##   [67,]  80000  747
##   [68,] 225000 1304
##   [69,] 244000 2223
##   [70,] 129500  845
##   [71,] 185000  832
##   [72,] 144900 1086
##   [73,] 107400  840
##   [74,]  91000  462
##   [75,] 135750  952
##   [76,] 127000  672
##   [77,] 136500 1768
##   [78,] 110000  440
##   [79,] 193500  896
##   [80,] 153500 1237
##   [81,] 245000 1563
##   [82,] 126500 1065
##   [83,] 168500  384
##   [84,] 260000 1288
##   [85,] 174000  684
##   [86,] 164500  612
##   [87,]  85000 1013
##   [88,] 123600  990
##   [89,]  98600 1235
##   [90,] 163500  876
##   [91,] 133900 1214
##   [92,] 204750  824
##   [93,] 185000  680
##   [94,] 214000 1588
##   [95,]  94750  960
##   [96,]  83000  458
##   [97,] 128950  950
##   [98,] 205000 1610
##   [99,] 178000  741
##  [100,] 198900 1226
##  [101,] 169500 1040
##  [102,] 250000 1053
##  [103,] 100000  641
##  [104,] 115000  789
##  [105,] 115000  793
##  [106,] 190000 1844
##  [107,] 136900  994
##  [108,] 180000  384
##  [109,] 383970 1264
##  [110,] 217000 1809
##  [111,] 259500 1028
##  [112,] 176000  729
##  [113,] 139000 1092
##  [114,] 155000 1125
##  [115,] 320000 1673
##  [116,] 163990  728
##  [117,] 180000  938
##  [118,] 100000  732
##  [119,] 136000 1080
##  [120,] 153900 1199
##  [121,] 181000 1362
##  [122,]  84500  520
##  [123,] 128000 1078
##  [124,]  87000  672
##  [125,] 155000  660
##  [126,] 150000 1008
##  [127,] 226000  924
##  [128,] 244000  992
##  [129,] 150750 1063
##  [130,] 220000 1267
##  [131,] 180000 1461
##  [132,] 174000 1304
##  [133,] 143000 1214
##  [134,] 171000 1907
##  [135,] 230000 1004
##  [136,] 231500  928
##  [137,] 115000  864
##  [138,] 260000 1734
##  [139,] 166000  910
##  [140,] 204000 1490
##  [141,] 125000 1728
##  [142,] 130000  970
##  [143,] 105000  715
##  [144,] 222500  884
##  [145,] 141000 1080
##  [146,] 115000  896
##  [147,] 122000  969
##  [148,] 372402 1710
##  [149,] 190000  825
##  [150,] 235000 1602
##  [151,] 125000 1200
##  [152,]  79000  572
##  [153,] 269500  774
##  [154,] 254900  991
##  [155,] 320000 1392
##  [156,] 162500 1232
##  [157,] 412500 1572
##  [158,] 220000 1541
##  [159,] 103200  882
##  [160,] 152000 1149
##  [161,] 127500  644
##  [162,] 190000 1617
##  [163,] 325624 1582
##  [164,] 183500  840
##  [165,] 228000 1686
##  [166,] 128500  720
##  [167,] 215000 1080
##  [168,] 239000 1064
##  [169,] 163000 1362
##  [170,] 184000 1606
##  [171,] 243000 1202
##  [172,] 211000 1151
##  [173,] 172500 1052
##  [174,] 501837 2216
##  [175,] 100000  968
##  [176,] 177000  756
##  [177,] 200100  793
##  [178,] 200000 1362
##  [179,] 127000  504
##  [180,] 475000 1107
##  [181,] 173000 1188
##  [182,] 135000  660
##  [183,] 153337 1086
##  [184,] 286000 1593
##  [185,] 315000  853
##  [186,] 184000  725
##  [187,] 192000 1431
##  [188,] 130000  970
##  [189,] 127000  864
##  [190,] 148500  855
##  [191,] 311872 1726
##  [192,] 235000 1360
##  [193,] 104000  755
##  [194,] 274900 1713
##  [195,] 140000 1121
##  [196,] 171500 1196
##  [197,] 112000  617
##  [198,] 149000  848
##  [199,] 110000  720
##  [200,] 180500 1424
##  [201,] 143900 1140
##  [202,] 141000 1100
##  [203,] 277000 1157
##  [204,] 145000 1092
##  [205,]  98000  864
##  [206,] 186000 1212
##  [207,] 252678  900
##  [208,] 156000  990
##  [209,] 161750  689
##  [210,] 134450 1070
##  [211,] 210000 1436
##  [212,] 107000  686
##  [213,] 311500  798
##  [214,] 167240 1248
##  [215,] 204900 1498
##  [216,] 200000 1010
##  [217,] 179900  713
##  [218,]  97000  864
##  [219,] 386250 2392
##  [220,] 112000  630
##  [221,] 290000 1203
##  [222,] 106000  483
##  [223,] 125000  912
##  [224,] 192500 1373
##  [225,] 148000 1194
##  [226,] 403000 1462
##  [227,]  94500  483
##  [228,] 128200  894
##  [229,] 216500  860
##  [230,]  89500  483
##  [231,] 185500 1414
##  [232,] 194500  996
##  [233,] 318000 1694
##  [234,] 113000  735
##  [235,] 262500 1566
##  [236,] 110500  686
##  [237,]  79000  540
##  [238,] 120000  626
##  [239,] 205000  948
##  [240,] 241500 1845
##  [241,] 137000 1020
##  [242,] 140000 1367
##  [243,] 180000  840
##  [244,] 277000 1444
##  [245,]  76500  728
##  [246,] 235000 1573
##  [247,] 173000  798
##  [248,] 158000 1302
##  [249,] 145000 1314
##  [250,] 230000  975
##  [251,] 207500  864
##  [252,] 220000 1604
##  [253,] 231500  963
##  [254,] 176000 1362
##  [255,] 276000 1482
##  [256,] 151000  506
##  [257,] 130000  926
##  [258,]  73000  680
##  [259,] 175500 1422
##  [260,] 185000  802
##  [261,] 179500  720
##  [262,] 120500  740
##  [263,] 148000 1143
##  [264,] 266000 1095
##  [265,] 241500 1385
##  [266,] 290000 1152
##  [267,] 139000 1240
##  [268,] 124500  816
##  [269,] 205000  952
##  [270,] 201000 1560
##  [271,] 141000  864
##  [272,] 415298 2121
##  [273,] 192000 1160
##  [274,] 228500  807
##  [275,] 185000 1262
##  [276,] 207500 1314
##  [277,] 244600 1468
##  [278,] 179200 1575
##  [279,] 164700  625
##  [280,] 159000  912
##  [281,]  88000  858
##  [282,] 122000  882
##  [283,] 153575  698
##  [284,] 233230 1079
##  [285,] 135900  780
##  [286,] 131000  768
##  [287,] 235000  795
##  [288,] 167000 1416
##  [289,] 142500 1003
##  [290,] 152000  910
##  [291,] 239000  975
##  [292,] 175000  702
##  [293,] 158500 1092
##  [294,] 157000 1165
##  [295,] 267000 1028
##  [296,] 205000 1541
##  [297,] 149900  894
##  [298,] 295000 1470
##  [299,] 305900 2000
##  [300,] 225000  700
##  [301,]  89500  319
##  [302,]  82500  861
##  [303,] 360000 1896
##  [304,] 165600  697
##  [305,] 132000  972
##  [306,] 119900  793
##  [307,] 375000 2136
##  [308,] 178000  728
##  [309,] 188500  716
##  [310,] 260000  845
##  [311,] 270000 1088
##  [312,] 260000 1347
##  [313,] 187500 1372
##  [314,] 342643 1249
##  [315,] 354000 1136
##  [316,] 301000 1502
##  [317,] 126175 1162
##  [318,] 242000  710
##  [319,]  87000  720
##  [320,] 324000 1719
##  [321,] 145250 1383
##  [322,] 214500  844
##  [323,]  78000  596
##  [324,] 119000 1728
##  [325,] 139000 1056
##  [326,] 284000 3206
##  [327,] 207000 1358
##  [328,] 192000  943
##  [329,] 228950 1499
##  [330,] 377426 1922
##  [331,] 214000 1536
##  [332,] 202500 1208
##  [333,] 155000 1215
##  [334,] 202900  967
##  [335,]  82000  721
##  [336,] 266000 1684
##  [337,]  85000  536
##  [338,] 140200  972
##  [339,] 151500  958
##  [340,] 157500 1478
##  [341,] 154000  764
##  [342,] 437154 1848
##  [343,] 318061 1869
##  [344,] 190000 1453
##  [345,]  95000  616
##  [346,] 105900  624
##  [347,] 140000  940
##  [348,] 177500 1200
##  [349,] 173000 1158
##  [350,] 134000 1142
##  [351,] 130000 1062
##  [352,] 280000 1086
##  [353,] 156000  888
##  [354,] 145000  883
##  [355,] 118000  483
##  [356,] 190000  796
##  [357,] 147000  672
##  [358,] 159000 1394
##  [359,] 165000 1099
##  [360,] 132000 1268
##  [361,] 162000 1063
##  [362,] 172400  953
##  [363,] 125000  744
##  [364,] 123000  608
##  [365,] 219500  847
##  [366,]  61000  683
##  [367,] 148000  870
##  [368,] 340000 1580
##  [369,] 394432 1856
##  [370,] 179000  982
##  [371,] 127000 1026
##  [372,] 187750 1293
##  [373,] 213500  939
##  [374,]  76000  784
##  [375,] 240000 1580
##  [376,] 192000 1256
##  [377,]  81000  658
##  [378,] 125000 1041
##  [379,] 191000 1468
##  [380,] 426000 1682
##  [381,] 119000  861
##  [382,] 215000  804
##  [383,] 100000  788
##  [384,] 109000  735
##  [385,] 129000 1144
##  [386,] 123000  894
##  [387,] 169500  864
##  [388,]  67000  961
##  [389,] 241000 1092
##  [390,] 245500 1260
##  [391,] 164990 1310
##  [392,] 108000  672
##  [393,] 258000 1141
##  [394,] 168000  806
##  [395,] 150000 1281
##  [396,] 115000 1064
##  [397,] 177000  840
##  [398,] 280000 1063
##  [399,] 339750 1034
##  [400,]  60000 1276
##  [401,] 145000 1056
##  [402,] 222000 1470
##  [403,] 115000 1008
##  [404,] 228000 1080
##  [405,] 181134 1340
##  [406,] 149500  672
##  [407,] 239000 1370
##  [408,] 126000  756
##  [409,] 142000 1056
##  [410,] 206300 1344
##  [411,] 215000 1602
##  [412,] 113000  988
##  [413,] 315000 1470
##  [414,] 139000 1196
##  [415,] 135000  651
##  [416,] 275000 1518
##  [417,] 109008  907
##  [418,] 195400 1208
##  [419,] 175000 1392
##  [420,]  85400  483
##  [421,]  79900  901
##  [422,] 122500  765
##  [423,] 181000  926
##  [424,]  81000  630
##  [425,] 212000  799
##  [426,] 116000  648
##  [427,] 119000  884
##  [428,]  90350  440
##  [429,] 110000  684
##  [430,] 555000 3094
##  [431,] 118000 1440
##  [432,] 162900 1078
##  [433,] 172500 1258
##  [434,] 210000  915
##  [435,] 127500 1436
##  [436,] 190000 1517
##  [437,] 199900  930
##  [438,] 119500  780
##  [439,] 120000  649
##  [440,] 110000  813
##  [441,] 280000 1533
##  [442,] 204000  872
##  [443,] 210000  768
##  [444,] 188000 1728
##  [445,] 175500 1242
##  [446,]  98000  624
##  [447,] 256000 1364
##  [448,] 161000  588
##  [449,] 110000  709
##  [450,] 263435  832
##  [451,] 155000  560
##  [452,]  62383  864
##  [453,] 188700  715
##  [454,] 124000 1040
##  [455,] 178740 1375
##  [456,] 167000 1277
##  [457,] 146500  728
##  [458,] 250000 1626
##  [459,] 187000  832
##  [460,] 212000 1488
##  [461,] 190000  808
##  [462,] 148000  547
##  [463,] 440000 1976
##  [464,] 251000 1494
##  [465,] 132500  970
##  [466,] 208900 1478
##  [467,] 380000 2153
##  [468,] 297000 1705
##  [469,]  89471  907
##  [470,] 326000 1833
##  [471,] 374000 1792
##  [472,] 155000  910
##  [473,] 164000 1216
##  [474,] 132500  999
##  [475,] 147000 1113
##  [476,] 156000 1073
##  [477,] 175000 1484
##  [478,] 160000  954
##  [479,]  86000  630
##  [480,] 115000  264
##  [481,] 133000  806
##  [482,] 172785  728
##  [483,] 155000 1269
##  [484,]  91300  190
##  [485,]  34900  720
##  [486,] 430000 3200
##  [487,] 184000 1026
##  [488,] 130000  864
##  [489,] 120000  912
##  [490,] 113000  672
##  [491,] 226700  866
##  [492,] 140000 1214
##  [493,] 289000 1501
##  [494,] 147000  855
##  [495,] 124500  960
##  [496,] 215000  777
##  [497,] 208300 1218
##  [498,] 161000  689
##  [499,] 124500 1041
##  [500,] 164900 1008
##  [501,] 202665 1368
##  [502,] 129900  864
##  [503,] 134000 1084
##  [504,]  96500  768
##  [505,] 402861 2006
##  [506,] 158000  689
##  [507,] 265000 1264
##  [508,] 211000  794
##  [509,] 234000 1276
##  [510,] 150000 1244
##  [511,] 159000 1004
##  [512,] 184750 3138
##  [513,] 315750 1379
##  [514,] 176000 1257
##  [515,] 132000  928
##  [516,] 446261 1452
##  [517,]  86000  528
##  [518,] 200624 2035
##  [519,] 175000 1461
##  [520,] 128000  611
##  [521,] 178000  707
##  [522,] 107500 1117
##  [523,] 188000  880
##  [524,] 111250  864
##  [525,] 158000 1051
##  [526,] 272000 1581
##  [527,] 315000 1838
##  [528,] 248000  969
##  [529,] 213250 1650
##  [530,] 133000  723
##  [531,] 179665  654
##  [532,] 229000 1204
##  [533,] 210000 1065
##  [534,] 129500  768
##  [535,] 125000  825
##  [536,] 263000  912
##  [537,] 140000 1069
##  [538,] 112500  928
##  [539,] 255500 1709
##  [540,] 284000  998
##  [541,] 113000  993
##  [542,] 141000 1092
##  [543,] 108000  637
##  [544,] 175000  729
##  [545,] 234000 1374
##  [546,] 121500 1392
##  [547,] 170000 1389
##  [548,] 108000  996
##  [549,] 185000 1163
##  [550,] 268000 1095
##  [551,] 128000  806
##  [552,] 325000 1122
##  [553,] 214000 1517
##  [554,] 316600 1496
##  [555,] 135960  943
##  [556,] 142600 1728
##  [557,] 120000  864
##  [558,] 224500  846
##  [559,] 170000  384
##  [560,] 139000  372
##  [561,] 118500  832
##  [562,] 145000  861
##  [563,] 164500 1164
##  [564,] 146000  689
##  [565,] 131500 1050
##  [566,] 181900 1144
##  [567,] 253293 2042
##  [568,] 118500  816
##  [569,] 325000 1237
##  [570,] 133000  884
##  [571,] 369900 1868
##  [572,] 130000  816
##  [573,] 137000  840
##  [574,] 143000 1437
##  [575,]  79500  742
##  [576,] 185900  770
##  [577,] 451950 1722
##  [578,] 138000  816
##  [579,] 140000  848
##  [580,] 110000  924
##  [581,] 319000 1814
##  [582,] 114504  684
##  [583,] 194201 1258
##  [584,] 217500 1430
##  [585,] 151000  716
##  [586,] 275000 1058
##  [587,] 141000  780
##  [588,] 220000  908
##  [589,] 151000  600
##  [590,] 221000 1494
##  [591,] 205000  768
##  [592,] 152000 1040
##  [593,] 225000  896
##  [594,] 359100  965
##  [595,] 118500 1029
##  [596,] 313000 1440
##  [597,] 148000 1032
##  [598,] 261500 1299
##  [599,] 147000 1120
##  [600,]  75500  630
##  [601,] 137500  936
##  [602,] 183200  783
##  [603,] 105500  832
##  [604,] 314813 1822
##  [605,] 305000 1482
##  [606,]  67000  864
##  [607,] 240000 1522
##  [608,] 135000  980
##  [609,] 168500  756
##  [610,] 165150  732
##  [611,] 160000 1116
##  [612,] 139900  978
##  [613,] 153000 1156
##  [614,] 135000 1040
##  [615,] 168500 1248
##  [616,] 124000  636
##  [617,] 209500 1554
##  [618,]  82500 1386
##  [619,] 139400 1056
##  [620,] 144000 1056
##  [621,] 200000 1440
##  [622,]  60000  264
##  [623,]  93000  811
##  [624,]  85000  796
##  [625,] 264561 1520
##  [626,] 274000 1518
##  [627,] 226000 1057
##  [628,] 345000 1952
##  [629,] 152000  780
##  [630,] 370878 1766
##  [631,] 143250  981
##  [632,] 155000 1094
##  [633,] 155000  756
##  [634,]  84500  630
##  [635,] 205950  813
##  [636,] 108000  755
##  [637,] 191000  880
##  [638,] 135000  756
##  [639,] 350000 2109
##  [640,]  88000  525
##  [641,] 145500 1053
##  [642,] 149000  776
##  [643,]  97500  912
##  [644,] 167000 1486
##  [645,] 197900  793
##  [646,] 402000 1629
##  [647,] 110000 1392
##  [648,] 137500 1138
##  [649,] 423000 2077
##  [650,] 230500 1406
##  [651,] 129000 1021
##  [652,] 193500 1408
##  [653,] 168000 1188
##  [654,] 137500  700
##  [655,] 173500  738
##  [656,] 103600  672
##  [657,] 165000 1208
##  [658,] 257500 1477
##  [659,] 140000 1136
##  [660,] 148500  855
##  [661,]  87000 1095
##  [662,] 109500  768
##  [663,] 372500 2046
##  [664,] 128500  988
##  [665,] 143000  923
##  [666,] 159434  793
##  [667,] 173000 1291
##  [668,] 285000 1626
##  [669,] 221000 1195
##  [670,] 207500 1190
##  [671,] 227875  874
##  [672,] 148800  551
##  [673,] 392000 1419
##  [674,] 194700 1362
##  [675,] 141000  848
##  [676,] 755000 2444
##  [677,] 335000 1210
##  [678,] 108480 1073
##  [679,] 141500  927
##  [680,] 176000 1112
##  [681,]  89000  616
##  [682,] 123500  980
##  [683,] 138500  894
##  [684,] 196000 1391
##  [685,] 312500 1800
##  [686,] 140000 1164
##  [687,] 361919 1234
##  [688,] 140000  360
##  [689,] 213000 1473
##  [690,] 302000 1643
##  [691,] 254000 1324
##  [692,] 179540  728
##  [693,] 109900  876
##  [694,]  52000  270
##  [695,] 102776  859
##  [696,] 189000 1228
##  [697,] 129000  960
##  [698,] 130500  725
##  [699,] 165000 1064
##  [700,] 159500  718
##  [701,] 157000 1176
##  [702,] 341000 1311
##  [703,] 128500  971
##  [704,] 275000 1742
##  [705,] 143000  848
##  [706,] 124500  864
##  [707,] 135000  941
##  [708,] 320000 1698
##  [709,] 120500  864
##  [710,] 222000  880
##  [711,] 194500 1232
##  [712,] 110000 1584
##  [713,] 103000  780
##  [714,] 236500 1595
##  [715,] 187500  868
##  [716,] 222500 1153
##  [717,] 131400  864
##  [718,] 108000  948
##  [719,] 163000  880
##  [720,] 239900  893
##  [721,] 179000 1200
##  [722,] 190000  864
##  [723,] 132000  264
##  [724,] 142000  912
##  [725,] 179000 1349
##  [726,] 175000  520
##  [727,] 180000 1337
##  [728,] 299800 1142
##  [729,] 236000  952
##  [730,] 265979 1240
##  [731,] 260400 1720
##  [732,]  96500  576
##  [733,] 162000  660
##  [734,] 217000 1479
##  [735,] 275500 1030
##  [736,] 156000 1026
##  [737,] 172500  729
##  [738,] 212000  866
##  [739,] 158900  672
##  [740,] 179400  744
##  [741,] 290000 1318
##  [742,] 127500  864
##  [743,] 100000 1145
##  [744,] 215200  756
##  [745,] 337000 1252
##  [746,] 270000 1494
##  [747,] 264132 1498
##  [748,] 196500  980
##  [749,] 160000  983
##  [750,] 216837 1860
##  [751,] 538000 1650
##  [752,] 134900  858
##  [753,] 102000  836
##  [754,] 107000 1029
##  [755,] 114500  912
##  [756,] 395000 1935
##  [757,] 162000 1204
##  [758,] 221500 1614
##  [759,] 142500  864
##  [760,] 135000  975
##  [761,] 176000 1237
##  [762,] 175900  761
##  [763,] 187100 1413
##  [764,] 165500 1097
##  [765,] 128000  742
##  [766,] 161500 1372
##  [767,] 139000  686
##  [768,] 233000  956
##  [769,] 107900  901
##  [770,] 187500  832
##  [771,] 160200 1145
##  [772,] 146800 1029
##  [773,] 269790 1117
##  [774,] 225000 1496
##  [775,] 194500  712
##  [776,] 171000  650
##  [777,] 143500  660
##  [778,] 110000  773
##  [779,] 485000 1926
##  [780,] 175000  731
##  [781,] 200000  616
##  [782,] 109900 1196
##  [783,] 189000  728
##  [784,] 582933 1734
##  [785,] 118000  936
##  [786,] 227680 1417
##  [787,] 135500  980
##  [788,] 223500 1324
##  [789,] 159950 1024
##  [790,] 106000  849
##  [791,] 181000 1040
##  [792,] 144500  848
##  [793,]  55993  540
##  [794,] 157900 1442
##  [795,] 116000  686
##  [796,] 224900 1649
##  [797,] 137000 1008
##  [798,] 271000 1568
##  [799,] 155000 1010
##  [800,] 224000 1358
##  [801,] 183000  798
##  [802,]  93000  936
##  [803,] 225000  847
##  [804,] 139500  778
##  [805,] 232600 1489
##  [806,] 385000 2078
##  [807,] 109500  784
##  [808,] 189000 1454
##  [809,] 185000 1013
##  [810,] 147400  600
##  [811,] 166000 1392
##  [812,] 151000  600
##  [813,] 237000  941
##  [814,] 167000 1516
##  [815,] 139950 1144
##  [816,] 128000 1067
##  [817,] 153500 1559
##  [818,] 100000  483
##  [819,] 144000 1099
##  [820,] 130500  768
##  [821,] 140000  672
##  [822,] 157500  650
##  [823,] 174900 1127
##  [824,] 141000 1800
##  [825,] 153900  876
##  [826,] 171000 1390
##  [827,] 213000  740
##  [828,] 133500  864
##  [829,] 240000  907
##  [830,] 187000  528
##  [831,] 131500  848
##  [832,] 215000 1273
##  [833,] 164000  918
##  [834,] 158000 1127
##  [835,] 170000 1763
##  [836,] 127000 1040
##  [837,] 147000  940
##  [838,] 174000  702
##  [839,] 152000 1090
##  [840,] 250000 1054
##  [841,] 189950  912
##  [842,] 131500 1039
##  [843,] 152000 1040
##  [844,] 132500 1148
##  [845,] 250580 1372
##  [846,] 148500 1002
##  [847,] 248900 1638
##  [848,] 129000 1040
##  [849,] 236000 1050
##  [850,] 109500  894
##  [851,] 200500  804
##  [852,] 116000  105
##  [853,] 133000  832
##  [854,]  66500  676
##  [855,] 303477 1184
##  [856,] 132250 1064
##  [857,] 350000 1462
##  [858,] 148000 1109
##  [859,] 136500  864
##  [860,] 157000 1090
##  [861,] 187500 1156
##  [862,] 178000  808
##  [863,] 118500  795
##  [864,] 100000  892
##  [865,] 328900 1698
##  [866,] 145000 1626
##  [867,] 135500  816
##  [868,] 268000 2217
##  [869,] 149500 1505
##  [870,] 122900  672
##  [871,] 172500  918
##  [872,] 154500 1059
##  [873,] 165000 1383
##  [874,] 140000  780
##  [875,] 106500  951
##  [876,] 611657 2330
##  [877,] 135000  912
##  [878,] 110000  858
##  [879,] 153000  992
##  [880,] 180000  783
##  [881,] 240000 1670
##  [882,] 125500  876
##  [883,] 128000 1056
##  [884,] 255000 1623
##  [885,] 250000 1017
##  [886,] 131000  864
##  [887,] 174000  742
##  [888,] 154300 1105
##  [889,] 143500 1268
##  [890,]  88000  768
##  [891,] 145000 1001
##  [892,] 173733  612
##  [893,]  75000  546
##  [894,]  35311  480
##  [895,] 135000 1134
##  [896,] 238000 1104
##  [897,] 176500 1184
##  [898,] 201000  928
##  [899,] 145900 1272
##  [900,] 169990 1316
##  [901,] 193000 1604
##  [902,] 207500 1686
##  [903,] 175000 1126
##  [904,] 285000 1181
##  [905,] 176000  832
##  [906,] 236500 1753
##  [907,] 222000  964
##  [908,] 201000 1466
##  [909,] 117500  925
##  [910,] 320000 1905
##  [911,] 190000 1500
##  [912,] 242000  585
##  [913,]  79900  600
##  [914,] 184900 1176
##  [915,] 253000 1113
##  [916,] 239799 1391
##  [917,] 244400 1032
##  [918,] 150900 1728
##  [919,] 214000  992
##  [920,] 150000 1440
##  [921,] 143000 1632
##  [922,] 137500  819
##  [923,] 124900 1088
##  [924,] 143000 1144
##  [925,] 270000 1616
##  [926,] 192500  936
##  [927,] 197500 1161
##  [928,] 129000  864
##  [929,] 119900  828
##  [930,] 133900  768
##  [931,] 172000  784
##  [932,] 127500  945
##  [933,] 145000  979
##  [934,] 124000  561
##  [935,] 132000 1057
##  [936,] 185000 1337
##  [937,] 155000  696
##  [938,] 116500  858
##  [939,] 272000 1330
##  [940,] 155000  804
##  [941,] 239000 1800
##  [942,] 214900  817
##  [943,] 178900  783
##  [944,] 160000  728
##  [945,] 135000 1098
##  [946,]  37900  600
##  [947,] 140000  588
##  [948,] 135000  720
##  [949,] 173000  764
##  [950,]  99500  918
##  [951,] 182000 1428
##  [952,] 167500  728
##  [953,] 165000  673
##  [954,]  85500  440
##  [955,] 199900 1241
##  [956,] 110000  894
##  [957,] 139000 1121
##  [958,] 178400  944
##  [959,] 336000 1225
##  [960,] 159895 1266
##  [961,] 255900 1128
##  [962,] 125000 1164
##  [963,] 117000  485
##  [964,] 395192 1930
##  [965,] 195000  848
##  [966,] 197000  770
##  [967,] 348000 1396
##  [968,] 168000  916
##  [969,] 187000  822
##  [970,] 173900  750
##  [971,] 337500 1700
##  [972,] 121600  747
##  [973,] 136500 1050
##  [974,] 185000 1442
##  [975,]  91000 1007
##  [976,] 206000 1187
##  [977,]  86000  691
##  [978,] 232000 1574
##  [979,] 136905 1680
##  [980,] 181000 1346
##  [981,] 149900  985
##  [982,] 163500 1657
##  [983,]  88000  546
##  [984,] 240000 1710
##  [985,] 102000 1008
##  [986,] 135000  720
##  [987,] 165000  602
##  [988,]  85000 1022
##  [989,] 119200 1082
##  [990,] 227000  810
##  [991,] 203000 1504
##  [992,] 187500 1220
##  [993,] 160000  384
##  [994,] 213490 1362
##  [995,] 176000 1132
##  [996,] 194000 1199
##  [997,]  87000  912
##  [998,] 191000 1346
##  [999,] 287000 1565
## [1000,] 112500  882
## [1001,] 167500 1268
## [1002,] 293077 1638
## [1003,] 105000  768
## [1004,] 118000  672
## [1005,] 160000  686
## [1006,] 197000  824
## [1007,] 310000 1338
## [1008,] 230000 1654
## [1009,] 119750  920
## [1010,] 315500 1620
## [1011,] 287000 1055
## [1012,]  97000  546
## [1013,]  80000  630
## [1014,] 155000 1134
## [1015,] 173000  800
## [1016,] 196000 1306
## [1017,] 262280 1475
## [1018,] 278000 2524
## [1019,] 556581 1992
## [1020,] 145000  990
## [1021,] 176485 1302
## [1022,] 200141 1316
## [1023,] 165000  816
## [1024,] 144500 1216
## [1025,] 255000 1065
## [1026,] 180000 1193
## [1027,] 185850 1364
## [1028,] 248000  973
## [1029,] 335000 1104
## [1030,] 220000  854
## [1031,] 213500 1338
## [1032,]  81000  894
## [1033,]  90000  662
## [1034,] 110500 1103
## [1035,] 154000 1154
## [1036,] 328000 1306
## [1037,] 178000  799
## [1038,] 167900  780
## [1039,] 151400  942
## [1040,] 135000  845
## [1041,] 135000 1048
## [1042,] 154000  727
## [1043,]  91500  810
## [1044,] 159500  690
## [1045,] 194000 1240
## [1046,] 219500  800
## [1047,] 170000  796
## [1048,] 138800 1096
## [1049,] 155900  848
## [1050,] 126000  990
## [1051,] 145000 1258
## [1052,] 133000 1040
## [1053,] 192000 1459
## [1054,] 160000 1251
## [1055,] 187500  691
## [1056,] 147000  936
## [1057,]  83500  546
## [1058,] 252000 1082
## [1059,] 137500  970
## [1060,] 197000 1247
## [1061,] 160000  600
## [1062,] 136500 1181
## [1063,] 146000  864
## [1064,] 129000  936
## [1065,] 176432 1314
## [1066,] 127000  684
## [1067,] 170000 1074
## [1068,] 128000  672
## [1069,] 157000 1271
## [1070,]  60000  290
## [1071,] 119500  950
## [1072,] 135000 1010
## [1073,] 159500  655
## [1074,] 106000  630
## [1075,] 325000 1463
## [1076,] 179900  910
## [1077,] 274725  868
## [1078,] 181000  924
## [1079,] 280000 1836
## [1080,] 188000  773
## [1081,] 205000  803
## [1082,] 129900  816
## [1083,] 134500 1008
## [1084,] 117000  833
## [1085,] 318000 1734
## [1086,] 184100  408
## [1087,] 130000  894
## [1088,] 140000  533
## [1089,] 133700 1040
## [1090,] 118400 1012
## [1091,] 212900 1552
## [1092,] 112000  672
## [1093,] 118000  698
## [1094,] 163900  384
## [1095,] 115000 1005
## [1096,] 174000 1373
## [1097,] 259000 1530
## [1098,] 215000  847
## [1099,] 140000  936
## [1100,] 135000 1122
## [1101,]  93500  974
## [1102,] 117500 1008
## [1103,] 239500 1128
## [1104,] 169000  916
## [1105,] 102000  960
## [1106,] 119000 1032
## [1107,]  94000  780
## [1108,] 196000 1567
## [1109,] 144000  915
## [1110,] 139000  952
## [1111,] 197500  780
## [1112,] 424870 1466
## [1113,]  80000 1006
## [1114,]  80000  672
## [1115,] 149000 1042
## [1116,] 180000 1298
## [1117,] 174500  704
## [1118,] 116900  572
## [1119,] 143000  650
## [1120,] 124000  932
## [1121,] 149900 1466
## [1122,] 230000 1073
## [1123,] 120500  816
## [1124,] 201800  864
## [1125,] 218000 1437
## [1126,] 179900 1219
## [1127,] 230000 1314
## [1128,] 235128 1580
## [1129,] 185000  901
## [1130,] 146000  855
## [1131,] 224000 1296
## [1132,] 129000  894
## [1133,] 108959 1198
## [1134,] 194000 1360
## [1135,] 233170 1502
## [1136,] 245350 1694
## [1137,] 173000  959
## [1138,] 235000 1127
## [1139,] 625000 1930
## [1140,] 171000 1096
## [1141,] 163000 1261
## [1142,] 171900  625
## [1143,] 200500 1598
## [1144,] 239000  952
## [1145,] 285000 1683
## [1146,] 119500  876
## [1147,] 115000  818
## [1148,] 154900  731
## [1149,] 250000 1216
## [1150,] 392500 1600
## [1151,] 745000 2396
## [1152,] 120000 1120
## [1153,] 186700 1572
## [1154,] 104900  784
## [1155,]  95000  978
## [1156,] 262000 1624
## [1157,] 195000  831
## [1158,] 189000  994
## [1159,] 168000 1249
## [1160,] 174000  776
## [1161,] 125000  702
## [1162,] 165000 1224
## [1163,] 158000  663
## [1164,] 176000  728
## [1165,] 219210  879
## [1166,] 144000  815
## [1167,] 178000 1212
## [1168,] 148000 1051
## [1169,] 116050  864
## [1170,] 197900  866
## [1171,] 117000  884
## [1172,] 213000 1630
## [1173,] 153500 1056
## [1174,] 271900 2158
## [1175,] 107000 1056
## [1176,] 200000 1682
## [1177,] 140000  931
## [1178,] 290000 1660
## [1179,] 189000 1055
## [1180,] 164000  559
## [1181,] 113000  672
## [1182,] 145000  648
## [1183,] 134500  925
## [1184,] 125000  894
## [1185,] 229456 1300
## [1186,]  91500  672
## [1187,] 115000  912
## [1188,] 134000  952
## [1189,] 143000 1040
## [1190,] 137900 2136
## [1191,] 184000  788
## [1192,] 145000  588
## [1193,] 214000  894
## [1194,] 147000  912
## [1195,] 367294 1702
## [1196,] 127000 1075
## [1197,] 190000 1361
## [1198,] 132500 1106
## [1199,] 142000 1188
## [1200,] 130000  940
## [1201,] 138887  747
## [1202,] 175500  764
## [1203,] 195000  847
## [1204,] 142500 1141
## [1205,] 265900 1476
## [1206,] 224900  884
## [1207,] 248328 1689
## [1208,] 170000 1053
## [1209,] 465000 2076
## [1210,] 230000  792
## [1211,] 178000  585
## [1212,] 186500  756
## [1213,] 169900 1012
## [1214,] 129500  735
## [1215,] 119000  876
## [1216,] 244000 2110
## [1217,] 171750 1405
## [1218,] 130000  864
## [1219,] 294000 1192
## [1220,] 165400  746
## [1221,] 127500  884
## [1222,] 301500 1986
## [1223,]  99900  864
## [1224,] 190000  856
## [1225,] 151000 1054
## [1226,] 181000  841
## [1227,] 128900 1050
## [1228,] 161500 1104
## [1229,] 180500  764
## [1230,] 181000 1405
## [1231,] 183900  691
## [1232,] 122000  925
## [1233,] 378500 2002
## [1234,] 381000  728
## [1235,] 144000  874
## [1236,] 260000 1332
## [1237,] 185750 1489
## [1238,] 137000  935
## [1239,] 177000 1019
## [1240,] 139000  661
## [1241,] 137000  928
## [1242,] 162000  723
## [1243,] 197900 1680
## [1244,] 237000 1128
## [1245,]  68400  698
## [1246,] 227000 1573
## [1247,] 180000 1309
## [1248,] 150500 1040
## [1249,] 139000  912
## [1250,] 169000  804
## [1251,] 132500  780
## [1252,] 143000 1328
## [1253,] 190000 1624
## [1254,] 278000 1501
## [1255,] 281000 1085
## [1256,] 180500 1152
## [1257,] 119500  630
## [1258,] 107500  994
## [1259,] 162900  832
## [1260,] 115000  864
## [1261,] 138500 1052
## [1262,] 155000 1120
## [1263,] 140000  547
## [1264,] 160000 6110
## [1265,] 154000 1246
## [1266,] 225000  978
## [1267,] 177500  771
## [1268,] 290000 1165
## [1269,] 232000 1616
## [1270,] 130000  976
## [1271,] 325000 1652
## [1272,] 202500 1368
## [1273,] 138000  990
## [1274,] 147000  924
## [1275,] 179200 1278
## [1276,] 335000 1902
## [1277,] 203000 1274
## [1278,] 302000 1453
## [1279,] 333168 1393
## [1280,] 119000  948
## [1281,] 206900  952
## [1282,] 295493 1622
## [1283,] 208900 1352
## [1284,] 275000 1753
## [1285,] 111000  864
## [1286,] 156500 1478
## [1287,] 190000  750
## [1288,]  82500  420
## [1289,] 147000 1795
## [1290,]  55000  796
## [1291,]  79000  544
## [1292,] 130500  816
## [1293,] 256000 1510
## [1294,] 176500  935
## [1295,] 227000 1588
## [1296,] 132500  911
## [1297,] 100000  816
## [1298,] 125500  803
## [1299,] 125000  765
## [1300,] 167900 1350
## [1301,] 135000 1656
## [1302,]  52500  693
## [1303,] 200000  916
## [1304,] 128500  864
## [1305,] 123000  858
## [1306,] 155000 1114
## [1307,] 228500 1284
## [1308,] 177000  896
## [1309,] 155835  728
## [1310,] 108500  960
## [1311,] 262500 1568
## [1312,] 283463 1732
## [1313,] 215000 1482
## [1314,] 122000  684
## [1315,] 200000 1248
## [1316,] 171000  858
## [1317,] 134900  698
## [1318,] 410000 2033
## [1319,] 235000  992
## [1320,] 170000  570
## [1321,] 110000  864
## [1322,] 149900 1078
## [1323,] 177500  756
## [1324,] 315000 1980
## [1325,] 189000  612
## [1326,] 260000 1530
## [1327,] 104900  715
## [1328,] 156932  616
## [1329,] 144152  600
## [1330,] 216000  814
## [1331,] 193000  873
## [1332,] 127000  757
## [1333,] 144000  848
## [1334,] 232000 1657
## [1335,] 105000  840
## [1336,] 165500  992
## [1337,] 274300 1108
## [1338,] 466500 2633
## [1339,] 250000 1026
## [1340,] 239000 1571
## [1341,]  91000  768
## [1342,] 117000  984
## [1343,]  83000  483
## [1344,] 167500  384
## [1345,]  58500  864
## [1346,] 237500 1205
## [1347,] 157000  596
## [1348,] 112000  816
## [1349,] 105000  560
## [1350,] 125500  796
## [1351,] 250000 1392
## [1352,] 136000  714
## [1353,] 377500 1746
## [1354,] 131000  735
## [1355,] 235000 1525
## [1356,] 124000 1584
## [1357,] 123000  864
## [1358,] 163000  482
## [1359,] 246578 1356
## [1360,] 281213 1094
## [1361,] 160000  747
## [1362,] 137500  939
## [1363,] 138000 1208
## [1364,] 137450  976
## [1365,] 120000  862
## [1366,] 193000  839
## [1367,] 193879 1286
## [1368,] 282922 1485
## [1369,] 105000  672
## [1370,] 275000 1594
## [1371,] 133000  768
## [1372,] 112000  833
## [1373,] 125500  622
## [1374,] 215000  791
## [1375,] 230000  944
## [1376,] 140000  856
## [1377,] 257000 1844
## [1378,] 207000  833
## [1379,] 175900 1386
## [1380,] 122500  777
## [1381,] 340000 1284
## [1382,] 124000 1144
## [1383,] 223000 1844
## [1384,] 179900  708
## [1385,] 127500 1069
## [1386,] 136500  848
## [1387,] 274970  697
## [1388,] 144000 1024
## [1389,] 142000 1252
## [1390,] 271000 1223
## [1391,] 140000  913
## [1392,] 119000  788
## [1393,] 182900 1440
## [1394,] 192140  732
## [1395,] 143750  958
## [1396,]  64500  656
## [1397,] 186500  936
## [1398,] 160000 1126
## [1399,] 174000 1319
## [1400,] 120500  864
## [1401,] 394617 1932
## [1402,] 149700  912
## [1403,] 197000  539
## [1404,] 191000  588
## [1405,] 149300  848
## [1406,] 310000 1017
## [1407,] 121000  952
## [1408,] 179600 1422
## [1409,] 129000  814
## [1410,] 157900 1188
## [1411,] 240000 1220
## [1412,] 112000  560
## [1413,]  92000  630
## [1414,] 136000  896
## [1415,] 287090 1573
## [1416,] 145000  547
## [1417,]  84500 1140
## [1418,] 185000 1221
## [1419,] 175000  953
## [1420,] 210000 1542
## [1421,] 266500 1152
## [1422,] 142125 1078
## [1423,] 147500 1256
min(FD)
## [1] 105

I removed the 0’s from both the independent and dependent variable as I could not figure out how to remove from just one.

require(MASS)
F.TBSF <- FD[,"TBSF"]
dist <- fitdistr(F.TBSF, "normal")
opt.lamda <- dist$estimate
samp <- rexp(1200, opt.lamda)
hist(samp, breaks = 25)

The two histograms look quite different. This second histogram is more right skewed, and although our initial one was right skewed as well, it was not to the degree of this one.

Build some type of regression model and submit your model to the competition board. Provide your complete model summary and results with analysis. Report your Kaggle.com user name and score.

#I would like to preface this by saying that I decided on the multiple regression model as it was the most straightforward and easy for me to handle. 

model <- lm(formula = train.data$SalePrice ~ train.data$OverallQual + train.data$GrLivArea  + train.data$GarageArea + train.data$GarageCars, data=train.data)
summary(model) 
## 
## Call:
## lm(formula = train.data$SalePrice ~ train.data$OverallQual + 
##     train.data$GrLivArea + train.data$GarageArea + train.data$GarageCars, 
##     data = train.data)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -372594  -21236   -1594   18625  301129 
## 
## Coefficients:
##                          Estimate Std. Error t value Pr(>|t|)    
## (Intercept)            -98436.050   4820.467 -20.420  < 2e-16 ***
## train.data$OverallQual  26988.854   1067.393  25.285  < 2e-16 ***
## train.data$GrLivArea       49.573      2.555  19.402  < 2e-16 ***
## train.data$GarageArea      41.478     10.627   3.903 9.93e-05 ***
## train.data$GarageCars   11317.522   3126.297   3.620 0.000305 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 40420 on 1455 degrees of freedom
## Multiple R-squared:  0.7418, Adjusted R-squared:  0.7411 
## F-statistic:  1045 on 4 and 1455 DF,  p-value: < 2.2e-16

From the summary of the linear model done, we can say our equation is:

\[SalePrice = -98436.050 + (26988.85*OverallQuality) + (49.573 *GrLivArea) + (11317.522*GarageCars) + (41.478 *GarageArea)\] I would like to check my equation by checking on the test data. I will load and compare my calculated SalePrice with the one provided in the test data.

test.data <- read.csv("https://raw.githubusercontent.com/komotunde/DATA605/master/test.csv", header  = TRUE)
head(test.data)
##     Id MSSubClass MSZoning LotFrontage LotArea Street Alley LotShape
## 1 1461         20       RH          80   11622   Pave  <NA>      Reg
## 2 1462         20       RL          81   14267   Pave  <NA>      IR1
## 3 1463         60       RL          74   13830   Pave  <NA>      IR1
## 4 1464         60       RL          78    9978   Pave  <NA>      IR1
## 5 1465        120       RL          43    5005   Pave  <NA>      IR1
## 6 1466         60       RL          75   10000   Pave  <NA>      IR1
##   LandContour Utilities LotConfig LandSlope Neighborhood Condition1
## 1         Lvl    AllPub    Inside       Gtl        NAmes      Feedr
## 2         Lvl    AllPub    Corner       Gtl        NAmes       Norm
## 3         Lvl    AllPub    Inside       Gtl      Gilbert       Norm
## 4         Lvl    AllPub    Inside       Gtl      Gilbert       Norm
## 5         HLS    AllPub    Inside       Gtl      StoneBr       Norm
## 6         Lvl    AllPub    Corner       Gtl      Gilbert       Norm
##   Condition2 BldgType HouseStyle OverallQual OverallCond YearBuilt
## 1       Norm     1Fam     1Story           5           6      1961
## 2       Norm     1Fam     1Story           6           6      1958
## 3       Norm     1Fam     2Story           5           5      1997
## 4       Norm     1Fam     2Story           6           6      1998
## 5       Norm   TwnhsE     1Story           8           5      1992
## 6       Norm     1Fam     2Story           6           5      1993
##   YearRemodAdd RoofStyle RoofMatl Exterior1st Exterior2nd MasVnrType
## 1         1961     Gable  CompShg     VinylSd     VinylSd       None
## 2         1958       Hip  CompShg     Wd Sdng     Wd Sdng    BrkFace
## 3         1998     Gable  CompShg     VinylSd     VinylSd       None
## 4         1998     Gable  CompShg     VinylSd     VinylSd    BrkFace
## 5         1992     Gable  CompShg     HdBoard     HdBoard       None
## 6         1994     Gable  CompShg     HdBoard     HdBoard       None
##   MasVnrArea ExterQual ExterCond Foundation BsmtQual BsmtCond BsmtExposure
## 1          0        TA        TA     CBlock       TA       TA           No
## 2        108        TA        TA     CBlock       TA       TA           No
## 3          0        TA        TA      PConc       Gd       TA           No
## 4         20        TA        TA      PConc       TA       TA           No
## 5          0        Gd        TA      PConc       Gd       TA           No
## 6          0        TA        TA      PConc       Gd       TA           No
##   BsmtFinType1 BsmtFinSF1 BsmtFinType2 BsmtFinSF2 BsmtUnfSF TotalBsmtSF
## 1          Rec        468          LwQ        144       270         882
## 2          ALQ        923          Unf          0       406        1329
## 3          GLQ        791          Unf          0       137         928
## 4          GLQ        602          Unf          0       324         926
## 5          ALQ        263          Unf          0      1017        1280
## 6          Unf          0          Unf          0       763         763
##   Heating HeatingQC CentralAir Electrical X1stFlrSF X2ndFlrSF LowQualFinSF
## 1    GasA        TA          Y      SBrkr       896         0            0
## 2    GasA        TA          Y      SBrkr      1329         0            0
## 3    GasA        Gd          Y      SBrkr       928       701            0
## 4    GasA        Ex          Y      SBrkr       926       678            0
## 5    GasA        Ex          Y      SBrkr      1280         0            0
## 6    GasA        Gd          Y      SBrkr       763       892            0
##   GrLivArea BsmtFullBath BsmtHalfBath FullBath HalfBath BedroomAbvGr
## 1       896            0            0        1        0            2
## 2      1329            0            0        1        1            3
## 3      1629            0            0        2        1            3
## 4      1604            0            0        2        1            3
## 5      1280            0            0        2        0            2
## 6      1655            0            0        2        1            3
##   KitchenAbvGr KitchenQual TotRmsAbvGrd Functional Fireplaces FireplaceQu
## 1            1          TA            5        Typ          0        <NA>
## 2            1          Gd            6        Typ          0        <NA>
## 3            1          TA            6        Typ          1          TA
## 4            1          Gd            7        Typ          1          Gd
## 5            1          Gd            5        Typ          0        <NA>
## 6            1          TA            7        Typ          1          TA
##   GarageType GarageYrBlt GarageFinish GarageCars GarageArea GarageQual
## 1     Attchd        1961          Unf          1        730         TA
## 2     Attchd        1958          Unf          1        312         TA
## 3     Attchd        1997          Fin          2        482         TA
## 4     Attchd        1998          Fin          2        470         TA
## 5     Attchd        1992          RFn          2        506         TA
## 6     Attchd        1993          Fin          2        440         TA
##   GarageCond PavedDrive WoodDeckSF OpenPorchSF EnclosedPorch X3SsnPorch
## 1         TA          Y        140           0             0          0
## 2         TA          Y        393          36             0          0
## 3         TA          Y        212          34             0          0
## 4         TA          Y        360          36             0          0
## 5         TA          Y          0          82             0          0
## 6         TA          Y        157          84             0          0
##   ScreenPorch PoolArea PoolQC Fence MiscFeature MiscVal MoSold YrSold
## 1         120        0   <NA> MnPrv        <NA>       0      6   2010
## 2           0        0   <NA>  <NA>        Gar2   12500      6   2010
## 3           0        0   <NA> MnPrv        <NA>       0      3   2010
## 4           0        0   <NA>  <NA>        <NA>       0      6   2010
## 5         144        0   <NA>  <NA>        <NA>       0      1   2010
## 6           0        0   <NA>  <NA>        <NA>       0      4   2010
##   SaleType SaleCondition
## 1       WD        Normal
## 2       WD        Normal
## 3       WD        Normal
## 4       WD        Normal
## 5       WD        Normal
## 6       WD        Normal
test.subset <- test.data[,c("Id", "OverallQual", "GrLivArea", "GarageCars", "GarageArea")]
head(test.subset)
##     Id OverallQual GrLivArea GarageCars GarageArea
## 1 1461           5       896          1        730
## 2 1462           6      1329          1        312
## 3 1463           5      1629          2        482
## 4 1464           6      1604          2        470
## 5 1465           8      1280          2        506
## 6 1466           6      1655          2        440
#I will find the sale price from the above equation and combine with our test subset data frame.

test.subset[is.na(test.subset)] <- 0

SalePrice <-  abs(-98436.050 + (26988.854  *test.data$OverallQual) + ( 49.573 *test.data$GrLivArea) + (11317.522*test.data$GarageCars) +  (41.478 *test.data$GarageArea))
head(SalePrice)
## [1] 122522.1 153638.2 159890.1 185141.9 224551.1 186425.8
require(knitr)
## Loading required package: knitr
new.df <- cbind(test.subset, SalePrice)
kable(new.df)
Id OverallQual GrLivArea GarageCars GarageArea SalePrice
1461 5 896 1 730 122522.090
1462 6 1329 1 312 153638.249
1463 5 1629 2 482 159890.077
1464 6 1604 2 470 185141.870
1465 8 1280 2 506 224551.134
1466 6 1655 2 440 186425.753
1467 6 1187 2 420 162396.029
1468 6 1465 2 393 175057.417
1469 7 1341 2 506 200586.233
1470 4 882 2 525 97653.746
1471 7 1337 2 511 200595.331
1472 6 987 1 264 134693.339
1473 5 1092 1 320 115232.418
1474 6 1456 2 440 176560.726
1475 7 836 1 308 156021.702
1476 9 2334 3 751 325269.562
1477 8 1544 3 868 263970.964
1478 9 1698 3 730 292870.096
1479 8 1822 3 678 269871.438
1480 9 2696 3 958 351800.934
1481 8 2250 3 756 294323.966
1482 8 1370 2 484 228100.188
1483 6 1324 2 430 169602.310
1484 7 1145 2 437 188007.943
1485 7 1374 2 400 197825.474
1486 7 1733 2 433 216990.955
1487 8 2475 3 962 314022.359
1488 8 1595 3 880 266996.923
1489 7 1218 2 676 201540.014
1490 6 1468 2 528 180805.666
1491 7 1659 2 484 215437.931
1492 5 1012 1 429 115787.680
1493 6 1494 2 461 179315.538
1494 8 2349 3 762 299480.561
1495 8 2225 3 713 291301.087
1496 7 1488 2 506 207873.464
1497 7 1680 2 588 220792.676
1498 7 1200 2 480 192518.012
1499 7 1200 2 480 192518.012
1500 6 1236 2 480 167313.786
1501 6 1512 2 440 179336.814
1502 7 1080 2 496 187232.900
1503 8 1418 3 852 257061.118
1504 8 1848 2 592 256275.706
1505 7 1492 2 596 211804.776
1506 6 1829 2 535 198991.865
1507 6 2495 2 660 237192.233
1508 6 1891 2 678 207996.745
1509 6 1645 2 441 185971.501
1510 5 1232 2 490 140541.420
1511 5 1209 2 504 139981.933
1512 5 1510 2 517 155442.620
1513 6 1775 2 480 194033.633
1514 5 1728 0 0 122170.364
1515 5 2461 2 400 197733.617
1516 6 1556 2 470 182762.366
1517 6 1128 1 315 143798.510
1518 5 1604 2 576 162549.684
1519 7 1480 2 620 212205.372
1520 5 1143 1 308 117262.905
1521 5 1206 1 312 120551.916
1522 6 1580 2 440 182707.778
1523 4 1337 1 263 98024.703
1524 5 1064 1 318 113761.418
1525 5 972 1 305 108661.488
1526 5 988 1 264 107754.058
1527 4 985 2 676 109022.943
1528 6 1224 1 280 147105.788
1529 5 1175 2 484 137466.891
1530 6 1395 2 440 173536.773
1531 4 1844 1 240 122204.220
1532 5 936 0 0 82908.548
1533 5 1347 2 551 148772.473
1534 6 1251 1 240 146785.139
1535 5 1633 1 240 138733.171
1536 5 1245 1 315 122609.697
1537 2 832 2 780 51774.278
1538 8 1566 1 288 218369.286
1539 8 2268 2 624 278423.662
1540 5 2256 0 0 148344.908
1541 6 1470 2 624 184886.700
1542 5 1612 1 363 142793.932
1543 7 2068 1 315 217385.984
1544 4 765 1 200 67055.833
1545 6 1132 1 240 140885.952
1546 6 1196 2 576 169312.754
1547 5 1453 1 240 129810.031
1548 6 1416 1 312 157951.100
1549 5 1040 2 624 136581.456
1550 5 1536 2 480 155196.832
1551 6 1068 1 288 139704.224
1552 4 1962 2 572 153142.052
1553 6 1560 0 0 140830.954
1554 6 1324 1 180 147915.288
1555 5 1675 1 365 145999.987
1556 5 1224 1 180 115969.134
1557 5 1392 0 0 105513.836
1558 6 919 1 231 129953.601
1559 4 1884 0 0 102914.898
1560 5 1680 2 450 161091.004
1561 4 1832 0 0 100337.102
1562 5 892 1 416 109299.706
1563 5 864 1 280 102270.654
1564 5 1373 2 591 151720.491
1565 5 1440 2 480 150437.824
1566 7 1483 2 690 215257.551
1567 4 756 2 440 87881.918
1568 6 1981 2 522 205987.747
1569 3 1610 1 480 93570.004
1570 6 1074 1 467 147426.224
1571 4 1531 1 209 105402.053
1572 5 1172 1 366 121106.246
1573 7 1508 2 572 211602.472
1574 5 1298 2 504 144393.930
1575 7 1433 2 528 206059.465
1576 6 1802 4 1017 240280.834
1577 7 1222 2 615 199208.148
1578 6 1445 2 484 177840.455
1579 5 965 2 580 131038.449
1580 7 1692 2 513 218276.702
1581 5 1026 1 308 111462.864
1582 5 876 2 484 122644.564
1583 8 1978 3 850 284739.042
1584 7 2098 2 621 242882.964
1585 6 848 2 420 145590.782
1586 3 640 1 240 35529.474
1587 5 992 1 319 110233.640
1588 5 1196 1 336 121051.658
1589 4 1120 2 480 107585.610
1590 6 1096 1 352 143746.860
1591 4 960 0 0 57109.446
1592 5 1296 1 260 122856.630
1593 6 856 2 399 145116.328
1594 4 2650 0 0 140887.816
1595 5 1666 0 0 119096.838
1596 7 2133 1 312 220483.795
1597 5 2177 2 484 187139.037
1598 7 1652 2 473 214634.662
1599 8 1034 2 598 216172.152
1600 8 1191 2 531 221176.087
1601 2 540 1 200 1924.200
1602 6 1107 1 625 155615.657
1603 4 952 1 330 81718.124
1604 8 1646 2 525 243482.934
1605 8 1916 3 741 277144.414
1606 6 1285 2 473 169452.517
1607 6 2048 2 776 219844.550
1608 7 1346 3 660 218539.232
1609 7 1214 2 520 194871.154
1610 5 1444 2 400 147317.876
1611 5 1264 2 528 143703.920
1612 5 1430 2 624 155914.926
1613 5 1344 2 686 154223.284
1614 5 945 1 253 105166.161
1615 4 1092 0 0 63653.082
1616 4 1092 0 0 63653.082
1617 4 1092 1 286 86833.312
1618 5 874 1 352 105752.800
1619 5 833 2 495 120969.183
1620 5 2432 2 616 205255.248
1621 5 1274 2 576 146190.594
1622 5 1479 1 275 132550.659
1623 8 1803 2 482 249482.341
1624 6 1797 2 616 200765.247
1625 6 882 1 502 139359.938
1626 6 1434 2 528 179120.184
1627 6 1608 2 470 185340.162
1628 8 2283 3 632 290816.603
1629 7 1628 2 390 210002.236
1630 8 2522 2 564 288526.524
1631 8 1478 2 495 233910.330
1632 8 1734 2 528 247969.792
1633 7 1382 2 396 198056.146
1634 6 1636 2 440 185483.866
1635 6 1516 2 409 178249.288
1636 6 1190 2 430 162959.528
1637 5 1934 2 567 178535.472
1638 7 2050 2 529 236687.484
1639 6 1671 2 484 189043.953
1640 7 2673 2 441 263921.399
1641 6 1707 2 479 190621.191
1642 7 1884 2 581 230615.222
1643 8 1874 2 588 257398.692
1644 8 1811 2 565 253321.599
1645 5 1621 2 478 159327.581
1646 6 1116 2 528 163355.970
1647 7 1193 2 506 193249.429
1648 5 1180 2 477 137424.410
1649 5 1050 1 336 113814.000
1650 4 864 2 576 98876.810
1651 4 864 2 576 98876.810
1652 6 987 1 264 134693.339
1653 6 987 1 288 135688.811
1654 6 1548 2 440 181121.442
1655 7 1055 2 440 183670.807
1656 6 1456 2 440 176560.726
1657 6 1548 2 440 181121.442
1658 6 1456 2 440 176560.726
1659 7 836 1 345 157556.388
1660 5 1120 2 656 141874.592
1661 9 2772 3 754 347106.970
1662 9 2690 3 864 347604.564
1663 9 2020 3 896 315717.950
1664 10 2674 3 762 369569.494
1665 9 1736 3 834 299067.582
1666 8 1782 3 932 278423.930
1667 8 2520 3 640 302897.228
1668 9 1743 3 927 303272.047
1669 9 1531 3 700 283347.065
1670 9 1808 3 850 303300.486
1671 7 1760 2 583 224551.126
1672 9 2452 3 886 336718.706
1673 8 2400 3 730 300681.488
1674 8 1606 3 871 267168.924
1675 6 1358 2 484 173527.604
1676 6 1306 2 624 176756.728
1677 7 1358 2 484 200516.458
1678 10 2492 3 949 368303.594
1679 8 2200 3 685 288900.378
1680 9 1884 2 649 287413.434
1681 9 1456 2 539 261633.610
1682 8 1712 3 701 265372.402
1683 7 1405 2 478 202597.521
1684 7 1456 2 390 201475.680
1685 6 1490 2 392 176255.264
1686 7 1220 2 397 190066.798
1687 7 1374 2 400 197825.474
1688 7 1630 2 436 212009.370
1689 7 1594 2 434 210141.786
1690 7 1489 2 400 203526.369
1691 7 1342 2 393 195948.792
1692 8 2004 3 644 277483.472
1693 7 1374 2 400 197825.474
1694 6 1514 2 394 177527.972
1695 7 1430 2 400 200601.562
1696 7 2312 3 658 266343.794
1697 7 1430 2 410 201016.342
1698 8 2687 3 810 318227.179
1699 8 2063 3 815 287501.017
1700 7 2061 2 647 242127.191
1701 8 2232 2 623 276597.556
1702 8 1696 3 972 275819.772
1703 8 1658 3 726 263732.410
1704 8 1702 3 844 270808.026
1705 8 1432 2 492 231505.538
1706 9 2490 3 795 334827.982
1707 7 1436 2 529 206249.662
1708 7 1402 2 625 208546.068
1709 9 1530 3 984 295077.244
1710 8 1448 2 692 240594.306
1711 8 1795 3 782 272846.679
1712 8 1836 2 517 252569.980
1713 7 1662 3 711 236319.678
1714 7 1553 2 588 214496.905
1715 7 1653 2 628 221113.325
1716 7 1218 2 576 197392.214
1717 7 1141 2 484 189759.117
1718 6 1158 0 0 120902.608
1719 7 1812 2 478 222773.732
1720 8 1512 3 845 261430.634
1721 7 1114 2 576 192236.622
1722 5 1114 0 0 91732.542
1723 5 1114 2 576 138258.914
1724 7 1450 3 788 229004.008
1725 7 2122 2 559 241501.080
1726 6 1730 2 528 193793.792
1727 6 1332 2 542 174644.430
1728 7 1540 2 495 209995.002
1729 6 1400 2 465 174821.588
1730 6 1882 2 612 204813.040
1731 5 980 2 400 124316.004
1732 5 864 2 732 132336.232
1733 5 864 1 440 108907.134
1734 5 1020 1 288 110335.866
1735 5 912 1 300 105479.718
1736 5 912 1 252 103488.774
1737 8 2014 3 864 287104.362
1738 7 1755 2 524 221856.059
1739 7 3005 3 704 302605.871
1740 6 1726 2 561 194964.274
1741 6 1256 2 641 174983.204
1742 6 1512 2 440 179336.814
1743 7 1452 2 506 206088.836
1744 8 1694 2 642 250715.364
1745 7 1740 2 540 221776.112
1746 8 2499 2 527 285851.659
1747 7 2067 2 784 248107.115
1748 6 2640 2 515 238366.008
1749 5 1336 2 502 146194.748
1750 6 1216 1 336 149031.972
1751 7 2288 2 520 248112.556
1752 5 864 1 312 103597.950
1753 5 1568 2 440 155124.048
1754 7 2061 2 498 235946.969
1755 6 1320 2 495 172100.088
1756 4 894 2 396 92897.960
1757 5 864 1 308 103432.038
1758 4 1362 3 768 142845.462
1759 5 1728 2 576 168696.736
1760 5 1313 2 610 149534.193
1761 5 1292 2 520 144760.140
1762 5 2140 2 549 188000.906
1763 6 1576 2 368 179523.070
1764 5 960 1 330 109103.562
1765 6 1691 2 550 192772.961
1766 6 1453 2 530 180145.027
1767 6 1567 2 542 186294.085
1768 5 1144 1 286 116399.962
1769 7 1329 2 441 197295.287
1770 6 988 1 297 136111.686
1771 5 1202 1 304 120021.800
1772 5 1382 1 350 130852.928
1773 4 1200 1 294 92519.020
1774 5 1866 2 495 172178.092
1775 6 1062 1 297 139780.088
1776 5 1112 2 480 134177.880
1777 5 793 1 240 97091.851
1778 5 1031 1 230 108475.445
1779 5 1210 1 616 133359.520
1780 7 1527 2 410 205824.923
1781 5 1200 1 246 117516.930
1782 3 792 1 366 48290.798
1783 5 1352 2 720 156030.120
1784 4 1039 1 281 83998.553
1785 5 1078 1 264 112215.628
1786 4 2377 2 528 171889.815
1787 7 1690 2 624 222781.614
1788 2 599 0 0 14764.115
1789 5 846 2 576 124973.350
1790 3 725 1 320 43061.419
1791 6 2544 3 907 261183.898
1792 6 1380 1 364 158323.328
1793 6 1040 2 480 157597.478
1794 6 951 2 480 153185.481
1795 6 1105 1 308 142367.985
1796 6 1142 1 384 147354.514
1797 6 1133 2 900 179628.527
1798 5 1041 1 294 111625.767
1799 5 732 1 240 94067.898
1800 5 1183 1 288 118416.265
1801 4 1461 1 384 109190.593
1802 6 1495 2 576 184135.081
1803 6 1806 2 483 195694.830
1804 5 941 2 564 129185.049
1805 6 1045 1 264 137568.573
1806 6 1378 1 162 149845.626
1807 6 1944 2 324 195940.902
1808 5 1306 2 472 143463.218
1809 5 1464 0 0 109083.092
1810 5 1558 2 400 152969.198
1811 4 1701 0 0 93843.039
1812 5 1447 0 0 108240.351
1813 5 1328 1 308 126433.910
1814 4 861 2 288 86782.427
1815 2 612 1 308 9973.080
1816 5 792 1 287 98991.744
1817 4 1510 2 720 136873.800
1818 6 2007 1 357 189115.253
1819 6 1288 1 280 150278.460
1820 4 816 0 0 49970.934
1821 6 1480 1 207 156768.582
1822 6 1521 3 640 199396.093
1823 3 797 0 0 22040.193
1824 6 1432 1 216 154762.380
1825 5 1654 1 336 143756.092
1826 5 1142 1 320 117711.068
1827 5 995 1 264 108101.069
1828 5 1582 1 250 136619.728
1829 5 1072 5 1184 195348.038
1830 6 1768 2 576 197668.510
1831 7 1944 1 216 207132.610
1832 5 2128 0 0 141999.564
1833 6 1930 1 316 183597.534
1834 6 1427 1 379 161275.429
1835 7 1864 0 0 182890.000
1836 6 1666 1 384 173330.766
1837 4 892 0 0 53738.482
1838 6 1403 1 308 157140.739
1839 4 704 1 220 64861.440
1840 5 1200 0 0 95995.820
1841 5 1152 1 252 115386.294
1842 5 1112 1 226 112324.946
1843 5 1052 1 668 127683.842
1844 6 1034 2 504 158295.512
1845 5 1774 1 384 151695.796
1846 6 1138 2 480 162455.632
1847 5 2071 1 336 164428.033
1848 2 660 0 0 11740.162
1849 4 1383 2 498 121369.913
1850 5 1073 1 340 115120.091
1851 6 1639 1 240 166019.463
1852 5 1089 1 252 112263.195
1853 5 1049 1 266 110860.967
1854 7 1061 2 462 184880.761
1855 6 1338 2 576 176352.120
1856 7 1879 2 473 225887.733
1857 5 2016 2 576 182973.760
1858 5 2228 2 720 199456.068
1859 5 1535 2 400 151829.019
1860 5 1229 2 672 147941.697
1861 5 1513 2 400 150738.413
1862 7 2787 4 820 307927.927
1863 7 2787 4 820 307927.927
1864 7 2787 4 820 307927.927
1865 9 1680 3 1138 308900.806
1866 9 1720 3 846 298772.150
1867 8 1468 3 904 261696.624
1868 8 1838 2 524 252959.472
1869 7 1290 2 662 204528.578
1870 8 1254 3 810 247189.070
1871 8 1498 3 844 260695.134
1872 6 1422 2 440 174875.244
1873 7 1759 2 525 222095.829
1874 5 990 1 440 115153.332
1875 7 1463 2 539 208002.913
1876 6 1772 2 492 194382.650
1877 7 1444 2 577 208637.190
1878 7 1492 2 608 212302.512
1879 5 907 1 343 107015.407
1880 5 914 2 444 122869.218
1881 7 1611 3 1231 255360.015
1882 8 2184 2 570 272019.718
1883 7 1725 2 550 221447.297
1884 7 1870 2 608 231041.106
1885 8 1513 2 521 236723.813
1886 8 1828 2 523 252422.264
1887 7 1417 2 511 204561.171
1888 8 1602 3 810 264440.474
1889 6 1396 2 440 173586.346
1890 4 1149 1 544 100360.297
1891 6 1072 2 525 161050.324
1892 4 876 1 320 77535.796
1893 5 1368 1 195 123729.816
1894 5 1678 0 0 119691.714
1895 5 1560 1 313 138142.236
1896 5 1298 1 256 122789.864
1897 5 1268 1 250 121053.806
1898 6 1242 1 180 143850.302
1899 6 1232 2 440 165456.374
1900 7 1228 1 215 171596.864
1901 5 1567 2 440 155074.475
1902 5 1273 1 307 123665.917
1903 7 2480 2 400 252653.212
1904 5 1112 1 390 119127.338
1905 6 1561 2 463 182719.885
1906 5 1523 1 295 135561.431
1907 6 1906 2 576 204509.584
1908 6 1032 2 452 156039.510
1909 6 1229 2 462 166220.171
1910 6 1229 2 462 166220.171
1911 6 1982 2 501 205166.282
1912 7 2365 2 551 253215.495
1913 5 2168 2 576 190508.856
1914 4 572 1 200 57488.244
1915 8 1648 2 482 241798.526
1916 2 810 1 280 18627.150
1917 8 2052 3 642 279780.020
1918 6 926 1 351 135277.972
1919 6 1287 2 541 172372.167
1920 5 1595 2 672 166085.415
1921 9 2036 3 780 311699.670
1922 9 1641 3 885 296473.525
1923 6 2237 2 440 215277.239
1924 7 1479 2 578 210413.723
1925 7 2014 2 486 233119.302
1926 9 1978 3 920 314631.356
1927 5 1008 1 384 113722.878
1928 5 1404 2 504 149648.668
1929 5 796 1 336 101222.458
1930 6 1091 1 429 146692.801
1931 5 883 2 698 131867.867
1932 5 1287 2 440 141194.035
1933 5 1632 2 898 177293.644
1934 6 1604 2 470 185141.870
1935 6 1470 2 420 176425.188
1936 6 1604 2 472 185224.826
1937 6 1636 2 386 183244.054
1938 5 1384 2 404 144509.408
1939 8 1682 2 528 245391.996
1940 8 1280 2 506 224551.134
1941 6 1633 2 460 186164.707
1942 6 1709 2 416 188107.223
1943 8 1337 2 462 225551.763
1944 8 2500 3 683 303689.322
1945 9 1884 3 670 299601.994
1946 6 1474 2 495 179734.330
1947 9 1710 2 557 274971.756
1948 6 1488 2 738 190507.506
1949 7 1688 2 528 218700.580
1950 7 1260 2 598 200386.796
1951 7 2064 2 550 238252.544
1952 7 1782 2 551 224314.436
1953 6 1211 2 461 165286.379
1954 7 2044 2 489 234730.926
1955 5 1308 2 484 144060.100
1956 7 2840 4 1314 331045.428
1957 6 1444 2 473 177334.624
1958 8 2340 3 787 300071.354
1959 5 1792 2 480 167887.520
1960 4 936 1 288 79182.880
1961 5 864 2 576 125865.664
1962 6 987 1 264 134693.339
1963 6 987 1 352 138343.403
1964 5 1302 1 264 123319.980
1965 6 1456 2 460 177390.286
1966 7 1055 2 440 183670.807
1967 8 1582 3 905 267389.424
1968 8 2464 3 650 300535.920
1969 9 1950 3 706 304367.020
1970 9 2748 3 850 349899.106
1971 10 2790 4 1150 402730.948
1972 9 2331 3 1003 335573.299
1973 8 2088 3 656 282145.340
1974 8 2332 3 756 298388.952
1975 10 2470 3 789 360576.508
1976 8 1575 3 732 259866.719
1977 8 2649 3 746 313688.813
1978 8 2690 3 795 317753.728
1979 9 1866 3 870 307005.280
1980 7 1367 2 484 200962.615
1981 9 1800 3 944 306802.834
1982 8 1342 2 550 229449.692
1983 8 1342 2 550 229449.692
1984 7 1626 2 474 213387.242
1985 7 1455 3 644 223279.041
1986 7 1576 3 668 230272.846
1987 7 1246 2 428 192641.514
1988 6 1515 2 393 177536.067
1989 7 1720 2 400 214977.732
1990 7 1986 2 434 229574.402
1991 7 1358 2 484 200516.458
1992 7 1892 2 431 224790.106
1993 7 1414 2 403 199932.828
1994 7 2322 2 400 244820.678
1995 7 1651 2 450 213631.095
1996 8 2199 2 516 270523.501
1997 9 2172 3 687 314584.144
1998 8 2006 3 938 289777.150
1999 7 2125 2 576 242354.925
2000 8 2501 3 751 306559.399
2001 7 2197 3 783 265827.649
2002 7 1578 3 642 229293.564
2003 8 1861 3 851 278980.479
2004 8 1874 3 880 280827.790
2005 8 1460 2 480 232395.846
2006 8 1372 2 588 232513.046
2007 8 1660 3 660 261094.008
2008 7 1218 2 462 192663.722
2009 6 1696 2 542 192689.002
2010 7 1663 2 478 215387.355
2011 6 1175 0 0 121745.349
2012 7 1162 2 483 190758.672
2013 6 1609 2 525 187671.025
2014 6 1680 2 474 189075.330
2015 7 1657 2 483 215297.307
2016 6 1677 2 627 195272.745
2017 7 1737 2 506 220217.141
2018 5 984 1 384 112533.126
2019 5 864 1 420 108077.574
2020 5 890 1 308 104720.936
2021 5 864 1 276 102104.742
2022 6 1430 2 484 177096.860
2023 5 1641 2 490 160816.777
2024 6 2683 2 473 238755.571
2025 9 2786 2 636 331589.066
2026 7 1245 2 495 195370.967
2027 6 1200 2 480 165529.158
2028 7 1392 2 540 204524.708
2029 6 1549 2 440 181171.015
2030 9 1638 2 495 268830.864
2031 9 1310 2 545 254644.820
2032 9 1419 2 588 261831.831
2033 9 1557 2 484 264359.193
2034 7 1404 2 462 201884.300
2035 7 1789 2 546 224454.057
2036 8 1586 2 480 238642.044
2037 8 1607 2 480 239683.077
2038 10 2393 2 846 347806.111
2039 8 1239 2 477 221315.779
2040 9 2944 3 864 360196.106
2041 8 1671 2 550 245759.209
2042 7 1812 2 469 222400.430
2043 6 1427 2 516 178275.437
2044 6 1740 2 512 193625.874
2045 7 1620 2 578 217403.516
2046 5 1625 2 484 159774.741
2047 5 1464 2 470 151212.796
2048 5 925 2 576 128889.617
2049 5 1728 2 576 168696.736
2050 7 1670 2 464 215153.674
2051 5 1014 1 267 109167.390
2052 5 1114 2 451 133074.164
2053 5 1118 1 264 114198.548
2054 4 906 1 231 75331.444
2055 5 1496 2 450 151969.572
2056 5 1337 1 264 125055.035
2057 5 1036 1 312 112124.506
2058 6 1988 2 480 204592.682
2059 5 1176 1 292 118235.166
2060 5 1440 1 480 139120.302
2061 6 1570 2 441 182253.526
2062 5 1104 1 384 118481.886
2063 5 882 1 240 101503.848
2064 5 1152 2 636 142631.368
2065 5 950 2 400 122828.814
2066 6 1790 2 540 197265.908
2067 5 1764 1 301 147757.392
2068 5 1824 2 484 169639.768
2069 4 869 1 390 80092.245
2070 5 1159 1 288 117226.513
2071 4 672 1 308 66925.168
2072 5 1436 4 1488 214684.400
2073 5 1044 2 372 126327.292
2074 7 1312 2 495 198692.358
2075 6 1081 1 401 145035.687
2076 5 876 2 576 126460.540
2077 5 1256 1 311 122989.088
2078 5 1027 1 299 111139.135
2079 6 1320 2 576 175459.806
2080 6 984 1 280 135208.268
2081 6 1278 1 240 148123.610
2082 5 1800 0 0 125739.620
2083 5 1588 2 480 157774.628
2084 5 825 1 350 103240.767
2085 5 1117 1 264 114148.975
2086 6 1133 1 308 143756.029
2087 5 1323 2 400 141319.543
2088 5 1360 1 330 128932.762
2089 5 672 1 256 91757.166
2090 6 1456 1 308 159768.108
2091 4 1594 0 0 88538.728
2092 4 1656 2 440 132497.618
2093 5 1740 1 225 143415.312
2094 7 1027 0 0 141397.399
2095 6 1436 2 828 191662.730
2096 5 899 1 200 100687.469
2097 5 1080 0 0 90047.060
2098 5 1499 3 869 180815.095
2099 2 407 1 297 645.643
2100 3 1588 0 0 61252.436
2101 5 1627 2 420 157219.295
2102 7 1450 1 288 185629.964
2103 5 1017 1 308 111016.707
2104 5 2350 2 393 191940.668
2105 5 1540 0 0 112850.640
2106 2 1086 2 400 48604.180
2107 7 2495 2 342 250991.083
2108 5 984 1 308 109380.798
2109 4 1093 1 308 87795.401
2110 5 1143 1 288 116433.345
2111 7 1668 1 252 194943.670
2112 5 1738 1 240 143938.336
2113 5 1210 1 240 117763.792
2114 6 1290 1 200 147059.366
2115 6 1672 1 240 167655.372
2116 5 949 2 370 121534.901
2117 6 1497 1 672 176898.593
2118 6 1342 1 240 151296.282
2119 6 1013 1 160 131668.525
2120 5 1216 1 355 122831.200
2121 4 896 1 280 76868.136
2122 4 1136 1 336 91088.424
2123 5 808 1 164 94683.118
2124 7 2009 2 400 229304.329
2125 5 1902 2 576 177322.438
2126 6 1716 2 672 199072.602
2127 6 1984 1 360 188099.508
2128 6 1609 1 228 164034.537
2129 6 768 2 440 142454.502
2130 6 1536 1 308 163733.948
2131 6 1969 2 400 200332.555
2132 5 1308 2 400 140575.948
2133 6 1040 2 320 150960.998
2134 6 1236 1 384 152014.376
2135 5 759 2 576 120660.499
2136 3 1344 0 0 49156.624
2137 5 1054 1 240 110030.404
2138 5 1075 2 440 130684.559
2139 6 1096 2 484 160539.478
2140 5 992 1 294 109196.690
2141 6 1034 2 504 158295.512
2142 5 1073 1 270 112216.631
2143 5 1126 2 506 135950.330
2144 5 1140 2 400 132247.684
2145 5 960 1 300 107859.222
2146 6 1188 2 621 170782.680
2147 5 1721 2 626 170423.625
2148 5 1350 3 627 163391.042
2149 5 904 3 912 153102.714
2150 7 1524 2 478 208496.708
2151 7 1079 1 249 165620.739
2152 5 1518 0 0 111760.034
2153 5 1509 1 322 135987.315
2154 5 864 0 0 79339.292
2155 6 1269 1 280 149336.573
2156 6 2814 2 614 251098.032
2157 7 1626 2 534 215875.922
2158 7 2200 2 453 240971.106
2159 7 2037 2 472 233678.789
2160 7 1356 2 484 200417.312
2161 8 1615 3 864 267324.735
2162 9 2276 3 1348 347156.694
2163 9 1766 3 874 302213.892
2164 8 1511 3 811 259970.809
2165 6 1643 2 438 185747.921
2166 5 990 2 528 130120.918
2167 7 1418 2 558 206560.210
2168 6 1771 2 600 198812.701
2169 7 1652 2 532 217081.864
2170 7 1823 2 626 229457.779
2171 5 1174 2 528 139242.350
2172 5 1076 2 576 136375.140
2173 5 1558 2 440 154628.318
2174 7 2161 2 570 243890.685
2175 9 1947 3 725 305006.383
2176 8 1786 3 715 269621.496
2177 7 2327 2 596 253198.231
2178 8 1764 2 560 250784.278
2179 6 848 2 420 145590.782
2180 6 1838 3 721 218470.452
2181 7 1445 2 470 204248.617
2182 7 1564 3 814 235733.758
2183 7 1361 2 610 205891.405
2184 5 1092 1 264 112909.650
2185 5 1033 2 504 131257.085
2186 6 1127 2 480 161910.329
2187 6 1117 2 542 163986.235
2188 6 1398 2 440 173685.492
2189 5 3820 2 624 274394.396
2190 4 1152 0 0 66627.462
2191 4 1152 0 0 66627.462
2192 4 784 0 0 48384.598
2193 5 1053 0 0 88708.589
2194 5 1137 0 0 92872.721
2195 4 930 1 286 78802.486
2196 4 1204 1 312 93463.916
2197 4 1292 1 205 93388.194
2198 7 1424 1 312 185336.538
2199 6 1920 2 480 201221.718
2200 6 1316 1 369 155358.046
2201 6 1264 2 400 165383.590
2202 8 1512 1 180 211212.720
2203 6 1603 2 599 190442.959
2204 5 1938 1 240 153852.936
2205 5 1374 1 225 125271.594
2206 6 1091 1 344 143167.171
2207 8 1873 2 786 265561.763
2208 7 2161 2 506 241236.093
2209 5 1898 2 484 173308.170
2210 6 1032 2 462 156454.290
2211 6 919 1 195 128460.393
2212 6 1090 1 240 138803.886
2213 5 1200 0 0 95995.820
2214 5 1656 1 288 141864.294
2215 5 912 1 360 107968.398
2216 5 1955 1 356 159507.125
2217 1 733 2 487 7724.643
2218 4 1361 1 185 95979.171
2219 4 1049 1 195 80927.175
2220 4 864 1 216 72627.208
2221 8 1648 2 525 243582.080
2222 7 1646 2 482 214710.526
2223 7 2032 3 786 257772.538
2224 7 1820 3 816 248507.402
2225 5 1872 2 484 172019.272
2226 4 1689 2 432 133801.703
2227 7 1501 2 512 208766.781
2228 8 1537 3 788 260305.713
2229 8 1780 2 612 253734.302
2230 5 1442 2 400 147218.730
2231 7 1612 3 666 231974.518
2232 6 1495 2 438 178411.117
2233 6 1256 2 578 172370.090
2234 8 1440 2 467 230865.172
2235 6 1675 2 435 187209.823
2236 8 1728 2 520 247340.530
2237 8 1964 3 892 285787.096
2238 7 1344 4 784 234900.880
2239 5 1092 0 0 90641.936
2240 6 1189 2 392 161333.791
2241 4 1200 3 850 138215.832
2242 5 1040 2 499 131396.706
2243 5 1475 1 336 134882.525
2244 4 988 1 297 82133.978
2245 4 988 1 297 82133.978
2246 5 1160 1 257 115990.268
2247 6 1092 0 0 117630.790
2248 5 816 1 264 99227.502
2249 5 845 1 264 100665.119
2250 5 889 2 484 123289.013
2251 5 1836 1 288 150787.434
2252 6 1587 2 525 186580.419
2253 6 1384 2 390 170917.570
2254 6 1694 2 398 186617.024
2255 6 1714 2 451 189806.818
2256 7 1553 2 420 207528.601
2257 6 2299 2 482 220092.841
2258 7 1187 2 420 189384.883
2259 6 1642 2 392 183790.360
2260 6 1128 2 480 161959.902
2261 8 1179 2 480 218465.833
2262 8 1321 2 484 225671.111
2263 8 2541 3 729 307629.803
2264 9 2338 3 1110 340358.456
2265 5 1424 3 828 175396.522
2266 9 1612 2 556 270072.124
2267 8 2234 2 724 280885.980
2268 10 2042 3 724 336663.194
2269 6 1284 2 480 169693.290
2270 7 1479 2 484 206514.791
2271 7 1664 2 663 223110.358
2272 7 1930 2 481 228747.780
2273 6 1177 2 495 165011.149
2274 6 1353 2 478 173030.871
2275 6 1220 2 944 185766.410
2276 7 1324 2 585 203020.254
2277 6 1877 2 488 199421.903
2278 5 1422 2 576 153527.398
2279 5 914 1 368 108399.368
2280 4 914 1 270 77345.670
2281 6 1337 2 511 173606.477
2282 6 1337 2 522 174062.735
2283 6 1092 1 264 139898.504
2284 6 1218 1 264 146144.702
2285 7 1055 1 319 167334.447
2286 5 988 1 360 111735.946
2287 9 1816 3 730 298719.710
2288 8 1694 3 856 270909.178
2289 8 2122 3 938 295527.618
2290 9 2656 3 1040 353219.210
2291 8 2550 3 670 305628.758
2292 10 2046 3 878 343249.098
2293 9 2552 3 932 343583.994
2294 9 2758 3 814 348901.628
2295 10 2290 3 1174 367622.398
2296 8 2152 2 728 276986.906
2297 8 2100 3 786 288132.356
2298 9 1802 3 843 302712.702
2299 8 2956 3 916 335958.984
2300 8 2385 3 818 303587.957
2301 8 1818 3 774 273655.034
2302 7 1614 3 878 240867.000
2303 8 1721 2 554 248403.771
2304 8 1828 3 876 278381.520
2305 6 1302 2 631 176848.782
2306 6 1302 2 631 176848.782
2307 6 1362 2 460 172730.424
2308 8 1554 2 627 243152.974
2309 9 1577 2 564 268668.893
2310 8 1324 2 550 228557.378
2311 7 1405 2 478 202597.521
2312 6 1496 2 572 184018.742
2313 6 1536 2 400 178867.446
2314 7 1458 2 454 204229.418
2315 6 1495 2 440 178494.073
2316 6 1746 3 350 198521.398
2317 6 1326 2 388 167959.380
2318 6 1504 2 440 178940.230
2319 7 1456 2 400 201890.460
2320 7 1258 2 462 194646.642
2321 8 1589 3 630 256329.985
2322 7 1266 2 388 191973.854
2323 7 1119 2 437 186719.045
2324 7 1374 2 400 197825.474
2325 7 1525 2 534 210869.049
2326 7 1394 2 400 198816.934
2327 7 1948 2 434 227690.628
2328 7 1995 2 435 230062.037
2329 6 1690 2 442 188243.764
2330 6 1644 2 460 186710.010
2331 8 2551 3 925 316255.221
2332 9 3078 3 806 364433.164
2333 8 2582 3 758 310865.158
2334 7 2385 3 600 267556.899
2335 8 2202 2 517 270713.698
2336 8 2538 3 933 315942.596
2337 7 1369 2 605 206080.599
2338 8 1542 3 852 263208.170
2339 8 1534 2 484 236230.160
2340 10 1966 3 1092 348159.550
2341 7 1528 2 480 208777.956
2342 8 1538 2 484 236428.452
2343 7 1506 2 672 215651.126
2344 7 1977 3 574 246252.687
2345 8 1830 3 859 277775.540
2346 8 1338 2 598 231242.344
2347 7 1335 2 575 203150.777
2348 8 1792 2 590 253416.662
2349 5 1588 2 561 161134.346
2350 8 1880 3 880 281125.228
2351 8 1584 2 594 243271.390
2352 8 1685 3 658 262250.377
2353 6 2443 3 744 249416.111
2354 6 1100 0 0 118027.374
2355 7 1143 0 0 147147.867
2356 5 1094 2 576 137267.454
2357 7 1486 2 566 210262.998
2358 6 1820 2 492 196762.154
2359 6 1266 1 283 149312.288
2360 5 894 1 308 104919.228
2361 5 1040 2 686 139153.092
2362 7 2503 2 564 260595.783
2363 5 1037 2 431 128427.483
2364 6 1055 2 542 160912.709
2365 8 1378 2 540 230819.540
2366 8 1151 2 484 217243.701
2367 8 1565 2 476 237435.099
2368 7 1352 2 466 199472.416
2369 8 1550 2 528 238848.360
2370 6 1501 2 440 178791.511
2371 6 1573 2 440 182360.767
2372 7 1358 2 625 206364.856
2373 8 2048 2 552 264531.186
2374 8 2362 2 1105 303034.442
2375 8 1494 2 478 233998.372
2376 7 2362 2 546 252859.386
2377 8 2497 2 676 291932.735
2378 6 1152 2 412 160329.150
2379 6 2411 2 570 229295.081
2380 6 1082 2 480 159679.544
2381 6 1295 2 528 172229.537
2382 7 1610 2 515 214294.672
2383 7 1594 2 472 211717.950
2384 7 2075 2 473 235604.041
2385 6 1093 2 484 160390.759
2386 6 1052 1 311 139865.050
2387 5 1107 1 308 115478.277
2388 4 1224 3 530 126132.624
2389 5 1074 2 396 128809.954
2390 5 1187 2 440 136236.735
2391 5 964 2 784 139450.388
2392 5 894 1 312 105085.140
2393 7 1200 2 440 190858.892
2394 6 1042 2 440 156037.504
2395 6 2154 2 539 215269.002
2396 6 1374 1 286 154790.606
2397 6 1652 2 510 189180.494
2398 5 908 2 512 125392.284
2399 3 666 0 0 15546.130
2400 3 670 0 0 15744.422
2401 5 808 1 308 100655.950
2402 5 1150 1 288 116780.356
2403 5 1560 3 792 180645.242
2404 5 1280 2 432 140515.200
2405 6 1254 2 525 170072.610
2406 6 936 1 315 134280.494
2407 5 1008 1 308 110570.550
2408 5 1053 2 692 140046.409
2409 5 1144 1 336 118473.862
2410 6 1721 2 464 190693.043
2411 5 922 1 308 106307.272
2412 5 1411 1 310 130631.425
2413 5 1216 1 336 122043.118
2414 5 1154 1 336 118969.592
2415 5 1560 2 484 156552.496
2416 6 948 2 410 150133.302
2417 6 1040 1 293 138523.570
2418 5 925 1 252 104133.223
2419 4 1540 1 352 111779.564
2420 5 925 1 390 109857.187
2421 4 1647 1 280 114097.459
2422 5 924 1 420 111051.954
2423 4 1544 0 0 86060.078
2424 5 1728 1 371 148876.224
2425 5 3086 3 1200 273216.664
2426 4 1281 2 580 119714.663
2427 5 1534 0 0 112553.202
2428 7 1651 1 276 195096.401
2429 5 888 1 240 101801.286
2430 6 952 1 288 133953.756
2431 5 1238 1 357 124004.762
2432 5 1040 1 286 111244.370
2433 5 1170 1 338 119845.716
2434 5 1242 1 324 122834.280
2435 5 1377 1 351 130646.541
2436 5 925 1 300 106124.167
2437 5 864 1 294 102851.346
2438 5 936 1 288 106171.734
2439 5 960 2 576 130624.672
2440 6 1296 2 576 174270.054
2441 5 1022 1 184 106121.300
2442 5 967 1 180 103228.873
2443 5 1072 2 379 128005.682
2444 5 1174 2 576 141233.294
2445 4 1141 1 252 87852.137
2446 4 1798 2 342 135472.140
2447 8 1772 2 816 261799.230
2448 6 1642 1 374 171726.234
2449 5 1232 2 480 140126.640
2450 6 1650 2 468 187339.272
2451 5 1358 1 336 129082.484
2452 7 2454 2 576 258664.442
2453 4 968 1 331 82552.770
2454 4 1382 1 384 105274.326
2455 5 1060 1 308 113148.346
2456 5 1435 1 308 131738.221
2457 5 1274 1 224 120272.816
2458 6 1232 1 217 144889.258
2459 5 884 1 240 101602.994
2460 6 1409 2 528 177880.859
2461 5 1322 1 280 124975.088
2462 5 1426 1 230 128056.780
2463 5 1281 2 379 138366.439
2464 6 2264 1 408 203970.892
2465 6 1376 2 576 178235.894
2466 5 1316 2 576 148272.660
2467 7 1344 2 456 198661.052
2468 5 1173 1 240 115929.591
2469 5 1214 1 216 116966.612
2470 6 2294 2 658 227145.104
2471 7 1952 1 299 210971.868
2472 6 2180 2 720 224065.418
2473 4 1315 2 436 115427.313
2474 4 1484 1 264 105353.412
2475 7 2267 2 498 246159.007
2476 5 1282 1 240 121333.048
2477 5 999 1 308 110124.393
2478 5 1452 2 572 154848.676
2479 4 1005 2 440 100225.595
2480 5 1020 2 528 131608.108
2481 5 1040 1 264 110331.854
2482 5 868 2 576 126063.956
2483 5 897 1 264 103242.915
2484 5 943 2 528 127790.987
2485 5 912 1 315 106101.888
2486 5 1375 1 323 129386.011
2487 5 2654 2 638 217172.970
2488 7 1302 1 224 175638.568
2489 6 1299 2 494 171017.577
2490 5 1176 1 303 118691.424
2491 4 998 2 460 100708.144
2492 6 1522 2 552 184478.080
2493 5 1325 2 576 148718.817
2494 5 1630 2 649 166866.476
2495 4 1242 1 336 96343.162
2496 6 2422 2 527 228056.830
2497 6 1626 1 332 169190.990
2498 5 864 1 399 107206.536
2499 4 943 1 308 80359.451
2500 5 1038 1 264 110232.708
2501 5 1342 1 256 124971.076
2502 5 1480 1 253 131687.716
2503 4 1362 1 280 99969.154
2504 6 1822 2 515 197815.294
2505 7 1958 2 499 230882.428
2506 8 1651 3 870 269358.231
2507 8 2140 3 894 294594.900
2508 8 1651 3 870 269358.231
2509 7 1546 3 796 234094.840
2510 8 1500 2 674 242425.498
2511 7 1270 2 524 197813.154
2512 7 1795 2 578 226078.791
2513 7 1873 2 619 231646.083
2514 8 1743 2 529 248457.427
2515 5 1022 2 747 140790.936
2516 6 1308 2 497 171588.168
2517 5 990 1 384 112830.564
2518 5 1097 1 242 112244.999
2519 7 1873 2 597 230733.567
2520 7 1753 2 534 222171.693
2521 7 1690 2 517 218343.468
2522 7 1842 2 486 224592.746
2523 5 894 2 440 121711.846
2524 5 1025 2 370 125302.449
2525 5 1009 2 576 133053.749
2526 5 1040 2 748 141724.728
2527 5 907 1 308 105563.677
2528 5 879 2 440 120968.251
2529 5 864 2 576 125865.664
2530 4 875 2 728 105726.769
2531 7 1673 2 583 220238.275
2532 7 1932 2 610 234197.588
2533 7 1729 2 542 221313.765
2534 8 1592 2 484 239105.394
2535 8 2439 2 560 284246.053
2536 7 1992 2 608 237089.012
2537 8 1341 2 482 226579.615
2538 7 1476 2 552 209186.576
2539 7 1190 2 578 196087.126
2540 6 1330 2 437 170190.094
2541 7 1491 2 484 207109.667
2542 5 1536 2 400 151878.592
2543 5 936 1 384 110153.622
2544 4 1088 2 520 107658.394
2545 5 1351 2 576 150007.715
2546 6 1179 2 622 170378.001
2547 6 1044 2 528 159786.714
2548 5 2233 2 579 193855.535
2549 5 1408 2 489 149224.790
2550 10 5095 3 1154 505845.103
2551 6 1072 2 525 161050.324
2552 5 960 1 392 111675.198
2553 4 1152 0 0 66627.462
2554 5 1195 0 0 95747.955
2555 6 865 1 216 126654.489
2556 4 768 1 355 73633.642
2557 4 864 2 528 96885.866
2558 5 2592 0 0 165001.436
2559 5 1422 1 352 132918.804
2560 6 1298 1 240 149115.070
2561 7 1098 1 216 165193.852
2562 6 1436 1 228 155458.408
2563 6 1461 1 225 156573.299
2564 7 1718 2 264 209237.578
2565 5 1226 2 400 136510.962
2566 4 1755 1 231 117418.921
2567 5 1355 2 528 148215.063
2568 6 1560 2 580 187523.238
2569 6 1488 2 552 182792.598
2570 6 1045 2 462 157098.739
2571 4 1680 2 628 141485.234
2572 8 1020 2 509 211786.588
2573 7 1696 2 625 223120.530
2574 8 2726 2 691 303907.122
2575 6 1215 2 720 176227.473
2576 5 1601 0 0 115874.593
2577 5 1828 0 0 NA
2578 5 816 1 100 92425.110
2579 2 845 1 256 19366.733
2580 5 1991 0 0 135208.063
2581 4 1073 2 720 115210.399
2582 5 1001 1 216 106407.563
2583 8 1625 2 495 241197.561
2584 6 1299 2 486 170685.753
2585 5 1392 3 650 166427.102
2586 7 1409 2 576 206860.657
2587 7 1478 2 506 207377.734
2588 7 918 1 360 162243.544
2589 6 1026 2 528 158894.400
2590 7 1501 2 512 208766.781
2591 6 2279 2 461 218230.343
2592 7 1689 2 433 214809.743
2593 8 1564 2 502 238463.954
2594 7 1240 2 528 196491.876
2595 8 1312 2 471 224685.740
2596 8 1922 3 692 275409.430
2597 6 1491 2 571 183729.399
2598 7 2486 2 452 255107.506
2599 10 1824 3 932 334483.704
2600 3 2034 4 1041 171810.680
2601 6 936 2 460 151612.326
2602 4 1092 1 253 85464.538
2603 4 992 1 297 82332.270
2604 4 1092 0 0 63653.082
2605 4 1092 1 286 86833.312
2606 5 1008 2 678 137234.932
2607 6 1356 2 528 175253.490
2608 5 1676 2 672 170100.828
2609 5 1432 2 531 152156.618
2610 5 796 0 0 75968.328
2611 4 1608 1 444 118966.504
2612 5 1178 2 502 138362.214
2613 5 816 1 264 99227.502
2614 5 887 1 288 103742.657
2615 6 1293 2 452 168978.063
2616 6 1024 1 313 138559.962
2617 5 1797 3 963 199486.781
2618 6 1390 2 550 177851.488
2619 7 1851 2 506 225868.463
2620 6 1525 2 400 178322.143
2621 6 1671 2 423 186513.795
2622 6 1776 2 443 192548.520
2623 8 2064 2 527 264287.404
2624 7 2212 3 773 266156.464
2625 8 2687 2 618 298945.881
2626 6 1169 2 402 160757.111
2627 8 1204 2 461 218917.076
2628 9 2798 3 670 344911.716
2629 10 3390 3 758 404897.850
2630 9 2473 3 675 329007.881
2631 10 2698 3 736 369680.818
2632 9 2795 3 660 344348.217
2633 9 1714 2 517 273510.928
2634 9 2000 3 722 307509.318
2635 6 1102 2 582 164901.760
2636 7 1857 2 482 225170.429
2637 7 1083 2 596 191529.419
2638 7 2318 2 541 250470.784
2639 6 1875 2 485 199198.323
2640 6 1103 2 462 159973.973
2641 4 874 2 576 99372.540
2642 6 1419 2 543 178998.759
2643 6 1092 2 440 158516.154
2644 5 1365 2 440 145060.729
2645 6 1030 1 264 136824.978
2646 6 948 1 264 132759.992
2647 6 1092 1 264 139898.504
2648 6 1069 2 440 157375.975
2649 5 1387 1 300 129026.893
2650 7 1055 1 319 167334.447
2651 6 1456 2 460 177390.286
2652 9 2589 3 831 341228.917
2653 8 1618 3 880 268137.102
2654 7 1740 3 874 246947.286
2655 9 1868 3 1085 316022.196
2656 9 2206 3 670 315564.500
2657 9 2091 2 521 292365.861
2658 8 2253 2 575 275647.645
2659 8 2389 3 672 297730.461
2660 8 2358 3 784 300839.234
2661 9 1792 3 925 305618.168
2662 9 1780 3 816 300502.190
2663 8 1914 3 746 277252.658
2664 9 1565 2 556 267742.193
2665 9 1686 3 899 299285.002
2666 9 1666 2 575 273537.148
2667 6 1456 2 390 174486.826
2668 7 1492 2 440 205334.208
2669 6 1326 2 427 169577.022
2670 8 2373 3 632 295278.173
2671 7 1492 2 440 205334.208
2672 7 1364 2 437 198864.430
2673 7 1511 2 398 204534.019
2674 7 1548 2 388 205953.440
2675 7 1142 2 440 187983.658
2676 7 1598 2 433 210298.600
2677 6 1889 2 431 197652.533
2678 7 2322 3 617 265138.926
2679 8 1976 3 885 286091.626
2680 8 2234 3 768 294028.534
2681 9 2855 3 774 352051.089
2682 8 2726 3 725 316634.896
2683 9 3500 3 959 391699.104
2684 8 2494 3 803 308369.244
2685 8 2799 3 704 319382.687
2686 8 1964 2 760 268994.478
2687 8 1670 3 928 272705.842
2688 8 1504 2 510 235821.398
2689 8 1278 2 584 227687.272
2690 9 2640 3 792 342139.498
2691 6 1716 2 615 196708.356
2692 6 1142 0 0 120109.440
2693 7 1400 2 612 207907.708
2694 6 1131 0 0 119564.137
2695 7 1686 2 462 215863.886
2696 7 1585 2 449 210317.799
2697 6 1837 2 688 205734.583
2698 6 1731 2 462 191105.817
2699 6 1398 2 542 177916.248
2700 6 1217 2 484 166537.811
2701 6 1320 2 472 171146.094
2702 5 988 2 624 134003.660
2703 6 1654 2 528 190026.244
2704 5 1211 2 576 143067.495
2705 5 984 1 310 109463.754
2706 5 909 1 294 105082.131
2707 5 925 2 484 125073.641
2708 5 1024 1 308 111363.718
2709 5 912 0 0 81718.796
2710 5 941 1 288 106419.599
2711 7 2646 2 550 267104.030
2712 8 2826 3 888 328353.110
2713 7 1143 2 588 194171.975
2714 7 1223 2 480 193658.191
2715 6 1524 2 440 179931.690
2716 7 1080 2 496 187232.900
2717 7 1694 1 434 203781.564
2718 8 1568 2 564 241233.882
2719 5 1193 2 501 139064.331
2720 7 1334 2 477 199036.360
2721 5 1051 2 504 132149.399
2722 5 1770 2 530 168870.814
2723 6 976 2 504 155420.278
2724 5 898 1 326 105864.124
2725 5 1051 1 264 110877.157
2726 5 1141 1 568 127948.039
2727 6 1565 1 299 164798.263
2728 6 1488 2 430 177732.282
2729 5 1440 2 480 150437.824
2730 5 1248 1 286 121555.554
2731 6 816 1 240 125220.884
2732 5 1043 1 273 110853.875
2733 5 1433 2 441 148473.171
2734 5 1624 1 240 138287.014
2735 5 1216 1 280 119720.350
2736 5 1728 1 234 143193.738
2737 5 936 1 240 104180.790
2738 5 1584 2 506 158654.764
2739 6 1246 2 441 166191.874
2740 6 1008 2 430 153937.242
2741 5 1364 1 331 129172.532
2742 6 1336 2 488 172602.910
2743 5 1370 1 300 128184.152
2744 6 1124 1 353 145176.382
2745 6 1050 1 286 138728.954
2746 5 1008 1 280 109409.166
2747 6 1575 2 400 180800.793
2748 5 1145 2 684 144275.301
2749 5 1005 1 319 110878.089
2750 5 1056 1 300 112618.230
2751 5 884 1 270 102847.334
2752 7 2039 3 791 258326.939
2753 5 1384 2 896 164916.584
2754 5 2640 3 1008 243143.330
2755 6 1312 2 649 178091.116
2756 3 713 1 371 44581.921
2757 3 715 2 660 67985.731
2758 4 720 1 280 68143.288
2759 6 1595 2 528 187101.437
2760 4 1760 2 648 146280.634
2761 6 1146 1 294 143819.786
2762 6 1207 1 264 145599.399
2763 6 1773 2 418 191362.851
2764 7 1472 2 484 206167.780
2765 7 2448 2 441 252767.474
2766 4 1521 1 597 120999.787
2767 3 1040 2 400 73312.676
2768 5 1556 0 0 113643.808
2769 5 1150 1 288 116780.356
2770 7 1045 2 528 186825.141
2771 5 864 1 336 104593.422
2772 5 1025 0 0 87320.545
2773 5 2014 2 624 184865.558
2774 5 1668 1 240 140468.226
2775 4 1657 1 162 109698.785
2776 6 1416 2 400 172918.686
2777 7 1428 2 576 207802.544
2778 7 1004 1 200 159870.342
2779 4 1951 2 576 152762.661
2780 6 1032 1 280 137587.772
2781 5 844 1 216 98624.602
2782 4 864 1 528 85568.344
2783 3 1376 1 216 71019.730
2784 5 960 2 576 130624.672
2785 5 1566 2 450 155439.682
2786 3 492 1 200 26533.550
2787 6 1182 1 378 149088.566
2788 3 840 1 250 45858.854
2789 7 2104 2 432 235341.060
2790 5 1248 0 0 98375.324
2791 5 960 2 624 132615.616
2792 3 1020 0 0 33094.972
2793 6 1827 1 240 175339.187
2794 3 1162 1 258 62153.184
2795 5 1324 1 180 120926.434
2796 5 816 1 210 96987.690
2797 6 2486 2 576 233261.924
2798 4 1430 2 370 118390.660
2799 5 1330 1 390 129934.252
2800 5 819 0 0 77108.507
2801 6 984 1 308 136369.652
2802 5 1422 1 288 130264.212
2803 6 1921 2 576 205253.179
2804 5 1640 2 394 156785.316
2805 5 1032 1 260 109769.358
2806 5 879 1 180 98866.449
2807 7 1073 1 246 165198.867
2808 5 1064 2 528 133789.320
2809 6 934 1 336 135052.386
2810 5 1059 1 286 112186.257
2811 5 1458 2 512 152657.434
2812 6 1040 2 616 163238.486
2813 5 1967 2 580 180710.595
2814 5 1949 2 586 180067.149
2815 5 872 1 322 104409.314
2816 7 1830 2 521 225449.600
2817 5 1000 2 575 132566.114
2818 5 810 2 576 123188.722
2819 7 1700 1 450 204742.650
2820 4 1350 2 504 119982.872
2821 5 1150 1 215 113752.462
2822 6 2009 3 795 230016.807
2823 6 3672 2 836 302839.782
2824 5 1560 2 528 158377.528
2825 5 1488 2 569 156508.870
2826 5 1057 1 288 112170.067
2827 6 1609 1 305 167228.343
2828 6 2559 2 506 233977.293
2829 6 1440 4 920 218312.042
2830 7 1876 3 848 252610.786
2831 7 1208 2 632 199219.252
2832 6 1846 2 495 198175.486
2833 8 1590 3 754 261522.830
2834 7 1809 2 638 229261.493
2835 7 1614 2 576 217023.122
2836 7 1596 2 610 217541.060
2837 6 1388 2 522 176590.958
2838 5 1100 2 462 132836.400
2839 6 1499 2 473 180061.139
2840 7 1425 2 591 208275.995
2841 7 1749 2 515 221185.319
2842 7 1779 2 586 225617.447
2843 6 1388 1 317 156770.446
2844 6 1282 3 672 188875.442
2845 5 864 1 297 102975.780
2846 7 1762 2 591 224982.096
2847 6 1755 2 530 195116.073
2848 8 1358 2 418 224767.764
2849 7 1909 2 529 229697.691
2850 8 2214 3 646 287976.758
2851 7 2049 2 467 234066.275
2852 7 1939 3 555 243580.831
2853 7 1995 2 610 237320.687
2854 6 848 2 420 145590.782
2855 7 1390 2 545 204632.952
2856 7 1737 2 578 223203.557
2857 7 1611 2 572 216708.491
2858 7 1336 2 502 200172.456
2859 4 1436 2 528 125241.622
2860 6 1012 0 0 113664.950
2861 5 1176 1 360 121055.670
2862 7 1724 2 616 224135.272
2863 6 914 0 0 108806.796
2864 7 2314 2 502 248654.850
2865 6 1072 2 525 161050.324
2866 7 1709 2 380 213602.869
2867 4 936 1 265 78228.886
2868 6 1338 2 528 174361.176
2869 4 1669 1 288 115519.889
2870 4 1482 2 609 130881.698
2871 4 1414 0 0 79615.588
2872 2 498 1 216 505.782
2873 4 1273 1 275 95349.767
2874 5 1551 1 240 134668.185
2875 6 1340 1 440 159492.736
2876 7 1479 1 312 188063.053
2877 6 1510 1 216 158629.074
2878 7 1636 1 288 194850.542
2879 5 1465 1 240 130404.907
2880 5 1288 1 240 121630.486
2881 6 1550 1 318 164842.750
2882 5 1717 1 410 149948.563
2883 7 1671 2 451 214664.033
2884 7 1609 3 579 228217.213
2885 6 1801 2 365 190552.561
2886 5 2315 1 342 176772.713
2887 5 976 1 215 105126.760
2888 6 1285 2 506 170821.291
2889 4 672 0 0 42832.422
2890 4 641 1 272 63895.197
2891 6 1638 1 384 171942.722
2892 3 729 0 0 18669.229
2893 5 1396 0 0 105712.128
2894 3 936 0 0 28930.840
2895 8 1778 2 495 248782.230
2896 8 1646 2 525 243482.934
2897 6 1625 2 576 190579.571
2898 6 1664 2 616 194172.038
2899 8 1491 2 490 234347.389
2900 6 1210 2 528 168015.832
2901 6 1650 2 518 189413.172
2902 6 1403 2 470 175177.697
2903 8 1960 3 714 278205.720
2904 9 1838 3 682 297819.372
2905 1 1600 1 270 30386.186
2906 7 1368 4 784 236090.632
2907 5 1304 1 336 126405.542
2908 5 874 1 288 103098.208
2909 5 1652 3 928 190846.966
2910 4 630 0 0 40750.356
2911 4 1092 1 253 85464.538
2912 5 1360 1 336 129181.630
2913 4 1092 1 286 86833.312
2914 4 1092 0 0 63653.082
2915 4 1092 0 0 63653.082
2916 4 1092 1 286 86833.312
2917 5 1224 2 576 143711.944
2918 5 970 0 0 84594.030
2919 7 2000 3 650 250545.194
write.csv(new.df, file = "kagglesubmission.csv")

#When I tried to submit the first time, I realized that my file was not in the proper format so I have to come make some changes

sub.df <- new.df[,c("Id", "SalePrice")]
kable(sub.df)
Id SalePrice
1461 122522.090
1462 153638.249
1463 159890.077
1464 185141.870
1465 224551.134
1466 186425.753
1467 162396.029
1468 175057.417
1469 200586.233
1470 97653.746
1471 200595.331
1472 134693.339
1473 115232.418
1474 176560.726
1475 156021.702
1476 325269.562
1477 263970.964
1478 292870.096
1479 269871.438
1480 351800.934
1481 294323.966
1482 228100.188
1483 169602.310
1484 188007.943
1485 197825.474
1486 216990.955
1487 314022.359
1488 266996.923
1489 201540.014
1490 180805.666
1491 215437.931
1492 115787.680
1493 179315.538
1494 299480.561
1495 291301.087
1496 207873.464
1497 220792.676
1498 192518.012
1499 192518.012
1500 167313.786
1501 179336.814
1502 187232.900
1503 257061.118
1504 256275.706
1505 211804.776
1506 198991.865
1507 237192.233
1508 207996.745
1509 185971.501
1510 140541.420
1511 139981.933
1512 155442.620
1513 194033.633
1514 122170.364
1515 197733.617
1516 182762.366
1517 143798.510
1518 162549.684
1519 212205.372
1520 117262.905
1521 120551.916
1522 182707.778
1523 98024.703
1524 113761.418
1525 108661.488
1526 107754.058
1527 109022.943
1528 147105.788
1529 137466.891
1530 173536.773
1531 122204.220
1532 82908.548
1533 148772.473
1534 146785.139
1535 138733.171
1536 122609.697
1537 51774.278
1538 218369.286
1539 278423.662
1540 148344.908
1541 184886.700
1542 142793.932
1543 217385.984
1544 67055.833
1545 140885.952
1546 169312.754
1547 129810.031
1548 157951.100
1549 136581.456
1550 155196.832
1551 139704.224
1552 153142.052
1553 140830.954
1554 147915.288
1555 145999.987
1556 115969.134
1557 105513.836
1558 129953.601
1559 102914.898
1560 161091.004
1561 100337.102
1562 109299.706
1563 102270.654
1564 151720.491
1565 150437.824
1566 215257.551
1567 87881.918
1568 205987.747
1569 93570.004
1570 147426.224
1571 105402.053
1572 121106.246
1573 211602.472
1574 144393.930
1575 206059.465
1576 240280.834
1577 199208.148
1578 177840.455
1579 131038.449
1580 218276.702
1581 111462.864
1582 122644.564
1583 284739.042
1584 242882.964
1585 145590.782
1586 35529.474
1587 110233.640
1588 121051.658
1589 107585.610
1590 143746.860
1591 57109.446
1592 122856.630
1593 145116.328
1594 140887.816
1595 119096.838
1596 220483.795
1597 187139.037
1598 214634.662
1599 216172.152
1600 221176.087
1601 1924.200
1602 155615.657
1603 81718.124
1604 243482.934
1605 277144.414
1606 169452.517
1607 219844.550
1608 218539.232
1609 194871.154
1610 147317.876
1611 143703.920
1612 155914.926
1613 154223.284
1614 105166.161
1615 63653.082
1616 63653.082
1617 86833.312
1618 105752.800
1619 120969.183
1620 205255.248
1621 146190.594
1622 132550.659
1623 249482.341
1624 200765.247
1625 139359.938
1626 179120.184
1627 185340.162
1628 290816.603
1629 210002.236
1630 288526.524
1631 233910.330
1632 247969.792
1633 198056.146
1634 185483.866
1635 178249.288
1636 162959.528
1637 178535.472
1638 236687.484
1639 189043.953
1640 263921.399
1641 190621.191
1642 230615.222
1643 257398.692
1644 253321.599
1645 159327.581
1646 163355.970
1647 193249.429
1648 137424.410
1649 113814.000
1650 98876.810
1651 98876.810
1652 134693.339
1653 135688.811
1654 181121.442
1655 183670.807
1656 176560.726
1657 181121.442
1658 176560.726
1659 157556.388
1660 141874.592
1661 347106.970
1662 347604.564
1663 315717.950
1664 369569.494
1665 299067.582
1666 278423.930
1667 302897.228
1668 303272.047
1669 283347.065
1670 303300.486
1671 224551.126
1672 336718.706
1673 300681.488
1674 267168.924
1675 173527.604
1676 176756.728
1677 200516.458
1678 368303.594
1679 288900.378
1680 287413.434
1681 261633.610
1682 265372.402
1683 202597.521
1684 201475.680
1685 176255.264
1686 190066.798
1687 197825.474
1688 212009.370
1689 210141.786
1690 203526.369
1691 195948.792
1692 277483.472
1693 197825.474
1694 177527.972
1695 200601.562
1696 266343.794
1697 201016.342
1698 318227.179
1699 287501.017
1700 242127.191
1701 276597.556
1702 275819.772
1703 263732.410
1704 270808.026
1705 231505.538
1706 334827.982
1707 206249.662
1708 208546.068
1709 295077.244
1710 240594.306
1711 272846.679
1712 252569.980
1713 236319.678
1714 214496.905
1715 221113.325
1716 197392.214
1717 189759.117
1718 120902.608
1719 222773.732
1720 261430.634
1721 192236.622
1722 91732.542
1723 138258.914
1724 229004.008
1725 241501.080
1726 193793.792
1727 174644.430
1728 209995.002
1729 174821.588
1730 204813.040
1731 124316.004
1732 132336.232
1733 108907.134
1734 110335.866
1735 105479.718
1736 103488.774
1737 287104.362
1738 221856.059
1739 302605.871
1740 194964.274
1741 174983.204
1742 179336.814
1743 206088.836
1744 250715.364
1745 221776.112
1746 285851.659
1747 248107.115
1748 238366.008
1749 146194.748
1750 149031.972
1751 248112.556
1752 103597.950
1753 155124.048
1754 235946.969
1755 172100.088
1756 92897.960
1757 103432.038
1758 142845.462
1759 168696.736
1760 149534.193
1761 144760.140
1762 188000.906
1763 179523.070
1764 109103.562
1765 192772.961
1766 180145.027
1767 186294.085
1768 116399.962
1769 197295.287
1770 136111.686
1771 120021.800
1772 130852.928
1773 92519.020
1774 172178.092
1775 139780.088
1776 134177.880
1777 97091.851
1778 108475.445
1779 133359.520
1780 205824.923
1781 117516.930
1782 48290.798
1783 156030.120
1784 83998.553
1785 112215.628
1786 171889.815
1787 222781.614
1788 14764.115
1789 124973.350
1790 43061.419
1791 261183.898
1792 158323.328
1793 157597.478
1794 153185.481
1795 142367.985
1796 147354.514
1797 179628.527
1798 111625.767
1799 94067.898
1800 118416.265
1801 109190.593
1802 184135.081
1803 195694.830
1804 129185.049
1805 137568.573
1806 149845.626
1807 195940.902
1808 143463.218
1809 109083.092
1810 152969.198
1811 93843.039
1812 108240.351
1813 126433.910
1814 86782.427
1815 9973.080
1816 98991.744
1817 136873.800
1818 189115.253
1819 150278.460
1820 49970.934
1821 156768.582
1822 199396.093
1823 22040.193
1824 154762.380
1825 143756.092
1826 117711.068
1827 108101.069
1828 136619.728
1829 195348.038
1830 197668.510
1831 207132.610
1832 141999.564
1833 183597.534
1834 161275.429
1835 182890.000
1836 173330.766
1837 53738.482
1838 157140.739
1839 64861.440
1840 95995.820
1841 115386.294
1842 112324.946
1843 127683.842
1844 158295.512
1845 151695.796
1846 162455.632
1847 164428.033
1848 11740.162
1849 121369.913
1850 115120.091
1851 166019.463
1852 112263.195
1853 110860.967
1854 184880.761
1855 176352.120
1856 225887.733
1857 182973.760
1858 199456.068
1859 151829.019
1860 147941.697
1861 150738.413
1862 307927.927
1863 307927.927
1864 307927.927
1865 308900.806
1866 298772.150
1867 261696.624
1868 252959.472
1869 204528.578
1870 247189.070
1871 260695.134
1872 174875.244
1873 222095.829
1874 115153.332
1875 208002.913
1876 194382.650
1877 208637.190
1878 212302.512
1879 107015.407
1880 122869.218
1881 255360.015
1882 272019.718
1883 221447.297
1884 231041.106
1885 236723.813
1886 252422.264
1887 204561.171
1888 264440.474
1889 173586.346
1890 100360.297
1891 161050.324
1892 77535.796
1893 123729.816
1894 119691.714
1895 138142.236
1896 122789.864
1897 121053.806
1898 143850.302
1899 165456.374
1900 171596.864
1901 155074.475
1902 123665.917
1903 252653.212
1904 119127.338
1905 182719.885
1906 135561.431
1907 204509.584
1908 156039.510
1909 166220.171
1910 166220.171
1911 205166.282
1912 253215.495
1913 190508.856
1914 57488.244
1915 241798.526
1916 18627.150
1917 279780.020
1918 135277.972
1919 172372.167
1920 166085.415
1921 311699.670
1922 296473.525
1923 215277.239
1924 210413.723
1925 233119.302
1926 314631.356
1927 113722.878
1928 149648.668
1929 101222.458
1930 146692.801
1931 131867.867
1932 141194.035
1933 177293.644
1934 185141.870
1935 176425.188
1936 185224.826
1937 183244.054
1938 144509.408
1939 245391.996
1940 224551.134
1941 186164.707
1942 188107.223
1943 225551.763
1944 303689.322
1945 299601.994
1946 179734.330
1947 274971.756
1948 190507.506
1949 218700.580
1950 200386.796
1951 238252.544
1952 224314.436
1953 165286.379
1954 234730.926
1955 144060.100
1956 331045.428
1957 177334.624
1958 300071.354
1959 167887.520
1960 79182.880
1961 125865.664
1962 134693.339
1963 138343.403
1964 123319.980
1965 177390.286
1966 183670.807
1967 267389.424
1968 300535.920
1969 304367.020
1970 349899.106
1971 402730.948
1972 335573.299
1973 282145.340
1974 298388.952
1975 360576.508
1976 259866.719
1977 313688.813
1978 317753.728
1979 307005.280
1980 200962.615
1981 306802.834
1982 229449.692
1983 229449.692
1984 213387.242
1985 223279.041
1986 230272.846
1987 192641.514
1988 177536.067
1989 214977.732
1990 229574.402
1991 200516.458
1992 224790.106
1993 199932.828
1994 244820.678
1995 213631.095
1996 270523.501
1997 314584.144
1998 289777.150
1999 242354.925
2000 306559.399
2001 265827.649
2002 229293.564
2003 278980.479
2004 280827.790
2005 232395.846
2006 232513.046
2007 261094.008
2008 192663.722
2009 192689.002
2010 215387.355
2011 121745.349
2012 190758.672
2013 187671.025
2014 189075.330
2015 215297.307
2016 195272.745
2017 220217.141
2018 112533.126
2019 108077.574
2020 104720.936
2021 102104.742
2022 177096.860
2023 160816.777
2024 238755.571
2025 331589.066
2026 195370.967
2027 165529.158
2028 204524.708
2029 181171.015
2030 268830.864
2031 254644.820
2032 261831.831
2033 264359.193
2034 201884.300
2035 224454.057
2036 238642.044
2037 239683.077
2038 347806.111
2039 221315.779
2040 360196.106
2041 245759.209
2042 222400.430
2043 178275.437
2044 193625.874
2045 217403.516
2046 159774.741
2047 151212.796
2048 128889.617
2049 168696.736
2050 215153.674
2051 109167.390
2052 133074.164
2053 114198.548
2054 75331.444
2055 151969.572
2056 125055.035
2057 112124.506
2058 204592.682
2059 118235.166
2060 139120.302
2061 182253.526
2062 118481.886
2063 101503.848
2064 142631.368
2065 122828.814
2066 197265.908
2067 147757.392
2068 169639.768
2069 80092.245
2070 117226.513
2071 66925.168
2072 214684.400
2073 126327.292
2074 198692.358
2075 145035.687
2076 126460.540
2077 122989.088
2078 111139.135
2079 175459.806
2080 135208.268
2081 148123.610
2082 125739.620
2083 157774.628
2084 103240.767
2085 114148.975
2086 143756.029
2087 141319.543
2088 128932.762
2089 91757.166
2090 159768.108
2091 88538.728
2092 132497.618
2093 143415.312
2094 141397.399
2095 191662.730
2096 100687.469
2097 90047.060
2098 180815.095
2099 645.643
2100 61252.436
2101 157219.295
2102 185629.964
2103 111016.707
2104 191940.668
2105 112850.640
2106 48604.180
2107 250991.083
2108 109380.798
2109 87795.401
2110 116433.345
2111 194943.670
2112 143938.336
2113 117763.792
2114 147059.366
2115 167655.372
2116 121534.901
2117 176898.593
2118 151296.282
2119 131668.525
2120 122831.200
2121 76868.136
2122 91088.424
2123 94683.118
2124 229304.329
2125 177322.438
2126 199072.602
2127 188099.508
2128 164034.537
2129 142454.502
2130 163733.948
2131 200332.555
2132 140575.948
2133 150960.998
2134 152014.376
2135 120660.499
2136 49156.624
2137 110030.404
2138 130684.559
2139 160539.478
2140 109196.690
2141 158295.512
2142 112216.631
2143 135950.330
2144 132247.684
2145 107859.222
2146 170782.680
2147 170423.625
2148 163391.042
2149 153102.714
2150 208496.708
2151 165620.739
2152 111760.034
2153 135987.315
2154 79339.292
2155 149336.573
2156 251098.032
2157 215875.922
2158 240971.106
2159 233678.789
2160 200417.312
2161 267324.735
2162 347156.694
2163 302213.892
2164 259970.809
2165 185747.921
2166 130120.918
2167 206560.210
2168 198812.701
2169 217081.864
2170 229457.779
2171 139242.350
2172 136375.140
2173 154628.318
2174 243890.685
2175 305006.383
2176 269621.496
2177 253198.231
2178 250784.278
2179 145590.782
2180 218470.452
2181 204248.617
2182 235733.758
2183 205891.405
2184 112909.650
2185 131257.085
2186 161910.329
2187 163986.235
2188 173685.492
2189 274394.396
2190 66627.462
2191 66627.462
2192 48384.598
2193 88708.589
2194 92872.721
2195 78802.486
2196 93463.916
2197 93388.194
2198 185336.538
2199 201221.718
2200 155358.046
2201 165383.590
2202 211212.720
2203 190442.959
2204 153852.936
2205 125271.594
2206 143167.171
2207 265561.763
2208 241236.093
2209 173308.170
2210 156454.290
2211 128460.393
2212 138803.886
2213 95995.820
2214 141864.294
2215 107968.398
2216 159507.125
2217 7724.643
2218 95979.171
2219 80927.175
2220 72627.208
2221 243582.080
2222 214710.526
2223 257772.538
2224 248507.402
2225 172019.272
2226 133801.703
2227 208766.781
2228 260305.713
2229 253734.302
2230 147218.730
2231 231974.518
2232 178411.117
2233 172370.090
2234 230865.172
2235 187209.823
2236 247340.530
2237 285787.096
2238 234900.880
2239 90641.936
2240 161333.791
2241 138215.832
2242 131396.706
2243 134882.525
2244 82133.978
2245 82133.978
2246 115990.268
2247 117630.790
2248 99227.502
2249 100665.119
2250 123289.013
2251 150787.434
2252 186580.419
2253 170917.570
2254 186617.024
2255 189806.818
2256 207528.601
2257 220092.841
2258 189384.883
2259 183790.360
2260 161959.902
2261 218465.833
2262 225671.111
2263 307629.803
2264 340358.456
2265 175396.522
2266 270072.124
2267 280885.980
2268 336663.194
2269 169693.290
2270 206514.791
2271 223110.358
2272 228747.780
2273 165011.149
2274 173030.871
2275 185766.410
2276 203020.254
2277 199421.903
2278 153527.398
2279 108399.368
2280 77345.670
2281 173606.477
2282 174062.735
2283 139898.504
2284 146144.702
2285 167334.447
2286 111735.946
2287 298719.710
2288 270909.178
2289 295527.618
2290 353219.210
2291 305628.758
2292 343249.098
2293 343583.994
2294 348901.628
2295 367622.398
2296 276986.906
2297 288132.356
2298 302712.702
2299 335958.984
2300 303587.957
2301 273655.034
2302 240867.000
2303 248403.771
2304 278381.520
2305 176848.782
2306 176848.782
2307 172730.424
2308 243152.974
2309 268668.893
2310 228557.378
2311 202597.521
2312 184018.742
2313 178867.446
2314 204229.418
2315 178494.073
2316 198521.398
2317 167959.380
2318 178940.230
2319 201890.460
2320 194646.642
2321 256329.985
2322 191973.854
2323 186719.045
2324 197825.474
2325 210869.049
2326 198816.934
2327 227690.628
2328 230062.037
2329 188243.764
2330 186710.010
2331 316255.221
2332 364433.164
2333 310865.158
2334 267556.899
2335 270713.698
2336 315942.596
2337 206080.599
2338 263208.170
2339 236230.160
2340 348159.550
2341 208777.956
2342 236428.452
2343 215651.126
2344 246252.687
2345 277775.540
2346 231242.344
2347 203150.777
2348 253416.662
2349 161134.346
2350 281125.228
2351 243271.390
2352 262250.377
2353 249416.111
2354 118027.374
2355 147147.867
2356 137267.454
2357 210262.998
2358 196762.154
2359 149312.288
2360 104919.228
2361 139153.092
2362 260595.783
2363 128427.483
2364 160912.709
2365 230819.540
2366 217243.701
2367 237435.099
2368 199472.416
2369 238848.360
2370 178791.511
2371 182360.767
2372 206364.856
2373 264531.186
2374 303034.442
2375 233998.372
2376 252859.386
2377 291932.735
2378 160329.150
2379 229295.081
2380 159679.544
2381 172229.537
2382 214294.672
2383 211717.950
2384 235604.041
2385 160390.759
2386 139865.050
2387 115478.277
2388 126132.624
2389 128809.954
2390 136236.735
2391 139450.388
2392 105085.140
2393 190858.892
2394 156037.504
2395 215269.002
2396 154790.606
2397 189180.494
2398 125392.284
2399 15546.130
2400 15744.422
2401 100655.950
2402 116780.356
2403 180645.242
2404 140515.200
2405 170072.610
2406 134280.494
2407 110570.550
2408 140046.409
2409 118473.862
2410 190693.043
2411 106307.272
2412 130631.425
2413 122043.118
2414 118969.592
2415 156552.496
2416 150133.302
2417 138523.570
2418 104133.223
2419 111779.564
2420 109857.187
2421 114097.459
2422 111051.954
2423 86060.078
2424 148876.224
2425 273216.664
2426 119714.663
2427 112553.202
2428 195096.401
2429 101801.286
2430 133953.756
2431 124004.762
2432 111244.370
2433 119845.716
2434 122834.280
2435 130646.541
2436 106124.167
2437 102851.346
2438 106171.734
2439 130624.672
2440 174270.054
2441 106121.300
2442 103228.873
2443 128005.682
2444 141233.294
2445 87852.137
2446 135472.140
2447 261799.230
2448 171726.234
2449 140126.640
2450 187339.272
2451 129082.484
2452 258664.442
2453 82552.770
2454 105274.326
2455 113148.346
2456 131738.221
2457 120272.816
2458 144889.258
2459 101602.994
2460 177880.859
2461 124975.088
2462 128056.780
2463 138366.439
2464 203970.892
2465 178235.894
2466 148272.660
2467 198661.052
2468 115929.591
2469 116966.612
2470 227145.104
2471 210971.868
2472 224065.418
2473 115427.313
2474 105353.412
2475 246159.007
2476 121333.048
2477 110124.393
2478 154848.676
2479 100225.595
2480 131608.108
2481 110331.854
2482 126063.956
2483 103242.915
2484 127790.987
2485 106101.888
2486 129386.011
2487 217172.970
2488 175638.568
2489 171017.577
2490 118691.424
2491 100708.144
2492 184478.080
2493 148718.817
2494 166866.476
2495 96343.162
2496 228056.830
2497 169190.990
2498 107206.536
2499 80359.451
2500 110232.708
2501 124971.076
2502 131687.716
2503 99969.154
2504 197815.294
2505 230882.428
2506 269358.231
2507 294594.900
2508 269358.231
2509 234094.840
2510 242425.498
2511 197813.154
2512 226078.791
2513 231646.083
2514 248457.427
2515 140790.936
2516 171588.168
2517 112830.564
2518 112244.999
2519 230733.567
2520 222171.693
2521 218343.468
2522 224592.746
2523 121711.846
2524 125302.449
2525 133053.749
2526 141724.728
2527 105563.677
2528 120968.251
2529 125865.664
2530 105726.769
2531 220238.275
2532 234197.588
2533 221313.765
2534 239105.394
2535 284246.053
2536 237089.012
2537 226579.615
2538 209186.576
2539 196087.126
2540 170190.094
2541 207109.667
2542 151878.592
2543 110153.622
2544 107658.394
2545 150007.715
2546 170378.001
2547 159786.714
2548 193855.535
2549 149224.790
2550 505845.103
2551 161050.324
2552 111675.198
2553 66627.462
2554 95747.955
2555 126654.489
2556 73633.642
2557 96885.866
2558 165001.436
2559 132918.804
2560 149115.070
2561 165193.852
2562 155458.408
2563 156573.299
2564 209237.578
2565 136510.962
2566 117418.921
2567 148215.063
2568 187523.238
2569 182792.598
2570 157098.739
2571 141485.234
2572 211786.588
2573 223120.530
2574 303907.122
2575 176227.473
2576 115874.593
2577 NA
2578 92425.110
2579 19366.733
2580 135208.063
2581 115210.399
2582 106407.563
2583 241197.561
2584 170685.753
2585 166427.102
2586 206860.657
2587 207377.734
2588 162243.544
2589 158894.400
2590 208766.781
2591 218230.343
2592 214809.743
2593 238463.954
2594 196491.876
2595 224685.740
2596 275409.430
2597 183729.399
2598 255107.506
2599 334483.704
2600 171810.680
2601 151612.326
2602 85464.538
2603 82332.270
2604 63653.082
2605 86833.312
2606 137234.932
2607 175253.490
2608 170100.828
2609 152156.618
2610 75968.328
2611 118966.504
2612 138362.214
2613 99227.502
2614 103742.657
2615 168978.063
2616 138559.962
2617 199486.781
2618 177851.488
2619 225868.463
2620 178322.143
2621 186513.795
2622 192548.520
2623 264287.404
2624 266156.464
2625 298945.881
2626 160757.111
2627 218917.076
2628 344911.716
2629 404897.850
2630 329007.881
2631 369680.818
2632 344348.217
2633 273510.928
2634 307509.318
2635 164901.760
2636 225170.429
2637 191529.419
2638 250470.784
2639 199198.323
2640 159973.973
2641 99372.540
2642 178998.759
2643 158516.154
2644 145060.729
2645 136824.978
2646 132759.992
2647 139898.504
2648 157375.975
2649 129026.893
2650 167334.447
2651 177390.286
2652 341228.917
2653 268137.102
2654 246947.286
2655 316022.196
2656 315564.500
2657 292365.861
2658 275647.645
2659 297730.461
2660 300839.234
2661 305618.168
2662 300502.190
2663 277252.658
2664 267742.193
2665 299285.002
2666 273537.148
2667 174486.826
2668 205334.208
2669 169577.022
2670 295278.173
2671 205334.208
2672 198864.430
2673 204534.019
2674 205953.440
2675 187983.658
2676 210298.600
2677 197652.533
2678 265138.926
2679 286091.626
2680 294028.534
2681 352051.089
2682 316634.896
2683 391699.104
2684 308369.244
2685 319382.687
2686 268994.478
2687 272705.842
2688 235821.398
2689 227687.272
2690 342139.498
2691 196708.356
2692 120109.440
2693 207907.708
2694 119564.137
2695 215863.886
2696 210317.799
2697 205734.583
2698 191105.817
2699 177916.248
2700 166537.811
2701 171146.094
2702 134003.660
2703 190026.244
2704 143067.495
2705 109463.754
2706 105082.131
2707 125073.641
2708 111363.718
2709 81718.796
2710 106419.599
2711 267104.030
2712 328353.110
2713 194171.975
2714 193658.191
2715 179931.690
2716 187232.900
2717 203781.564
2718 241233.882
2719 139064.331
2720 199036.360
2721 132149.399
2722 168870.814
2723 155420.278
2724 105864.124
2725 110877.157
2726 127948.039
2727 164798.263
2728 177732.282
2729 150437.824
2730 121555.554
2731 125220.884
2732 110853.875
2733 148473.171
2734 138287.014
2735 119720.350
2736 143193.738
2737 104180.790
2738 158654.764
2739 166191.874
2740 153937.242
2741 129172.532
2742 172602.910
2743 128184.152
2744 145176.382
2745 138728.954
2746 109409.166
2747 180800.793
2748 144275.301
2749 110878.089
2750 112618.230
2751 102847.334
2752 258326.939
2753 164916.584
2754 243143.330
2755 178091.116
2756 44581.921
2757 67985.731
2758 68143.288
2759 187101.437
2760 146280.634
2761 143819.786
2762 145599.399
2763 191362.851
2764 206167.780
2765 252767.474
2766 120999.787
2767 73312.676
2768 113643.808
2769 116780.356
2770 186825.141
2771 104593.422
2772 87320.545
2773 184865.558
2774 140468.226
2775 109698.785
2776 172918.686
2777 207802.544
2778 159870.342
2779 152762.661
2780 137587.772
2781 98624.602
2782 85568.344
2783 71019.730
2784 130624.672
2785 155439.682
2786 26533.550
2787 149088.566
2788 45858.854
2789 235341.060
2790 98375.324
2791 132615.616
2792 33094.972
2793 175339.187
2794 62153.184
2795 120926.434
2796 96987.690
2797 233261.924
2798 118390.660
2799 129934.252
2800 77108.507
2801 136369.652
2802 130264.212
2803 205253.179
2804 156785.316
2805 109769.358
2806 98866.449
2807 165198.867
2808 133789.320
2809 135052.386
2810 112186.257
2811 152657.434
2812 163238.486
2813 180710.595
2814 180067.149
2815 104409.314
2816 225449.600
2817 132566.114
2818 123188.722
2819 204742.650
2820 119982.872
2821 113752.462
2822 230016.807
2823 302839.782
2824 158377.528
2825 156508.870
2826 112170.067
2827 167228.343
2828 233977.293
2829 218312.042
2830 252610.786
2831 199219.252
2832 198175.486
2833 261522.830
2834 229261.493
2835 217023.122
2836 217541.060
2837 176590.958
2838 132836.400
2839 180061.139
2840 208275.995
2841 221185.319
2842 225617.447
2843 156770.446
2844 188875.442
2845 102975.780
2846 224982.096
2847 195116.073
2848 224767.764
2849 229697.691
2850 287976.758
2851 234066.275
2852 243580.831
2853 237320.687
2854 145590.782
2855 204632.952
2856 223203.557
2857 216708.491
2858 200172.456
2859 125241.622
2860 113664.950
2861 121055.670
2862 224135.272
2863 108806.796
2864 248654.850
2865 161050.324
2866 213602.869
2867 78228.886
2868 174361.176
2869 115519.889
2870 130881.698
2871 79615.588
2872 505.782
2873 95349.767
2874 134668.185
2875 159492.736
2876 188063.053
2877 158629.074
2878 194850.542
2879 130404.907
2880 121630.486
2881 164842.750
2882 149948.563
2883 214664.033
2884 228217.213
2885 190552.561
2886 176772.713
2887 105126.760
2888 170821.291
2889 42832.422
2890 63895.197
2891 171942.722
2892 18669.229
2893 105712.128
2894 28930.840
2895 248782.230
2896 243482.934
2897 190579.571
2898 194172.038
2899 234347.389
2900 168015.832
2901 189413.172
2902 175177.697
2903 278205.720
2904 297819.372
2905 30386.186
2906 236090.632
2907 126405.542
2908 103098.208
2909 190846.966
2910 40750.356
2911 85464.538
2912 129181.630
2913 86833.312
2914 63653.082
2915 63653.082
2916 86833.312
2917 143711.944
2918 84594.030
2919 250545.194
write.csv(sub.df, file = "kagglesubmission2.csv", quote=FALSE, row.names=FALSE)