rm(list = ls())
gc()
## used (Mb) gc trigger (Mb) max used (Mb)
## Ncells 356564 19.1 592000 31.7 460000 24.6
## Vcells 544584 4.2 1023718 7.9 826154 6.4
data("iris")
str(iris)
## 'data.frame': 150 obs. of 5 variables:
## $ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
## $ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
## $ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
## $ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
## $ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...
mean(iris$Sepal.Length)
## [1] 5.843333
sd(iris$Sepal.Length)
## [1] 0.8280661
#http://stackoverflow.com/questions/2547402/is-there-a-built-in-function-for-finding-the-mode
Mode <- function(x) {
ux <- unique(x)
ux[which.max(tabulate(match(x, ux)))]
}
Mode(iris$Sepal.Length)
## [1] 5
#??skewness
library(e1071)
skewness(iris$Sepal.Length)
## [1] 0.3086407
kurtosis(iris$Sepal.Length)
## [1] -0.6058125
library(MASS)
data(Boston)
#?sqrt
myfunction=function(x){
sqrt(x)
}
myfunction(Boston$medv)
## [1] 4.898979 4.647580 5.890671 5.779273 6.016644 5.357238 4.785394
## [8] 5.205766 4.062019 4.347413 3.872983 4.347413 4.658326 4.516636
## [15] 4.266146 4.460942 4.806246 4.183300 4.494441 4.266146 3.687818
## [22] 4.427189 3.898718 3.807887 3.949684 3.728270 4.074310 3.847077
## [29] 4.289522 4.582576 3.563706 3.807887 3.633180 3.619392 3.674235
## [36] 4.347413 4.472136 4.582576 4.969909 5.549775 5.907622 5.157519
## [43] 5.029911 4.969909 4.604346 4.393177 4.472136 4.074310 3.794733
## [50] 4.404543 4.438468 4.527693 5.000000 4.837355 4.347413 5.949790
## [57] 4.969909 5.621388 4.827007 4.427189 4.324350 4.000000 4.711688
## [64] 5.000000 5.744563 4.847680 4.404543 4.690416 4.171331 4.571652
## [71] 4.919350 4.658326 4.774935 4.837355 4.909175 4.626013 4.472136
## [78] 4.560702 4.604346 4.505552 5.291503 4.888763 4.979960 4.785394
## [85] 4.888763 5.157519 4.743416 4.711688 4.857983 5.357238 4.753946
## [92] 4.690416 4.785394 5.000000 4.538722 5.329165 4.626013 6.220932
## [99] 6.618157 5.761944 5.244044 5.147815 4.312772 4.393177 4.483302
## [106] 4.415880 4.415880 4.516636 4.449719 4.404543 4.658326 4.774935
## [113] 4.335897 4.324350 4.301163 4.277850 4.604346 4.381780 4.516636
## [120] 4.393177 4.690416 4.505552 4.527693 4.159327 4.335897 4.626013
## [127] 3.962323 4.024922 4.242641 3.781534 4.381780 4.427189 4.795832
## [134] 4.289522 3.949684 4.254409 4.171331 4.135215 3.646917 4.219005
## [141] 3.741657 3.794733 3.660601 3.949684 3.435113 3.714835 3.949684
## [148] 3.820995 4.219005 3.924283 4.636809 4.427189 3.911521 4.404543
## [155] 4.123106 3.949684 3.619392 6.426508 4.929503 4.827007 5.196152
## [162] 7.071068 7.071068 7.071068 4.764452 5.000000 7.071068 4.878524
## [169] 4.878524 4.722288 4.171331 4.370355 4.806246 4.857983 4.753946
## [176] 5.422177 4.816638 4.959839 5.468089 6.099180 6.308724 6.016644
## [183] 6.156298 5.700877 5.138093 5.440588 7.071068 5.656854 5.458938
## [190] 5.907622 6.082763 5.522681 6.033241 5.576737 5.394442 7.071068
## [197] 5.770615 5.504544 5.882176 5.907622 5.735852 4.909175 6.503845
## [204] 6.964194 7.071068 4.753946 4.939636 4.743416 4.939636 4.472136
## [211] 4.658326 4.393177 4.732864 5.300943 4.868265 5.000000 4.827007
## [218] 5.357238 4.636809 4.795832 5.167204 4.658326 5.244044 5.486347
## [225] 6.693280 7.071068 6.131884 5.621388 6.833740 5.612486 4.929503
## [232] 5.630275 6.457554 6.949820 5.385165 4.898979 5.009990 5.612486
## [239] 4.868265 4.827007 4.690416 4.483302 4.711688 4.868265 4.195235
## [246] 4.301163 4.929503 4.527693 4.949747 5.118594 4.939636 4.979960
## [253] 5.440588 6.542171 4.679744 4.571652 6.633250 7.071068 6.000000
## [260] 5.486347 5.813777 6.565059 6.985700 5.567764 6.041523 4.774935
## [267] 5.540758 7.071068 6.595453 4.549725 4.593474 5.019960 4.939636
## [274] 5.932959 5.692100 5.656854 5.761944 5.753260 5.394442 5.924525
## [281] 6.737952 5.949790 6.782330 7.071068 5.674504 4.690416 4.483302
## [288] 4.816638 4.722288 4.979960 5.338539 6.107373 5.282045 4.888763
## [295] 4.658326 5.347897 5.205766 4.505552 4.743416 5.385165 4.979960
## [302] 4.690416 5.138093 5.753260 6.008328 5.329165 5.779273 5.310367
## [309] 4.774935 4.505552 4.012481 4.701064 4.404543 4.647580 4.878524
## [316] 4.024922 4.219005 4.449719 4.806246 4.582576 4.878524 4.806246
## [323] 4.516636 4.301163 5.000000 4.959839 4.795832 4.711688 4.393177
## [330] 4.753946 4.449719 4.135215 4.404543 4.711688 4.549725 4.593474
## [337] 4.415880 4.301163 4.538722 4.358899 4.324350 5.718391 4.062019
## [344] 4.888763 5.585696 4.183300 4.147288 4.806246 4.949747 5.157519
## [351] 4.785394 4.909175 4.312772 5.486347 4.266146 4.538722 4.219005
## [358] 4.658326 4.764452 4.753946 5.000000 4.460942 4.560702 4.098780
## [365] 4.679744 5.244044 4.679744 4.806246 7.071068 7.071068 7.071068
## [372] 7.071068 7.071068 3.714835 3.714835 3.872983 3.728270 3.646917
## [379] 3.619392 3.193744 3.224903 3.301515 3.361547 3.507136 2.966479
## [386] 2.683282 3.240370 2.720294 3.193744 3.391165 3.885872 4.816638
## [393] 3.114482 3.714835 3.563706 3.619392 3.535534 2.915476 2.236068
## [400] 2.509980 2.366432 2.683282 3.478505 2.880972 2.915476 2.236068
## [407] 3.449638 5.282045 4.147288 5.244044 3.872983 4.147288 4.230839
## [414] 4.037326 2.645751 2.683282 2.738613 3.224903 2.966479 2.898275
## [421] 4.086563 3.768289 4.560702 3.660601 3.420526 2.880972 3.193744
## [428] 3.301515 3.316625 3.082207 3.807887 3.754997 4.012481 3.781534
## [435] 3.420526 3.660601 3.098387 2.949576 2.898275 3.577709 3.240370
## [442] 4.135215 4.289522 3.924283 3.286335 3.435113 3.860052 3.549648
## [449] 3.754997 3.605551 3.660601 3.898718 4.012481 4.219005 3.860052
## [456] 3.754997 3.563706 3.674235 3.860052 4.472136 4.049691 4.207137
## [463] 4.415880 4.494441 4.626013 4.460942 4.358899 4.370355 4.370355
## [470] 4.483302 4.460942 4.427189 4.816638 5.458938 3.714835 3.646917
## [477] 4.086563 3.464102 3.820995 4.626013 4.795832 4.868265 5.000000
## [484] 4.669047 4.538722 4.604346 4.370355 4.538722 3.898718 2.645751
## [491] 2.846050 3.687818 4.483302 4.669047 4.949747 4.806246 4.438468
## [498] 4.277850 4.604346 4.183300 4.098780 4.732864 4.538722 4.888763
## [505] 4.690416 3.449638