Getting started with R
Govind Prakash
11/02/2021
Class 1 (4th January)
Using R console like a calculator
2 + 4## [1] 62 ^ 4## [1] 162 - 4## [1] -2Class 2 (6th january)
as.character(1)## [1] "1"as.numeric(1)## [1] 1Functions for Sum of 2 numbers
sumof2numbers<-function(x,y){
x+y
}
sumof2numbers(2,3)## [1] 5CREATING OBJECTS in R
a <- 10 * 6
a<-6
6->a
a## [1] 6Note : Letters are case sensetive
A <- 2 + 6
A## [1] 8a## [1] 6OVERWRITING OBJECTS
a <- 0
a## [1] 0NAMING OBJECTS
Objects can be named as following
object1 <- 3
my.object <- 3
my_object <- 3
myObject <- 3Note: Object names should not start with numbers, or should not contain any signs like - or !
REMOVING OBJECTs
rm(a)
rm(object1)DATA CLASSES
12.6 # NUMERIC## [1] 12.6"Male" # CHARACTER## [1] "Male"TRUE # LOGICAL## [1] TRUEDATA STRUCTURES
VECTOR
c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)## [1] 1 2 3 4 5 6 7 8 9 10c(1:10)## [1] 1 2 3 4 5 6 7 8 9 10Character strings must be in quote
c("Mon", "Tue", "Wed", "Thur", "Fri")## [1] "Mon" "Tue" "Wed" "Thur" "Fri"c(Mon, Tue, Wed, Thur, Fri) ## Error in eval(expr, envir, enclos): object 'Mon' not foundLogical values must be in capitals
c(FALSE, TRUE, TRUE, FALSE, FALSE) #Correct way## [1] FALSE TRUE TRUE FALSE FALSEc(false, true) #Incorrect way, it will show eror## Error in eval(expr, envir, enclos): object 'false' not foundmyVector <- c(F, F, F, T, T) # BUT CAN BE ABBREVIATED
myVector## [1] FALSE FALSE FALSE TRUE TRUENumber operations can also be performed in R
numbers <- c(1:10)
numbers * 2 # OPERATIONS CAN BE PERFORMED ON VECTORS## [1] 2 4 6 8 10 12 14 16 18 20numbers + 3## [1] 4 5 6 7 8 9 10 11 12 13numbers + numbers## [1] 2 4 6 8 10 12 14 16 18 20LIST
Lists can contain lists and vectors
list(1, 2, 3, "hello", FALSE)## [[1]]
## [1] 1
##
## [[2]]
## [1] 2
##
## [[3]]
## [1] 3
##
## [[4]]
## [1] "hello"
##
## [[5]]
## [1] FALSElist(myVector, 1, 2, 3, "hello", FALSE) #Lists can contain lists and vectors## [[1]]
## [1] FALSE FALSE FALSE TRUE TRUE
##
## [[2]]
## [1] 1
##
## [[3]]
## [1] 2
##
## [[4]]
## [1] 3
##
## [[5]]
## [1] "hello"
##
## [[6]]
## [1] FALSElist(myVector, c(1, 2, 3), "hello", FALSE)## [[1]]
## [1] FALSE FALSE FALSE TRUE TRUE
##
## [[2]]
## [1] 1 2 3
##
## [[3]]
## [1] "hello"
##
## [[4]]
## [1] FALSESUBSETTING VECTORS —-
days <- c("Mon", "Tue", "Wed", "Thur", "Fri")
days## [1] "Mon" "Tue" "Wed" "Thur" "Fri"days[1]## [1] "Mon"days[4]## [1] "Thur"days[c(1, 3, 4)]## [1] "Mon" "Wed" "Thur"days[1:4]## [1] "Mon" "Tue" "Wed" "Thur"days[-5]## [1] "Mon" "Tue" "Wed" "Thur"R base functions
Create a vector for example
myValues <- c(1:100)
myValues## [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
## [19] 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36
## [37] 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54
## [55] 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72
## [73] 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90
## [91] 91 92 93 94 95 96 97 98 99 100using basic functions on the vector created above
mean(myValues)## [1] 50.5median(myValues)## [1] 50.5min(myValues)## [1] 1max(myValues)## [1] 100sum(myValues)## [1] 5050sd(myValues)## [1] 29.01149class(myValues)## [1] "integer"length(myValues) # SOME FUNCTIONS RETURN SINGLE VALUES (AGGREGATE FUNCTIONS)## [1] 100log(myValues) # OTHERS RETURN A VALUE FOR EACH COMPONENT OF THE VECTOR## [1] 0.0000000 0.6931472 1.0986123 1.3862944 1.6094379 1.7917595 1.9459101
## [8] 2.0794415 2.1972246 2.3025851 2.3978953 2.4849066 2.5649494 2.6390573
## [15] 2.7080502 2.7725887 2.8332133 2.8903718 2.9444390 2.9957323 3.0445224
## [22] 3.0910425 3.1354942 3.1780538 3.2188758 3.2580965 3.2958369 3.3322045
## [29] 3.3672958 3.4011974 3.4339872 3.4657359 3.4965076 3.5263605 3.5553481
## [36] 3.5835189 3.6109179 3.6375862 3.6635616 3.6888795 3.7135721 3.7376696
## [43] 3.7612001 3.7841896 3.8066625 3.8286414 3.8501476 3.8712010 3.8918203
## [50] 3.9120230 3.9318256 3.9512437 3.9702919 3.9889840 4.0073332 4.0253517
## [57] 4.0430513 4.0604430 4.0775374 4.0943446 4.1108739 4.1271344 4.1431347
## [64] 4.1588831 4.1743873 4.1896547 4.2046926 4.2195077 4.2341065 4.2484952
## [71] 4.2626799 4.2766661 4.2904594 4.3040651 4.3174881 4.3307333 4.3438054
## [78] 4.3567088 4.3694479 4.3820266 4.3944492 4.4067192 4.4188406 4.4308168
## [85] 4.4426513 4.4543473 4.4659081 4.4773368 4.4886364 4.4998097 4.5108595
## [92] 4.5217886 4.5325995 4.5432948 4.5538769 4.5643482 4.5747110 4.5849675
## [99] 4.5951199 4.6051702log10(myValues) # CAREFUL: DIFFERENCE BETWEEN LOG10 AND LOG## [1] 0.0000000 0.3010300 0.4771213 0.6020600 0.6989700 0.7781513 0.8450980
## [8] 0.9030900 0.9542425 1.0000000 1.0413927 1.0791812 1.1139434 1.1461280
## [15] 1.1760913 1.2041200 1.2304489 1.2552725 1.2787536 1.3010300 1.3222193
## [22] 1.3424227 1.3617278 1.3802112 1.3979400 1.4149733 1.4313638 1.4471580
## [29] 1.4623980 1.4771213 1.4913617 1.5051500 1.5185139 1.5314789 1.5440680
## [36] 1.5563025 1.5682017 1.5797836 1.5910646 1.6020600 1.6127839 1.6232493
## [43] 1.6334685 1.6434527 1.6532125 1.6627578 1.6720979 1.6812412 1.6901961
## [50] 1.6989700 1.7075702 1.7160033 1.7242759 1.7323938 1.7403627 1.7481880
## [57] 1.7558749 1.7634280 1.7708520 1.7781513 1.7853298 1.7923917 1.7993405
## [64] 1.8061800 1.8129134 1.8195439 1.8260748 1.8325089 1.8388491 1.8450980
## [71] 1.8512583 1.8573325 1.8633229 1.8692317 1.8750613 1.8808136 1.8864907
## [78] 1.8920946 1.8976271 1.9030900 1.9084850 1.9138139 1.9190781 1.9242793
## [85] 1.9294189 1.9344985 1.9395193 1.9444827 1.9493900 1.9542425 1.9590414
## [92] 1.9637878 1.9684829 1.9731279 1.9777236 1.9822712 1.9867717 1.9912261
## [99] 1.9956352 2.0000000sqrt(myValues)## [1] 1.000000 1.414214 1.732051 2.000000 2.236068 2.449490 2.645751
## [8] 2.828427 3.000000 3.162278 3.316625 3.464102 3.605551 3.741657
## [15] 3.872983 4.000000 4.123106 4.242641 4.358899 4.472136 4.582576
## [22] 4.690416 4.795832 4.898979 5.000000 5.099020 5.196152 5.291503
## [29] 5.385165 5.477226 5.567764 5.656854 5.744563 5.830952 5.916080
## [36] 6.000000 6.082763 6.164414 6.244998 6.324555 6.403124 6.480741
## [43] 6.557439 6.633250 6.708204 6.782330 6.855655 6.928203 7.000000
## [50] 7.071068 7.141428 7.211103 7.280110 7.348469 7.416198 7.483315
## [57] 7.549834 7.615773 7.681146 7.745967 7.810250 7.874008 7.937254
## [64] 8.000000 8.062258 8.124038 8.185353 8.246211 8.306624 8.366600
## [71] 8.426150 8.485281 8.544004 8.602325 8.660254 8.717798 8.774964
## [78] 8.831761 8.888194 8.944272 9.000000 9.055385 9.110434 9.165151
## [85] 9.219544 9.273618 9.327379 9.380832 9.433981 9.486833 9.539392
## [92] 9.591663 9.643651 9.695360 9.746794 9.797959 9.848858 9.899495
## [99] 9.949874 10.000000rnorm generates random normal numbers
rnorm(100, mean = 5)## [1] 5.525566 3.814519 4.702563 6.208822 4.346607 5.519410 7.654901 4.712833
## [9] 5.368665 3.616163 5.110539 5.676110 5.417995 6.420221 5.054575 3.293389
## [17] 6.097654 4.784377 5.226478 5.048361 4.076718 4.307540 3.946324 5.360169
## [25] 4.788813 5.135769 4.490388 5.777243 5.128229 4.880949 5.568678 5.334628
## [33] 5.673896 6.297962 4.964711 5.152698 5.043838 5.858819 5.209126 6.072786
## [41] 6.012677 5.099100 5.217281 5.585232 3.831265 4.269470 4.890978 4.140757
## [49] 4.532185 3.530727 5.702170 5.416452 5.084769 4.693600 4.860489 7.646559
## [57] 6.120365 4.897720 3.147115 3.172988 6.016113 3.630943 7.546740 4.539044
## [65] 4.509835 5.805231 4.914224 5.504038 5.778634 4.109317 4.017710 4.365688
## [73] 4.473374 4.037357 5.098571 5.784132 3.692752 3.802747 4.857528 5.434453
## [81] 3.834286 6.251667 5.517172 4.893479 4.974838 5.716647 5.738641 2.272920
## [89] 5.332243 4.224944 3.821933 5.099773 6.576524 4.228925 5.719275 4.769642
## [97] 4.753711 5.481111 5.167510 4.729634Plotting histograms for that
hist(rnorm(100, mean = 5)) #with mean 5
hist(rnorm(100, mean = 58)) # with mean 58
Class 3 (8th January)
creating vectors
Printing numbers 1 to 200
id<- 1:200
id## [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
## [19] 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36
## [37] 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54
## [55] 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72
## [73] 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90
## [91] 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108
## [109] 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126
## [127] 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144
## [145] 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162
## [163] 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180
## [181] 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198
## [199] 199 200repeat command for repeating things group, rep(“character to be repeated”, Number fow many times)
group <- c(rep("Drugs", 100), rep("operation", 100))
group## [1] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [7] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [13] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [19] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [25] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [31] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [37] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [43] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [49] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [55] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [61] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [67] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [73] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [79] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [85] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [91] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [97] "Drugs" "Drugs" "Drugs" "Drugs" "operation" "operation"
## [103] "operation" "operation" "operation" "operation" "operation" "operation"
## [109] "operation" "operation" "operation" "operation" "operation" "operation"
## [115] "operation" "operation" "operation" "operation" "operation" "operation"
## [121] "operation" "operation" "operation" "operation" "operation" "operation"
## [127] "operation" "operation" "operation" "operation" "operation" "operation"
## [133] "operation" "operation" "operation" "operation" "operation" "operation"
## [139] "operation" "operation" "operation" "operation" "operation" "operation"
## [145] "operation" "operation" "operation" "operation" "operation" "operation"
## [151] "operation" "operation" "operation" "operation" "operation" "operation"
## [157] "operation" "operation" "operation" "operation" "operation" "operation"
## [163] "operation" "operation" "operation" "operation" "operation" "operation"
## [169] "operation" "operation" "operation" "operation" "operation" "operation"
## [175] "operation" "operation" "operation" "operation" "operation" "operation"
## [181] "operation" "operation" "operation" "operation" "operation" "operation"
## [187] "operation" "operation" "operation" "operation" "operation" "operation"
## [193] "operation" "operation" "operation" "operation" "operation" "operation"
## [199] "operation" "operation"repeat above command twice
group2 <- rep(c(rep("Drugs", 50), rep("Operation", 50)), 2)
group2## [1] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [7] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [13] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [19] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [25] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [31] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [37] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [43] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [49] "Drugs" "Drugs" "Operation" "Operation" "Operation" "Operation"
## [55] "Operation" "Operation" "Operation" "Operation" "Operation" "Operation"
## [61] "Operation" "Operation" "Operation" "Operation" "Operation" "Operation"
## [67] "Operation" "Operation" "Operation" "Operation" "Operation" "Operation"
## [73] "Operation" "Operation" "Operation" "Operation" "Operation" "Operation"
## [79] "Operation" "Operation" "Operation" "Operation" "Operation" "Operation"
## [85] "Operation" "Operation" "Operation" "Operation" "Operation" "Operation"
## [91] "Operation" "Operation" "Operation" "Operation" "Operation" "Operation"
## [97] "Operation" "Operation" "Operation" "Operation" "Drugs" "Drugs"
## [103] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [109] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [115] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [121] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [127] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [133] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [139] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [145] "Drugs" "Drugs" "Drugs" "Drugs" "Drugs" "Drugs"
## [151] "Operation" "Operation" "Operation" "Operation" "Operation" "Operation"
## [157] "Operation" "Operation" "Operation" "Operation" "Operation" "Operation"
## [163] "Operation" "Operation" "Operation" "Operation" "Operation" "Operation"
## [169] "Operation" "Operation" "Operation" "Operation" "Operation" "Operation"
## [175] "Operation" "Operation" "Operation" "Operation" "Operation" "Operation"
## [181] "Operation" "Operation" "Operation" "Operation" "Operation" "Operation"
## [187] "Operation" "Operation" "Operation" "Operation" "Operation" "Operation"
## [193] "Operation" "Operation" "Operation" "Operation" "Operation" "Operation"
## [199] "Operation" "Operation"rnorm creates normal distributions
response<- c(rnorm(100, mean = 25, sd= 2), rnorm(100, mean = 50, sd= 2))
response## [1] 26.80533 26.55060 23.58058 25.68493 22.12950 18.99046 22.03747 27.65881
## [9] 26.43358 24.74455 28.16819 25.81016 23.19817 26.18462 26.47969 28.21697
## [17] 25.38650 26.15827 24.66158 24.92544 25.18497 24.70714 24.75738 28.19955
## [25] 20.72135 25.99964 26.47283 24.58968 26.59795 23.94284 26.76003 26.08344
## [33] 24.72098 24.86450 26.13243 24.27846 23.89170 26.63645 24.25653 23.04673
## [41] 26.16241 29.85531 24.59542 23.64706 26.00042 22.20051 27.14468 26.17978
## [49] 24.50010 26.30749 22.77102 29.55440 24.49164 25.83466 25.58087 21.97737
## [57] 22.37261 26.45771 27.90773 24.22325 22.91497 28.39449 23.49575 23.65552
## [65] 25.75617 26.64830 21.99210 25.56302 25.35750 28.01134 23.06784 27.78751
## [73] 25.06506 25.17743 24.63536 29.09254 26.21080 24.56126 26.39246 20.99567
## [81] 25.72990 23.61803 22.92957 27.96510 27.21658 22.79032 24.46237 24.21356
## [89] 24.65004 26.60751 23.31286 25.11325 26.05494 25.11752 28.67326 27.08991
## [97] 23.48586 22.27982 23.55798 24.74972 46.87659 46.54813 46.94171 50.29901
## [105] 54.09288 51.27623 52.58003 49.88500 50.05028 52.56509 50.06240 49.77475
## [113] 51.47784 47.75730 50.73849 50.68809 50.49996 51.52809 49.71822 44.87377
## [121] 51.57697 50.75424 53.80118 48.83440 52.18185 47.45741 50.64502 54.00101
## [129] 48.55335 50.87153 46.02759 50.81819 49.64849 51.76852 47.12066 49.26348
## [137] 49.13574 51.01604 49.42068 50.02449 50.77558 51.55696 49.09173 50.31173
## [145] 52.05382 49.64667 51.28264 50.20772 48.59954 52.78944 50.79428 47.30692
## [153] 51.16326 46.38045 52.19304 48.58236 48.25652 50.97736 51.65313 52.81524
## [161] 50.83697 48.56458 49.41166 51.72445 51.27281 49.05383 52.27794 47.52532
## [169] 50.14345 49.83502 47.95329 51.19970 51.50500 47.99536 50.27848 50.68705
## [177] 47.37837 52.20489 49.92055 51.98342 48.11065 51.46874 47.58519 51.11418
## [185] 50.85123 51.69591 52.05145 52.28200 47.53014 46.81935 50.19280 51.66155
## [193] 50.27819 50.21602 52.63525 54.00458 48.46788 45.62074 49.56229 51.93520now we will add all the adove created data sets and make our dataframe
mydata<- data.frame(Patient= id, Treatment= group2, Response= response)
mydata## Patient Treatment Response
## 1 1 Drugs 26.80533
## 2 2 Drugs 26.55060
## 3 3 Drugs 23.58058
## 4 4 Drugs 25.68493
## 5 5 Drugs 22.12950
## 6 6 Drugs 18.99046
## 7 7 Drugs 22.03747
## 8 8 Drugs 27.65881
## 9 9 Drugs 26.43358
## 10 10 Drugs 24.74455
## 11 11 Drugs 28.16819
## 12 12 Drugs 25.81016
## 13 13 Drugs 23.19817
## 14 14 Drugs 26.18462
## 15 15 Drugs 26.47969
## 16 16 Drugs 28.21697
## 17 17 Drugs 25.38650
## 18 18 Drugs 26.15827
## 19 19 Drugs 24.66158
## 20 20 Drugs 24.92544
## 21 21 Drugs 25.18497
## 22 22 Drugs 24.70714
## 23 23 Drugs 24.75738
## 24 24 Drugs 28.19955
## 25 25 Drugs 20.72135
## 26 26 Drugs 25.99964
## 27 27 Drugs 26.47283
## 28 28 Drugs 24.58968
## 29 29 Drugs 26.59795
## 30 30 Drugs 23.94284
## 31 31 Drugs 26.76003
## 32 32 Drugs 26.08344
## 33 33 Drugs 24.72098
## 34 34 Drugs 24.86450
## 35 35 Drugs 26.13243
## 36 36 Drugs 24.27846
## 37 37 Drugs 23.89170
## 38 38 Drugs 26.63645
## 39 39 Drugs 24.25653
## 40 40 Drugs 23.04673
## 41 41 Drugs 26.16241
## 42 42 Drugs 29.85531
## 43 43 Drugs 24.59542
## 44 44 Drugs 23.64706
## 45 45 Drugs 26.00042
## 46 46 Drugs 22.20051
## 47 47 Drugs 27.14468
## 48 48 Drugs 26.17978
## 49 49 Drugs 24.50010
## 50 50 Drugs 26.30749
## 51 51 Operation 22.77102
## 52 52 Operation 29.55440
## 53 53 Operation 24.49164
## 54 54 Operation 25.83466
## 55 55 Operation 25.58087
## 56 56 Operation 21.97737
## 57 57 Operation 22.37261
## 58 58 Operation 26.45771
## 59 59 Operation 27.90773
## 60 60 Operation 24.22325
## 61 61 Operation 22.91497
## 62 62 Operation 28.39449
## 63 63 Operation 23.49575
## 64 64 Operation 23.65552
## 65 65 Operation 25.75617
## 66 66 Operation 26.64830
## 67 67 Operation 21.99210
## 68 68 Operation 25.56302
## 69 69 Operation 25.35750
## 70 70 Operation 28.01134
## 71 71 Operation 23.06784
## 72 72 Operation 27.78751
## 73 73 Operation 25.06506
## 74 74 Operation 25.17743
## 75 75 Operation 24.63536
## 76 76 Operation 29.09254
## 77 77 Operation 26.21080
## 78 78 Operation 24.56126
## 79 79 Operation 26.39246
## 80 80 Operation 20.99567
## 81 81 Operation 25.72990
## 82 82 Operation 23.61803
## 83 83 Operation 22.92957
## 84 84 Operation 27.96510
## 85 85 Operation 27.21658
## 86 86 Operation 22.79032
## 87 87 Operation 24.46237
## 88 88 Operation 24.21356
## 89 89 Operation 24.65004
## 90 90 Operation 26.60751
## 91 91 Operation 23.31286
## 92 92 Operation 25.11325
## 93 93 Operation 26.05494
## 94 94 Operation 25.11752
## 95 95 Operation 28.67326
## 96 96 Operation 27.08991
## 97 97 Operation 23.48586
## 98 98 Operation 22.27982
## 99 99 Operation 23.55798
## 100 100 Operation 24.74972
## 101 101 Drugs 46.87659
## 102 102 Drugs 46.54813
## 103 103 Drugs 46.94171
## 104 104 Drugs 50.29901
## 105 105 Drugs 54.09288
## 106 106 Drugs 51.27623
## 107 107 Drugs 52.58003
## 108 108 Drugs 49.88500
## 109 109 Drugs 50.05028
## 110 110 Drugs 52.56509
## 111 111 Drugs 50.06240
## 112 112 Drugs 49.77475
## 113 113 Drugs 51.47784
## 114 114 Drugs 47.75730
## 115 115 Drugs 50.73849
## 116 116 Drugs 50.68809
## 117 117 Drugs 50.49996
## 118 118 Drugs 51.52809
## 119 119 Drugs 49.71822
## 120 120 Drugs 44.87377
## 121 121 Drugs 51.57697
## 122 122 Drugs 50.75424
## 123 123 Drugs 53.80118
## 124 124 Drugs 48.83440
## 125 125 Drugs 52.18185
## 126 126 Drugs 47.45741
## 127 127 Drugs 50.64502
## 128 128 Drugs 54.00101
## 129 129 Drugs 48.55335
## 130 130 Drugs 50.87153
## 131 131 Drugs 46.02759
## 132 132 Drugs 50.81819
## 133 133 Drugs 49.64849
## 134 134 Drugs 51.76852
## 135 135 Drugs 47.12066
## 136 136 Drugs 49.26348
## 137 137 Drugs 49.13574
## 138 138 Drugs 51.01604
## 139 139 Drugs 49.42068
## 140 140 Drugs 50.02449
## 141 141 Drugs 50.77558
## 142 142 Drugs 51.55696
## 143 143 Drugs 49.09173
## 144 144 Drugs 50.31173
## 145 145 Drugs 52.05382
## 146 146 Drugs 49.64667
## 147 147 Drugs 51.28264
## 148 148 Drugs 50.20772
## 149 149 Drugs 48.59954
## 150 150 Drugs 52.78944
## 151 151 Operation 50.79428
## 152 152 Operation 47.30692
## 153 153 Operation 51.16326
## 154 154 Operation 46.38045
## 155 155 Operation 52.19304
## 156 156 Operation 48.58236
## 157 157 Operation 48.25652
## 158 158 Operation 50.97736
## 159 159 Operation 51.65313
## 160 160 Operation 52.81524
## 161 161 Operation 50.83697
## 162 162 Operation 48.56458
## 163 163 Operation 49.41166
## 164 164 Operation 51.72445
## 165 165 Operation 51.27281
## 166 166 Operation 49.05383
## 167 167 Operation 52.27794
## 168 168 Operation 47.52532
## 169 169 Operation 50.14345
## 170 170 Operation 49.83502
## 171 171 Operation 47.95329
## 172 172 Operation 51.19970
## 173 173 Operation 51.50500
## 174 174 Operation 47.99536
## 175 175 Operation 50.27848
## 176 176 Operation 50.68705
## 177 177 Operation 47.37837
## 178 178 Operation 52.20489
## 179 179 Operation 49.92055
## 180 180 Operation 51.98342
## 181 181 Operation 48.11065
## 182 182 Operation 51.46874
## 183 183 Operation 47.58519
## 184 184 Operation 51.11418
## 185 185 Operation 50.85123
## 186 186 Operation 51.69591
## 187 187 Operation 52.05145
## 188 188 Operation 52.28200
## 189 189 Operation 47.53014
## 190 190 Operation 46.81935
## 191 191 Operation 50.19280
## 192 192 Operation 51.66155
## 193 193 Operation 50.27819
## 194 194 Operation 50.21602
## 195 195 Operation 52.63525
## 196 196 Operation 54.00458
## 197 197 Operation 48.46788
## 198 198 Operation 45.62074
## 199 199 Operation 49.56229
## 200 200 Operation 51.93520subsetting dataframe
first comes ROws then column
mydata[1, 2] ## [1] "Drugs"mydata[2, 3]## [1] 26.5506Using a range
mydata[1:20, 2:3]## Treatment Response
## 1 Drugs 26.80533
## 2 Drugs 26.55060
## 3 Drugs 23.58058
## 4 Drugs 25.68493
## 5 Drugs 22.12950
## 6 Drugs 18.99046
## 7 Drugs 22.03747
## 8 Drugs 27.65881
## 9 Drugs 26.43358
## 10 Drugs 24.74455
## 11 Drugs 28.16819
## 12 Drugs 25.81016
## 13 Drugs 23.19817
## 14 Drugs 26.18462
## 15 Drugs 26.47969
## 16 Drugs 28.21697
## 17 Drugs 25.38650
## 18 Drugs 26.15827
## 19 Drugs 24.66158
## 20 Drugs 24.92544Filtering directly by names
mydata[,"Response"]## [1] 26.80533 26.55060 23.58058 25.68493 22.12950 18.99046 22.03747 27.65881
## [9] 26.43358 24.74455 28.16819 25.81016 23.19817 26.18462 26.47969 28.21697
## [17] 25.38650 26.15827 24.66158 24.92544 25.18497 24.70714 24.75738 28.19955
## [25] 20.72135 25.99964 26.47283 24.58968 26.59795 23.94284 26.76003 26.08344
## [33] 24.72098 24.86450 26.13243 24.27846 23.89170 26.63645 24.25653 23.04673
## [41] 26.16241 29.85531 24.59542 23.64706 26.00042 22.20051 27.14468 26.17978
## [49] 24.50010 26.30749 22.77102 29.55440 24.49164 25.83466 25.58087 21.97737
## [57] 22.37261 26.45771 27.90773 24.22325 22.91497 28.39449 23.49575 23.65552
## [65] 25.75617 26.64830 21.99210 25.56302 25.35750 28.01134 23.06784 27.78751
## [73] 25.06506 25.17743 24.63536 29.09254 26.21080 24.56126 26.39246 20.99567
## [81] 25.72990 23.61803 22.92957 27.96510 27.21658 22.79032 24.46237 24.21356
## [89] 24.65004 26.60751 23.31286 25.11325 26.05494 25.11752 28.67326 27.08991
## [97] 23.48586 22.27982 23.55798 24.74972 46.87659 46.54813 46.94171 50.29901
## [105] 54.09288 51.27623 52.58003 49.88500 50.05028 52.56509 50.06240 49.77475
## [113] 51.47784 47.75730 50.73849 50.68809 50.49996 51.52809 49.71822 44.87377
## [121] 51.57697 50.75424 53.80118 48.83440 52.18185 47.45741 50.64502 54.00101
## [129] 48.55335 50.87153 46.02759 50.81819 49.64849 51.76852 47.12066 49.26348
## [137] 49.13574 51.01604 49.42068 50.02449 50.77558 51.55696 49.09173 50.31173
## [145] 52.05382 49.64667 51.28264 50.20772 48.59954 52.78944 50.79428 47.30692
## [153] 51.16326 46.38045 52.19304 48.58236 48.25652 50.97736 51.65313 52.81524
## [161] 50.83697 48.56458 49.41166 51.72445 51.27281 49.05383 52.27794 47.52532
## [169] 50.14345 49.83502 47.95329 51.19970 51.50500 47.99536 50.27848 50.68705
## [177] 47.37837 52.20489 49.92055 51.98342 48.11065 51.46874 47.58519 51.11418
## [185] 50.85123 51.69591 52.05145 52.28200 47.53014 46.81935 50.19280 51.66155
## [193] 50.27819 50.21602 52.63525 54.00458 48.46788 45.62074 49.56229 51.93520Filtering by conditions, the following will go to response and filter out datas whose response is greater than 26
mydata[mydata$Response>26, ] ## Patient Treatment Response
## 1 1 Drugs 26.80533
## 2 2 Drugs 26.55060
## 8 8 Drugs 27.65881
## 9 9 Drugs 26.43358
## 11 11 Drugs 28.16819
## 14 14 Drugs 26.18462
## 15 15 Drugs 26.47969
## 16 16 Drugs 28.21697
## 18 18 Drugs 26.15827
## 24 24 Drugs 28.19955
## 27 27 Drugs 26.47283
## 29 29 Drugs 26.59795
## 31 31 Drugs 26.76003
## 32 32 Drugs 26.08344
## 35 35 Drugs 26.13243
## 38 38 Drugs 26.63645
## 41 41 Drugs 26.16241
## 42 42 Drugs 29.85531
## 45 45 Drugs 26.00042
## 47 47 Drugs 27.14468
## 48 48 Drugs 26.17978
## 50 50 Drugs 26.30749
## 52 52 Operation 29.55440
## 58 58 Operation 26.45771
## 59 59 Operation 27.90773
## 62 62 Operation 28.39449
## 66 66 Operation 26.64830
## 70 70 Operation 28.01134
## 72 72 Operation 27.78751
## 76 76 Operation 29.09254
## 77 77 Operation 26.21080
## 79 79 Operation 26.39246
## 84 84 Operation 27.96510
## 85 85 Operation 27.21658
## 90 90 Operation 26.60751
## 93 93 Operation 26.05494
## 95 95 Operation 28.67326
## 96 96 Operation 27.08991
## 101 101 Drugs 46.87659
## 102 102 Drugs 46.54813
## 103 103 Drugs 46.94171
## 104 104 Drugs 50.29901
## 105 105 Drugs 54.09288
## 106 106 Drugs 51.27623
## 107 107 Drugs 52.58003
## 108 108 Drugs 49.88500
## 109 109 Drugs 50.05028
## 110 110 Drugs 52.56509
## 111 111 Drugs 50.06240
## 112 112 Drugs 49.77475
## 113 113 Drugs 51.47784
## 114 114 Drugs 47.75730
## 115 115 Drugs 50.73849
## 116 116 Drugs 50.68809
## 117 117 Drugs 50.49996
## 118 118 Drugs 51.52809
## 119 119 Drugs 49.71822
## 120 120 Drugs 44.87377
## 121 121 Drugs 51.57697
## 122 122 Drugs 50.75424
## 123 123 Drugs 53.80118
## 124 124 Drugs 48.83440
## 125 125 Drugs 52.18185
## 126 126 Drugs 47.45741
## 127 127 Drugs 50.64502
## 128 128 Drugs 54.00101
## 129 129 Drugs 48.55335
## 130 130 Drugs 50.87153
## 131 131 Drugs 46.02759
## 132 132 Drugs 50.81819
## 133 133 Drugs 49.64849
## 134 134 Drugs 51.76852
## 135 135 Drugs 47.12066
## 136 136 Drugs 49.26348
## 137 137 Drugs 49.13574
## 138 138 Drugs 51.01604
## 139 139 Drugs 49.42068
## 140 140 Drugs 50.02449
## 141 141 Drugs 50.77558
## 142 142 Drugs 51.55696
## 143 143 Drugs 49.09173
## 144 144 Drugs 50.31173
## 145 145 Drugs 52.05382
## 146 146 Drugs 49.64667
## 147 147 Drugs 51.28264
## 148 148 Drugs 50.20772
## 149 149 Drugs 48.59954
## 150 150 Drugs 52.78944
## 151 151 Operation 50.79428
## 152 152 Operation 47.30692
## 153 153 Operation 51.16326
## 154 154 Operation 46.38045
## 155 155 Operation 52.19304
## 156 156 Operation 48.58236
## 157 157 Operation 48.25652
## 158 158 Operation 50.97736
## 159 159 Operation 51.65313
## 160 160 Operation 52.81524
## 161 161 Operation 50.83697
## 162 162 Operation 48.56458
## 163 163 Operation 49.41166
## 164 164 Operation 51.72445
## 165 165 Operation 51.27281
## 166 166 Operation 49.05383
## 167 167 Operation 52.27794
## 168 168 Operation 47.52532
## 169 169 Operation 50.14345
## 170 170 Operation 49.83502
## 171 171 Operation 47.95329
## 172 172 Operation 51.19970
## 173 173 Operation 51.50500
## 174 174 Operation 47.99536
## 175 175 Operation 50.27848
## 176 176 Operation 50.68705
## 177 177 Operation 47.37837
## 178 178 Operation 52.20489
## 179 179 Operation 49.92055
## 180 180 Operation 51.98342
## 181 181 Operation 48.11065
## 182 182 Operation 51.46874
## 183 183 Operation 47.58519
## 184 184 Operation 51.11418
## 185 185 Operation 50.85123
## 186 186 Operation 51.69591
## 187 187 Operation 52.05145
## 188 188 Operation 52.28200
## 189 189 Operation 47.53014
## 190 190 Operation 46.81935
## 191 191 Operation 50.19280
## 192 192 Operation 51.66155
## 193 193 Operation 50.27819
## 194 194 Operation 50.21602
## 195 195 Operation 52.63525
## 196 196 Operation 54.00458
## 197 197 Operation 48.46788
## 198 198 Operation 45.62074
## 199 199 Operation 49.56229
## 200 200 Operation 51.93520#applying multiple operator for subsetting and filtering AND operator: it will filter out the results which will satisfy both the conditions
mydata[mydata$Treatment=="Drugs" && mydata$Response<50, ] ## Patient Treatment Response
## 1 1 Drugs 26.80533
## 2 2 Drugs 26.55060
## 3 3 Drugs 23.58058
## 4 4 Drugs 25.68493
## 5 5 Drugs 22.12950
## 6 6 Drugs 18.99046
## 7 7 Drugs 22.03747
## 8 8 Drugs 27.65881
## 9 9 Drugs 26.43358
## 10 10 Drugs 24.74455
## 11 11 Drugs 28.16819
## 12 12 Drugs 25.81016
## 13 13 Drugs 23.19817
## 14 14 Drugs 26.18462
## 15 15 Drugs 26.47969
## 16 16 Drugs 28.21697
## 17 17 Drugs 25.38650
## 18 18 Drugs 26.15827
## 19 19 Drugs 24.66158
## 20 20 Drugs 24.92544
## 21 21 Drugs 25.18497
## 22 22 Drugs 24.70714
## 23 23 Drugs 24.75738
## 24 24 Drugs 28.19955
## 25 25 Drugs 20.72135
## 26 26 Drugs 25.99964
## 27 27 Drugs 26.47283
## 28 28 Drugs 24.58968
## 29 29 Drugs 26.59795
## 30 30 Drugs 23.94284
## 31 31 Drugs 26.76003
## 32 32 Drugs 26.08344
## 33 33 Drugs 24.72098
## 34 34 Drugs 24.86450
## 35 35 Drugs 26.13243
## 36 36 Drugs 24.27846
## 37 37 Drugs 23.89170
## 38 38 Drugs 26.63645
## 39 39 Drugs 24.25653
## 40 40 Drugs 23.04673
## 41 41 Drugs 26.16241
## 42 42 Drugs 29.85531
## 43 43 Drugs 24.59542
## 44 44 Drugs 23.64706
## 45 45 Drugs 26.00042
## 46 46 Drugs 22.20051
## 47 47 Drugs 27.14468
## 48 48 Drugs 26.17978
## 49 49 Drugs 24.50010
## 50 50 Drugs 26.30749
## 51 51 Operation 22.77102
## 52 52 Operation 29.55440
## 53 53 Operation 24.49164
## 54 54 Operation 25.83466
## 55 55 Operation 25.58087
## 56 56 Operation 21.97737
## 57 57 Operation 22.37261
## 58 58 Operation 26.45771
## 59 59 Operation 27.90773
## 60 60 Operation 24.22325
## 61 61 Operation 22.91497
## 62 62 Operation 28.39449
## 63 63 Operation 23.49575
## 64 64 Operation 23.65552
## 65 65 Operation 25.75617
## 66 66 Operation 26.64830
## 67 67 Operation 21.99210
## 68 68 Operation 25.56302
## 69 69 Operation 25.35750
## 70 70 Operation 28.01134
## 71 71 Operation 23.06784
## 72 72 Operation 27.78751
## 73 73 Operation 25.06506
## 74 74 Operation 25.17743
## 75 75 Operation 24.63536
## 76 76 Operation 29.09254
## 77 77 Operation 26.21080
## 78 78 Operation 24.56126
## 79 79 Operation 26.39246
## 80 80 Operation 20.99567
## 81 81 Operation 25.72990
## 82 82 Operation 23.61803
## 83 83 Operation 22.92957
## 84 84 Operation 27.96510
## 85 85 Operation 27.21658
## 86 86 Operation 22.79032
## 87 87 Operation 24.46237
## 88 88 Operation 24.21356
## 89 89 Operation 24.65004
## 90 90 Operation 26.60751
## 91 91 Operation 23.31286
## 92 92 Operation 25.11325
## 93 93 Operation 26.05494
## 94 94 Operation 25.11752
## 95 95 Operation 28.67326
## 96 96 Operation 27.08991
## 97 97 Operation 23.48586
## 98 98 Operation 22.27982
## 99 99 Operation 23.55798
## 100 100 Operation 24.74972
## 101 101 Drugs 46.87659
## 102 102 Drugs 46.54813
## 103 103 Drugs 46.94171
## 104 104 Drugs 50.29901
## 105 105 Drugs 54.09288
## 106 106 Drugs 51.27623
## 107 107 Drugs 52.58003
## 108 108 Drugs 49.88500
## 109 109 Drugs 50.05028
## 110 110 Drugs 52.56509
## 111 111 Drugs 50.06240
## 112 112 Drugs 49.77475
## 113 113 Drugs 51.47784
## 114 114 Drugs 47.75730
## 115 115 Drugs 50.73849
## 116 116 Drugs 50.68809
## 117 117 Drugs 50.49996
## 118 118 Drugs 51.52809
## 119 119 Drugs 49.71822
## 120 120 Drugs 44.87377
## 121 121 Drugs 51.57697
## 122 122 Drugs 50.75424
## 123 123 Drugs 53.80118
## 124 124 Drugs 48.83440
## 125 125 Drugs 52.18185
## 126 126 Drugs 47.45741
## 127 127 Drugs 50.64502
## 128 128 Drugs 54.00101
## 129 129 Drugs 48.55335
## 130 130 Drugs 50.87153
## 131 131 Drugs 46.02759
## 132 132 Drugs 50.81819
## 133 133 Drugs 49.64849
## 134 134 Drugs 51.76852
## 135 135 Drugs 47.12066
## 136 136 Drugs 49.26348
## 137 137 Drugs 49.13574
## 138 138 Drugs 51.01604
## 139 139 Drugs 49.42068
## 140 140 Drugs 50.02449
## 141 141 Drugs 50.77558
## 142 142 Drugs 51.55696
## 143 143 Drugs 49.09173
## 144 144 Drugs 50.31173
## 145 145 Drugs 52.05382
## 146 146 Drugs 49.64667
## 147 147 Drugs 51.28264
## 148 148 Drugs 50.20772
## 149 149 Drugs 48.59954
## 150 150 Drugs 52.78944
## 151 151 Operation 50.79428
## 152 152 Operation 47.30692
## 153 153 Operation 51.16326
## 154 154 Operation 46.38045
## 155 155 Operation 52.19304
## 156 156 Operation 48.58236
## 157 157 Operation 48.25652
## 158 158 Operation 50.97736
## 159 159 Operation 51.65313
## 160 160 Operation 52.81524
## 161 161 Operation 50.83697
## 162 162 Operation 48.56458
## 163 163 Operation 49.41166
## 164 164 Operation 51.72445
## 165 165 Operation 51.27281
## 166 166 Operation 49.05383
## 167 167 Operation 52.27794
## 168 168 Operation 47.52532
## 169 169 Operation 50.14345
## 170 170 Operation 49.83502
## 171 171 Operation 47.95329
## 172 172 Operation 51.19970
## 173 173 Operation 51.50500
## 174 174 Operation 47.99536
## 175 175 Operation 50.27848
## 176 176 Operation 50.68705
## 177 177 Operation 47.37837
## 178 178 Operation 52.20489
## 179 179 Operation 49.92055
## 180 180 Operation 51.98342
## 181 181 Operation 48.11065
## 182 182 Operation 51.46874
## 183 183 Operation 47.58519
## 184 184 Operation 51.11418
## 185 185 Operation 50.85123
## 186 186 Operation 51.69591
## 187 187 Operation 52.05145
## 188 188 Operation 52.28200
## 189 189 Operation 47.53014
## 190 190 Operation 46.81935
## 191 191 Operation 50.19280
## 192 192 Operation 51.66155
## 193 193 Operation 50.27819
## 194 194 Operation 50.21602
## 195 195 Operation 52.63525
## 196 196 Operation 54.00458
## 197 197 Operation 48.46788
## 198 198 Operation 45.62074
## 199 199 Operation 49.56229
## 200 200 Operation 51.93520OR operator: it will filter out the results which will satisfy either of the conditions
mydata[mydata$Treatment=="Drugs" | mydata$Response<50, ]## Patient Treatment Response
## 1 1 Drugs 26.80533
## 2 2 Drugs 26.55060
## 3 3 Drugs 23.58058
## 4 4 Drugs 25.68493
## 5 5 Drugs 22.12950
## 6 6 Drugs 18.99046
## 7 7 Drugs 22.03747
## 8 8 Drugs 27.65881
## 9 9 Drugs 26.43358
## 10 10 Drugs 24.74455
## 11 11 Drugs 28.16819
## 12 12 Drugs 25.81016
## 13 13 Drugs 23.19817
## 14 14 Drugs 26.18462
## 15 15 Drugs 26.47969
## 16 16 Drugs 28.21697
## 17 17 Drugs 25.38650
## 18 18 Drugs 26.15827
## 19 19 Drugs 24.66158
## 20 20 Drugs 24.92544
## 21 21 Drugs 25.18497
## 22 22 Drugs 24.70714
## 23 23 Drugs 24.75738
## 24 24 Drugs 28.19955
## 25 25 Drugs 20.72135
## 26 26 Drugs 25.99964
## 27 27 Drugs 26.47283
## 28 28 Drugs 24.58968
## 29 29 Drugs 26.59795
## 30 30 Drugs 23.94284
## 31 31 Drugs 26.76003
## 32 32 Drugs 26.08344
## 33 33 Drugs 24.72098
## 34 34 Drugs 24.86450
## 35 35 Drugs 26.13243
## 36 36 Drugs 24.27846
## 37 37 Drugs 23.89170
## 38 38 Drugs 26.63645
## 39 39 Drugs 24.25653
## 40 40 Drugs 23.04673
## 41 41 Drugs 26.16241
## 42 42 Drugs 29.85531
## 43 43 Drugs 24.59542
## 44 44 Drugs 23.64706
## 45 45 Drugs 26.00042
## 46 46 Drugs 22.20051
## 47 47 Drugs 27.14468
## 48 48 Drugs 26.17978
## 49 49 Drugs 24.50010
## 50 50 Drugs 26.30749
## 51 51 Operation 22.77102
## 52 52 Operation 29.55440
## 53 53 Operation 24.49164
## 54 54 Operation 25.83466
## 55 55 Operation 25.58087
## 56 56 Operation 21.97737
## 57 57 Operation 22.37261
## 58 58 Operation 26.45771
## 59 59 Operation 27.90773
## 60 60 Operation 24.22325
## 61 61 Operation 22.91497
## 62 62 Operation 28.39449
## 63 63 Operation 23.49575
## 64 64 Operation 23.65552
## 65 65 Operation 25.75617
## 66 66 Operation 26.64830
## 67 67 Operation 21.99210
## 68 68 Operation 25.56302
## 69 69 Operation 25.35750
## 70 70 Operation 28.01134
## 71 71 Operation 23.06784
## 72 72 Operation 27.78751
## 73 73 Operation 25.06506
## 74 74 Operation 25.17743
## 75 75 Operation 24.63536
## 76 76 Operation 29.09254
## 77 77 Operation 26.21080
## 78 78 Operation 24.56126
## 79 79 Operation 26.39246
## 80 80 Operation 20.99567
## 81 81 Operation 25.72990
## 82 82 Operation 23.61803
## 83 83 Operation 22.92957
## 84 84 Operation 27.96510
## 85 85 Operation 27.21658
## 86 86 Operation 22.79032
## 87 87 Operation 24.46237
## 88 88 Operation 24.21356
## 89 89 Operation 24.65004
## 90 90 Operation 26.60751
## 91 91 Operation 23.31286
## 92 92 Operation 25.11325
## 93 93 Operation 26.05494
## 94 94 Operation 25.11752
## 95 95 Operation 28.67326
## 96 96 Operation 27.08991
## 97 97 Operation 23.48586
## 98 98 Operation 22.27982
## 99 99 Operation 23.55798
## 100 100 Operation 24.74972
## 101 101 Drugs 46.87659
## 102 102 Drugs 46.54813
## 103 103 Drugs 46.94171
## 104 104 Drugs 50.29901
## 105 105 Drugs 54.09288
## 106 106 Drugs 51.27623
## 107 107 Drugs 52.58003
## 108 108 Drugs 49.88500
## 109 109 Drugs 50.05028
## 110 110 Drugs 52.56509
## 111 111 Drugs 50.06240
## 112 112 Drugs 49.77475
## 113 113 Drugs 51.47784
## 114 114 Drugs 47.75730
## 115 115 Drugs 50.73849
## 116 116 Drugs 50.68809
## 117 117 Drugs 50.49996
## 118 118 Drugs 51.52809
## 119 119 Drugs 49.71822
## 120 120 Drugs 44.87377
## 121 121 Drugs 51.57697
## 122 122 Drugs 50.75424
## 123 123 Drugs 53.80118
## 124 124 Drugs 48.83440
## 125 125 Drugs 52.18185
## 126 126 Drugs 47.45741
## 127 127 Drugs 50.64502
## 128 128 Drugs 54.00101
## 129 129 Drugs 48.55335
## 130 130 Drugs 50.87153
## 131 131 Drugs 46.02759
## 132 132 Drugs 50.81819
## 133 133 Drugs 49.64849
## 134 134 Drugs 51.76852
## 135 135 Drugs 47.12066
## 136 136 Drugs 49.26348
## 137 137 Drugs 49.13574
## 138 138 Drugs 51.01604
## 139 139 Drugs 49.42068
## 140 140 Drugs 50.02449
## 141 141 Drugs 50.77558
## 142 142 Drugs 51.55696
## 143 143 Drugs 49.09173
## 144 144 Drugs 50.31173
## 145 145 Drugs 52.05382
## 146 146 Drugs 49.64667
## 147 147 Drugs 51.28264
## 148 148 Drugs 50.20772
## 149 149 Drugs 48.59954
## 150 150 Drugs 52.78944
## 152 152 Operation 47.30692
## 154 154 Operation 46.38045
## 156 156 Operation 48.58236
## 157 157 Operation 48.25652
## 162 162 Operation 48.56458
## 163 163 Operation 49.41166
## 166 166 Operation 49.05383
## 168 168 Operation 47.52532
## 170 170 Operation 49.83502
## 171 171 Operation 47.95329
## 174 174 Operation 47.99536
## 177 177 Operation 47.37837
## 179 179 Operation 49.92055
## 181 181 Operation 48.11065
## 183 183 Operation 47.58519
## 189 189 Operation 47.53014
## 190 190 Operation 46.81935
## 197 197 Operation 48.46788
## 198 198 Operation 45.62074
## 199 199 Operation 49.56229Adding new column
We can ad new data column by first definig it and then adding it by dataset$newcolumn<- newcolumn
age<- round(rnorm(200, mean= 40, sd= 10)) #defined age column as average age of 40 years old
mydata$age<- age #added age column in mydata dataset
head(mydata)## Patient Treatment Response age
## 1 1 Drugs 26.80533 29
## 2 2 Drugs 26.55060 39
## 3 3 Drugs 23.58058 33
## 4 4 Drugs 25.68493 42
## 5 5 Drugs 22.12950 41
## 6 6 Drugs 18.99046 46reading Data in R
Check current working directory bygetwd()
getwd()## [1] "X:/1.Study/4th year semester 2/Biostat/Assignment 1"Change current working directory by setwd() by giving path in double counts and forward slash
setwd("X:/1.Study/4th year semester 2/Biostat/Assignment 1")now check again
getwd()## [1] "X:/1.Study/4th year semester 2/Biostat/Assignment 1"Importing Datasets
for importing life expectancy data set in global environment, the argument “check.names = F” is to remove that extra X from the header
LifeExpectancyInYears<- read.csv("life_expectancy_years.csv", header = T, check.names = F )Applying functions on the dataset
dim(LifeExpectancyInYears) #to check dimensions of datasets## [1] 187 302head(LifeExpectancyInYears) #gives first 6 rows and columns## country 1800 1801 1802 1803 1804 1805 1806 1807 1808 1809 1810
## 1 Afghanistan 28.2 28.2 28.2 28.2 28.2 28.2 28.1 28.1 28.1 28.1 28.1
## 2 Albania 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4
## 3 Algeria 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8
## 4 Andorra NA NA NA NA NA NA NA NA NA NA NA
## 5 Angola 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0
## 6 Antigua and Barbuda 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5
## 1811 1812 1813 1814 1815 1816 1817 1818 1819 1820 1821 1822 1823 1824 1825
## 1 28.1 28.1 28.1 28.1 28.1 28.1 28.0 28.0 28.0 28.0 28.0 28.0 28.0 28.0 27.9
## 2 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4
## 3 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8
## 4 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
## 5 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0
## 6 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5
## 1826 1827 1828 1829 1830 1831 1832 1833 1834 1835 1836 1837 1838 1839 1840
## 1 27.9 27.9 27.9 27.9 27.9 27.9 27.9 27.9 27.9 27.9 27.8 27.8 27.8 27.8 27.8
## 2 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4
## 3 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8
## 4 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
## 5 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0
## 6 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5
## 1841 1842 1843 1844 1845 1846 1847 1848 1849 1850 1851 1852 1853 1854 1855
## 1 27.8 27.8 27.8 27.8 27.8 27.7 27.7 27.7 27.7 27.7 27.7 27.7 27.7 27.7 27.6
## 2 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4
## 3 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8 20.0 15.0 22.0 28.8 28.8 28.8 28.8
## 4 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
## 5 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0
## 6 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5
## 1856 1857 1858 1859 1860 1861 1862 1863 1864 1865 1866 1867 1868 1869 1870
## 1 27.6 27.6 27.6 27.6 27.6 27.6 27.6 27.6 27.6 27.5 27.5 27.5 27.5 27.5 27.5
## 2 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4
## 3 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8 28.8 21.0 11.0 15.0 22.0
## 4 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
## 5 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0 27.0
## 6 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5 33.5
## 1871 1872 1873 1874 1875 1876 1877 1878 1879 1880 1881 1882 1883 1884 1885
## 1 27.6 27.6 27.7 27.8 27.8 27.9 27.9 28.0 28.1 28.1 28.2 28.3 28.3 28.4 28.5
## 2 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4
## 3 28.9 28.9 29.0 29.0 29.0 29.1 29.1 29.2 29.2 29.3 29.3 29.4 29.4 29.4 29.5
## 4 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
## 5 27.1 27.1 27.2 27.3 27.3 27.4 27.5 27.5 27.6 27.7 27.7 27.8 27.9 27.9 28.0
## 6 33.5 33.5 33.6 33.6 33.6 33.6 33.6 33.6 33.6 33.6 33.6 33.6 33.6 33.6 33.6
## 1886 1887 1888 1889 1890 1891 1892 1893 1894 1895 1896 1897 1898 1899 1900
## 1 28.5 28.6 28.6 28.7 28.8 28.8 28.9 29.0 29.0 29.1 29.1 29.2 29.3 29.3 29.4
## 2 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4
## 3 29.5 29.6 29.6 29.7 29.7 29.8 29.8 29.8 29.9 29.9 30.0 30.0 30.1 30.1 30.2
## 4 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
## 5 28.1 28.1 28.2 28.3 28.4 28.4 28.5 28.6 28.6 28.7 28.8 28.8 28.9 29.0 29.0
## 6 33.6 33.7 33.7 33.7 33.7 33.7 33.7 33.7 33.7 33.7 33.7 33.7 33.7 33.8 33.8
## 1901 1902 1903 1904 1905 1906 1907 1908 1909 1910 1911 1912 1913 1914 1915
## 1 29.5 29.5 29.6 29.7 29.7 29.8 29.9 29.9 30.0 30.0 30.1 30.2 30.2 30.3 30.3
## 2 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4
## 3 30.3 30.4 31.4 25.4 28.1 29.6 29.5 29.5 31.0 32.7 32.4 33.8 31.6 31.1 30.6
## 4 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
## 5 29.1 29.2 29.3 29.3 29.4 29.4 29.5 29.6 29.7 29.7 29.8 29.9 29.9 30.0 30.1
## 6 33.8 33.8 33.8 33.8 33.8 33.8 33.8 33.8 33.8 33.8 33.8 33.8 33.9 33.9 33.9
## 1916 1917 1918 1919 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930
## 1 30.4 30.5 7.97 30.6 30.6 30.7 30.8 30.8 30.9 31.0 31.0 31.1 31.1 31.2 31.3
## 2 35.4 35.4 19.40 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 35.4 36.3
## 3 30.3 30.3 23.70 30.4 29.6 29.6 29.4 32.0 33.5 34.3 33.6 28.8 32.4 32.7 34.0
## 4 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
## 5 30.1 30.2 11.70 30.4 30.4 30.5 30.6 30.6 30.7 30.8 30.8 30.9 31.0 31.0 31.1
## 6 33.9 33.9 22.00 33.9 33.9 33.9 34.8 35.6 36.4 37.3 38.1 39.0 39.8 40.7 41.5
## 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945
## 1 31.3 31.4 31.4 31.5 31.6 31.6 31.7 31.8 31.8 31.9 31.9 32.0 32.1 32.1 32.2
## 2 37.2 38.1 39.0 39.9 40.7 41.6 42.5 43.4 43.0 42.0 41.5 40.0 37.0 34.0 47.0
## 3 31.9 33.3 34.6 34.0 35.9 37.1 35.2 34.6 36.9 37.3 35.6 34.9 30.2 35.7 33.5
## 4 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
## 5 31.2 31.2 31.3 31.4 31.4 31.5 31.6 31.6 31.7 31.8 32.1 32.5 32.8 33.1 33.5
## 6 42.4 43.2 44.1 44.9 45.8 46.6 47.5 48.3 49.2 50.0 50.9 51.7 52.6 53.4 54.3
## 1946 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960
## 1 32.2 32.3 32.4 32.4 32.5 32.9 33.6 34.3 35.0 35.7 36.4 37.1 37.9 38.6 39.3
## 2 50.0 51.5 52.4 53.3 54.1 54.4 54.8 55.4 56.1 57.0 57.9 58.9 60.0 61.1 62.2
## 3 35.7 39.1 42.3 44.8 47.3 47.5 48.0 48.6 49.1 49.6 50.2 50.8 51.3 51.9 52.5
## 4 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
## 5 33.8 34.1 34.5 34.8 35.2 35.5 36.0 36.6 37.1 37.7 38.3 38.8 39.4 40.0 40.6
## 6 55.1 56.0 56.8 57.7 58.5 58.8 59.3 59.8 60.4 60.9 61.4 61.9 62.4 62.9 63.3
## 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975
## 1 40.0 40.8 41.5 42.3 43.0 43.7 44.5 45.2 45.9 46.6 46.8 46.8 46.9 47.0 47.1
## 2 63.3 64.2 64.9 65.4 65.8 66.1 66.3 66.4 66.6 66.9 67.5 68.1 68.7 69.3 69.8
## 3 53.1 53.7 54.3 54.9 55.4 56.0 56.5 57.0 57.6 58.1 58.4 58.8 59.2 59.7 60.1
## 4 NA NA NA NA NA NA NA NA NA 75.5 75.8 76.1 76.4 76.7 77.0
## 5 41.1 41.7 42.3 42.9 43.5 44.1 44.7 45.3 45.9 46.5 46.7 46.9 47.1 47.3 47.2
## 6 63.8 64.2 64.7 65.1 65.5 65.8 66.2 66.6 67.0 67.3 67.7 68.1 68.5 68.8 68.9
## 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990
## 1 47.3 47.5 45.9 44.4 44.1 44.9 44.6 42.8 40.5 42.4 43.4 45.5 47.9 51.7 52.6
## 2 70.3 70.8 71.2 71.5 71.7 71.8 72.0 72.1 72.3 72.4 72.6 72.6 72.8 73.1 73.3
## 3 60.6 61.2 61.8 62.5 62.8 64.0 65.1 66.4 67.6 68.7 69.5 70.2 70.8 71.3 71.7
## 4 77.2 77.5 77.8 78.1 78.2 78.3 78.3 78.3 78.5 78.6 78.7 78.8 78.8 78.9 79.0
## 5 47.2 47.3 47.4 47.5 47.6 47.7 47.7 47.7 47.8 47.9 47.9 47.7 47.5 47.8 47.9
## 6 69.1 69.5 69.8 70.5 71.1 71.6 72.1 72.6 72.8 73.0 73.3 73.7 73.8 74.0 74.3
## 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
## 1 52.4 52.9 53.1 52.7 53.3 53.8 53.7 52.8 54.4 54.6 54.8 55.6 56.4 56.9 57.4
## 2 73.0 73.4 73.9 74.5 74.6 74.4 72.5 74.5 74.6 74.9 75.2 75.3 75.4 75.6 76.0
## 3 72.2 72.5 72.7 72.8 72.9 73.3 73.2 73.5 73.9 74.0 74.2 74.5 74.6 75.0 75.3
## 4 79.1 79.1 79.3 79.5 79.7 80.0 80.3 80.6 80.9 81.2 81.4 81.6 81.7 81.7 81.8
## 5 48.5 48.6 47.3 48.7 49.5 50.1 50.2 49.3 50.7 51.7 52.4 53.5 54.2 54.8 55.7
## 6 74.5 74.4 74.3 74.3 74.1 74.2 74.4 74.5 74.6 74.7 74.9 75.2 75.4 75.6 75.8
## 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
## 1 57.6 58.0 58.8 59.3 59.9 60.4 60.8 61.3 61.2 61.2 61.2 63.4 63.7 64.1 64.4
## 2 76.4 76.9 77.0 77.5 77.6 77.7 77.8 77.9 77.9 78.0 78.1 78.2 78.3 78.5 78.6
## 3 75.5 75.7 75.9 76.1 76.3 76.5 76.8 76.9 77.0 77.1 77.4 77.7 77.9 78.1 78.3
## 4 82.0 82.1 82.2 82.2 82.3 82.4 82.4 82.5 82.5 82.6 82.7 82.7 NA NA NA
## 5 56.4 57.5 58.4 59.1 59.9 60.6 61.3 61.9 62.8 63.3 63.8 64.2 64.6 65.0 65.4
## 6 76.0 76.3 76.4 76.6 76.6 76.7 76.7 76.8 76.8 76.9 77.0 77.0 77.2 77.3 77.4
## 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035
## 1 64.7 65.1 65.4 65.7 65.9 66.2 66.5 66.7 67.0 67.2 67.4 67.7 67.9 68.1 68.3
## 2 78.7 78.8 78.9 79.1 79.2 79.3 79.5 79.7 79.8 80.0 80.2 80.3 80.5 80.6 80.8
## 3 78.5 78.7 78.8 79.0 79.2 79.4 79.6 79.7 79.9 80.1 80.3 80.4 80.6 80.8 80.9
## 4 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
## 5 65.7 66.0 66.4 66.7 67.0 67.3 67.6 67.9 68.2 68.5 68.8 69.1 69.3 69.6 69.9
## 6 77.5 77.7 77.8 77.9 78.1 78.2 78.3 78.5 78.6 78.7 78.8 79.0 79.1 79.2 79.4
## 2036 2037 2038 2039 2040 2041 2042 2043 2044 2045 2046 2047 2048 2049 2050
## 1 68.5 68.7 68.9 69.0 69.2 69.4 69.6 69.7 69.9 70.1 70.2 70.4 70.5 70.7 70.8
## 2 80.9 81.0 81.2 81.3 81.4 81.6 81.7 81.8 82.0 82.1 82.3 82.4 82.5 82.7 82.8
## 3 81.1 81.2 81.4 81.6 81.7 81.9 82.0 82.2 82.3 82.5 82.7 82.8 83.0 83.1 83.3
## 4 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
## 5 70.1 70.4 70.6 70.8 71.1 71.3 71.5 71.7 71.9 72.1 72.3 72.5 72.7 72.8 73.0
## 6 79.5 79.6 79.7 79.9 80.0 80.1 80.3 80.4 80.5 80.6 80.8 80.9 81.0 81.1 81.3
## 2051 2052 2053 2054 2055 2056 2057 2058 2059 2060 2061 2062 2063 2064 2065
## 1 71.0 71.1 71.3 71.4 71.6 71.7 71.8 72.0 72.1 72.3 72.4 72.5 72.7 72.8 72.9
## 2 83.0 83.1 83.2 83.4 83.5 83.6 83.7 83.9 84.0 84.1 84.2 84.3 84.5 84.6 84.7
## 3 83.4 83.6 83.7 83.8 84.0 84.1 84.3 84.4 84.6 84.7 84.8 85.0 85.1 85.2 85.3
## 4 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
## 5 73.2 73.3 73.5 73.7 73.8 74.0 74.2 74.3 74.5 74.6 74.8 74.9 75.0 75.2 75.3
## 6 81.4 81.5 81.7 81.8 81.9 82.0 82.2 82.3 82.4 82.5 82.7 82.8 82.9 83.0 83.2
## 2066 2067 2068 2069 2070 2071 2072 2073 2074 2075 2076 2077 2078 2079 2080
## 1 73.1 73.2 73.3 73.5 73.6 73.7 73.9 74.0 74.2 74.3 74.4 74.6 74.7 74.8 75.0
## 2 84.8 84.9 85.0 85.1 85.2 85.3 85.4 85.5 85.7 85.8 85.8 86.0 86.0 86.2 86.3
## 3 85.5 85.6 85.7 85.8 86.0 86.1 86.2 86.3 86.4 86.5 86.7 86.8 86.9 87.0 87.1
## 4 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
## 5 75.5 75.6 75.7 75.9 76.0 76.2 76.3 76.4 76.5 76.7 76.8 77.0 77.1 77.2 77.3
## 6 83.3 83.4 83.5 83.7 83.8 83.9 84.0 84.1 84.3 84.4 84.5 84.6 84.7 84.8 84.9
## 2081 2082 2083 2084 2085 2086 2087 2088 2089 2090 2091 2092 2093 2094 2095
## 1 75.1 75.2 75.4 75.5 75.6 75.8 75.9 76.0 76.2 76.3 76.5 76.6 76.7 76.9 77.0
## 2 86.4 86.5 86.6 86.7 86.8 86.9 87.0 87.1 87.2 87.3 87.4 87.5 87.6 87.7 87.8
## 3 87.2 87.3 87.4 87.5 87.6 87.7 87.8 87.9 88.0 88.2 88.3 88.4 88.5 88.6 88.7
## 4 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
## 5 77.5 77.6 77.7 77.8 78.0 78.1 78.2 78.4 78.5 78.6 78.7 78.9 79.0 79.1 79.3
## 6 85.0 85.2 85.3 85.4 85.5 85.6 85.7 85.8 85.9 86.0 86.1 86.2 86.3 86.4 86.5
## 2096 2097 2098 2099 2100
## 1 77.1 77.3 77.4 77.5 77.7
## 2 87.9 88.0 88.1 88.2 88.3
## 3 88.8 88.9 89.0 89.1 89.2
## 4 NA NA NA NA NA
## 5 79.4 79.5 79.7 79.8 79.9
## 6 86.6 86.7 86.8 86.9 87.0str(LifeExpectancyInYears) # shows as strings## 'data.frame': 187 obs. of 302 variables:
## $ country: chr "Afghanistan" "Albania" "Algeria" "Andorra" ...
## $ 1800 : num 28.2 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1801 : num 28.2 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1802 : num 28.2 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1803 : num 28.2 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1804 : num 28.2 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1805 : num 28.2 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1806 : num 28.1 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1807 : num 28.1 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1808 : num 28.1 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1809 : num 28.1 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1810 : num 28.1 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1811 : num 28.1 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1812 : num 28.1 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1813 : num 28.1 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1814 : num 28.1 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1815 : num 28.1 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1816 : num 28.1 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1817 : num 28 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1818 : num 28 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1819 : num 28 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1820 : num 28 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1821 : num 28 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1822 : num 28 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1823 : num 28 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1824 : num 28 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1825 : num 27.9 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1826 : num 27.9 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1827 : num 27.9 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1828 : num 27.9 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1829 : num 27.9 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1830 : num 27.9 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1831 : num 27.9 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1832 : num 27.9 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1833 : num 27.9 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1834 : num 27.9 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1835 : num 27.9 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1836 : num 27.8 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1837 : num 27.8 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1838 : num 27.8 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1839 : num 27.8 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1840 : num 27.8 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1841 : num 27.8 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1842 : num 27.8 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1843 : num 27.8 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1844 : num 27.8 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1845 : num 27.8 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1846 : num 27.7 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1847 : num 27.7 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1848 : num 27.7 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1849 : num 27.7 35.4 20 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1850 : num 27.7 35.4 15 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1851 : num 27.7 35.4 22 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1852 : num 27.7 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1853 : num 27.7 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1854 : num 27.7 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1855 : num 27.6 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1856 : num 27.6 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1857 : num 27.6 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1858 : num 27.6 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1859 : num 27.6 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1860 : num 27.6 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1861 : num 27.6 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1862 : num 27.6 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1863 : num 27.6 35.4 28.8 NA 27 33.5 33.2 34 34 34.4 ...
## $ 1864 : num 27.6 35.4 28.8 NA 27 33.5 33.2 33.5 34 34.4 ...
## $ 1865 : num 27.5 35.4 28.8 NA 27 33.5 33.2 33 34 34.4 ...
## $ 1866 : num 27.5 35.4 28.8 NA 27 33.5 33.2 32.4 34 34.4 ...
## $ 1867 : num 27.5 35.4 21 NA 27 33.5 33.2 31.9 34 34.4 ...
## $ 1868 : num 27.5 35.4 11 NA 27 33.5 33.2 31.4 34 34.4 ...
## $ 1869 : num 27.5 35.4 15 NA 27 33.5 33.2 31.4 34 34.4 ...
## $ 1870 : num 27.5 35.4 22 NA 27 33.5 33.2 31.5 34 34.4 ...
## $ 1871 : num 27.6 35.4 28.9 NA 27.1 33.5 33.2 31.5 34.6 34.5 ...
## $ 1872 : num 27.6 35.4 28.9 NA 27.1 33.5 33.2 31.5 35.1 34.5 ...
## $ 1873 : num 27.7 35.4 29 NA 27.2 33.6 33.2 31.5 35.6 34.6 ...
## $ 1874 : num 27.8 35.4 29 NA 27.3 33.6 33.2 31.7 36.2 34.6 ...
## $ 1875 : num 27.8 35.4 29 NA 27.3 33.6 33.2 31.9 36.7 34.7 ...
## $ 1876 : num 27.9 35.4 29.1 NA 27.4 33.6 33.1 32.1 37.2 34.7 ...
## $ 1877 : num 27.9 35.4 29.1 NA 27.5 33.6 33.1 32.2 37.8 34.8 ...
## $ 1878 : num 28 35.4 29.2 NA 27.5 33.6 33.1 32.4 38.3 34.9 ...
## $ 1879 : num 28.1 35.4 29.2 NA 27.6 33.6 33.1 32.6 38.8 34.9 ...
## $ 1880 : num 28.1 35.4 29.3 NA 27.7 33.6 33.1 32.8 39.4 35 ...
## $ 1881 : num 28.2 35.4 29.3 NA 27.7 33.6 33 32.9 39.9 35 ...
## $ 1882 : num 28.3 35.4 29.4 NA 27.8 33.6 32.9 33.1 40.4 35.2 ...
## $ 1883 : num 28.3 35.4 29.4 NA 27.9 33.6 32.7 33.3 41 35.5 ...
## $ 1884 : num 28.4 35.4 29.4 NA 27.9 33.6 32.6 33.5 41.5 35.7 ...
## $ 1885 : num 28.5 35.4 29.5 NA 28 33.6 32.5 33.6 42 35.9 ...
## $ 1886 : num 28.5 35.4 29.5 NA 28.1 33.6 32.8 33.8 42.5 36.2 ...
## $ 1887 : num 28.6 35.4 29.6 NA 28.1 33.7 33.1 34 43.1 36.4 ...
## $ 1888 : num 28.6 35.4 29.6 NA 28.2 33.7 33.4 34.2 43.6 36.6 ...
## $ 1889 : num 28.7 35.4 29.7 NA 28.3 33.7 33.6 34.3 44.1 36.9 ...
## $ 1890 : num 28.8 35.4 29.7 NA 28.4 33.7 33.9 34.5 44.7 37.1 ...
## $ 1891 : num 28.8 35.4 29.8 NA 28.4 33.7 33.8 34.7 45.2 37.3 ...
## $ 1892 : num 28.9 35.4 29.8 NA 28.5 33.7 33.6 34.9 45.7 37.8 ...
## $ 1893 : num 29 35.4 29.8 NA 28.6 33.7 33.5 35 46.3 38.3 ...
## $ 1894 : num 29 35.4 29.9 NA 28.6 33.7 33.3 35.2 46.8 38.7 ...
## $ 1895 : num 29.1 35.4 29.9 NA 28.7 33.7 33.2 35.4 47.3 39.2 ...
## $ 1896 : num 29.1 35.4 30 NA 28.8 33.7 33.9 35.5 47.9 39.7 ...
## $ 1897 : num 29.2 35.4 30 NA 28.8 33.7 34.6 35.7 48.4 40.2 ...
## [list output truncated]summary(LifeExpectancyInYears) #shows summary## country 1800 1801 1802
## Length:187 Min. :23.40 Min. :23.40 Min. :23.40
## Class :character 1st Qu.:29.07 1st Qu.:28.98 1st Qu.:28.90
## Mode :character Median :31.75 Median :31.65 Median :31.55
## Mean :31.50 Mean :31.46 Mean :31.48
## 3rd Qu.:33.83 3rd Qu.:33.90 3rd Qu.:33.83
## Max. :42.90 Max. :40.30 Max. :44.40
## NA's :3 NA's :3 NA's :3
## 1803 1804 1805 1806
## Min. :19.60 Min. :23.40 Min. :23.40 Min. :23.40
## 1st Qu.:28.90 1st Qu.:28.98 1st Qu.:29.07 1st Qu.:29.07
## Median :31.50 Median :31.55 Median :31.65 Median :31.75
## Mean :31.38 Mean :31.46 Mean :31.59 Mean :31.64
## 3rd Qu.:33.62 3rd Qu.:33.73 3rd Qu.:33.83 3rd Qu.:33.92
## Max. :44.80 Max. :42.80 Max. :44.30 Max. :45.80
## NA's :3 NA's :3 NA's :3 NA's :3
## 1807 1808 1809 1810
## Min. :23.40 Min. :12.50 Min. :13.40 Min. :23.40
## 1st Qu.:29.07 1st Qu.:28.98 1st Qu.:28.88 1st Qu.:29.07
## Median :31.75 Median :31.55 Median :31.50 Median :31.75
## Mean :31.60 Mean :31.38 Mean :31.31 Mean :31.54
## 3rd Qu.:33.92 3rd Qu.:33.73 3rd Qu.:33.62 3rd Qu.:33.83
## Max. :43.60 Max. :43.50 Max. :41.70 Max. :43.10
## NA's :3 NA's :3 NA's :3 NA's :3
## 1811 1812 1813 1814
## Min. :23.40 Min. :23.00 Min. :23.40 Min. :23.40
## 1st Qu.:29.07 1st Qu.:29.07 1st Qu.:29.07 1st Qu.:29.07
## Median :31.65 Median :31.70 Median :31.65 Median :31.65
## Mean :31.50 Mean :31.49 Mean :31.48 Mean :31.54
## 3rd Qu.:33.83 3rd Qu.:33.83 3rd Qu.:33.73 3rd Qu.:33.92
## Max. :40.10 Max. :43.50 Max. :43.00 Max. :41.70
## NA's :3 NA's :3 NA's :3 NA's :3
## 1815 1816 1817 1818
## Min. :23.40 Min. :23.40 Min. :23.40 Min. : 5.50
## 1st Qu.:29.07 1st Qu.:29.07 1st Qu.:29.07 1st Qu.:29.07
## Median :31.75 Median :31.65 Median :31.75 Median :31.75
## Mean :31.68 Mean :31.66 Mean :31.76 Mean :31.60
## 3rd Qu.:34.00 3rd Qu.:33.92 3rd Qu.:34.00 3rd Qu.:34.00
## Max. :45.60 Max. :46.30 Max. :48.90 Max. :46.80
## NA's :3 NA's :3 NA's :3 NA's :3
## 1819 1820 1821 1822
## Min. : 1.50 Min. : 6.50 Min. :23.40 Min. :23.40
## 1st Qu.:29.07 1st Qu.:29.15 1st Qu.:29.15 1st Qu.:29.15
## Median :31.75 Median :31.75 Median :31.65 Median :31.80
## Mean :31.50 Mean :31.58 Mean :31.65 Mean :31.76
## 3rd Qu.:34.00 3rd Qu.:34.00 3rd Qu.:33.92 3rd Qu.:34.00
## Max. :45.80 Max. :47.00 Max. :44.70 Max. :48.40
## NA's :3 NA's :3 NA's :3 NA's :3
## 1823 1824 1825 1826
## Min. :23.40 Min. :23.40 Min. :23.40 Min. :23.40
## 1st Qu.:29.15 1st Qu.:29.15 1st Qu.:29.15 1st Qu.:28.98
## Median :31.80 Median :31.80 Median :31.80 Median :31.75
## Mean :31.81 Mean :31.75 Mean :31.70 Mean :31.62
## 3rd Qu.:34.00 3rd Qu.:34.00 3rd Qu.:34.00 3rd Qu.:34.00
## Max. :48.80 Max. :47.60 Max. :49.20 Max. :47.60
## NA's :3 NA's :3 NA's :3 NA's :3
## 1827 1828 1829 1830
## Min. :23.40 Min. :23.40 Min. :23.40 Min. :23.40
## 1st Qu.:28.98 1st Qu.:28.98 1st Qu.:29.15 1st Qu.:29.15
## Median :31.75 Median :31.75 Median :31.75 Median :31.85
## Mean :31.66 Mean :31.60 Mean :31.58 Mean :31.67
## 3rd Qu.:34.00 3rd Qu.:34.00 3rd Qu.:34.00 3rd Qu.:34.00
## Max. :48.40 Max. :46.20 Max. :46.30 Max. :45.80
## NA's :3 NA's :3 NA's :3 NA's :3
## 1831 1832 1833 1834
## Min. :23.40 Min. :23.00 Min. :20.40 Min. :23.40
## 1st Qu.:29.15 1st Qu.:29.15 1st Qu.:29.15 1st Qu.:29.15
## Median :31.80 Median :31.75 Median :31.80 Median :31.80
## Mean :31.63 Mean :31.59 Mean :31.59 Mean :31.57
## 3rd Qu.:34.00 3rd Qu.:33.92 3rd Qu.:34.00 3rd Qu.:34.00
## Max. :45.70 Max. :47.60 Max. :44.90 Max. :42.00
## NA's :3 NA's :3 NA's :3 NA's :3
## 1835 1836 1837 1838
## Min. :23.40 Min. :23.40 Min. :23.40 Min. :23.40
## 1st Qu.:28.98 1st Qu.:29.15 1st Qu.:28.98 1st Qu.:29.15
## Median :31.80 Median :31.65 Median :31.80 Median :31.85
## Mean :31.71 Mean :31.67 Mean :31.61 Mean :31.67
## 3rd Qu.:34.00 3rd Qu.:33.92 3rd Qu.:34.00 3rd Qu.:34.00
## Max. :47.10 Max. :46.50 Max. :44.20 Max. :43.10
## NA's :3 NA's :3 NA's :3 NA's :3
## 1839 1840 1841 1842
## Min. :23.40 Min. :23.40 Min. :23.00 Min. :22.40
## 1st Qu.:28.98 1st Qu.:29.20 1st Qu.:29.15 1st Qu.:29.15
## Median :31.80 Median :31.90 Median :31.85 Median :31.85
## Mean :31.66 Mean :31.75 Mean :31.80 Mean :31.77
## 3rd Qu.:34.00 3rd Qu.:34.00 3rd Qu.:34.05 3rd Qu.:34.05
## Max. :43.00 Max. :45.60 Max. :49.50 Max. :48.40
## NA's :3 NA's :3 NA's :3 NA's :3
## 1843 1844 1845 1846
## Min. :23.40 Min. :15.00 Min. :23.40 Min. :18.30
## 1st Qu.:28.98 1st Qu.:29.15 1st Qu.:29.15 1st Qu.:28.98
## Median :31.80 Median :31.85 Median :31.85 Median :31.75
## Mean :31.76 Mean :31.82 Mean :31.88 Mean :31.57
## 3rd Qu.:34.00 3rd Qu.:34.05 3rd Qu.:34.05 3rd Qu.:34.00
## Max. :48.40 Max. :49.70 Max. :50.10 Max. :48.00
## NA's :3 NA's :3 NA's :3 NA's :3
## 1847 1848 1849 1850
## Min. :23.40 Min. :14.90 Min. :14.10 Min. :14.00
## 1st Qu.:29.15 1st Qu.:28.98 1st Qu.:29.15 1st Qu.:29.20
## Median :31.85 Median :31.85 Median :31.80 Median :31.80
## Mean :31.65 Mean :31.64 Mean :31.48 Mean :31.67
## 3rd Qu.:34.00 3rd Qu.:34.05 3rd Qu.:34.00 3rd Qu.:34.00
## Max. :44.80 Max. :45.10 Max. :48.00 Max. :49.50
## NA's :3 NA's :3 NA's :3 NA's :3
## 1851 1852 1853 1854
## Min. :22.00 Min. :23.40 Min. :23.40 Min. : 7.50
## 1st Qu.:29.20 1st Qu.:29.20 1st Qu.:29.15 1st Qu.:28.90
## Median :31.80 Median :31.85 Median :31.85 Median :31.80
## Mean :31.82 Mean :31.83 Mean :31.83 Mean :31.70
## 3rd Qu.:34.05 3rd Qu.:34.05 3rd Qu.:34.00 3rd Qu.:34.05
## Max. :49.70 Max. :48.50 Max. :48.60 Max. :51.60
## NA's :3 NA's :3 NA's :3 NA's :3
## 1855 1856 1857 1858
## Min. :23.40 Min. :17.60 Min. :23.40 Min. :23.40
## 1st Qu.:28.98 1st Qu.:28.98 1st Qu.:29.15 1st Qu.:29.15
## Median :31.80 Median :31.75 Median :31.80 Median :31.85
## Mean :31.74 Mean :31.75 Mean :31.76 Mean :31.76
## 3rd Qu.:34.00 3rd Qu.:34.00 3rd Qu.:34.05 3rd Qu.:34.05
## Max. :50.40 Max. :50.40 Max. :50.20 Max. :51.60
## NA's :3 NA's :3 NA's :3 NA's :3
## 1859 1860 1861 1862
## Min. :23.40 Min. :19.80 Min. :22.00 Min. :22.70
## 1st Qu.:29.15 1st Qu.:28.98 1st Qu.:29.15 1st Qu.:28.98
## Median :31.70 Median :31.75 Median :31.75 Median :31.75
## Mean :31.73 Mean :31.81 Mean :31.77 Mean :31.70
## 3rd Qu.:34.00 3rd Qu.:34.00 3rd Qu.:34.00 3rd Qu.:34.00
## Max. :49.90 Max. :50.00 Max. :47.60 Max. :47.60
## NA's :3 NA's :3 NA's :3 NA's :3
## 1863 1864 1865 1866
## Min. :23.40 Min. :23.20 Min. :22.30 Min. :21.00
## 1st Qu.:29.15 1st Qu.:28.90 1st Qu.:28.90 1st Qu.:28.88
## Median :31.80 Median :31.70 Median :31.70 Median :31.65
## Mean :31.76 Mean :31.69 Mean :31.65 Mean :31.52
## 3rd Qu.:34.00 3rd Qu.:34.00 3rd Qu.:34.00 3rd Qu.:33.73
## Max. :47.60 Max. :48.80 Max. :50.40 Max. :49.90
## NA's :3 NA's :3 NA's :3 NA's :3
## 1867 1868 1869 1870
## Min. : 4.00 Min. : 8.11 Min. :15.00 Min. :19.90
## 1st Qu.:28.90 1st Qu.:28.88 1st Qu.:28.88 1st Qu.:29.15
## Median :31.70 Median :31.55 Median :31.55 Median :31.75
## Mean :31.53 Mean :31.25 Mean :31.57 Mean :31.82
## 3rd Qu.:34.00 3rd Qu.:34.00 3rd Qu.:34.00 3rd Qu.:34.25
## Max. :47.90 Max. :47.20 Max. :49.30 Max. :50.90
## NA's :3 NA's :3 NA's :3 NA's :3
## 1871 1872 1873 1874
## Min. :20.00 Min. :20.00 Min. :20.10 Min. :20.30
## 1st Qu.:29.15 1st Qu.:29.00 1st Qu.:29.20 1st Qu.:29.48
## Median :31.65 Median :31.70 Median :31.70 Median :31.80
## Mean :31.76 Mean :31.85 Mean :31.95 Mean :32.01
## 3rd Qu.:34.25 3rd Qu.:34.60 3rd Qu.:34.70 3rd Qu.:34.70
## Max. :49.70 Max. :50.10 Max. :49.70 Max. :47.80
## NA's :3 NA's :3 NA's :3 NA's :3
## 1875 1876 1877 1878
## Min. : 1.01 Min. :20.00 Min. :19.00 Min. :20.00
## 1st Qu.:29.48 1st Qu.:29.50 1st Qu.:29.50 1st Qu.:29.50
## Median :31.75 Median :31.80 Median :31.85 Median :31.90
## Mean :31.90 Mean :32.11 Mean :32.20 Mean :32.21
## 3rd Qu.:35.02 3rd Qu.:34.85 3rd Qu.:34.92 3rd Qu.:35.00
## Max. :47.60 Max. :46.80 Max. :49.80 Max. :51.80
## NA's :3 NA's :3 NA's :3 NA's :3
## 1879 1880 1881 1882
## Min. :21.20 Min. :21.40 Min. :21.60 Min. :17.70
## 1st Qu.:29.60 1st Qu.:29.68 1st Qu.:29.75 1st Qu.:29.50
## Median :31.95 Median :32.00 Median :32.05 Median :32.00
## Mean :32.34 Mean :32.35 Mean :32.41 Mean :32.37
## 3rd Qu.:35.02 3rd Qu.:35.02 3rd Qu.:35.02 3rd Qu.:35.12
## Max. :53.20 Max. :51.90 Max. :50.50 Max. :48.60
## NA's :3 NA's :3 NA's :3 NA's :3
## 1883 1884 1885 1886
## Min. :22.00 Min. :22.20 Min. :22.40 Min. :22.60
## 1st Qu.:29.70 1st Qu.:29.95 1st Qu.:29.80 1st Qu.:30.05
## Median :32.00 Median :32.05 Median :32.10 Median :32.15
## Mean :32.53 Mean :32.69 Mean :32.76 Mean :32.83
## 3rd Qu.:35.20 3rd Qu.:35.23 3rd Qu.:35.33 3rd Qu.:35.33
## Max. :49.60 Max. :50.80 Max. :51.00 Max. :51.70
## NA's :3 NA's :3 NA's :3 NA's :3
## 1887 1888 1889 1890
## Min. :22.80 Min. :17.00 Min. : 5.00 Min. : 4.00
## 1st Qu.:29.88 1st Qu.:30.12 1st Qu.:29.95 1st Qu.:29.90
## Median :32.10 Median :32.20 Median :32.15 Median :32.15
## Mean :32.89 Mean :32.94 Mean :32.93 Mean :32.71
## 3rd Qu.:35.42 3rd Qu.:35.42 3rd Qu.:35.50 3rd Qu.:35.42
## Max. :51.70 Max. :52.30 Max. :52.50 Max. :50.50
## NA's :3 NA's :3 NA's :3 NA's :3
## 1891 1892 1893 1894
## Min. : 8.00 Min. :14.00 Min. : 8.08 Min. :21.80
## 1st Qu.:30.10 1st Qu.:30.05 1st Qu.:29.98 1st Qu.:30.00
## Median :32.20 Median :32.20 Median :32.20 Median :32.35
## Mean :32.92 Mean :32.94 Mean :33.01 Mean :33.25
## 3rd Qu.:35.52 3rd Qu.:35.42 3rd Qu.:35.42 3rd Qu.:35.45
## Max. :51.10 Max. :52.70 Max. :52.60 Max. :52.10
## NA's :3 NA's :3 NA's :3 NA's :3
## 1895 1896 1897 1898
## Min. :21.60 Min. :19.60 Min. :18.60 Min. :19.90
## 1st Qu.:29.98 1st Qu.:30.00 1st Qu.:30.07 1st Qu.:30.05
## Median :32.30 Median :32.35 Median :32.40 Median :32.45
## Mean :33.34 Mean :33.44 Mean :33.52 Mean :33.57
## 3rd Qu.:35.60 3rd Qu.:35.60 3rd Qu.:35.60 3rd Qu.:35.60
## Max. :54.10 Max. :53.80 Max. :54.10 Max. :54.70
## NA's :3 NA's :3 NA's :3 NA's :3
## 1899 1900 1901 1902
## Min. :19.10 Min. :18.40 Min. :21.20 Min. :12.90
## 1st Qu.:30.05 1st Qu.:30.20 1st Qu.:30.15 1st Qu.:30.05
## Median :32.50 Median :32.55 Median :32.65 Median :32.65
## Mean :33.55 Mean :33.61 Mean :33.80 Mean :33.90
## 3rd Qu.:35.62 3rd Qu.:35.62 3rd Qu.:35.62 3rd Qu.:35.70
## Max. :51.60 Max. :53.40 Max. :54.50 Max. :56.40
## NA's :3 NA's :3 NA's :3 NA's :3
## 1903 1904 1905 1906
## Min. :20.30 Min. : 5.19 Min. :10.40 Min. :20.30
## 1st Qu.:30.10 1st Qu.:30.18 1st Qu.:30.27 1st Qu.:30.10
## Median :32.75 Median :32.80 Median :32.75 Median :32.65
## Mean :33.95 Mean :33.99 Mean :34.04 Mean :34.18
## 3rd Qu.:35.73 3rd Qu.:35.73 3rd Qu.:35.80 3rd Qu.:35.73
## Max. :55.10 Max. :56.00 Max. :55.00 Max. :56.80
## NA's :3 NA's :3 NA's :3 NA's :3
## 1907 1908 1909 1910
## Min. :18.10 Min. :21.20 Min. :21.40 Min. :21.50
## 1st Qu.:30.18 1st Qu.:30.40 1st Qu.:30.68 1st Qu.:30.68
## Median :32.75 Median :32.90 Median :32.85 Median :32.90
## Mean :34.30 Mean :34.42 Mean :34.68 Mean :34.83
## 3rd Qu.:35.73 3rd Qu.:35.83 3rd Qu.:35.83 3rd Qu.:35.83
## Max. :57.00 Max. :56.40 Max. :58.40 Max. :58.00
## NA's :3 NA's :3 NA's :3 NA's :3
## 1911 1912 1913 1914
## Min. :21.70 Min. :21.80 Min. :22.00 Min. :22.10
## 1st Qu.:30.77 1st Qu.:30.70 1st Qu.:30.70 1st Qu.:30.57
## Median :33.05 Median :33.15 Median :32.95 Median :32.90
## Mean :34.96 Mean :35.19 Mean :35.22 Mean :34.96
## 3rd Qu.:36.02 3rd Qu.:36.10 3rd Qu.:36.12 3rd Qu.:36.12
## Max. :58.00 Max. :58.00 Max. :58.90 Max. :58.50
## NA's :3 NA's :3 NA's :3 NA's :3
## 1915 1916 1917 1918 1919
## Min. : 7.21 Min. :19.60 Min. :20.10 Min. : 1.10 Min. :11.8
## 1st Qu.:30.60 1st Qu.:30.60 1st Qu.:30.40 1st Qu.:13.20 1st Qu.:30.6
## Median :33.00 Median :33.00 Median :32.90 Median :22.00 Median :33.1
## Mean :34.59 Mean :34.71 Mean :34.55 Mean :22.95 Mean :34.7
## 3rd Qu.:35.92 3rd Qu.:35.92 3rd Qu.:35.73 3rd Qu.:29.18 3rd Qu.:35.9
## Max. :58.40 Max. :58.50 Max. :59.00 Max. :56.20 Max. :60.1
## NA's :3 NA's :3 NA's :3 NA's :3 NA's :3
## 1920 1921 1922 1923
## Min. :15.20 Min. :11.90 Min. :13.90 Min. :23.40
## 1st Qu.:30.48 1st Qu.:30.57 1st Qu.:30.75 1st Qu.:31.20
## Median :32.90 Median :33.05 Median :33.55 Median :33.70
## Mean :34.96 Mean :35.44 Mean :35.77 Mean :36.52
## 3rd Qu.:35.90 3rd Qu.:36.33 3rd Qu.:36.73 3rd Qu.:37.92
## Max. :60.60 Max. :61.70 Max. :63.00 Max. :63.00
## NA's :3 NA's :3 NA's :3 NA's :3
## 1924 1925 1926 1927
## Min. :23.60 Min. :23.60 Min. :23.60 Min. :23.60
## 1st Qu.:31.27 1st Qu.:31.27 1st Qu.:31.40 1st Qu.:31.45
## Median :33.90 Median :34.05 Median :34.25 Median :34.35
## Mean :36.81 Mean :36.99 Mean :37.38 Mean :37.54
## 3rd Qu.:38.62 3rd Qu.:39.30 3rd Qu.:40.02 3rd Qu.:40.65
## Max. :63.00 Max. :63.30 Max. :63.10 Max. :63.00
## NA's :3 NA's :3 NA's :3 NA's :3
## 1928 1929 1930 1931
## Min. :23.60 Min. :23.60 Min. :23.70 Min. :16.30
## 1st Qu.:31.57 1st Qu.:31.60 1st Qu.:31.90 1st Qu.:31.85
## Median :34.40 Median :34.50 Median :34.65 Median :34.50
## Mean :37.86 Mean :37.88 Mean :38.37 Mean :38.35
## 3rd Qu.:41.27 3rd Qu.:41.70 3rd Qu.:42.42 3rd Qu.:43.12
## Max. :63.80 Max. :63.30 Max. :65.10 Max. :65.50
## NA's :3 NA's :3 NA's :3 NA's :3
## 1932 1933 1934 1935
## Min. : 8.15 Min. : 4.07 Min. :23.70 Min. :23.70
## 1st Qu.:31.85 1st Qu.:31.68 1st Qu.:32.40 1st Qu.:32.48
## Median :34.60 Median :34.70 Median :35.75 Median :36.35
## Mean :38.34 Mean :38.13 Mean :39.67 Mean :40.07
## 3rd Qu.:43.55 3rd Qu.:44.10 3rd Qu.:44.90 3rd Qu.:46.12
## Max. :65.80 Max. :66.20 Max. :66.70 Max. :66.60
## NA's :3 NA's :3 NA's :3 NA's :3
## 1936 1937 1938 1939
## Min. :23.00 Min. :23.70 Min. :23.70 Min. :23.70
## 1st Qu.:33.08 1st Qu.:33.30 1st Qu.:33.45 1st Qu.:33.73
## Median :36.75 Median :36.80 Median :37.25 Median :38.10
## Mean :40.56 Mean :40.88 Mean :41.40 Mean :41.87
## 3rd Qu.:47.23 3rd Qu.:47.75 3rd Qu.:48.55 3rd Qu.:49.33
## Max. :66.80 Max. :67.10 Max. :67.50 Max. :67.80
## NA's :3 NA's :3 NA's :3 NA's :3
## 1940 1941 1942 1943
## Min. :23.70 Min. :12.00 Min. :14.90 Min. :13.90
## 1st Qu.:33.75 1st Qu.:32.90 1st Qu.:32.50 1st Qu.:32.48
## Median :38.40 Median :36.70 Median :36.60 Median :37.15
## Mean :41.82 Mean :40.34 Mean :40.14 Mean :39.91
## 3rd Qu.:49.35 3rd Qu.:47.02 3rd Qu.:48.15 3rd Qu.:47.90
## Max. :66.70 Max. :67.00 Max. :68.90 Max. :68.70
## NA's :3 NA's :3 NA's :3 NA's :3
## 1944 1945 1946 1947
## Min. :15.40 Min. :15.90 Min. :22.30 Min. :11.10
## 1st Qu.:32.60 1st Qu.:33.90 1st Qu.:35.77 1st Qu.:37.00
## Median :36.45 Median :38.90 Median :44.50 Median :43.40
## Mean :39.72 Mean :41.55 Mean :45.14 Mean :45.67
## 3rd Qu.:46.45 3rd Qu.:47.17 3rd Qu.:53.70 3rd Qu.:54.23
## Max. :68.20 Max. :68.60 Max. :69.50 Max. :69.80
## NA's :3 NA's :3 NA's :3 NA's :3
## 1948 1949 1950 1951
## Min. :23.70 Min. :23.80 Min. :23.80 Min. :24.20
## 1st Qu.:38.27 1st Qu.:39.42 1st Qu.:40.77 1st Qu.:40.92
## Median :47.35 Median :48.75 Median :50.00 Median :50.25
## Mean :47.83 Mean :48.96 Mean :50.08 Mean :50.29
## 3rd Qu.:56.85 3rd Qu.:58.00 3rd Qu.:58.95 3rd Qu.:59.48
## Max. :71.20 Max. :71.40 Max. :71.60 Max. :72.30
## NA's :3 NA's :3 NA's :3 NA's :3
## 1952 1953 1954 1955
## Min. :25.20 Min. :26.20 Min. :27.10 Min. :28.10
## 1st Qu.:41.17 1st Qu.:41.83 1st Qu.:42.38 1st Qu.:43.00
## Median :50.70 Median :51.30 Median :52.05 Median :52.65
## Mean :50.90 Mean :51.54 Mean :52.22 Mean :52.80
## 3rd Qu.:59.92 3rd Qu.:60.98 3rd Qu.:61.35 3rd Qu.:61.92
## Max. :72.50 Max. :73.00 Max. :73.30 Max. :73.30
## NA's :3 NA's :3 NA's :3 NA's :3
## 1956 1957 1958 1959
## Min. :29.10 Min. :30.10 Min. :31.00 Min. :32.00
## 1st Qu.:43.60 1st Qu.:44.30 1st Qu.:45.08 1st Qu.:45.42
## Median :53.80 Median :54.45 Median :55.00 Median :55.45
## Mean :53.33 Mean :53.80 Mean :54.42 Mean :54.86
## 3rd Qu.:62.45 3rd Qu.:63.15 3rd Qu.:63.90 3rd Qu.:64.12
## Max. :73.30 Max. :73.40 Max. :73.40 Max. :73.30
## NA's :3 NA's :3 NA's :3 NA's :3
## 1960 1961 1962 1963
## Min. :31.60 Min. :33.90 Min. :34.50 Min. :34.90
## 1st Qu.:45.98 1st Qu.:46.40 1st Qu.:46.75 1st Qu.:47.27
## Median :55.90 Median :56.35 Median :56.80 Median :57.45
## Mean :55.41 Mean :55.93 Mean :56.40 Mean :56.92
## 3rd Qu.:64.62 3rd Qu.:65.00 3rd Qu.:65.33 3rd Qu.:65.65
## Max. :74.00 Max. :73.70 Max. :73.60 Max. :73.50
## NA's :3 NA's :3 NA's :3 NA's :3
## 1964 1965 1966 1967
## Min. :35.30 Min. :35.80 Min. :36.50 Min. :37.20
## 1st Qu.:47.67 1st Qu.:48.17 1st Qu.:48.60 1st Qu.:49.50
## Median :58.15 Median :58.90 Median :59.95 Median :60.90
## Mean :57.46 Mean :57.86 Mean :58.32 Mean :58.77
## 3rd Qu.:66.05 3rd Qu.:66.50 3rd Qu.:66.92 3rd Qu.:67.42
## Max. :73.90 Max. :73.80 Max. :74.10 Max. :74.10
## NA's :3 NA's :3 NA's :3 NA's :3
## 1968 1969 1970 1971
## Min. :38.00 Min. :36.90 Min. :39.70 Min. :39.90
## 1st Qu.:50.23 1st Qu.:50.58 1st Qu.:51.65 1st Qu.:52.20
## Median :61.40 Median :61.70 Median :62.30 Median :63.00
## Mean :59.14 Mean :59.51 Mean :60.16 Mean :60.59
## 3rd Qu.:67.92 3rd Qu.:68.25 3rd Qu.:68.80 3rd Qu.:68.95
## Max. :74.00 Max. :74.10 Max. :75.50 Max. :75.80
## NA's :3 NA's :3
## 1972 1973 1974 1975
## Min. :18.50 Min. :40.50 Min. :38.90 Min. :24.90
## 1st Qu.:52.45 1st Qu.:53.25 1st Qu.:53.70 1st Qu.:54.30
## Median :63.40 Median :63.50 Median :63.90 Median :64.50
## Mean :60.82 Mean :61.22 Mean :61.62 Mean :61.95
## 3rd Qu.:69.30 3rd Qu.:69.25 3rd Qu.:69.35 3rd Qu.:69.70
## Max. :76.10 Max. :76.40 Max. :76.70 Max. :77.00
##
## 1976 1977 1978 1979
## Min. :24.80 Min. :24.60 Min. :24.30 Min. :24.10
## 1st Qu.:54.55 1st Qu.:55.10 1st Qu.:55.40 1st Qu.:56.05
## Median :64.60 Median :65.20 Median :65.50 Median :66.20
## Mean :62.18 Mean :62.66 Mean :62.93 Mean :63.22
## 3rd Qu.:69.85 3rd Qu.:70.10 3rd Qu.:70.40 3rd Qu.:70.60
## Max. :77.20 Max. :77.50 Max. :77.80 Max. :78.10
##
## 1980 1981 1982 1983
## Min. :43.40 Min. :43.20 Min. :43.70 Min. :41.40
## 1st Qu.:56.05 1st Qu.:56.25 1st Qu.:56.25 1st Qu.:57.25
## Median :66.50 Median :66.70 Median :66.80 Median :67.40
## Mean :63.74 Mean :63.95 Mean :64.05 Mean :64.47
## 3rd Qu.:70.75 3rd Qu.:71.00 3rd Qu.:71.15 3rd Qu.:71.25
## Max. :78.20 Max. :78.30 Max. :78.30 Max. :78.30
##
## 1984 1985 1986 1987
## Min. :40.50 Min. :42.40 Min. :43.40 Min. :44.80
## 1st Qu.:57.85 1st Qu.:58.25 1st Qu.:58.65 1st Qu.:58.65
## Median :67.80 Median :68.10 Median :68.60 Median :68.90
## Mean :64.73 Mean :65.00 Mean :65.36 Mean :65.53
## 3rd Qu.:71.30 3rd Qu.:71.55 3rd Qu.:71.75 3rd Qu.:71.85
## Max. :78.50 Max. :78.60 Max. :78.70 Max. :78.80
##
## 1988 1989 1990 1991
## Min. :45.40 Min. :46.00 Min. :46.60 Min. :46.90
## 1st Qu.:58.65 1st Qu.:59.45 1st Qu.:59.95 1st Qu.:60.05
## Median :68.90 Median :69.60 Median :69.50 Median :69.70
## Mean :65.66 Mean :66.07 Mean :66.19 Mean :66.30
## 3rd Qu.:71.95 3rd Qu.:71.90 3rd Qu.:72.15 3rd Qu.:72.50
## Max. :78.90 Max. :79.10 Max. :79.30 Max. :79.40
##
## 1992 1993 1994 1995
## Min. :46.50 Min. :46.10 Min. : 9.64 Min. :44.30
## 1st Qu.:60.15 1st Qu.:60.20 1st Qu.:60.60 1st Qu.:60.35
## Median :69.40 Median :69.20 Median :69.50 Median :69.40
## Mean :66.36 Mean :66.37 Mean :66.23 Mean :66.48
## 3rd Qu.:72.60 3rd Qu.:72.80 3rd Qu.:73.10 3rd Qu.:73.30
## Max. :79.50 Max. :79.70 Max. :80.10 Max. :80.00
##
## 1996 1997 1998 1999
## Min. :43.90 Min. :43.60 Min. :44.30 Min. :43.40
## 1st Qu.:60.15 1st Qu.:60.20 1st Qu.:60.15 1st Qu.:59.95
## Median :70.10 Median :70.40 Median :70.60 Median :70.70
## Mean :66.69 Mean :66.82 Mean :66.98 Mean :67.14
## 3rd Qu.:73.40 3rd Qu.:73.75 3rd Qu.:73.80 3rd Qu.:74.05
## Max. :80.50 Max. :80.80 Max. :80.80 Max. :81.00
##
## 2000 2001 2002 2003
## Min. :44.30 Min. :44.30 Min. :44.40 Min. :44.50
## 1st Qu.:60.55 1st Qu.:61.00 1st Qu.:61.35 1st Qu.:61.55
## Median :71.10 Median :71.10 Median :71.30 Median :72.00
## Mean :67.49 Mean :67.77 Mean :67.97 Mean :68.26
## 3rd Qu.:74.50 3rd Qu.:74.80 3rd Qu.:74.95 3rd Qu.:75.15
## Max. :81.40 Max. :81.70 Max. :82.00 Max. :82.10
##
## 2004 2005 2006 2007
## Min. :43.90 Min. :43.60 Min. :43.90 Min. :44.20
## 1st Qu.:61.60 1st Qu.:61.70 1st Qu.:62.05 1st Qu.:62.45
## Median :71.90 Median :72.20 Median :72.60 Median :72.60
## Mean :68.51 Mean :68.84 Mean :69.19 Mean :69.54
## 3rd Qu.:75.50 3rd Qu.:75.60 3rd Qu.:76.00 3rd Qu.:76.30
## Max. :82.30 Max. :82.30 Max. :82.60 Max. :82.80
##
## 2008 2009 2010 2011
## Min. :44.50 Min. :44.90 Min. :32.50 Min. :48.00
## 1st Qu.:62.70 1st Qu.:63.30 1st Qu.:63.90 1st Qu.:64.20
## Median :72.80 Median :72.90 Median :73.30 Median :73.40
## Mean :69.85 Mean :70.21 Mean :70.48 Mean :70.91
## 3rd Qu.:76.45 3rd Qu.:76.75 3rd Qu.:77.00 3rd Qu.:77.15
## Max. :82.90 Max. :83.10 Max. :83.20 Max. :83.40
##
## 2012 2013 2014 2015
## Min. :48.90 Min. :48.50 Min. :48.70 Min. :50.50
## 1st Qu.:65.00 1st Qu.:65.45 1st Qu.:65.95 1st Qu.:66.95
## Median :73.20 Median :73.10 Median :73.10 Median :73.30
## Mean :71.31 Mean :71.64 Mean :71.87 Mean :72.14
## 3rd Qu.:77.45 3rd Qu.:77.60 3rd Qu.:77.75 3rd Qu.:77.85
## Max. :83.60 Max. :83.90 Max. :84.20 Max. :84.40
##
## 2016 2017 2018 2019
## Min. :51.70 Min. :51.90 Min. :52.40 Min. :52.90
## 1st Qu.:67.30 1st Qu.:67.80 1st Qu.:68.10 1st Qu.:68.28
## Median :73.70 Median :74.00 Median :74.15 Median :74.20
## Mean :72.45 Mean :72.74 Mean :72.97 Mean :73.18
## 3rd Qu.:78.05 3rd Qu.:78.15 3rd Qu.:78.33 3rd Qu.:78.50
## Max. :84.70 Max. :84.80 Max. :85.00 Max. :85.10
## NA's :3 NA's :3
## 2020 2021 2022 2023
## Min. :53.30 Min. :53.60 Min. :53.90 Min. :54.20
## 1st Qu.:68.47 1st Qu.:68.72 1st Qu.:69.00 1st Qu.:69.20
## Median :74.35 Median :74.50 Median :74.65 Median :74.95
## Mean :73.39 Mean :73.59 Mean :73.78 Mean :73.97
## 3rd Qu.:78.60 3rd Qu.:78.72 3rd Qu.:78.90 3rd Qu.:79.00
## Max. :85.30 Max. :85.40 Max. :85.50 Max. :85.70
## NA's :3 NA's :3 NA's :3 NA's :3
## 2024 2025 2026 2027
## Min. :54.50 Min. :54.80 Min. :55.10 Min. :55.40
## 1st Qu.:69.35 1st Qu.:69.50 1st Qu.:69.67 1st Qu.:69.97
## Median :75.10 Median :75.25 Median :75.40 Median :75.50
## Mean :74.16 Mean :74.34 Mean :74.52 Mean :74.72
## 3rd Qu.:79.12 3rd Qu.:79.30 3rd Qu.:79.40 3rd Qu.:79.60
## Max. :85.80 Max. :85.90 Max. :86.00 Max. :86.20
## NA's :3 NA's :3 NA's :3 NA's :3
## 2028 2029 2030 2031
## Min. :55.70 Min. :56.00 Min. :56.30 Min. :56.60
## 1st Qu.:70.28 1st Qu.:70.50 1st Qu.:70.70 1st Qu.:70.95
## Median :75.70 Median :75.80 Median :75.95 Median :76.10
## Mean :74.90 Mean :75.09 Mean :75.27 Mean :75.44
## 3rd Qu.:79.72 3rd Qu.:79.92 3rd Qu.:80.10 3rd Qu.:80.30
## Max. :86.30 Max. :86.40 Max. :86.50 Max. :86.60
## NA's :3 NA's :3 NA's :3 NA's :3
## 2032 2033 2034 2035
## Min. :56.90 Min. :57.20 Min. :57.40 Min. :57.70
## 1st Qu.:71.20 1st Qu.:71.30 1st Qu.:71.47 1st Qu.:71.60
## Median :76.30 Median :76.45 Median :76.65 Median :76.75
## Mean :75.62 Mean :75.79 Mean :75.96 Mean :76.13
## 3rd Qu.:80.50 3rd Qu.:80.65 3rd Qu.:80.83 3rd Qu.:80.95
## Max. :86.80 Max. :86.90 Max. :87.00 Max. :87.10
## NA's :3 NA's :3 NA's :3 NA's :3
## 2036 2037 2038 2039
## Min. :58.00 Min. :58.30 Min. :58.50 Min. :58.80
## 1st Qu.:71.83 1st Qu.:71.95 1st Qu.:72.17 1st Qu.:72.30
## Median :76.90 Median :77.05 Median :77.20 Median :77.30
## Mean :76.30 Mean :76.46 Mean :76.61 Mean :76.78
## 3rd Qu.:81.12 3rd Qu.:81.33 3rd Qu.:81.42 3rd Qu.:81.60
## Max. :87.30 Max. :87.40 Max. :87.50 Max. :87.60
## NA's :3 NA's :3 NA's :3 NA's :3
## 2040 2041 2042 2043
## Min. :59.00 Min. :59.30 Min. :59.50 Min. :59.70
## 1st Qu.:72.40 1st Qu.:72.67 1st Qu.:72.88 1st Qu.:73.08
## Median :77.40 Median :77.55 Median :77.70 Median :77.85
## Mean :76.93 Mean :77.09 Mean :77.25 Mean :77.40
## 3rd Qu.:81.72 3rd Qu.:81.90 3rd Qu.:82.03 3rd Qu.:82.20
## Max. :87.70 Max. :87.80 Max. :88.00 Max. :88.10
## NA's :3 NA's :3 NA's :3 NA's :3
## 2044 2045 2046 2047
## Min. :60.00 Min. :60.20 Min. :60.40 Min. :60.60
## 1st Qu.:73.20 1st Qu.:73.30 1st Qu.:73.50 1st Qu.:73.60
## Median :77.95 Median :78.15 Median :78.30 Median :78.45
## Mean :77.55 Mean :77.70 Mean :77.85 Mean :78.00
## 3rd Qu.:82.30 3rd Qu.:82.50 3rd Qu.:82.62 3rd Qu.:82.80
## Max. :88.20 Max. :88.30 Max. :88.50 Max. :88.60
## NA's :3 NA's :3 NA's :3 NA's :3
## 2048 2049 2050 2051
## Min. :60.80 Min. :61.00 Min. :61.20 Min. :61.40
## 1st Qu.:73.70 1st Qu.:73.80 1st Qu.:73.97 1st Qu.:74.08
## Median :78.60 Median :78.75 Median :78.90 Median :79.05
## Mean :78.15 Mean :78.29 Mean :78.44 Mean :78.58
## 3rd Qu.:82.92 3rd Qu.:83.10 3rd Qu.:83.22 3rd Qu.:83.40
## Max. :88.70 Max. :88.80 Max. :88.90 Max. :89.00
## NA's :3 NA's :3 NA's :3 NA's :3
## 2052 2053 2054 2055
## Min. :61.60 Min. :61.80 Min. :62.00 Min. :62.20
## 1st Qu.:74.28 1st Qu.:74.38 1st Qu.:74.50 1st Qu.:74.67
## Median :79.25 Median :79.35 Median :79.55 Median :79.70
## Mean :78.72 Mean :78.87 Mean :79.00 Mean :79.14
## 3rd Qu.:83.50 3rd Qu.:83.70 3rd Qu.:83.80 3rd Qu.:83.92
## Max. :89.20 Max. :89.30 Max. :89.40 Max. :89.50
## NA's :3 NA's :3 NA's :3 NA's :3
## 2056 2057 2058 2059
## Min. :62.30 Min. :62.50 Min. :62.70 Min. :62.90
## 1st Qu.:74.80 1st Qu.:74.90 1st Qu.:75.08 1st Qu.:75.20
## Median :79.85 Median :80.00 Median :80.10 Median :80.25
## Mean :79.28 Mean :79.42 Mean :79.56 Mean :79.69
## 3rd Qu.:84.03 3rd Qu.:84.20 3rd Qu.:84.33 3rd Qu.:84.42
## Max. :89.60 Max. :89.80 Max. :89.90 Max. :90.00
## NA's :3 NA's :3 NA's :3 NA's :3
## 2060 2061 2062 2063
## Min. :63.00 Min. :63.20 Min. :63.40 Min. :63.50
## 1st Qu.:75.30 1st Qu.:75.50 1st Qu.:75.60 1st Qu.:75.78
## Median :80.40 Median :80.55 Median :80.70 Median :80.85
## Mean :79.83 Mean :79.96 Mean :80.10 Mean :80.24
## 3rd Qu.:84.60 3rd Qu.:84.72 3rd Qu.:84.83 3rd Qu.:85.00
## Max. :90.10 Max. :90.20 Max. :90.30 Max. :90.50
## NA's :3 NA's :3 NA's :3 NA's :3
## 2064 2065 2066 2067
## Min. :63.70 Min. :63.80 Min. :64.00 Min. :64.10
## 1st Qu.:75.90 1st Qu.:76.00 1st Qu.:76.17 1st Qu.:76.30
## Median :81.00 Median :81.15 Median :81.25 Median :81.40
## Mean :80.36 Mean :80.50 Mean :80.62 Mean :80.76
## 3rd Qu.:85.10 3rd Qu.:85.20 3rd Qu.:85.30 3rd Qu.:85.50
## Max. :90.60 Max. :90.70 Max. :90.80 Max. :90.90
## NA's :3 NA's :3 NA's :3 NA's :3
## 2068 2069 2070 2071
## Min. :64.30 Min. :64.40 Min. :64.50 Min. :64.70
## 1st Qu.:76.40 1st Qu.:76.58 1st Qu.:76.70 1st Qu.:76.80
## Median :81.55 Median :81.65 Median :81.80 Median :81.95
## Mean :80.89 Mean :81.01 Mean :81.15 Mean :81.27
## 3rd Qu.:85.60 3rd Qu.:85.70 3rd Qu.:85.80 3rd Qu.:85.92
## Max. :91.00 Max. :91.20 Max. :91.30 Max. :91.40
## NA's :3 NA's :3 NA's :3 NA's :3
## 2072 2073 2074 2075
## Min. :64.80 Min. :64.90 Min. :65.10 Min. :65.20
## 1st Qu.:77.00 1st Qu.:77.10 1st Qu.:77.28 1st Qu.:77.38
## Median :82.05 Median :82.20 Median :82.30 Median :82.50
## Mean :81.40 Mean :81.53 Mean :81.66 Mean :81.78
## 3rd Qu.:86.03 3rd Qu.:86.12 3rd Qu.:86.30 3rd Qu.:86.40
## Max. :91.50 Max. :91.60 Max. :91.70 Max. :91.80
## NA's :3 NA's :3 NA's :3 NA's :3
## 2076 2077 2078 2079
## Min. :65.30 Min. :65.50 Min. :65.60 Min. :65.70
## 1st Qu.:77.58 1st Qu.:77.67 1st Qu.:77.78 1st Qu.:77.97
## Median :82.60 Median :82.70 Median :82.80 Median :82.95
## Mean :81.91 Mean :82.04 Mean :82.17 Mean :82.28
## 3rd Qu.:86.50 3rd Qu.:86.62 3rd Qu.:86.72 3rd Qu.:86.83
## Max. :92.00 Max. :92.10 Max. :92.20 Max. :92.30
## NA's :3 NA's :3 NA's :3 NA's :3
## 2080 2081 2082 2083
## Min. :65.80 Min. :66.00 Min. :66.10 Min. :66.20
## 1st Qu.:78.08 1st Qu.:78.25 1st Qu.:78.38 1st Qu.:78.47
## Median :83.05 Median :83.15 Median :83.25 Median :83.35
## Mean :82.41 Mean :82.53 Mean :82.66 Mean :82.78
## 3rd Qu.:86.92 3rd Qu.:87.03 3rd Qu.:87.12 3rd Qu.:87.22
## Max. :92.40 Max. :92.50 Max. :92.70 Max. :92.80
## NA's :3 NA's :3 NA's :3 NA's :3
## 2084 2085 2086 2087
## Min. :66.30 Min. :66.50 Min. :66.60 Min. :66.70
## 1st Qu.:78.65 1st Qu.:78.78 1st Qu.:78.88 1st Qu.:79.00
## Median :83.45 Median :83.55 Median :83.70 Median :83.80
## Mean :82.91 Mean :83.03 Mean :83.15 Mean :83.27
## 3rd Qu.:87.33 3rd Qu.:87.50 3rd Qu.:87.53 3rd Qu.:87.70
## Max. :92.90 Max. :93.00 Max. :93.10 Max. :93.30
## NA's :3 NA's :3 NA's :3 NA's :3
## 2088 2089 2090 2091
## Min. :66.80 Min. :66.90 Min. :67.00 Min. :67.10
## 1st Qu.:79.17 1st Qu.:79.28 1st Qu.:79.40 1st Qu.:79.50
## Median :83.90 Median :84.00 Median :84.10 Median :84.20
## Mean :83.39 Mean :83.52 Mean :83.63 Mean :83.76
## 3rd Qu.:87.80 3rd Qu.:87.90 3rd Qu.:88.00 3rd Qu.:88.12
## Max. :93.40 Max. :93.50 Max. :93.60 Max. :93.70
## NA's :3 NA's :3 NA's :3 NA's :3
## 2092 2093 2094 2095
## Min. :67.30 Min. :67.40 Min. :67.50 Min. :67.60
## 1st Qu.:79.70 1st Qu.:79.80 1st Qu.:79.90 1st Qu.:80.08
## Median :84.35 Median :84.45 Median :84.55 Median :84.65
## Mean :83.88 Mean :84.00 Mean :84.12 Mean :84.24
## 3rd Qu.:88.22 3rd Qu.:88.33 3rd Qu.:88.50 3rd Qu.:88.60
## Max. :93.90 Max. :94.00 Max. :94.10 Max. :94.20
## NA's :3 NA's :3 NA's :3 NA's :3
## 2096 2097 2098 2099
## Min. :67.70 Min. :67.80 Min. :67.90 Min. :68.00
## 1st Qu.:80.20 1st Qu.:80.38 1st Qu.:80.47 1st Qu.:80.58
## Median :84.75 Median :84.85 Median :85.00 Median :85.15
## Mean :84.36 Mean :84.48 Mean :84.59 Mean :84.71
## 3rd Qu.:88.70 3rd Qu.:88.80 3rd Qu.:88.90 3rd Qu.:89.00
## Max. :94.30 Max. :94.40 Max. :94.50 Max. :94.70
## NA's :3 NA's :3 NA's :3 NA's :3
## 2100
## Min. :68.10
## 1st Qu.:80.78
## Median :85.25
## Mean :84.83
## 3rd Qu.:89.10
## Max. :94.80
## NA's :3plotting data
plots scatter plot of 2nd column or 1800s column for all countries
plot(LifeExpectancyInYears[,2]) 
Life expectancy of all countries increased after 150 rs after great divergence, and industrialisation
plot(LifeExpectancyInYears[,150]) 
To see life expectancy of one country over years or to compare two countries, as the column names are in list so to plot them as vector you need to unlist them by unlist and then make them vector by using as.vector
also as we want to separate a row so we can’t just use $ sign to extract that thing so for rows you need to do this
plot(as.vector(unlist(LifeExpectancyInYears[162, 2:302])), as.vector(unlist(colnames(LifeExpectancyInYears)[2:302])), xlab = "Life expectancy in Years", ylab = "years" )
lifeexpectancy of all countries relative to 1800 and 1801 it means values are same, not much has changed in 1 year
plot(LifeExpectancyInYears[,2], LifeExpectancyInYears[,3])
in 100 years many countries life expectancy has changed drastically
plot(LifeExpectancyInYears[,2], LifeExpectancyInYears[,101])
subset the life expectancy of a particular country
LifeExpectancyInYears[LifeExpectancyInYears$country==“Country name”,]
so now we’ll compare lifeexpectancy between Sweden and India, for this at first we’ll unlist it convert it into numeric value by as.numeric and also omit (NA- not available) values by na.omit
as.vector(na.omit(as.numeric(unlist(LifeExpectancyInYears[LifeExpectancyInYears$country=="Sweden",]))))-> swedenlife## Warning in
## na.omit(as.numeric(unlist(LifeExpectancyInYears[LifeExpectancyInYears$country
## == : NAs introduced by coercionas.vector(na.omit(as.numeric(unlist(LifeExpectancyInYears[LifeExpectancyInYears$country=="India",]))))-> indialife## Warning in
## na.omit(as.numeric(unlist(LifeExpectancyInYears[LifeExpectancyInYears$country
## == : NAs introduced by coercionas.vector(na.omit(as.numeric(unlist(LifeExpectancyInYears[LifeExpectancyInYears$country=="Bangladesh",]))))-> banglalife## Warning in
## na.omit(as.numeric(unlist(LifeExpectancyInYears[LifeExpectancyInYears$country
## == : NAs introduced by coercionas.vector(na.omit(as.numeric(unlist(LifeExpectancyInYears[LifeExpectancyInYears$country=="Switzeland",]))))-> Switzerlandlife
as.vector(na.omit(as.numeric(unlist(LifeExpectancyInYears[LifeExpectancyInYears$country=="Spain",]))))-> Spainlife## Warning in
## na.omit(as.numeric(unlist(LifeExpectancyInYears[LifeExpectancyInYears$country
## == : NAs introduced by coercionas.vector(na.omit(as.numeric(unlist(LifeExpectancyInYears[LifeExpectancyInYears$country=="Norway",]))))-> Norwaylife## Warning in
## na.omit(as.numeric(unlist(LifeExpectancyInYears[LifeExpectancyInYears$country
## == : NAs introduced by coercionas.vector(na.omit(as.numeric(unlist(LifeExpectancyInYears[LifeExpectancyInYears$country=="Finland",]))))-> Finlandlife## Warning in
## na.omit(as.numeric(unlist(LifeExpectancyInYears[LifeExpectancyInYears$country
## == : NAs introduced by coercionas.vector(na.omit(as.numeric(unlist(LifeExpectancyInYears[LifeExpectancyInYears$country=="United States",]))))-> USlife## Warning in
## na.omit(as.numeric(unlist(LifeExpectancyInYears[LifeExpectancyInYears$country
## == : NAs introduced by coercionPar function is usefull in compairing two values as here Sweden and India, to plot histograms side by side, help you set your display how you want to show multiple graphs,mfrow tells how many subplots you want to plot (1, 2) means we wanted to plot 1 row and 2 columns
par(mfrow=c(1,2))
hist(swedenlife) #a histogram shows frequency
hist(indialife)
plot(c(1800:2100), swedenlife, col="red", main = "Life Expectancy in Years", pch=15, ylim = c(0,100), xlab = "Years", ylab = "Life Expectancy") #pch is just a pint type
points(c(1800:2100),indialife, col="blue")
points(c(1800:2100),banglalife,pch=20, col="green")
legend(x= "topleft", #position
legend = c("sweden", "India", "Bangladesh"), #Texts
fill = c("red", "blue", "green")) #colours