Project 1: University Rankings
Michael Hahsler
Tue Oct 4 15:49:31 2016
Here I only look at the Times Higher Education World University Ranking.
Load data
times <- read.csv("timesData.csv")
head(times)## world_rank university_name
## 1 1 Harvard University
## 2 2 California Institute of Technology
## 3 3 Massachusetts Institute of Technology
## 4 4 Stanford University
## 5 5 Princeton University
## 6 6 University of Cambridge
## country teaching international research citations
## 1 United States of America 99.7 72.4 98.7 98.8
## 2 United States of America 97.7 54.6 98.0 99.9
## 3 United States of America 97.8 82.3 91.4 99.9
## 4 United States of America 98.3 29.5 98.1 99.2
## 5 United States of America 90.9 70.3 95.4 99.9
## 6 United Kingdom 90.5 77.7 94.1 94.0
## income total_score num_students student_staff_ratio
## 1 34.5 96.1 20,152 8.9
## 2 83.7 96.0 2,243 6.9
## 3 87.5 95.6 11,074 9.0
## 4 64.3 94.3 15,596 7.8
## 5 - 94.2 7,929 8.4
## 6 57.0 91.2 18,812 11.8
## international_students female_male_ratio year
## 1 25% 2011
## 2 27% 33 : 67 2011
## 3 33% 37 : 63 2011
## 4 22% 42 : 58 2011
## 5 27% 45 : 55 2011
## 6 34% 46 : 54 2011summary(times)## world_rank university_name
## 301-350: 248 Aarhus University : 6
## 601-800: 200 Arizona State University : 6
## 351-400: 198 Australian National University: 6
## 276-300: 104 Bielefeld University : 6
## 201-225: 103 Bilkent University : 6
## 226-250: 100 Birkbeck, University of London: 6
## (Other):1650 (Other) :2567
## country teaching international
## United States of America: 659 Min. : 9.9 20.7 : 10
## United Kingdom : 300 1st Qu.:24.7 29.6 : 10
## Germany : 152 Median :33.9 - : 9
## Australia : 117 Mean :37.8 34.3 : 9
## Canada : 108 3rd Qu.:46.4 46.8 : 9
## Japan : 98 Max. :99.7 48.4 : 9
## (Other) :1169 (Other):2547
## research citations income total_score
## Min. : 2.90 Min. : 1.20 - : 218 - :1402
## 1st Qu.:19.60 1st Qu.: 45.50 100.0 : 68 49.0 : 13
## Median :30.50 Median : 62.50 28.0 : 26 51.1 : 12
## Mean :35.91 Mean : 60.92 31.1 : 20 46.6 : 11
## 3rd Qu.:47.25 3rd Qu.: 79.05 28.8 : 19 46.9 : 10
## Max. :99.40 Max. :100.00 28.5 : 18 50.1 : 10
## (Other):2234 (Other):1145
## num_students student_staff_ratio international_students
## : 59 Min. : 0.60 7% : 142
## 10,221 : 6 1st Qu.: 11.97 10% : 133
## 10,410 : 6 Median : 16.10 9% : 130
## 10,441 : 6 Mean : 18.45 5% : 120
## 10,901 : 6 3rd Qu.: 21.50 8% : 119
## 10,930 : 6 Max. :162.60 12% : 104
## (Other):2514 NA's :59 (Other):1855
## female_male_ratio year
## : 233 Min. :2011
## 54 : 46: 185 1st Qu.:2013
## 52 : 48: 151 Median :2014
## 53 : 47: 138 Mean :2014
## 55 : 45: 135 3rd Qu.:2016
## 56 : 44: 132 Max. :2016
## (Other):1629This needs some cleaning!
Many numeric columns are read in as factors because they contain some non-numeric characters (-, %, ‘missing’, etc.)
Ranking variable
rnk <- as.character(times$world_rank)
unique(rnk)## [1] "1" "2" "3" "4" "5" "6" "8"
## [8] "9" "10" "11" "12" "13" "14" "15"
## [15] "17" "18" "19" "20" "21" "22" "23"
## [22] "24" "25" "26" "27" "28" "29" "30"
## [29] "32" "33" "34" "35" "36" "37" "38"
## [36] "39" "40" "41" "42" "43" "47" "48"
## [43] "49" "51" "52" "53" "54" "55" "56"
## [50] "57" "58" "59" "60" "61" "63" "64"
## [57] "65" "66" "67" "68" "71" "72" "73"
## [64] "75" "76" "77" "78" "79" "81" "83"
## [71] "85" "86" "87" "88" "89" "90" "93"
## [78] "94" "95" "98" "99" "100" "101" "102"
## [85] "103" "104" "105" "106" "107" "109" "111"
## [92] "112" "114" "115" "117" "118" "119" "120"
## [99] "122" "124" "127" "128" "129" "130" "132"
## [106] "135" "136" "137" "138" "139" "140" "142"
## [113] "143" "144" "145" "147" "149" "151" "152"
## [120] "155" "156" "158" "159" "161" "163" "164"
## [127] "165" "167" "168" "170" "171" "172" "173"
## [134] "174" "177" "178" "181" "182" "183" "184"
## [141] "185" "186" "187" "189" "190" "193" "195"
## [148] "196" "197" "199" "7" "16" "31" "44"
## [155] "45" "46" "62" "69" "70" "74" "80"
## [162] "84" "91" "92" "96" "97" "108" "110"
## [169] "113" "116" "121" "123" "125" "131" "133"
## [176] "134" "141" "146" "148" "150" "154" "157"
## [183] "162" "166" "169" "176" "180" "191" "192"
## [190] "194" "200" "201-225" "226-250" "251-275" "276-300" "301-350"
## [197] "350-400" "50" "82" "153" "198" "351-400" "126"
## [204] "160" "188" "175" "=39" "=44" "=47" "=56"
## [211] "=60" "=65" "=76" "=82" "=88" "=90" "=94"
## [218] "=99" "=101" "=104" "=106" "=110" "=113" "=120"
## [225] "=123" "=125" "=127" "=131" "=133" "=138" "=144"
## [232] "=149" "=158" "=161" "=164" "=167" "=172" "=176"
## [239] "179" "=180" "=182" "=185" "=190" "=193" "=196"
## [246] "201-250" "251-300" "401-500" "501-600" "601-800"cbind(rnk, as.numeric(rnk))## Warning in cbind(rnk, as.numeric(rnk)): NAs introduced by coercion## rnk
## [1,] "1" "1"
## [2,] "2" "2"
## [3,] "3" "3"
## [4,] "4" "4"
## [5,] "5" "5"
## [6,] "6" "6"
## [7,] "6" "6"
## [8,] "8" "8"
## [9,] "9" "9"
## [10,] "10" "10"
## [11,] "11" "11"
## [12,] "12" "12"
## [13,] "13" "13"
## [14,] "14" "14"
## [15,] "15" "15"
## [16,] "15" "15"
## [17,] "17" "17"
## [18,] "18" "18"
## [19,] "19" "19"
## [20,] "20" "20"
## [21,] "21" "21"
## [22,] "22" "22"
## [23,] "23" "23"
## [24,] "24" "24"
## [25,] "25" "25"
## [26,] "26" "26"
## [27,] "27" "27"
## [28,] "28" "28"
## [29,] "29" "29"
## [30,] "30" "30"
## [31,] "30" "30"
## [32,] "32" "32"
## [33,] "33" "33"
## [34,] "34" "34"
## [35,] "35" "35"
## [36,] "36" "36"
## [37,] "37" "37"
## [38,] "38" "38"
## [39,] "39" "39"
## [40,] "40" "40"
## [41,] "41" "41"
## [42,] "42" "42"
## [43,] "43" "43"
## [44,] "43" "43"
## [45,] "43" "43"
## [46,] "43" "43"
## [47,] "47" "47"
## [48,] "48" "48"
## [49,] "49" "49"
## [50,] "49" "49"
## [51,] "51" "51"
## [52,] "52" "52"
## [53,] "53" "53"
## [54,] "54" "54"
## [55,] "55" "55"
## [56,] "56" "56"
## [57,] "57" "57"
## [58,] "58" "58"
## [59,] "59" "59"
## [60,] "60" "60"
## [61,] "61" "61"
## [62,] "61" "61"
## [63,] "63" "63"
## [64,] "64" "64"
## [65,] "65" "65"
## [66,] "66" "66"
## [67,] "67" "67"
## [68,] "68" "68"
## [69,] "68" "68"
## [70,] "68" "68"
## [71,] "71" "71"
## [72,] "72" "72"
## [73,] "73" "73"
## [74,] "73" "73"
## [75,] "75" "75"
## [76,] "76" "76"
## [77,] "77" "77"
## [78,] "78" "78"
## [79,] "79" "79"
## [80,] "79" "79"
## [81,] "81" "81"
## [82,] "81" "81"
## [83,] "83" "83"
## [84,] "83" "83"
## [85,] "85" "85"
## [86,] "86" "86"
## [87,] "87" "87"
## [88,] "88" "88"
## [89,] "89" "89"
## [90,] "90" "90"
## [91,] "90" "90"
## [92,] "90" "90"
## [93,] "93" "93"
## [94,] "94" "94"
## [95,] "95" "95"
## [96,] "95" "95"
## [97,] "95" "95"
## [98,] "98" "98"
## [99,] "99" "99"
## [100,] "100" "100"
## [101,] "101" "101"
## [102,] "102" "102"
## [103,] "103" "103"
## [104,] "104" "104"
## [105,] "105" "105"
## [106,] "106" "106"
## [107,] "107" "107"
## [108,] "107" "107"
## [109,] "109" "109"
## [110,] "109" "109"
## [111,] "111" "111"
## [112,] "112" "112"
## [113,] "112" "112"
## [114,] "114" "114"
## [115,] "115" "115"
## [116,] "115" "115"
## [117,] "117" "117"
## [118,] "118" "118"
## [119,] "119" "119"
## [120,] "120" "120"
## [121,] "120" "120"
## [122,] "122" "122"
## [123,] "122" "122"
## [124,] "124" "124"
## [125,] "124" "124"
## [126,] "124" "124"
## [127,] "127" "127"
## [128,] "128" "128"
## [129,] "129" "129"
## [130,] "130" "130"
## [131,] "130" "130"
## [132,] "132" "132"
## [133,] "132" "132"
## [134,] "132" "132"
## [135,] "135" "135"
## [136,] "136" "136"
## [137,] "137" "137"
## [138,] "138" "138"
## [139,] "139" "139"
## [140,] "140" "140"
## [141,] "140" "140"
## [142,] "142" "142"
## [143,] "143" "143"
## [144,] "144" "144"
## [145,] "145" "145"
## [146,] "145" "145"
## [147,] "147" "147"
## [148,] "147" "147"
## [149,] "149" "149"
## [150,] "149" "149"
## [151,] "151" "151"
## [152,] "152" "152"
## [153,] "152" "152"
## [154,] "152" "152"
## [155,] "155" "155"
## [156,] "156" "156"
## [157,] "156" "156"
## [158,] "158" "158"
## [159,] "159" "159"
## [160,] "159" "159"
## [161,] "161" "161"
## [162,] "161" "161"
## [163,] "163" "163"
## [164,] "164" "164"
## [165,] "165" "165"
## [166,] "165" "165"
## [167,] "167" "167"
## [168,] "168" "168"
## [169,] "168" "168"
## [170,] "170" "170"
## [171,] "171" "171"
## [172,] "172" "172"
## [173,] "173" "173"
## [174,] "174" "174"
## [175,] "174" "174"
## [176,] "174" "174"
## [177,] "177" "177"
## [178,] "178" "178"
## [179,] "178" "178"
## [180,] "178" "178"
## [181,] "181" "181"
## [182,] "182" "182"
## [183,] "183" "183"
## [184,] "184" "184"
## [185,] "185" "185"
## [186,] "186" "186"
## [187,] "187" "187"
## [188,] "187" "187"
## [189,] "189" "189"
## [190,] "190" "190"
## [191,] "190" "190"
## [192,] "190" "190"
## [193,] "193" "193"
## [194,] "193" "193"
## [195,] "195" "195"
## [196,] "196" "196"
## [197,] "197" "197"
## [198,] "197" "197"
## [199,] "199" "199"
## [200,] "199" "199"
## [201,] "1" "1"
## [202,] "2" "2"
## [203,] "2" "2"
## [204,] "4" "4"
## [205,] "5" "5"
## [206,] "6" "6"
## [207,] "7" "7"
## [208,] "8" "8"
## [209,] "9" "9"
## [210,] "10" "10"
## [211,] "11" "11"
## [212,] "12" "12"
## [213,] "13" "13"
## [214,] "14" "14"
## [215,] "15" "15"
## [216,] "16" "16"
## [217,] "17" "17"
## [218,] "18" "18"
## [219,] "19" "19"
## [220,] "20" "20"
## [221,] "21" "21"
## [222,] "22" "22"
## [223,] "22" "22"
## [224,] "24" "24"
## [225,] "25" "25"
## [226,] "26" "26"
## [227,] "27" "27"
## [228,] "28" "28"
## [229,] "29" "29"
## [230,] "30" "30"
## [231,] "31" "31"
## [232,] "32" "32"
## [233,] "33" "33"
## [234,] "34" "34"
## [235,] "35" "35"
## [236,] "36" "36"
## [237,] "37" "37"
## [238,] "38" "38"
## [239,] "38" "38"
## [240,] "40" "40"
## [241,] "41" "41"
## [242,] "42" "42"
## [243,] "43" "43"
## [244,] "44" "44"
## [245,] "45" "45"
## [246,] "46" "46"
## [247,] "47" "47"
## [248,] "48" "48"
## [249,] "49" "49"
## [250,] "49" "49"
## [251,] "51" "51"
## [252,] "52" "52"
## [253,] "53" "53"
## [254,] "54" "54"
## [255,] "55" "55"
## [256,] "56" "56"
## [257,] "57" "57"
## [258,] "58" "58"
## [259,] "59" "59"
## [260,] "59" "59"
## [261,] "61" "61"
## [262,] "62" "62"
## [263,] "63" "63"
## [264,] "64" "64"
## [265,] "65" "65"
## [266,] "66" "66"
## [267,] "67" "67"
## [268,] "68" "68"
## [269,] "69" "69"
## [270,] "70" "70"
## [271,] "71" "71"
## [272,] "72" "72"
## [273,] "73" "73"
## [274,] "74" "74"
## [275,] "75" "75"
## [276,] "75" "75"
## [277,] "77" "77"
## [278,] "77" "77"
## [279,] "79" "79"
## [280,] "80" "80"
## [281,] "81" "81"
## [282,] "81" "81"
## [283,] "83" "83"
## [284,] "84" "84"
## [285,] "85" "85"
## [286,] "86" "86"
## [287,] "87" "87"
## [288,] "88" "88"
## [289,] "89" "89"
## [290,] "90" "90"
## [291,] "91" "91"
## [292,] "92" "92"
## [293,] "93" "93"
## [294,] "94" "94"
## [295,] "94" "94"
## [296,] "96" "96"
## [297,] "97" "97"
## [298,] "98" "98"
## [299,] "99" "99"
## [300,] "100" "100"
## [301,] "101" "101"
## [302,] "102" "102"
## [303,] "103" "103"
## [304,] "104" "104"
## [305,] "104" "104"
## [306,] "106" "106"
## [307,] "107" "107"
## [308,] "108" "108"
## [309,] "109" "109"
## [310,] "110" "110"
## [311,] "111" "111"
## [312,] "112" "112"
## [313,] "113" "113"
## [314,] "114" "114"
## [315,] "115" "115"
## [316,] "116" "116"
## [317,] "117" "117"
## [318,] "117" "117"
## [319,] "119" "119"
## [320,] "120" "120"
## [321,] "121" "121"
## [322,] "121" "121"
## [323,] "123" "123"
## [324,] "124" "124"
## [325,] "125" "125"
## [326,] "125" "125"
## [327,] "127" "127"
## [328,] "127" "127"
## [329,] "127" "127"
## [330,] "130" "130"
## [331,] "131" "131"
## [332,] "131" "131"
## [333,] "133" "133"
## [334,] "134" "134"
## [335,] "135" "135"
## [336,] "135" "135"
## [337,] "135" "135"
## [338,] "138" "138"
## [339,] "139" "139"
## [340,] "140" "140"
## [341,] "141" "141"
## [342,] "141" "141"
## [343,] "143" "143"
## [344,] "144" "144"
## [345,] "145" "145"
## [346,] "146" "146"
## [347,] "146" "146"
## [348,] "148" "148"
## [349,] "149" "149"
## [350,] "150" "150"
## [351,] "151" "151"
## [352,] "151" "151"
## [353,] "151" "151"
## [354,] "154" "154"
## [355,] "154" "154"
## [356,] "156" "156"
## [357,] "157" "157"
## [358,] "157" "157"
## [359,] "159" "159"
## [360,] "159" "159"
## [361,] "159" "159"
## [362,] "162" "162"
## [363,] "162" "162"
## [364,] "164" "164"
## [365,] "164" "164"
## [366,] "166" "166"
## [367,] "167" "167"
## [368,] "168" "168"
## [369,] "169" "169"
## [370,] "169" "169"
## [371,] "169" "169"
## [372,] "172" "172"
## [373,] "173" "173"
## [374,] "173" "173"
## [375,] "173" "173"
## [376,] "176" "176"
## [377,] "177" "177"
## [378,] "178" "178"
## [379,] "178" "178"
## [380,] "180" "180"
## [381,] "181" "181"
## [382,] "181" "181"
## [383,] "181" "181"
## [384,] "184" "184"
## [385,] "185" "185"
## [386,] "186" "186"
## [387,] "187" "187"
## [388,] "187" "187"
## [389,] "189" "189"
## [390,] "189" "189"
## [391,] "191" "191"
## [392,] "192" "192"
## [393,] "193" "193"
## [394,] "194" "194"
## [395,] "195" "195"
## [396,] "196" "196"
## [397,] "197" "197"
## [398,] "197" "197"
## [399,] "197" "197"
## [400,] "200" "200"
## [401,] "201-225" NA
## [402,] "201-225" NA
## [403,] "201-225" NA
## [404,] "201-225" NA
## [405,] "201-225" NA
## [406,] "201-225" NA
## [407,] "201-225" NA
## [408,] "201-225" NA
## [409,] "201-225" NA
## [410,] "201-225" NA
## [411,] "201-225" NA
## [412,] "201-225" NA
## [413,] "201-225" NA
## [414,] "201-225" NA
## [415,] "201-225" NA
## [416,] "201-225" NA
## [417,] "201-225" NA
## [418,] "201-225" NA
## [419,] "201-225" NA
## [420,] "201-225" NA
## [421,] "201-225" NA
## [422,] "201-225" NA
## [423,] "201-225" NA
## [424,] "201-225" NA
## [425,] "201-225" NA
## [426,] "201-225" NA
## [427,] "201-225" NA
## [428,] "226-250" NA
## [429,] "226-250" NA
## [430,] "226-250" NA
## [431,] "226-250" NA
## [432,] "226-250" NA
## [433,] "226-250" NA
## [434,] "226-250" NA
## [435,] "226-250" NA
## [436,] "226-250" NA
## [437,] "226-250" NA
## [438,] "226-250" NA
## [439,] "226-250" NA
## [440,] "226-250" NA
## [441,] "226-250" NA
## [442,] "226-250" NA
## [443,] "226-250" NA
## [444,] "226-250" NA
## [445,] "226-250" NA
## [446,] "226-250" NA
## [447,] "226-250" NA
## [448,] "226-250" NA
## [449,] "226-250" NA
## [450,] "226-250" NA
## [451,] "251-275" NA
## [452,] "251-275" NA
## [453,] "251-275" NA
## [454,] "251-275" NA
## [455,] "251-275" NA
## [456,] "251-275" NA
## [457,] "251-275" NA
## [458,] "251-275" NA
## [459,] "251-275" NA
## [460,] "251-275" NA
## [461,] "251-275" NA
## [462,] "251-275" NA
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## [1074,] "72" "72"
## [1075,] "73" "73"
## [1076,] "74" "74"
## [1077,] "74" "74"
## [1078,] "76" "76"
## [1079,] "77" "77"
## [1080,] "78" "78"
## [1081,] "79" "79"
## [1082,] "80" "80"
## [1083,] "80" "80"
## [1084,] "80" "80"
## [1085,] "83" "83"
## [1086,] "83" "83"
## [1087,] "85" "85"
## [1088,] "86" "86"
## [1089,] "87" "87"
## [1090,] "88" "88"
## [1091,] "88" "88"
## [1092,] "90" "90"
## [1093,] "91" "91"
## [1094,] "92" "92"
## [1095,] "93" "93"
## [1096,] "94" "94"
## [1097,] "95" "95"
## [1098,] "96" "96"
## [1099,] "97" "97"
## [1100,] "98" "98"
## [1101,] "98" "98"
## [1102,] "100" "100"
## [1103,] "100" "100"
## [1104,] "102" "102"
## [1105,] "103" "103"
## [1106,] "103" "103"
## [1107,] "103" "103"
## [1108,] "106" "106"
## [1109,] "106" "106"
## [1110,] "108" "108"
## [1111,] "109" "109"
## [1112,] "109" "109"
## [1113,] "111" "111"
## [1114,] "112" "112"
## [1115,] "112" "112"
## [1116,] "114" "114"
## [1117,] "114" "114"
## [1118,] "114" "114"
## [1119,] "117" "117"
## [1120,] "117" "117"
## [1121,] "117" "117"
## [1122,] "117" "117"
## [1123,] "121" "121"
## [1124,] "121" "121"
## [1125,] "123" "123"
## [1126,] "124" "124"
## [1127,] "125" "125"
## [1128,] "126" "126"
## [1129,] "126" "126"
## [1130,] "128" "128"
## [1131,] "129" "129"
## [1132,] "129" "129"
## [1133,] "131" "131"
## [1134,] "132" "132"
## [1135,] "132" "132"
## [1136,] "132" "132"
## [1137,] "135" "135"
## [1138,] "136" "136"
## [1139,] "137" "137"
## [1140,] "138" "138"
## [1141,] "139" "139"
## [1142,] "139" "139"
## [1143,] "141" "141"
## [1144,] "142" "142"
## [1145,] "143" "143"
## [1146,] "144" "144"
## [1147,] "144" "144"
## [1148,] "146" "146"
## [1149,] "146" "146"
## [1150,] "148" "148"
## [1151,] "148" "148"
## [1152,] "150" "150"
## [1153,] "150" "150"
## [1154,] "152" "152"
## [1155,] "153" "153"
## [1156,] "154" "154"
## [1157,] "155" "155"
## [1158,] "156" "156"
## [1159,] "157" "157"
## [1160,] "157" "157"
## [1161,] "159" "159"
## [1162,] "160" "160"
## [1163,] "161" "161"
## [1164,] "161" "161"
## [1165,] "161" "161"
## [1166,] "164" "164"
## [1167,] "164" "164"
## [1168,] "164" "164"
## [1169,] "164" "164"
## [1170,] "168" "168"
## [1171,] "169" "169"
## [1172,] "170" "170"
## [1173,] "170" "170"
## [1174,] "172" "172"
## [1175,] "172" "172"
## [1176,] "174" "174"
## [1177,] "174" "174"
## [1178,] "176" "176"
## [1179,] "176" "176"
## [1180,] "178" "178"
## [1181,] "178" "178"
## [1182,] "180" "180"
## [1183,] "181" "181"
## [1184,] "181" "181"
## [1185,] "183" "183"
## [1186,] "184" "184"
## [1187,] "185" "185"
## [1188,] "185" "185"
## [1189,] "185" "185"
## [1190,] "188" "188"
## [1191,] "188" "188"
## [1192,] "190" "190"
## [1193,] "191" "191"
## [1194,] "191" "191"
## [1195,] "193" "193"
## [1196,] "194" "194"
## [1197,] "194" "194"
## [1198,] "196" "196"
## [1199,] "197" "197"
## [1200,] "198" "198"
## [1201,] "199" "199"
## [1202,] "199" "199"
## [1203,] "201-225" NA
## [1204,] "201-225" NA
## [1205,] "201-225" NA
## [1206,] "201-225" NA
## [1207,] "201-225" NA
## [1208,] "201-225" NA
## [1209,] "201-225" NA
## [1210,] "201-225" NA
## [1211,] "201-225" NA
## [1212,] "201-225" NA
## [1213,] "201-225" NA
## [1214,] "201-225" NA
## [1215,] "201-225" NA
## [1216,] "201-225" NA
## [1217,] "201-225" NA
## [1218,] "201-225" NA
## [1219,] "201-225" NA
## [1220,] "201-225" NA
## [1221,] "201-225" NA
## [1222,] "201-225" NA
## [1223,] "201-225" NA
## [1224,] "201-225" NA
## [1225,] "201-225" NA
## [1226,] "201-225" NA
## [1227,] "201-225" NA
## [1228,] "201-225" NA
## [1229,] "226-250" NA
## [1230,] "226-250" NA
## [1231,] "226-250" NA
## [1232,] "226-250" NA
## [1233,] "226-250" NA
## [1234,] "226-250" NA
## [1235,] "226-250" NA
## [1236,] "226-250" NA
## [1237,] "226-250" NA
## [1238,] "226-250" NA
## [1239,] "226-250" NA
## [1240,] "226-250" NA
## [1241,] "226-250" NA
## [1242,] "226-250" NA
## [1243,] "226-250" NA
## [1244,] "226-250" NA
## [1245,] "226-250" NA
## [1246,] "226-250" NA
## [1247,] "226-250" NA
## [1248,] "226-250" NA
## [1249,] "226-250" NA
## [1250,] "226-250" NA
## [1251,] "226-250" NA
## [1252,] "226-250" NA
## [1253,] "226-250" NA
## [1254,] "226-250" NA
## [1255,] "226-250" NA
## [1256,] "251-275" NA
## [1257,] "251-275" NA
## [1258,] "251-275" NA
## [1259,] "251-275" NA
## [1260,] "251-275" NA
## [1261,] "251-275" NA
## [1262,] "251-275" NA
## [1263,] "251-275" NA
## [1264,] "251-275" NA
## [1265,] "251-275" NA
## [1266,] "251-275" NA
## [1267,] "251-275" NA
## [1268,] "251-275" NA
## [1269,] "251-275" NA
## [1270,] "251-275" NA
## [1271,] "251-275" NA
## [1272,] "251-275" NA
## [1273,] "251-275" NA
## [1274,] "251-275" NA
## [1275,] "251-275" NA
## [1276,] "251-275" NA
## [1277,] "251-275" NA
## [1278,] "276-300" NA
## [1279,] "276-300" NA
## [1280,] "276-300" NA
## [1281,] "276-300" NA
## [1282,] "276-300" NA
## [1283,] "276-300" NA
## [1284,] "276-300" NA
## [1285,] "276-300" NA
## [1286,] "276-300" NA
## [1287,] "276-300" NA
## [1288,] "276-300" NA
## [1289,] "276-300" NA
## [1290,] "276-300" NA
## [1291,] "276-300" NA
## [1292,] "276-300" NA
## [1293,] "276-300" NA
## [1294,] "276-300" NA
## [1295,] "276-300" NA
## [1296,] "276-300" NA
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## [1298,] "276-300" NA
## [1299,] "276-300" NA
## [1300,] "276-300" NA
## [1301,] "276-300" NA
## [1302,] "276-300" NA
## [1303,] "301-350" NA
## [1304,] "301-350" NA
## [1305,] "301-350" NA
## [1306,] "301-350" NA
## [1307,] "301-350" NA
## [1308,] "301-350" NA
## [1309,] "301-350" NA
## [1310,] "301-350" NA
## [1311,] "301-350" NA
## [1312,] "301-350" NA
## [1313,] "301-350" NA
## [1314,] "301-350" NA
## [1315,] "301-350" NA
## [1316,] "301-350" NA
## [1317,] "301-350" NA
## [1318,] "301-350" NA
## [1319,] "301-350" NA
## [1320,] "301-350" NA
## [1321,] "301-350" NA
## [1322,] "301-350" NA
## [1323,] "301-350" NA
## [1324,] "301-350" NA
## [1325,] "301-350" NA
## [1326,] "301-350" NA
## [1327,] "301-350" NA
## [1328,] "301-350" NA
## [1329,] "301-350" NA
## [1330,] "301-350" NA
## [1331,] "301-350" NA
## [1332,] "301-350" NA
## [1333,] "301-350" NA
## [1334,] "301-350" NA
## [1335,] "301-350" NA
## [1336,] "301-350" NA
## [1337,] "301-350" NA
## [1338,] "301-350" NA
## [1339,] "301-350" NA
## [1340,] "301-350" NA
## [1341,] "301-350" NA
## [1342,] "301-350" NA
## [1343,] "301-350" NA
## [1344,] "301-350" NA
## [1345,] "301-350" NA
## [1346,] "301-350" NA
## [1347,] "301-350" NA
## [1348,] "301-350" NA
## [1349,] "301-350" NA
## [1350,] "301-350" NA
## [1351,] "301-350" NA
## [1352,] "301-350" NA
## [1353,] "301-350" NA
## [1354,] "301-350" NA
## [1355,] "301-350" NA
## [1356,] "351-400" NA
## [1357,] "351-400" NA
## [1358,] "351-400" NA
## [1359,] "351-400" NA
## [1360,] "351-400" NA
## [1361,] "351-400" NA
## [1362,] "351-400" NA
## [1363,] "351-400" NA
## [1364,] "351-400" NA
## [1365,] "351-400" NA
## [1366,] "351-400" NA
## [1367,] "351-400" NA
## [1368,] "351-400" NA
## [1369,] "351-400" NA
## [1370,] "351-400" NA
## [1371,] "351-400" NA
## [1372,] "351-400" NA
## [1373,] "351-400" NA
## [1374,] "351-400" NA
## [1375,] "351-400" NA
## [1376,] "351-400" NA
## [1377,] "351-400" NA
## [1378,] "351-400" NA
## [1379,] "351-400" NA
## [1380,] "351-400" NA
## [1381,] "351-400" NA
## [1382,] "351-400" NA
## [1383,] "351-400" NA
## [1384,] "351-400" NA
## [1385,] "351-400" NA
## [1386,] "351-400" NA
## [1387,] "351-400" NA
## [1388,] "351-400" NA
## [1389,] "351-400" NA
## [1390,] "351-400" NA
## [1391,] "351-400" NA
## [1392,] "351-400" NA
## [1393,] "351-400" NA
## [1394,] "351-400" NA
## [1395,] "351-400" NA
## [1396,] "351-400" NA
## [1397,] "351-400" NA
## [1398,] "351-400" NA
## [1399,] "351-400" NA
## [1400,] "351-400" NA
## [1401,] "351-400" NA
## [1402,] "351-400" NA
## [1403,] "1" "1"
## [1404,] "2" "2"
## [1405,] "3" "3"
## [1406,] "4" "4"
## [1407,] "5" "5"
## [1408,] "6" "6"
## [1409,] "7" "7"
## [1410,] "8" "8"
## [1411,] "9" "9"
## [1412,] "9" "9"
## [1413,] "11" "11"
## [1414,] "12" "12"
## [1415,] "13" "13"
## [1416,] "14" "14"
## [1417,] "15" "15"
## [1418,] "16" "16"
## [1419,] "17" "17"
## [1420,] "18" "18"
## [1421,] "19" "19"
## [1422,] "20" "20"
## [1423,] "21" "21"
## [1424,] "22" "22"
## [1425,] "23" "23"
## [1426,] "24" "24"
## [1427,] "25" "25"
## [1428,] "26" "26"
## [1429,] "27" "27"
## [1430,] "28" "28"
## [1431,] "29" "29"
## [1432,] "29" "29"
## [1433,] "29" "29"
## [1434,] "32" "32"
## [1435,] "33" "33"
## [1436,] "34" "34"
## [1437,] "34" "34"
## [1438,] "36" "36"
## [1439,] "37" "37"
## [1440,] "38" "38"
## [1441,] "39" "39"
## [1442,] "40" "40"
## [1443,] "41" "41"
## [1444,] "42" "42"
## [1445,] "43" "43"
## [1446,] "44" "44"
## [1447,] "45" "45"
## [1448,] "46" "46"
## [1449,] "46" "46"
## [1450,] "48" "48"
## [1451,] "49" "49"
## [1452,] "50" "50"
## [1453,] "51" "51"
## [1454,] "52" "52"
## [1455,] "52" "52"
## [1456,] "54" "54"
## [1457,] "55" "55"
## [1458,] "55" "55"
## [1459,] "57" "57"
## [1460,] "58" "58"
## [1461,] "59" "59"
## [1462,] "60" "60"
## [1463,] "61" "61"
## [1464,] "61" "61"
## [1465,] "63" "63"
## [1466,] "64" "64"
## [1467,] "65" "65"
## [1468,] "66" "66"
## [1469,] "67" "67"
## [1470,] "68" "68"
## [1471,] "69" "69"
## [1472,] "70" "70"
## [1473,] "71" "71"
## [1474,] "72" "72"
## [1475,] "73" "73"
## [1476,] "74" "74"
## [1477,] "75" "75"
## [1478,] "75" "75"
## [1479,] "77" "77"
## [1480,] "78" "78"
## [1481,] "79" "79"
## [1482,] "80" "80"
## [1483,] "81" "81"
## [1484,] "82" "82"
## [1485,] "83" "83"
## [1486,] "83" "83"
## [1487,] "85" "85"
## [1488,] "86" "86"
## [1489,] "86" "86"
## [1490,] "88" "88"
## [1491,] "88" "88"
## [1492,] "90" "90"
## [1493,] "91" "91"
## [1494,] "91" "91"
## [1495,] "93" "93"
## [1496,] "94" "94"
## [1497,] "94" "94"
## [1498,] "96" "96"
## [1499,] "97" "97"
## [1500,] "98" "98"
## [1501,] "98" "98"
## [1502,] "98" "98"
## [1503,] "101" "101"
## [1504,] "102" "102"
## [1505,] "103" "103"
## [1506,] "103" "103"
## [1507,] "103" "103"
## [1508,] "103" "103"
## [1509,] "107" "107"
## [1510,] "107" "107"
## [1511,] "109" "109"
## [1512,] "109" "109"
## [1513,] "111" "111"
## [1514,] "111" "111"
## [1515,] "113" "113"
## [1516,] "113" "113"
## [1517,] "113" "113"
## [1518,] "116" "116"
## [1519,] "117" "117"
## [1520,] "118" "118"
## [1521,] "119" "119"
## [1522,] "120" "120"
## [1523,] "121" "121"
## [1524,] "121" "121"
## [1525,] "121" "121"
## [1526,] "124" "124"
## [1527,] "124" "124"
## [1528,] "126" "126"
## [1529,] "126" "126"
## [1530,] "126" "126"
## [1531,] "129" "129"
## [1532,] "130" "130"
## [1533,] "131" "131"
## [1534,] "132" "132"
## [1535,] "132" "132"
## [1536,] "132" "132"
## [1537,] "135" "135"
## [1538,] "136" "136"
## [1539,] "136" "136"
## [1540,] "138" "138"
## [1541,] "139" "139"
## [1542,] "140" "140"
## [1543,] "141" "141"
## [1544,] "141" "141"
## [1545,] "141" "141"
## [1546,] "144" "144"
## [1547,] "144" "144"
## [1548,] "146" "146"
## [1549,] "147" "147"
## [1550,] "148" "148"
## [1551,] "148" "148"
## [1552,] "150" "150"
## [1553,] "150" "150"
## [1554,] "152" "152"
## [1555,] "153" "153"
## [1556,] "154" "154"
## [1557,] "155" "155"
## [1558,] "156" "156"
## [1559,] "157" "157"
## [1560,] "157" "157"
## [1561,] "157" "157"
## [1562,] "160" "160"
## [1563,] "160" "160"
## [1564,] "162" "162"
## [1565,] "163" "163"
## [1566,] "164" "164"
## [1567,] "165" "165"
## [1568,] "165" "165"
## [1569,] "165" "165"
## [1570,] "165" "165"
## [1571,] "169" "169"
## [1572,] "170" "170"
## [1573,] "171" "171"
## [1574,] "171" "171"
## [1575,] "173" "173"
## [1576,] "173" "173"
## [1577,] "175" "175"
## [1578,] "175" "175"
## [1579,] "177" "177"
## [1580,] "178" "178"
## [1581,] "178" "178"
## [1582,] "180" "180"
## [1583,] "180" "180"
## [1584,] "182" "182"
## [1585,] "182" "182"
## [1586,] "182" "182"
## [1587,] "185" "185"
## [1588,] "186" "186"
## [1589,] "186" "186"
## [1590,] "188" "188"
## [1591,] "188" "188"
## [1592,] "188" "188"
## [1593,] "191" "191"
## [1594,] "192" "192"
## [1595,] "193" "193"
## [1596,] "193" "193"
## [1597,] "195" "195"
## [1598,] "196" "196"
## [1599,] "196" "196"
## [1600,] "198" "198"
## [1601,] "199" "199"
## [1602,] "200" "200"
## [1603,] "200" "200"
## [1604,] "201-225" NA
## [1605,] "201-225" NA
## [1606,] "201-225" NA
## [1607,] "201-225" NA
## [1608,] "201-225" NA
## [1609,] "201-225" NA
## [1610,] "201-225" NA
## [1611,] "201-225" NA
## [1612,] "201-225" NA
## [1613,] "201-225" NA
## [1614,] "201-225" NA
## [1615,] "201-225" NA
## [1616,] "201-225" NA
## [1617,] "201-225" NA
## [1618,] "201-225" NA
## [1619,] "201-225" NA
## [1620,] "201-225" NA
## [1621,] "201-225" NA
## [1622,] "201-225" NA
## [1623,] "201-225" NA
## [1624,] "201-225" NA
## [1625,] "201-225" NA
## [1626,] "201-225" NA
## [1627,] "201-225" NA
## [1628,] "201-225" NA
## [1629,] "226-250" NA
## [1630,] "226-250" NA
## [1631,] "226-250" NA
## [1632,] "226-250" NA
## [1633,] "226-250" NA
## [1634,] "226-250" NA
## [1635,] "226-250" NA
## [1636,] "226-250" NA
## [1637,] "226-250" NA
## [1638,] "226-250" NA
## [1639,] "226-250" NA
## [1640,] "226-250" NA
## [1641,] "226-250" NA
## [1642,] "226-250" NA
## [1643,] "226-250" NA
## [1644,] "226-250" NA
## [1645,] "226-250" NA
## [1646,] "226-250" NA
## [1647,] "226-250" NA
## [1648,] "226-250" NA
## [1649,] "226-250" NA
## [1650,] "226-250" NA
## [1651,] "226-250" NA
## [1652,] "226-250" NA
## [1653,] "251-275" NA
## [1654,] "251-275" NA
## [1655,] "251-275" NA
## [1656,] "251-275" NA
## [1657,] "251-275" NA
## [1658,] "251-275" NA
## [1659,] "251-275" NA
## [1660,] "251-275" NA
## [1661,] "251-275" NA
## [1662,] "251-275" NA
## [1663,] "251-275" NA
## [1664,] "251-275" NA
## [1665,] "251-275" NA
## [1666,] "251-275" NA
## [1667,] "251-275" NA
## [1668,] "251-275" NA
## [1669,] "251-275" NA
## [1670,] "251-275" NA
## [1671,] "251-275" NA
## [1672,] "251-275" NA
## [1673,] "251-275" NA
## [1674,] "251-275" NA
## [1675,] "251-275" NA
## [1676,] "251-275" NA
## [1677,] "251-275" NA
## [1678,] "276-300" NA
## [1679,] "276-300" NA
## [1680,] "276-300" NA
## [1681,] "276-300" NA
## [1682,] "276-300" NA
## [1683,] "276-300" NA
## [1684,] "276-300" NA
## [1685,] "276-300" NA
## [1686,] "276-300" NA
## [1687,] "276-300" NA
## [1688,] "276-300" NA
## [1689,] "276-300" NA
## [1690,] "276-300" NA
## [1691,] "276-300" NA
## [1692,] "276-300" NA
## [1693,] "276-300" NA
## [1694,] "276-300" NA
## [1695,] "276-300" NA
## [1696,] "276-300" NA
## [1697,] "276-300" NA
## [1698,] "276-300" NA
## [1699,] "276-300" NA
## [1700,] "276-300" NA
## [1701,] "276-300" NA
## [1702,] "276-300" NA
## [1703,] "276-300" NA
## [1704,] "276-300" NA
## [1705,] "276-300" NA
## [1706,] "301-350" NA
## [1707,] "301-350" NA
## [1708,] "301-350" NA
## [1709,] "301-350" NA
## [1710,] "301-350" NA
## [1711,] "301-350" NA
## [1712,] "301-350" NA
## [1713,] "301-350" NA
## [1714,] "301-350" NA
## [1715,] "301-350" NA
## [1716,] "301-350" NA
## [1717,] "301-350" NA
## [1718,] "301-350" NA
## [1719,] "301-350" NA
## [1720,] "301-350" NA
## [1721,] "301-350" NA
## [1722,] "301-350" NA
## [1723,] "301-350" NA
## [1724,] "301-350" NA
## [1725,] "301-350" NA
## [1726,] "301-350" NA
## [1727,] "301-350" NA
## [1728,] "301-350" NA
## [1729,] "301-350" NA
## [1730,] "301-350" NA
## [1731,] "301-350" NA
## [1732,] "301-350" NA
## [1733,] "301-350" NA
## [1734,] "301-350" NA
## [1735,] "301-350" NA
## [1736,] "301-350" NA
## [1737,] "301-350" NA
## [1738,] "301-350" NA
## [1739,] "301-350" NA
## [1740,] "301-350" NA
## [1741,] "301-350" NA
## [1742,] "301-350" NA
## [1743,] "301-350" NA
## [1744,] "301-350" NA
## [1745,] "301-350" NA
## [1746,] "301-350" NA
## [1747,] "301-350" NA
## [1748,] "301-350" NA
## [1749,] "301-350" NA
## [1750,] "301-350" NA
## [1751,] "301-350" NA
## [1752,] "301-350" NA
## [1753,] "301-350" NA
## [1754,] "351-400" NA
## [1755,] "351-400" NA
## [1756,] "351-400" NA
## [1757,] "351-400" NA
## [1758,] "351-400" NA
## [1759,] "351-400" NA
## [1760,] "351-400" NA
## [1761,] "351-400" NA
## [1762,] "351-400" NA
## [1763,] "351-400" NA
## [1764,] "351-400" NA
## [1765,] "351-400" NA
## [1766,] "351-400" NA
## [1767,] "351-400" NA
## [1768,] "351-400" NA
## [1769,] "351-400" NA
## [1770,] "351-400" NA
## [1771,] "351-400" NA
## [1772,] "351-400" NA
## [1773,] "351-400" NA
## [1774,] "351-400" NA
## [1775,] "351-400" NA
## [1776,] "351-400" NA
## [1777,] "351-400" NA
## [1778,] "351-400" NA
## [1779,] "351-400" NA
## [1780,] "351-400" NA
## [1781,] "351-400" NA
## [1782,] "351-400" NA
## [1783,] "351-400" NA
## [1784,] "351-400" NA
## [1785,] "351-400" NA
## [1786,] "351-400" NA
## [1787,] "351-400" NA
## [1788,] "351-400" NA
## [1789,] "351-400" NA
## [1790,] "351-400" NA
## [1791,] "351-400" NA
## [1792,] "351-400" NA
## [1793,] "351-400" NA
## [1794,] "351-400" NA
## [1795,] "351-400" NA
## [1796,] "351-400" NA
## [1797,] "351-400" NA
## [1798,] "351-400" NA
## [1799,] "351-400" NA
## [1800,] "351-400" NA
## [1801,] "351-400" NA
## [1802,] "351-400" NA
## [1803,] "351-400" NA
## [1804,] "1" "1"
## [1805,] "2" "2"
## [1806,] "3" "3"
## [1807,] "4" "4"
## [1808,] "5" "5"
## [1809,] "6" "6"
## [1810,] "7" "7"
## [1811,] "8" "8"
## [1812,] "9" "9"
## [1813,] "10" "10"
## [1814,] "11" "11"
## [1815,] "12" "12"
## [1816,] "13" "13"
## [1817,] "14" "14"
## [1818,] "15" "15"
## [1819,] "16" "16"
## [1820,] "17" "17"
## [1821,] "18" "18"
## [1822,] "19" "19"
## [1823,] "20" "20"
## [1824,] "21" "21"
## [1825,] "22" "22"
## [1826,] "23" "23"
## [1827,] "24" "24"
## [1828,] "25" "25"
## [1829,] "26" "26"
## [1830,] "27" "27"
## [1831,] "28" "28"
## [1832,] "29" "29"
## [1833,] "30" "30"
## [1834,] "31" "31"
## [1835,] "32" "32"
## [1836,] "33" "33"
## [1837,] "34" "34"
## [1838,] "35" "35"
## [1839,] "36" "36"
## [1840,] "37" "37"
## [1841,] "38" "38"
## [1842,] "=39" NA
## [1843,] "=39" NA
## [1844,] "41" "41"
## [1845,] "42" "42"
## [1846,] "43" "43"
## [1847,] "=44" NA
## [1848,] "=44" NA
## [1849,] "46" "46"
## [1850,] "=47" NA
## [1851,] "=47" NA
## [1852,] "49" "49"
## [1853,] "50" "50"
## [1854,] "51" "51"
## [1855,] "52" "52"
## [1856,] "53" "53"
## [1857,] "54" "54"
## [1858,] "55" "55"
## [1859,] "=56" NA
## [1860,] "=56" NA
## [1861,] "58" "58"
## [1862,] "59" "59"
## [1863,] "=60" NA
## [1864,] "=60" NA
## [1865,] "62" "62"
## [1866,] "63" "63"
## [1867,] "64" "64"
## [1868,] "=65" NA
## [1869,] "=65" NA
## [1870,] "67" "67"
## [1871,] "68" "68"
## [1872,] "69" "69"
## [1873,] "70" "70"
## [1874,] "71" "71"
## [1875,] "72" "72"
## [1876,] "73" "73"
## [1877,] "74" "74"
## [1878,] "75" "75"
## [1879,] "=76" NA
## [1880,] "=76" NA
## [1881,] "78" "78"
## [1882,] "79" "79"
## [1883,] "80" "80"
## [1884,] "81" "81"
## [1885,] "=82" NA
## [1886,] "=82" NA
## [1887,] "84" "84"
## [1888,] "85" "85"
## [1889,] "86" "86"
## [1890,] "87" "87"
## [1891,] "=88" NA
## [1892,] "=88" NA
## [1893,] "=90" NA
## [1894,] "=90" NA
## [1895,] "=90" NA
## [1896,] "93" "93"
## [1897,] "=94" NA
## [1898,] "=94" NA
## [1899,] "=94" NA
## [1900,] "97" "97"
## [1901,] "98" "98"
## [1902,] "=99" NA
## [1903,] "=99" NA
## [1904,] "=101" NA
## [1905,] "=101" NA
## [1906,] "=101" NA
## [1907,] "=104" NA
## [1908,] "=104" NA
## [1909,] "=106" NA
## [1910,] "=106" NA
## [1911,] "=106" NA
## [1912,] "108" "108"
## [1913,] "109" "109"
## [1914,] "=110" NA
## [1915,] "=110" NA
## [1916,] "112" "112"
## [1917,] "=113" NA
## [1918,] "=113" NA
## [1919,] "=113" NA
## [1920,] "116" "116"
## [1921,] "117" "117"
## [1922,] "118" "118"
## [1923,] "119" "119"
## [1924,] "=120" NA
## [1925,] "=120" NA
## [1926,] "=120" NA
## [1927,] "=123" NA
## [1928,] "=123" NA
## [1929,] "=125" NA
## [1930,] "=125" NA
## [1931,] "=127" NA
## [1932,] "=127" NA
## [1933,] "129" "129"
## [1934,] "130" "130"
## [1935,] "=131" NA
## [1936,] "=131" NA
## [1937,] "=133" NA
## [1938,] "=133" NA
## [1939,] "135" "135"
## [1940,] "136" "136"
## [1941,] "137" "137"
## [1942,] "=138" NA
## [1943,] "=138" NA
## [1944,] "140" "140"
## [1945,] "141" "141"
## [1946,] "142" "142"
## [1947,] "143" "143"
## [1948,] "=144" NA
## [1949,] "=144" NA
## [1950,] "146" "146"
## [1951,] "147" "147"
## [1952,] "148" "148"
## [1953,] "=149" NA
## [1954,] "=149" NA
## [1955,] "=149" NA
## [1956,] "153" "153"
## [1957,] "154" "154"
## [1958,] "155" "155"
## [1959,] "156" "156"
## [1960,] "157" "157"
## [1961,] "=158" NA
## [1962,] "=158" NA
## [1963,] "160" "160"
## [1964,] "=161" NA
## [1965,] "=161" NA
## [1966,] "163" "163"
## [1967,] "=164" NA
## [1968,] "=164" NA
## [1969,] "=164" NA
## [1970,] "=167" NA
## [1971,] "=167" NA
## [1972,] "=167" NA
## [1973,] "=167" NA
## [1974,] "=167" NA
## [1975,] "=172" NA
## [1976,] "=172" NA
## [1977,] "174" "174"
## [1978,] "175" "175"
## [1979,] "=176" NA
## [1980,] "=176" NA
## [1981,] "178" "178"
## [1982,] "179" "179"
## [1983,] "=180" NA
## [1984,] "=180" NA
## [1985,] "=182" NA
## [1986,] "=182" NA
## [1987,] "=182" NA
## [1988,] "=185" NA
## [1989,] "=185" NA
## [1990,] "=185" NA
## [1991,] "188" "188"
## [1992,] "189" "189"
## [1993,] "=190" NA
## [1994,] "=190" NA
## [1995,] "192" "192"
## [1996,] "=193" NA
## [1997,] "=193" NA
## [1998,] "195" "195"
## [1999,] "=196" NA
## [2000,] "=196" NA
## [2001,] "198" "198"
## [2002,] "199" "199"
## [2003,] "200" "200"
## [2004,] "201-250" NA
## [2005,] "201-250" NA
## [2006,] "201-250" NA
## [2007,] "201-250" NA
## [2008,] "201-250" NA
## [2009,] "201-250" NA
## [2010,] "201-250" NA
## [2011,] "201-250" NA
## [2012,] "201-250" NA
## [2013,] "201-250" NA
## [2014,] "201-250" NA
## [2015,] "201-250" NA
## [2016,] "201-250" NA
## [2017,] "201-250" NA
## [2018,] "201-250" NA
## [2019,] "201-250" NA
## [2020,] "201-250" NA
## [2021,] "201-250" NA
## [2022,] "201-250" NA
## [2023,] "201-250" NA
## [2024,] "201-250" NA
## [2025,] "201-250" NA
## [2026,] "201-250" NA
## [2027,] "201-250" NA
## [2028,] "201-250" NA
## [2029,] "201-250" NA
## [2030,] "201-250" NA
## [2031,] "201-250" NA
## [2032,] "201-250" NA
## [2033,] "201-250" NA
## [2034,] "201-250" NA
## [2035,] "201-250" NA
## [2036,] "201-250" NA
## [2037,] "201-250" NA
## [2038,] "201-250" NA
## [2039,] "201-250" NA
## [2040,] "201-250" NA
## [2041,] "201-250" NA
## [2042,] "201-250" NA
## [2043,] "201-250" NA
## [2044,] "201-250" NA
## [2045,] "201-250" NA
## [2046,] "201-250" NA
## [2047,] "201-250" NA
## [2048,] "201-250" NA
## [2049,] "201-250" NA
## [2050,] "201-250" NA
## [2051,] "201-250" NA
## [2052,] "201-250" NA
## [2053,] "201-250" NA
## [2054,] "201-250" NA
## [2055,] "201-250" NA
## [2056,] "201-250" NA
## [2057,] "251-300" NA
## [2058,] "251-300" NA
## [2059,] "251-300" NA
## [2060,] "251-300" NA
## [2061,] "251-300" NA
## [2062,] "251-300" NA
## [2063,] "251-300" NA
## [2064,] "251-300" NA
## [2065,] "251-300" NA
## [2066,] "251-300" NA
## [2067,] "251-300" NA
## [2068,] "251-300" NA
## [2069,] "251-300" NA
## [2070,] "251-300" NA
## [2071,] "251-300" NA
## [2072,] "251-300" NA
## [2073,] "251-300" NA
## [2074,] "251-300" NA
## [2075,] "251-300" NA
## [2076,] "251-300" NA
## [2077,] "251-300" NA
## [2078,] "251-300" NA
## [2079,] "251-300" NA
## [2080,] "251-300" NA
## [2081,] "251-300" NA
## [2082,] "251-300" NA
## [2083,] "251-300" NA
## [2084,] "251-300" NA
## [2085,] "251-300" NA
## [2086,] "251-300" NA
## [2087,] "251-300" NA
## [2088,] "251-300" NA
## [2089,] "251-300" NA
## [2090,] "251-300" NA
## [2091,] "251-300" NA
## [2092,] "251-300" NA
## [2093,] "251-300" NA
## [2094,] "251-300" NA
## [2095,] "251-300" NA
## [2096,] "251-300" NA
## [2097,] "251-300" NA
## [2098,] "251-300" NA
## [2099,] "251-300" NA
## [2100,] "251-300" NA
## [2101,] "251-300" NA
## [2102,] "251-300" NA
## [2103,] "251-300" NA
## [2104,] "251-300" NA
## [2105,] "251-300" NA
## [2106,] "301-350" NA
## [2107,] "301-350" NA
## [2108,] "301-350" NA
## [2109,] "301-350" NA
## [2110,] "301-350" NA
## [2111,] "301-350" NA
## [2112,] "301-350" NA
## [2113,] "301-350" NA
## [2114,] "301-350" NA
## [2115,] "301-350" NA
## [2116,] "301-350" NA
## [2117,] "301-350" NA
## [2118,] "301-350" NA
## [2119,] "301-350" NA
## [2120,] "301-350" NA
## [2121,] "301-350" NA
## [2122,] "301-350" NA
## [2123,] "301-350" NA
## [2124,] "301-350" NA
## [2125,] "301-350" NA
## [2126,] "301-350" NA
## [2127,] "301-350" NA
## [2128,] "301-350" NA
## [2129,] "301-350" NA
## [2130,] "301-350" NA
## [2131,] "301-350" NA
## [2132,] "301-350" NA
## [2133,] "301-350" NA
## [2134,] "301-350" NA
## [2135,] "301-350" NA
## [2136,] "301-350" NA
## [2137,] "301-350" NA
## [2138,] "301-350" NA
## [2139,] "301-350" NA
## [2140,] "301-350" NA
## [2141,] "301-350" NA
## [2142,] "301-350" NA
## [2143,] "301-350" NA
## [2144,] "301-350" NA
## [2145,] "301-350" NA
## [2146,] "301-350" NA
## [2147,] "301-350" NA
## [2148,] "301-350" NA
## [2149,] "301-350" NA
## [2150,] "301-350" NA
## [2151,] "301-350" NA
## [2152,] "301-350" NA
## [2153,] "301-350" NA
## [2154,] "351-400" NA
## [2155,] "351-400" NA
## [2156,] "351-400" NA
## [2157,] "351-400" NA
## [2158,] "351-400" NA
## [2159,] "351-400" NA
## [2160,] "351-400" NA
## [2161,] "351-400" NA
## [2162,] "351-400" NA
## [2163,] "351-400" NA
## [2164,] "351-400" NA
## [2165,] "351-400" NA
## [2166,] "351-400" NA
## [2167,] "351-400" NA
## [2168,] "351-400" NA
## [2169,] "351-400" NA
## [2170,] "351-400" NA
## [2171,] "351-400" NA
## [2172,] "351-400" NA
## [2173,] "351-400" NA
## [2174,] "351-400" NA
## [2175,] "351-400" NA
## [2176,] "351-400" NA
## [2177,] "351-400" NA
## [2178,] "351-400" NA
## [2179,] "351-400" NA
## [2180,] "351-400" NA
## [2181,] "351-400" NA
## [2182,] "351-400" NA
## [2183,] "351-400" NA
## [2184,] "351-400" NA
## [2185,] "351-400" NA
## [2186,] "351-400" NA
## [2187,] "351-400" NA
## [2188,] "351-400" NA
## [2189,] "351-400" NA
## [2190,] "351-400" NA
## [2191,] "351-400" NA
## [2192,] "351-400" NA
## [2193,] "351-400" NA
## [2194,] "351-400" NA
## [2195,] "351-400" NA
## [2196,] "351-400" NA
## [2197,] "351-400" NA
## [2198,] "351-400" NA
## [2199,] "351-400" NA
## [2200,] "351-400" NA
## [2201,] "351-400" NA
## [2202,] "351-400" NA
## [2203,] "351-400" NA
## [2204,] "351-400" NA
## [2205,] "401-500" NA
## [2206,] "401-500" NA
## [2207,] "401-500" NA
## [2208,] "401-500" NA
## [2209,] "401-500" NA
## [2210,] "401-500" NA
## [2211,] "401-500" NA
## [2212,] "401-500" NA
## [2213,] "401-500" NA
## [2214,] "401-500" NA
## [2215,] "401-500" NA
## [2216,] "401-500" NA
## [2217,] "401-500" NA
## [2218,] "401-500" NA
## [2219,] "401-500" NA
## [2220,] "401-500" NA
## [2221,] "401-500" NA
## [2222,] "401-500" NA
## [2223,] "401-500" NA
## [2224,] "401-500" NA
## [2225,] "401-500" NA
## [2226,] "401-500" NA
## [2227,] "401-500" NA
## [2228,] "401-500" NA
## [2229,] "401-500" NA
## [2230,] "401-500" NA
## [2231,] "401-500" NA
## [2232,] "401-500" NA
## [2233,] "401-500" NA
## [2234,] "401-500" NA
## [2235,] "401-500" NA
## [2236,] "401-500" NA
## [2237,] "401-500" NA
## [2238,] "401-500" NA
## [2239,] "401-500" NA
## [2240,] "401-500" NA
## [2241,] "401-500" NA
## [2242,] "401-500" NA
## [2243,] "401-500" NA
## [2244,] "401-500" NA
## [2245,] "401-500" NA
## [2246,] "401-500" NA
## [2247,] "401-500" NA
## [2248,] "401-500" NA
## [2249,] "401-500" NA
## [2250,] "401-500" NA
## [2251,] "401-500" NA
## [2252,] "401-500" NA
## [2253,] "401-500" NA
## [2254,] "401-500" NA
## [2255,] "401-500" NA
## [2256,] "401-500" NA
## [2257,] "401-500" NA
## [2258,] "401-500" NA
## [2259,] "401-500" NA
## [2260,] "401-500" NA
## [2261,] "401-500" NA
## [2262,] "401-500" NA
## [2263,] "401-500" NA
## [2264,] "401-500" NA
## [2265,] "401-500" NA
## [2266,] "401-500" NA
## [2267,] "401-500" NA
## [2268,] "401-500" NA
## [2269,] "401-500" NA
## [2270,] "401-500" NA
## [2271,] "401-500" NA
## [2272,] "401-500" NA
## [2273,] "401-500" NA
## [2274,] "401-500" NA
## [2275,] "401-500" NA
## [2276,] "401-500" NA
## [2277,] "401-500" NA
## [2278,] "401-500" NA
## [2279,] "401-500" NA
## [2280,] "401-500" NA
## [2281,] "401-500" NA
## [2282,] "401-500" NA
## [2283,] "401-500" NA
## [2284,] "401-500" NA
## [2285,] "401-500" NA
## [2286,] "401-500" NA
## [2287,] "401-500" NA
## [2288,] "401-500" NA
## [2289,] "401-500" NA
## [2290,] "401-500" NA
## [2291,] "401-500" NA
## [2292,] "401-500" NA
## [2293,] "401-500" NA
## [2294,] "401-500" NA
## [2295,] "401-500" NA
## [2296,] "401-500" NA
## [2297,] "401-500" NA
## [2298,] "401-500" NA
## [2299,] "401-500" NA
## [2300,] "401-500" NA
## [2301,] "401-500" NA
## [2302,] "401-500" NA
## [2303,] "401-500" NA
## [2304,] "501-600" NA
## [2305,] "501-600" NA
## [2306,] "501-600" NA
## [2307,] "501-600" NA
## [2308,] "501-600" NA
## [2309,] "501-600" NA
## [2310,] "501-600" NA
## [2311,] "501-600" NA
## [2312,] "501-600" NA
## [2313,] "501-600" NA
## [2314,] "501-600" NA
## [2315,] "501-600" NA
## [2316,] "501-600" NA
## [2317,] "501-600" NA
## [2318,] "501-600" NA
## [2319,] "501-600" NA
## [2320,] "501-600" NA
## [2321,] "501-600" NA
## [2322,] "501-600" NA
## [2323,] "501-600" NA
## [2324,] "501-600" NA
## [2325,] "501-600" NA
## [2326,] "501-600" NA
## [2327,] "501-600" NA
## [2328,] "501-600" NA
## [2329,] "501-600" NA
## [2330,] "501-600" NA
## [2331,] "501-600" NA
## [2332,] "501-600" NA
## [2333,] "501-600" NA
## [2334,] "501-600" NA
## [2335,] "501-600" NA
## [2336,] "501-600" NA
## [2337,] "501-600" NA
## [2338,] "501-600" NA
## [2339,] "501-600" NA
## [2340,] "501-600" NA
## [2341,] "501-600" NA
## [2342,] "501-600" NA
## [2343,] "501-600" NA
## [2344,] "501-600" NA
## [2345,] "501-600" NA
## [2346,] "501-600" NA
## [2347,] "501-600" NA
## [2348,] "501-600" NA
## [2349,] "501-600" NA
## [2350,] "501-600" NA
## [2351,] "501-600" NA
## [2352,] "501-600" NA
## [2353,] "501-600" NA
## [2354,] "501-600" NA
## [2355,] "501-600" NA
## [2356,] "501-600" NA
## [2357,] "501-600" NA
## [2358,] "501-600" NA
## [2359,] "501-600" NA
## [2360,] "501-600" NA
## [2361,] "501-600" NA
## [2362,] "501-600" NA
## [2363,] "501-600" NA
## [2364,] "501-600" NA
## [2365,] "501-600" NA
## [2366,] "501-600" NA
## [2367,] "501-600" NA
## [2368,] "501-600" NA
## [2369,] "501-600" NA
## [2370,] "501-600" NA
## [2371,] "501-600" NA
## [2372,] "501-600" NA
## [2373,] "501-600" NA
## [2374,] "501-600" NA
## [2375,] "501-600" NA
## [2376,] "501-600" NA
## [2377,] "501-600" NA
## [2378,] "501-600" NA
## [2379,] "501-600" NA
## [2380,] "501-600" NA
## [2381,] "501-600" NA
## [2382,] "501-600" NA
## [2383,] "501-600" NA
## [2384,] "501-600" NA
## [2385,] "501-600" NA
## [2386,] "501-600" NA
## [2387,] "501-600" NA
## [2388,] "501-600" NA
## [2389,] "501-600" NA
## [2390,] "501-600" NA
## [2391,] "501-600" NA
## [2392,] "501-600" NA
## [2393,] "501-600" NA
## [2394,] "501-600" NA
## [2395,] "501-600" NA
## [2396,] "501-600" NA
## [2397,] "501-600" NA
## [2398,] "501-600" NA
## [2399,] "501-600" NA
## [2400,] "501-600" NA
## [2401,] "501-600" NA
## [2402,] "501-600" NA
## [2403,] "501-600" NA
## [2404,] "601-800" NA
## [2405,] "601-800" NA
## [2406,] "601-800" NA
## [2407,] "601-800" NA
## [2408,] "601-800" NA
## [2409,] "601-800" NA
## [2410,] "601-800" NA
## [2411,] "601-800" NA
## [2412,] "601-800" NA
## [2413,] "601-800" NA
## [2414,] "601-800" NA
## [2415,] "601-800" NA
## [2416,] "601-800" NA
## [2417,] "601-800" NA
## [2418,] "601-800" NA
## [2419,] "601-800" NA
## [2420,] "601-800" NA
## [2421,] "601-800" NA
## [2422,] "601-800" NA
## [2423,] "601-800" NA
## [2424,] "601-800" NA
## [2425,] "601-800" NA
## [2426,] "601-800" NA
## [2427,] "601-800" NA
## [2428,] "601-800" NA
## [2429,] "601-800" NA
## [2430,] "601-800" NA
## [2431,] "601-800" NA
## [2432,] "601-800" NA
## [2433,] "601-800" NA
## [2434,] "601-800" NA
## [2435,] "601-800" NA
## [2436,] "601-800" NA
## [2437,] "601-800" NA
## [2438,] "601-800" NA
## [2439,] "601-800" NA
## [2440,] "601-800" NA
## [2441,] "601-800" NA
## [2442,] "601-800" NA
## [2443,] "601-800" NA
## [2444,] "601-800" NA
## [2445,] "601-800" NA
## [2446,] "601-800" NA
## [2447,] "601-800" NA
## [2448,] "601-800" NA
## [2449,] "601-800" NA
## [2450,] "601-800" NA
## [2451,] "601-800" NA
## [2452,] "601-800" NA
## [2453,] "601-800" NA
## [2454,] "601-800" NA
## [2455,] "601-800" NA
## [2456,] "601-800" NA
## [2457,] "601-800" NA
## [2458,] "601-800" NA
## [2459,] "601-800" NA
## [2460,] "601-800" NA
## [2461,] "601-800" NA
## [2462,] "601-800" NA
## [2463,] "601-800" NA
## [2464,] "601-800" NA
## [2465,] "601-800" NA
## [2466,] "601-800" NA
## [2467,] "601-800" NA
## [2468,] "601-800" NA
## [2469,] "601-800" NA
## [2470,] "601-800" NA
## [2471,] "601-800" NA
## [2472,] "601-800" NA
## [2473,] "601-800" NA
## [2474,] "601-800" NA
## [2475,] "601-800" NA
## [2476,] "601-800" NA
## [2477,] "601-800" NA
## [2478,] "601-800" NA
## [2479,] "601-800" NA
## [2480,] "601-800" NA
## [2481,] "601-800" NA
## [2482,] "601-800" NA
## [2483,] "601-800" NA
## [2484,] "601-800" NA
## [2485,] "601-800" NA
## [2486,] "601-800" NA
## [2487,] "601-800" NA
## [2488,] "601-800" NA
## [2489,] "601-800" NA
## [2490,] "601-800" NA
## [2491,] "601-800" NA
## [2492,] "601-800" NA
## [2493,] "601-800" NA
## [2494,] "601-800" NA
## [2495,] "601-800" NA
## [2496,] "601-800" NA
## [2497,] "601-800" NA
## [2498,] "601-800" NA
## [2499,] "601-800" NA
## [2500,] "601-800" NA
## [2501,] "601-800" NA
## [2502,] "601-800" NA
## [2503,] "601-800" NA
## [2504,] "601-800" NA
## [2505,] "601-800" NA
## [2506,] "601-800" NA
## [2507,] "601-800" NA
## [2508,] "601-800" NA
## [2509,] "601-800" NA
## [2510,] "601-800" NA
## [2511,] "601-800" NA
## [2512,] "601-800" NA
## [2513,] "601-800" NA
## [2514,] "601-800" NA
## [2515,] "601-800" NA
## [2516,] "601-800" NA
## [2517,] "601-800" NA
## [2518,] "601-800" NA
## [2519,] "601-800" NA
## [2520,] "601-800" NA
## [2521,] "601-800" NA
## [2522,] "601-800" NA
## [2523,] "601-800" NA
## [2524,] "601-800" NA
## [2525,] "601-800" NA
## [2526,] "601-800" NA
## [2527,] "601-800" NA
## [2528,] "601-800" NA
## [2529,] "601-800" NA
## [2530,] "601-800" NA
## [2531,] "601-800" NA
## [2532,] "601-800" NA
## [2533,] "601-800" NA
## [2534,] "601-800" NA
## [2535,] "601-800" NA
## [2536,] "601-800" NA
## [2537,] "601-800" NA
## [2538,] "601-800" NA
## [2539,] "601-800" NA
## [2540,] "601-800" NA
## [2541,] "601-800" NA
## [2542,] "601-800" NA
## [2543,] "601-800" NA
## [2544,] "601-800" NA
## [2545,] "601-800" NA
## [2546,] "601-800" NA
## [2547,] "601-800" NA
## [2548,] "601-800" NA
## [2549,] "601-800" NA
## [2550,] "601-800" NA
## [2551,] "601-800" NA
## [2552,] "601-800" NA
## [2553,] "601-800" NA
## [2554,] "601-800" NA
## [2555,] "601-800" NA
## [2556,] "601-800" NA
## [2557,] "601-800" NA
## [2558,] "601-800" NA
## [2559,] "601-800" NA
## [2560,] "601-800" NA
## [2561,] "601-800" NA
## [2562,] "601-800" NA
## [2563,] "601-800" NA
## [2564,] "601-800" NA
## [2565,] "601-800" NA
## [2566,] "601-800" NA
## [2567,] "601-800" NA
## [2568,] "601-800" NA
## [2569,] "601-800" NA
## [2570,] "601-800" NA
## [2571,] "601-800" NA
## [2572,] "601-800" NA
## [2573,] "601-800" NA
## [2574,] "601-800" NA
## [2575,] "601-800" NA
## [2576,] "601-800" NA
## [2577,] "601-800" NA
## [2578,] "601-800" NA
## [2579,] "601-800" NA
## [2580,] "601-800" NA
## [2581,] "601-800" NA
## [2582,] "601-800" NA
## [2583,] "601-800" NA
## [2584,] "601-800" NA
## [2585,] "601-800" NA
## [2586,] "601-800" NA
## [2587,] "601-800" NA
## [2588,] "601-800" NA
## [2589,] "601-800" NA
## [2590,] "601-800" NA
## [2591,] "601-800" NA
## [2592,] "601-800" NA
## [2593,] "601-800" NA
## [2594,] "601-800" NA
## [2595,] "601-800" NA
## [2596,] "601-800" NA
## [2597,] "601-800" NA
## [2598,] "601-800" NA
## [2599,] "601-800" NA
## [2600,] "601-800" NA
## [2601,] "601-800" NA
## [2602,] "601-800" NA
## [2603,] "601-800" NAget rid of = and ranges (look up regular expressions!)
rnk <- sub(pattern = "=", "", rnk)
rnk <- sub(pattern = "-.*", "", rnk)
rnk <- as.numeric(rnk)
summary(rnk)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1 109 201 235 301 601times$world_rank <- rnkIntl
intl <- as.character(times$international)
unique(intl)## [1] "72.4" "54.6" "82.3" "29.5" "70.3" "77.7" "77.2" "39.6"
## [9] "90.0" "59.2" "48.1" "62.8" "58.5" "62.4" "93.7" "53.3"
## [17] "-" "90.9" "32.9" "39.1" "91.4" "90.8" "49.0" "49.4"
## [25] "60.5" "18.4" "73.2" "32.6" "64.3" "93.3" "21.5" "31.6"
## [33] "55.9" "97.8" "85.9" "88.0" "68.6" "56.4" "77.9" "67.3"
## [41] "97.4" "44.9" "93.9" "44.5" "43.7" "31.2" "100.0" "66.3"
## [49] "22.1" "23.0" "28.3" "22.6" "43.0" "38.1" "31.8" "52.3"
## [57] "43.1" "35.6" "25.2" "56.5" "64.0" "31.7" "67.2" "16.7"
## [65] "89.6" "42.2" "87.5" "20.9" "84.2" "52.2" "36.7" "72.8"
## [73] "74.2" "66.6" "63.4" "22.5" "65.7" "99.5" "79.1" "92.9"
## [81] "56.8" "69.0" "87.9" "24.4" "87.0" "21.9" "91.3" "35.4"
## [89] "31.0" "37.6" "85.3" "24.2" "85.7" "48.0" "26.8" "62.6"
## [97] "34.1" "83.3" "19.9" "71.8" "47.7" "24.8" "29.2" "34.2"
## [105] "63.0" "95.7" "29.6" "50.2" "91.0" "30.4" "24.7" "73.8"
## [113] "40.0" "71.6" "55.1" "20.1" "46.2" "84.1" "62.7" "30.6"
## [121] "30.7" "54.4" "22.3" "52.6" "24.3" "94.3" "19.3" "82.9"
## [129] "86.1" "47.4" "88.5" "80.5" "70.7" "44.1" "37.7" "23.2"
## [137] "16.3" "58.6" "16.8" "24.1" "21.3" "38.2" "59.8" "33.4"
## [145] "50.0" "40.3" "35.5" "29.3" "56.1" "96.3" "74.8" "45.8"
## [153] "46.1" "87.1" "46.8" "57.9" "63.8" "27.2" "93.6" "47.3"
## [161] "57.8" "60.6" "18.9" "28.0" "64.2" "63.2" "15.9" "51.8"
## [169] "51.9" "56.0" "67.5" "57.2" "91.9" "49.6" "79.2" "92.2"
## [177] "58.8" "50.4" "55.5" "67.6" "41.0" "59.9" "97.5" "34.3"
## [185] "91.8" "47.2" "53.4" "55.0" "46.9" "88.7" "65.0" "36.9"
## [193] "35.3" "23.8" "81.4" "38.8" "50.7" "82.0" "31.5" "83.7"
## [201] "79.8" "82.5" "93.8" "51.4" "93.0" "45.7" "25.6" "20.2"
## [209] "54.3" "98.9" "96.0" "80.4" "51.7" "21.1" "25.0" "37.2"
## [217] "41.1" "88.1" "26.5" "66.2" "87.4" "80.1" "27.3" "72.0"
## [225] "73.7" "56.7" "58.1" "39.7" "62.3" "80.8" "37.3" "75.9"
## [233] "41.3" "30.8" "61.2" "25.3" "75.8" "66.7" "89.1" "36.3"
## [241] "59.1" "65.2" "33.1" "29.9" "34.0" "28.4" "71.9" "68.2"
## [249] "68.1" "73.9" "71.3" "79.5" "24.9" "64.5" "29.8" "92.4"
## [257] "77.6" "23.3" "86.7" "89.4" "53.0" "72.7" "69.3" "25.9"
## [265] "26.1" "88.8" "78.3" "78.6" "48.8" "64.8" "38.3" "26.4"
## [273] "29.1" "86.6" "72.6" "30.0" "32.7" "68.5" "76.2" "19.7"
## [281] "69.5" "62.1" "84.8" "20.7" "73.4" "85.5" "83.2" "23.9"
## [289] "17.2" "36.0" "75.1" "30.1" "67.1" "89.8" "72.5" "30.3"
## [297] "85.1" "62.5" "70.5" "22.9" "57.6" "73.1" "63.9" "82.1"
## [305] "55.6" "73.5" "14.8" "61.6" "63.7" "41.4" "64.9" "32.1"
## [313] "86.4" "84.9" "56.2" "45.9" "48.5" "67.8" "38.4" "21.2"
## [321] "17.7" "38.0" "48.9" "50.8" "52.0" "49.2" "81.7" "20.6"
## [329] "90.1" "48.4" "90.7" "26.0" "70.4" "55.7" "44.0" "66.0"
## [337] "25.5" "37.8" "36.1" "23.4" "43.5" "17.8" "34.9" "42.7"
## [345] "56.3" "33.2" "26.9" "45.5" "45.2" "89.9" "56.6" "19.5"
## [353] "16.0" "57.7" "89.5" "46.6" "44.4" "69.1" "80.6" "34.6"
## [361] "35.9" "71.7" "89.0" "25.1" "24.6" "18.8" "58.9" "23.5"
## [369] "52.9" "76.7" "19.1" "71.0" "18.0" "63.5" "42.6" "33.3"
## [377] "56.9" "18.3" "43.3" "76.3" "49.7" "75.3" "47.0" "36.2"
## [385] "46.7" "14.3" "39.5" "48.6" "15.6" "33.6" "32.4" "20.5"
## [393] "12.7" "26.6" "77.0" "33.5" "37.1" "76.5" "27.7" "68.7"
## [401] "40.2" "18.6" "26.2" "42.0" "15.0" "81.5" "36.4" "35.8"
## [409] "13.9" "84.5" "28.5" "27.9" "79.0" "21.0" "82.6" "23.6"
## [417] "18.1" "31.4" "45.0" "77.8" "32.3" "22.2" "48.3" "63.3"
## [425] "64.6" "30.5" "55.8" "27.4" "81.8" "21.8" "28.8" "27.1"
## [433] "21.7" "12.8" "81.6" "54.5" "83.6" "55.3" "54.7" "42.3"
## [441] "66.1" "57.3" "53.8" "33.8" "47.6" "65.1" "42.1" "27.6"
## [449] "92.3" "78.9" "58.3" "87.2" "98.8" "38.7" "44.3" "54.1"
## [457] "28.7" "46.3" "39.2" "26.3" "43.4" "86.0" "27.0" "83.0"
## [465] "54.8" "78.1" "31.1" "51.0" "59.0" "29.4" "67.7" "61.3"
## [473] "36.6" "64.4" "57.0" "74.6" "90.5" "66.9" "49.8" "34.7"
## [481] "49.1" "36.8" "41.6" "35.2" "40.4" "31.3" "57.5" "66.4"
## [489] "61.5" "27.5" "86.3" "69.8" "85.2" "92.5" "70.1" "32.5"
## [497] "80.9" "60.9" "82.7" "77.4" "95.3" "50.3" "32.0" "69.7"
## [505] "47.1" "54.9" "52.4" "77.3" "74.1" "53.9" "24.5" "52.8"
## [513] "66.8" "61.0" "54.0" "82.2" "68.9" "74.4" "51.2" "25.8"
## [521] "88.4" "19.0" "65.9" "45.3" "38.6" "49.9" "58.0" "30.9"
## [529] "46.0" "22.0" "68.3" "65.3" "58.4" "16.1" "62.2" "85.4"
## [537] "51.3" "44.8" "78.2" "65.4" "86.8" "69.2" "47.8" "19.6"
## [545] "40.5" "44.6" "35.7" "43.2" "30.2" "71.4" "63.1" "47.5"
## [553] "20.8" "54.2" "28.1" "27.8" "62.0" "61.8" "71.5" "59.5"
## [561] "59.7" "39.0" "37.0" "34.4" "70.2" "81.0" "35.0" "85.6"
## [569] "33.9" "68.4" "41.7" "48.2" "73.3" "48.7" "42.4" "74.7"
## [577] "28.6" "40.8" "39.8" "32.8" "65.8" "90.2" "68.0" "59.6"
## [585] "46.4" "96.7" "59.3" "40.6" "49.5" "70.0" "81.3" "98.2"
## [593] "41.8" "80.3" "33.7" "44.2" "53.7" "79.7" "51.5" "91.1"
## [601] "75.0" "76.8" "58.7" "65.5" "73.6" "92.6" "75.6" "83.5"
## [609] "86.2" "67.4" "39.4" "81.2" "76.0" "72.2" "61.9" "57.1"
## [617] "78.5" "43.6" "79.6" "50.6" "61.1" "88.6" "72.3" "55.4"
## [625] "77.5" "67.0" "23.7" "70.6" "37.9" "62.9" "29.0" "25.4"
## [633] "42.8" "45.1" "69.4" "28.9" "82.4" "67.9" "40.7" "38.5"
## [641] "83.9" "70.8" "68.8" "87.8" "71.2" "22.8" "50.1" "81.1"
## [649] "38.9" "37.4" "80.0" "87.3" "28.2" "53.2" "42.9" "15.3"
## [657] "17.3" "14.7" "74.3" "34.5" "21.6" "50.9" "22.4" "26.7"
## [665] "43.9" "69.9" "39.3" "29.7" "84.3" "92.7" "96.6" "43.8"
## [673] "50.5" "90.6" "94.9" "47.9" "41.2" "46.5" "81.9" "94.5"
## [681] "78.7" "76.6" "91.2" "51.1" "32.2" "78.8" "89.7" "64.7"
## [689] "86.9" "96.8" "94.4" "84.0" "84.7" "80.7" "44.7" "79.3"
## [697] "60.1" "60.3" "60.4" "39.9" "93.4" "79.4" "84.4" "61.4"
## [705] "59.4" "18.2" "41.5" "89.2" "37.5" "19.4" "76.1" "88.2"
## [713] "52.1" "34.8" "45.6" "66.5" "16.6" "20.0" "53.6" "60.0"
## [721] "74.9" "21.4" "91.5" "97.9" "96.2" "49.3" "98.6" "33.0"
## [729] "94.6" "89.3" "87.6" "85.8" "58.2" "90.3" "95.5" "63.6"
## [737] "52.7" "93.5" "94.7" "92.8" "90.4" "80.2" "98.5" "88.3"
## [745] "53.1" "31.9" "99.8" "65.6" "60.2" "40.1" "45.4" "16.4"
## [753] "53.5" "76.9" "97.6" "78.0" "72.9" "17.1" "75.5" "25.7"
## [761] "93.1" "15.5" "13.3" "12.2" "98.4" "35.1" "15.8" "36.5"
## [769] "41.9" "23.1" "7.7" "17.6" "12.9" "22.7" "17.4" "14.1"
## [777] "17.5" "95.0" "17.9" "18.7" "95.6" "7.2" "16.9" "13.7"
## [785] "13.1" "15.7" "20.4" "19.8" "69.6" "15.4" "13.4" "14.5"
## [793] "18.5" "55.2" "20.3" "7.1" "17.0" "14.2" "15.2" "99.9"
## [801] "13.8" "14.0" "16.5" "14.9"intl[intl == '-'] <- NA
unique(intl)## [1] "72.4" "54.6" "82.3" "29.5" "70.3" "77.7" "77.2" "39.6"
## [9] "90.0" "59.2" "48.1" "62.8" "58.5" "62.4" "93.7" "53.3"
## [17] NA "90.9" "32.9" "39.1" "91.4" "90.8" "49.0" "49.4"
## [25] "60.5" "18.4" "73.2" "32.6" "64.3" "93.3" "21.5" "31.6"
## [33] "55.9" "97.8" "85.9" "88.0" "68.6" "56.4" "77.9" "67.3"
## [41] "97.4" "44.9" "93.9" "44.5" "43.7" "31.2" "100.0" "66.3"
## [49] "22.1" "23.0" "28.3" "22.6" "43.0" "38.1" "31.8" "52.3"
## [57] "43.1" "35.6" "25.2" "56.5" "64.0" "31.7" "67.2" "16.7"
## [65] "89.6" "42.2" "87.5" "20.9" "84.2" "52.2" "36.7" "72.8"
## [73] "74.2" "66.6" "63.4" "22.5" "65.7" "99.5" "79.1" "92.9"
## [81] "56.8" "69.0" "87.9" "24.4" "87.0" "21.9" "91.3" "35.4"
## [89] "31.0" "37.6" "85.3" "24.2" "85.7" "48.0" "26.8" "62.6"
## [97] "34.1" "83.3" "19.9" "71.8" "47.7" "24.8" "29.2" "34.2"
## [105] "63.0" "95.7" "29.6" "50.2" "91.0" "30.4" "24.7" "73.8"
## [113] "40.0" "71.6" "55.1" "20.1" "46.2" "84.1" "62.7" "30.6"
## [121] "30.7" "54.4" "22.3" "52.6" "24.3" "94.3" "19.3" "82.9"
## [129] "86.1" "47.4" "88.5" "80.5" "70.7" "44.1" "37.7" "23.2"
## [137] "16.3" "58.6" "16.8" "24.1" "21.3" "38.2" "59.8" "33.4"
## [145] "50.0" "40.3" "35.5" "29.3" "56.1" "96.3" "74.8" "45.8"
## [153] "46.1" "87.1" "46.8" "57.9" "63.8" "27.2" "93.6" "47.3"
## [161] "57.8" "60.6" "18.9" "28.0" "64.2" "63.2" "15.9" "51.8"
## [169] "51.9" "56.0" "67.5" "57.2" "91.9" "49.6" "79.2" "92.2"
## [177] "58.8" "50.4" "55.5" "67.6" "41.0" "59.9" "97.5" "34.3"
## [185] "91.8" "47.2" "53.4" "55.0" "46.9" "88.7" "65.0" "36.9"
## [193] "35.3" "23.8" "81.4" "38.8" "50.7" "82.0" "31.5" "83.7"
## [201] "79.8" "82.5" "93.8" "51.4" "93.0" "45.7" "25.6" "20.2"
## [209] "54.3" "98.9" "96.0" "80.4" "51.7" "21.1" "25.0" "37.2"
## [217] "41.1" "88.1" "26.5" "66.2" "87.4" "80.1" "27.3" "72.0"
## [225] "73.7" "56.7" "58.1" "39.7" "62.3" "80.8" "37.3" "75.9"
## [233] "41.3" "30.8" "61.2" "25.3" "75.8" "66.7" "89.1" "36.3"
## [241] "59.1" "65.2" "33.1" "29.9" "34.0" "28.4" "71.9" "68.2"
## [249] "68.1" "73.9" "71.3" "79.5" "24.9" "64.5" "29.8" "92.4"
## [257] "77.6" "23.3" "86.7" "89.4" "53.0" "72.7" "69.3" "25.9"
## [265] "26.1" "88.8" "78.3" "78.6" "48.8" "64.8" "38.3" "26.4"
## [273] "29.1" "86.6" "72.6" "30.0" "32.7" "68.5" "76.2" "19.7"
## [281] "69.5" "62.1" "84.8" "20.7" "73.4" "85.5" "83.2" "23.9"
## [289] "17.2" "36.0" "75.1" "30.1" "67.1" "89.8" "72.5" "30.3"
## [297] "85.1" "62.5" "70.5" "22.9" "57.6" "73.1" "63.9" "82.1"
## [305] "55.6" "73.5" "14.8" "61.6" "63.7" "41.4" "64.9" "32.1"
## [313] "86.4" "84.9" "56.2" "45.9" "48.5" "67.8" "38.4" "21.2"
## [321] "17.7" "38.0" "48.9" "50.8" "52.0" "49.2" "81.7" "20.6"
## [329] "90.1" "48.4" "90.7" "26.0" "70.4" "55.7" "44.0" "66.0"
## [337] "25.5" "37.8" "36.1" "23.4" "43.5" "17.8" "34.9" "42.7"
## [345] "56.3" "33.2" "26.9" "45.5" "45.2" "89.9" "56.6" "19.5"
## [353] "16.0" "57.7" "89.5" "46.6" "44.4" "69.1" "80.6" "34.6"
## [361] "35.9" "71.7" "89.0" "25.1" "24.6" "18.8" "58.9" "23.5"
## [369] "52.9" "76.7" "19.1" "71.0" "18.0" "63.5" "42.6" "33.3"
## [377] "56.9" "18.3" "43.3" "76.3" "49.7" "75.3" "47.0" "36.2"
## [385] "46.7" "14.3" "39.5" "48.6" "15.6" "33.6" "32.4" "20.5"
## [393] "12.7" "26.6" "77.0" "33.5" "37.1" "76.5" "27.7" "68.7"
## [401] "40.2" "18.6" "26.2" "42.0" "15.0" "81.5" "36.4" "35.8"
## [409] "13.9" "84.5" "28.5" "27.9" "79.0" "21.0" "82.6" "23.6"
## [417] "18.1" "31.4" "45.0" "77.8" "32.3" "22.2" "48.3" "63.3"
## [425] "64.6" "30.5" "55.8" "27.4" "81.8" "21.8" "28.8" "27.1"
## [433] "21.7" "12.8" "81.6" "54.5" "83.6" "55.3" "54.7" "42.3"
## [441] "66.1" "57.3" "53.8" "33.8" "47.6" "65.1" "42.1" "27.6"
## [449] "92.3" "78.9" "58.3" "87.2" "98.8" "38.7" "44.3" "54.1"
## [457] "28.7" "46.3" "39.2" "26.3" "43.4" "86.0" "27.0" "83.0"
## [465] "54.8" "78.1" "31.1" "51.0" "59.0" "29.4" "67.7" "61.3"
## [473] "36.6" "64.4" "57.0" "74.6" "90.5" "66.9" "49.8" "34.7"
## [481] "49.1" "36.8" "41.6" "35.2" "40.4" "31.3" "57.5" "66.4"
## [489] "61.5" "27.5" "86.3" "69.8" "85.2" "92.5" "70.1" "32.5"
## [497] "80.9" "60.9" "82.7" "77.4" "95.3" "50.3" "32.0" "69.7"
## [505] "47.1" "54.9" "52.4" "77.3" "74.1" "53.9" "24.5" "52.8"
## [513] "66.8" "61.0" "54.0" "82.2" "68.9" "74.4" "51.2" "25.8"
## [521] "88.4" "19.0" "65.9" "45.3" "38.6" "49.9" "58.0" "30.9"
## [529] "46.0" "22.0" "68.3" "65.3" "58.4" "16.1" "62.2" "85.4"
## [537] "51.3" "44.8" "78.2" "65.4" "86.8" "69.2" "47.8" "19.6"
## [545] "40.5" "44.6" "35.7" "43.2" "30.2" "71.4" "63.1" "47.5"
## [553] "20.8" "54.2" "28.1" "27.8" "62.0" "61.8" "71.5" "59.5"
## [561] "59.7" "39.0" "37.0" "34.4" "70.2" "81.0" "35.0" "85.6"
## [569] "33.9" "68.4" "41.7" "48.2" "73.3" "48.7" "42.4" "74.7"
## [577] "28.6" "40.8" "39.8" "32.8" "65.8" "90.2" "68.0" "59.6"
## [585] "46.4" "96.7" "59.3" "40.6" "49.5" "70.0" "81.3" "98.2"
## [593] "41.8" "80.3" "33.7" "44.2" "53.7" "79.7" "51.5" "91.1"
## [601] "75.0" "76.8" "58.7" "65.5" "73.6" "92.6" "75.6" "83.5"
## [609] "86.2" "67.4" "39.4" "81.2" "76.0" "72.2" "61.9" "57.1"
## [617] "78.5" "43.6" "79.6" "50.6" "61.1" "88.6" "72.3" "55.4"
## [625] "77.5" "67.0" "23.7" "70.6" "37.9" "62.9" "29.0" "25.4"
## [633] "42.8" "45.1" "69.4" "28.9" "82.4" "67.9" "40.7" "38.5"
## [641] "83.9" "70.8" "68.8" "87.8" "71.2" "22.8" "50.1" "81.1"
## [649] "38.9" "37.4" "80.0" "87.3" "28.2" "53.2" "42.9" "15.3"
## [657] "17.3" "14.7" "74.3" "34.5" "21.6" "50.9" "22.4" "26.7"
## [665] "43.9" "69.9" "39.3" "29.7" "84.3" "92.7" "96.6" "43.8"
## [673] "50.5" "90.6" "94.9" "47.9" "41.2" "46.5" "81.9" "94.5"
## [681] "78.7" "76.6" "91.2" "51.1" "32.2" "78.8" "89.7" "64.7"
## [689] "86.9" "96.8" "94.4" "84.0" "84.7" "80.7" "44.7" "79.3"
## [697] "60.1" "60.3" "60.4" "39.9" "93.4" "79.4" "84.4" "61.4"
## [705] "59.4" "18.2" "41.5" "89.2" "37.5" "19.4" "76.1" "88.2"
## [713] "52.1" "34.8" "45.6" "66.5" "16.6" "20.0" "53.6" "60.0"
## [721] "74.9" "21.4" "91.5" "97.9" "96.2" "49.3" "98.6" "33.0"
## [729] "94.6" "89.3" "87.6" "85.8" "58.2" "90.3" "95.5" "63.6"
## [737] "52.7" "93.5" "94.7" "92.8" "90.4" "80.2" "98.5" "88.3"
## [745] "53.1" "31.9" "99.8" "65.6" "60.2" "40.1" "45.4" "16.4"
## [753] "53.5" "76.9" "97.6" "78.0" "72.9" "17.1" "75.5" "25.7"
## [761] "93.1" "15.5" "13.3" "12.2" "98.4" "35.1" "15.8" "36.5"
## [769] "41.9" "23.1" "7.7" "17.6" "12.9" "22.7" "17.4" "14.1"
## [777] "17.5" "95.0" "17.9" "18.7" "95.6" "7.2" "16.9" "13.7"
## [785] "13.1" "15.7" "20.4" "19.8" "69.6" "15.4" "13.4" "14.5"
## [793] "18.5" "55.2" "20.3" "7.1" "17.0" "14.2" "15.2" "99.9"
## [801] "13.8" "14.0" "16.5" "14.9"intl <- as.numeric(intl)
summary(intl)## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 7.10 33.42 50.30 52.01 69.00 100.00 9times$international <- intlStudents
ns <- as.character(times$num_students)
ns <- sub(pattern = ",", "", ns)
ns <- as.numeric(ns)
summary(ns)## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 462 12640 20850 23870 29990 379200 59times$num_students <- nsClean the other variables as well!
tmp <- as.character(times$female_male_ratio)
tmp <- sub(pattern = " :.*", "", tmp)
tmp <- as.numeric(tmp)## Warning: NAs introduced by coerciontimes$female_male_ratio <- NULL
tmp <- as.character(times$international_students)
tmp <- sub(pattern = "%", "", tmp)
tmp <- as.numeric(tmp)
times$international_students <- tmp
tmp <- as.character(times$income)
tmp <- sub(pattern = "-", "", tmp)
tmp <- as.numeric(tmp)
times$income <- tmp
tmp <- as.character(times$total_score)
tmp <- sub(pattern = "-", "", tmp)
tmp <- as.numeric(tmp)
times$total_score <- tmp
summary(times)## world_rank university_name
## Min. : 1 Aarhus University : 6
## 1st Qu.:109 Arizona State University : 6
## Median :201 Australian National University: 6
## Mean :235 Bielefeld University : 6
## 3rd Qu.:301 Bilkent University : 6
## Max. :601 Birkbeck, University of London: 6
## (Other) :2567
## country teaching international
## United States of America: 659 Min. : 9.9 Min. : 7.10
## United Kingdom : 300 1st Qu.:24.7 1st Qu.: 33.42
## Germany : 152 Median :33.9 Median : 50.30
## Australia : 117 Mean :37.8 Mean : 52.01
## Canada : 108 3rd Qu.:46.4 3rd Qu.: 69.00
## Japan : 98 Max. :99.7 Max. :100.00
## (Other) :1169 NA's :9
## research citations income total_score
## Min. : 2.90 Min. : 1.20 Min. : 24.20 Min. :41.40
## 1st Qu.:19.60 1st Qu.: 45.50 1st Qu.: 33.00 1st Qu.:50.30
## Median :30.50 Median : 62.50 Median : 41.00 Median :56.00
## Mean :35.91 Mean : 60.92 Mean : 48.98 Mean :59.85
## 3rd Qu.:47.25 3rd Qu.: 79.05 3rd Qu.: 59.00 3rd Qu.:66.20
## Max. :99.40 Max. :100.00 Max. :100.00 Max. :96.10
## NA's :218 NA's :1402
## num_students student_staff_ratio international_students
## Min. : 462 Min. : 0.60 Min. : 0.00
## 1st Qu.: 12638 1st Qu.: 11.97 1st Qu.: 8.00
## Median : 20851 Median : 16.10 Median :13.00
## Mean : 23874 Mean : 18.45 Mean :15.44
## 3rd Qu.: 29991 3rd Qu.: 21.50 3rd Qu.:21.00
## Max. :379231 Max. :162.60 Max. :82.00
## NA's :59 NA's :59 NA's :67
## year
## Min. :2011
## 1st Qu.:2013
## Median :2014
## Mean :2014
## 3rd Qu.:2016
## Max. :2016
## Some visualization
hist(times$world_rank)
Note: This is weird!!!
hist(times$num_students, breaks = 100)
hist(times$international)
plot(times$world_rank, times$num_students)
plot(times$world_rank, times$num_students, log = "y")
plot(times$world_rank, times$international)
Fit a (log) linear model on the data with rank > 10
plot(times$world_rank, times$teaching)
plot(times$world_rank, times$teaching, log ="x")
cor(times$world_rank, times$teaching)## [1] -0.7401785cor(times$world_rank, times$teaching, method = "spearman")## [1] -0.8341955cor(log(times$world_rank), times$teaching)## [1] -0.8977434l <- lm(teaching ~ log(world_rank), data = times[times$world_rank>10,])
summary(l)##
## Call:
## lm(formula = teaching ~ log(world_rank), data = times[times$world_rank >
## 10, ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -20.132 -5.425 -0.241 4.649 36.931
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 120.8969 0.9415 128.40 <2e-16 ***
## log(world_rank) -16.2215 0.1787 -90.76 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7.688 on 2541 degrees of freedom
## Multiple R-squared: 0.7643, Adjusted R-squared: 0.7642
## F-statistic: 8238 on 1 and 2541 DF, p-value: < 2.2e-16x <- 1:600
lines(x, predict(l, data.frame(world_rank=x)), col = "red")
plot(times$world_rank, times$teaching)
lines(x, predict(l, data.frame(world_rank=x)), col = "red")
plot(times$world_rank, times$research)
plot(times$world_rank, times$research, log = "x")
More Analysis
sum(times$world_rank==1)## [1] 6times[times$world_rank==1, ]## world_rank university_name
## 1 1 Harvard University
## 201 1 California Institute of Technology
## 603 1 California Institute of Technology
## 1003 1 California Institute of Technology
## 1403 1 California Institute of Technology
## 1804 1 California Institute of Technology
## country teaching international research citations
## 1 United States of America 99.7 72.4 98.7 98.8
## 201 United States of America 95.7 56.0 98.2 99.9
## 603 United States of America 96.3 59.8 99.4 99.7
## 1003 United States of America 94.4 65.8 98.2 99.8
## 1403 United States of America 92.2 67.0 98.1 99.7
## 1804 United States of America 95.6 64.0 97.6 99.8
## income total_score num_students student_staff_ratio
## 1 34.5 96.1 20152 8.9
## 201 97.0 94.8 2243 6.9
## 603 95.6 95.5 2243 6.9
## 1003 91.2 94.9 2243 6.9
## 1403 89.1 94.3 2243 6.9
## 1804 97.8 95.2 2243 6.9
## international_students year
## 1 25 2011
## 201 27 2012
## 603 27 2013
## 1003 27 2014
## 1403 27 2015
## 1804 27 2016There is different year so we probalby need to factor this in!
hist(times[times$year==2016,]$world_rank)
OK, this makes more sense!!!
What about SMU?
times[times$university_name=="Southern Methodist University",]## world_rank university_name country
## 975 351 Southern Methodist University United States of America
## teaching international research citations income total_score
## 975 18.6 35.2 9 67.3 NA NA
## num_students student_staff_ratio international_students year
## 975 NA NA NA 2013Combine two rankings
cwur <- read.csv("cwurData.csv")
head(cwur)## world_rank institution country
## 1 1 Harvard University USA
## 2 2 Massachusetts Institute of Technology USA
## 3 3 Stanford University USA
## 4 4 University of Cambridge United Kingdom
## 5 5 California Institute of Technology USA
## 6 6 Princeton University USA
## national_rank quality_of_education alumni_employment quality_of_faculty
## 1 1 7 9 1
## 2 2 9 17 3
## 3 3 17 11 5
## 4 1 10 24 4
## 5 4 2 29 7
## 6 5 8 14 2
## publications influence citations broad_impact patents score year
## 1 1 1 1 NA 5 100.00 2012
## 2 12 4 4 NA 1 91.67 2012
## 3 4 2 2 NA 15 89.50 2012
## 4 16 16 11 NA 50 86.17 2012
## 5 37 22 22 NA 18 85.21 2012
## 6 53 33 26 NA 101 82.50 2012summary(cwur)## world_rank institution
## Min. : 1.0 Arizona State University : 4
## 1st Qu.: 175.8 Boston University : 4
## Median : 450.5 Brown University : 4
## Mean : 459.6 California Institute of Technology: 4
## 3rd Qu.: 725.2 Carnegie Mellon University : 4
## Max. :1000.0 Columbia University : 4
## (Other) :2176
## country national_rank quality_of_education
## USA :573 Min. : 1.00 Min. : 1.0
## China :167 1st Qu.: 6.00 1st Qu.:175.8
## Japan :159 Median : 21.00 Median :355.0
## United Kingdom:144 Mean : 40.28 Mean :275.1
## Germany :115 3rd Qu.: 49.00 3rd Qu.:367.0
## France :109 Max. :229.00 Max. :367.0
## (Other) :933
## alumni_employment quality_of_faculty publications influence
## Min. : 1.0 Min. : 1.0 Min. : 1.0 Min. : 1.0
## 1st Qu.:175.8 1st Qu.:175.8 1st Qu.: 175.8 1st Qu.:175.8
## Median :450.5 Median :210.0 Median : 450.5 Median :450.5
## Mean :357.1 Mean :178.9 Mean : 459.9 Mean :459.8
## 3rd Qu.:478.0 3rd Qu.:218.0 3rd Qu.: 725.0 3rd Qu.:725.2
## Max. :567.0 Max. :218.0 Max. :1000.0 Max. :991.0
##
## citations broad_impact patents score
## Min. : 1.0 Min. : 1.0 Min. : 1.0 Min. : 43.36
## 1st Qu.:161.0 1st Qu.: 250.5 1st Qu.:170.8 1st Qu.: 44.46
## Median :406.0 Median : 496.0 Median :426.0 Median : 45.10
## Mean :413.4 Mean : 496.7 Mean :433.3 Mean : 47.80
## 3rd Qu.:645.0 3rd Qu.: 741.0 3rd Qu.:714.2 3rd Qu.: 47.55
## Max. :812.0 Max. :1000.0 Max. :871.0 Max. :100.00
## NA's :200
## year
## Min. :2012
## 1st Qu.:2014
## Median :2014
## Mean :2014
## 3rd Qu.:2015
## Max. :2015
## this needs cleaning Let us combine the rankings for 2015
times2015 <- times[times$year=="2015",]
summary(times2015$year)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2015 2015 2015 2015 2015 2015cwur2015 <- cwur[cwur$year=="2015",]
summary(cwur2015$year)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2015 2015 2015 2015 2015 2015meger does a database JOIN (by defines the keys and all specifies that we want a FULL JOIN)
ranking <- merge(times2015, cwur2015,
by.x="university_name", by.y="institution", all = TRUE)
plot(ranking$world_rank.x, ranking$world_rank.y,
xlab = "Times Rank", ylab= "CWUR Rank")
Do a bar plot for SMU
Calculate average over all universities
m <- sapply(cwur2015[, -c(1:3, 14)], median, na.rm = TRUE)
oldpar <- par(mar = c(4,10,1,1))
barplot(m, las =2, horiz = TRUE, xlab = "Median Rank")
par(oldpar)Add SMU
smu <- cwur2015[cwur2015$institution=="Southern Methodist University",-c(1:3, 14)]
data <- as.matrix(rbind(SMU = smu, Median = m))
oldpar <- par(mar = c(4,10,1,1))
#barplot(unlist(smu[,-(2:3)]), las =2, horiz = TRUE)
barplot(data, las =2, horiz = TRUE, beside = TRUE, xlab = "Median Rank")
par(oldpar)Note: Add a legend
Look at the distribution in the ranking
plot(cwur2015$world_rank, cwur2015$national_rank)
plot(cwur2015$world_rank, cwur2015$national_rank, col = cwur2015$country)
l <- split(cwur2015, cwur2015$country)
plot(NA, xlim = c(0,1000), ylim=c(0,300), xlab = "World Rank", ylab="National Rank")
for(i in 1:length(l)) lines(l[[i]]$world_rank, l[[i]]$national_rank, col = i)
num_of_universities <- sapply(l, nrow)
plot(NA, xlim = c(0,1000), ylim=c(0,1), xlab = "World Rank", ylab="National Rank", main = "Country Comparison")
for(i in 1:length(l)) lines(l[[i]]$world_rank, l[[i]]$national_rank/num_of_universities[i], col = i)
Countries with more than 10 universities in the ranking and normalize ranks. It would be better to normalize with the actual number of universities in the country and not with the number of universities in the ranking.
countries <- which(num_of_universities>=10)
plot(NA, xlim = c(0,1), ylim=c(0,1), xlab = "Normalized World Rank",
ylab="Normalized National Rank", main = "Country Comparison")
for(i in 1:length(countries)) lines(l[[countries[i]]]$world_rank/1000, l[[countries[i]]]$national_rank/num_of_universities[countries[i]], col = i, lty =i)
legend(x = "bottomright", legend = names(countries), col = 1:length(countries),lwd =1, lty = 1:length(countries), cex=.7)
abline(a = 0, b = 1, col ="grey", lwd = 3)
Country ranking (area under the courve would be better)
country_rnk <- sapply(1:length(countries), function(i) mean((l[[countries[i]]]$national_rank/num_of_universities[countries[i]] - l[[countries[i]]]$world_rank/1000)))
names(country_rnk) <- names(countries)
country_rnk## Australia Austria Belgium Brazil Canada
## -0.001000000 -0.003583333 0.178800000 -0.224333333 0.072696970
## China France Germany India Italy
## -0.165590361 -0.032938776 0.120854545 -0.118875000 0.017297872
## Japan Netherlands South Korea Spain Sweden
## -0.072824324 0.310153846 -0.030777778 -0.108475000 0.278000000
## Taiwan Turkey United Kingdom USA
## -0.180857143 -0.195800000 0.082630769 0.146829694sort(country_rnk, decreasing = TRUE)## Netherlands Sweden Belgium USA Germany
## 0.310153846 0.278000000 0.178800000 0.146829694 0.120854545
## United Kingdom Canada Italy Australia Austria
## 0.082630769 0.072696970 0.017297872 -0.001000000 -0.003583333
## South Korea France Japan Spain India
## -0.030777778 -0.032938776 -0.072824324 -0.108475000 -0.118875000
## China Taiwan Turkey Brazil
## -0.165590361 -0.180857143 -0.195800000 -0.224333333Compare countries using the total number of universities
from: http://www.webometrics.info/en/node/54
Note: This ranking only uses Google Scholar
universities_by_country <- read.csv("universities_per_country.csv")
head(universities_by_country)## COUNTRY X1.100 X101.300 X301.500 X501.1000 X1001.5000
## 1 United States of America 57 49 44 96 801
## 2 United Kingdom 8 17 13 39 64
## 3 China 7 11 13 34 503
## 4 Canada 5 13 6 8 52
## 5 Australia 4 4 12 10 10
## 6 Germany 2 21 18 20 70
## X50001.10000 ALL
## 1 1351 3295
## 2 57 287
## 3 976 2313
## 4 84 352
## 5 21 202
## 6 166 455rownames(universities_by_country) <- universities_by_country$COUNTRY
universities_by_country$TOP100 <- universities_by_country[,2]
universities_by_country$TOP500 <- universities_by_country[,2] + universities_by_country[,2] + universities_by_country[,3]
fraction100 <- universities_by_country$TOP100/universities_by_country$ALL
names(fraction100) <- rownames(universities_by_country)
oldpar <- par(mar = c(12,4,4,3))
barplot(sort(fraction100[fraction100>0], decreasing = TRUE), las=2, main = "Proportion of Universities in Top 100")
par(oldpar)
fraction500 <- universities_by_country$TOP500/universities_by_country$ALL
names(fraction500) <- rownames(universities_by_country)
oldpar <- par(mar = c(12,4,4,3))
barplot(sort(fraction500[fraction500>0], decreasing = TRUE), las=2, main = "Proportion of Universities in Top 500")
par(oldpar)Look at correlation
library(seriation)
m <- na.omit(times2015)
rownames(m) <- m[,2]
m <- m[,-c(2,3,9,13)]
hmap(cor(m), margins=c(10,10))
hmap(abs(cor(m)), margins=c(10,10))
top 25 universities
hmap(scale(m[1:25,]), margins=c(10,20))
hmap(t(scale(m[1:25,])), margins=c(17,10), method = "OLO")
PCA
pr <- prcomp(scale(m))
plot(pr)
biplot(pr, col = c("grey", "red"), main = "All Universities (2015)")
pr <- prcomp(scale(m[1:10,]))
plot(pr)
biplot(pr, col = c("grey", "red"), xlim=c(-1,1), ylim=c(-.5,1), , main = "Top 10 (2015)")
pr <- prcomp(scale(m[1:50,]))
biplot(pr, col = c("grey", "red"), main = "Top 50 (2015)")