├── data ├── UCI │ ├── ionosphere.arff │ ├── iris.arff │ └── mushroom.arff ├── abalone.data ├── abalone.json ├── abalone.names ├── abc-transporter.fasta ├── accident-fatalities.tsv ├── agaricus-lepiota.data ├── agaricus-lepiota.names ├── all_160.P3.csv ├── all_160_in_51.P3.csv ├── all_160_in_51.P35.csv ├── big.txt ├── census-race.json ├── chick-weight.json ├── chn-land.csv ├── clusters.json ├── comments.xml ├── companions.clj ├── companions.txt ├── currencies.ttl ├── dehydratase.fasta ├── delicious-rss-214k.json.xz ├── elephas.fasta ├── flights_with_colnames.csv.gz ├── ibm.csv ├── maltophilia.fasta ├── mchu.fasta ├── ovax-chick.fasta ├── pg1661.txt ├── salmonella.fasta ├── seqeuence-1.fasta ├── sequences.fasta ├── small-sample-header.csv ├── small-sample-header.xls ├── small-sample-list.html ├── small-sample-table.html ├── small-sample.csv ├── small-sample.json ├── small-sample.sqlite ├── small-sample.xml ├── sotu.tar.gz ├── transferase.fasta ├── world-bank-filtered.csv ├── x-rates-usd.html └── x-rates-usd_files │ ├── ga.js │ ├── logo-fxcm-lg.png │ ├── output.3.js │ ├── output.6.css │ ├── webtrends.1.js │ ├── xrates_lg_tm.png │ └── xrates_sm_tm.png └── index.md /data/UCI/iris.arff: -------------------------------------------------------------------------------- 1 | % 1. Title: Iris Plants Database 2 | % 3 | % 2. Sources: 4 | % (a) Creator: R.A. Fisher 5 | % (b) Donor: Michael Marshall (MARSHALL%PLU@io.arc.nasa.gov) 6 | % (c) Date: July, 1988 7 | % 8 | % 3. Past Usage: 9 | % - Publications: too many to mention!!! Here are a few. 10 | % 1. Fisher,R.A. "The use of multiple measurements in taxonomic problems" 11 | % Annual Eugenics, 7, Part II, 179-188 (1936); also in "Contributions 12 | % to Mathematical Statistics" (John Wiley, NY, 1950). 13 | % 2. Duda,R.O., & Hart,P.E. (1973) Pattern Classification and Scene Analysis. 14 | % (Q327.D83) John Wiley & Sons. ISBN 0-471-22361-1. See page 218. 15 | % 3. Dasarathy, B.V. (1980) "Nosing Around the Neighborhood: A New System 16 | % Structure and Classification Rule for Recognition in Partially Exposed 17 | % Environments". IEEE Transactions on Pattern Analysis and Machine 18 | % Intelligence, Vol. PAMI-2, No. 1, 67-71. 19 | % -- Results: 20 | % -- very low misclassification rates (0% for the setosa class) 21 | % 4. Gates, G.W. (1972) "The Reduced Nearest Neighbor Rule". IEEE 22 | % Transactions on Information Theory, May 1972, 431-433. 23 | % -- Results: 24 | % -- very low misclassification rates again 25 | % 5. See also: 1988 MLC Proceedings, 54-64. Cheeseman et al's AUTOCLASS II 26 | % conceptual clustering system finds 3 classes in the data. 27 | % 28 | % 4. Relevant Information: 29 | % --- This is perhaps the best known database to be found in the pattern 30 | % recognition literature. Fisher's paper is a classic in the field 31 | % and is referenced frequently to this day. (See Duda & Hart, for 32 | % example.) The data set contains 3 classes of 50 instances each, 33 | % where each class refers to a type of iris plant. One class is 34 | % linearly separable from the other 2; the latter are NOT linearly 35 | % separable from each other. 36 | % --- Predicted attribute: class of iris plant. 37 | % --- This is an exceedingly simple domain. 38 | % 39 | % 5. Number of Instances: 150 (50 in each of three classes) 40 | % 41 | % 6. Number of Attributes: 4 numeric, predictive attributes and the class 42 | % 43 | % 7. Attribute Information: 44 | % 1. sepal length in cm 45 | % 2. sepal width in cm 46 | % 3. petal length in cm 47 | % 4. petal width in cm 48 | % 5. class: 49 | % -- Iris Setosa 50 | % -- Iris Versicolour 51 | % -- Iris Virginica 52 | % 53 | % 8. Missing Attribute Values: None 54 | % 55 | % Summary Statistics: 56 | % Min Max Mean SD Class Correlation 57 | % sepal length: 4.3 7.9 5.84 0.83 0.7826 58 | % sepal width: 2.0 4.4 3.05 0.43 -0.4194 59 | % petal length: 1.0 6.9 3.76 1.76 0.9490 (high!) 60 | % petal width: 0.1 2.5 1.20 0.76 0.9565 (high!) 61 | % 62 | % 9. Class Distribution: 33.3% for each of 3 classes. 63 | 64 | @RELATION iris 65 | 66 | @ATTRIBUTE sepallength REAL 67 | @ATTRIBUTE sepalwidth REAL 68 | @ATTRIBUTE petallength REAL 69 | @ATTRIBUTE petalwidth REAL 70 | @ATTRIBUTE class {Iris-setosa,Iris-versicolor,Iris-virginica} 71 | 72 | @DATA 73 | 5.1,3.5,1.4,0.2,Iris-setosa 74 | 4.9,3.0,1.4,0.2,Iris-setosa 75 | 4.7,3.2,1.3,0.2,Iris-setosa 76 | 4.6,3.1,1.5,0.2,Iris-setosa 77 | 5.0,3.6,1.4,0.2,Iris-setosa 78 | 5.4,3.9,1.7,0.4,Iris-setosa 79 | 4.6,3.4,1.4,0.3,Iris-setosa 80 | 5.0,3.4,1.5,0.2,Iris-setosa 81 | 4.4,2.9,1.4,0.2,Iris-setosa 82 | 4.9,3.1,1.5,0.1,Iris-setosa 83 | 5.4,3.7,1.5,0.2,Iris-setosa 84 | 4.8,3.4,1.6,0.2,Iris-setosa 85 | 4.8,3.0,1.4,0.1,Iris-setosa 86 | 4.3,3.0,1.1,0.1,Iris-setosa 87 | 5.8,4.0,1.2,0.2,Iris-setosa 88 | 5.7,4.4,1.5,0.4,Iris-setosa 89 | 5.4,3.9,1.3,0.4,Iris-setosa 90 | 5.1,3.5,1.4,0.3,Iris-setosa 91 | 5.7,3.8,1.7,0.3,Iris-setosa 92 | 5.1,3.8,1.5,0.3,Iris-setosa 93 | 5.4,3.4,1.7,0.2,Iris-setosa 94 | 5.1,3.7,1.5,0.4,Iris-setosa 95 | 4.6,3.6,1.0,0.2,Iris-setosa 96 | 5.1,3.3,1.7,0.5,Iris-setosa 97 | 4.8,3.4,1.9,0.2,Iris-setosa 98 | 5.0,3.0,1.6,0.2,Iris-setosa 99 | 5.0,3.4,1.6,0.4,Iris-setosa 100 | 5.2,3.5,1.5,0.2,Iris-setosa 101 | 5.2,3.4,1.4,0.2,Iris-setosa 102 | 4.7,3.2,1.6,0.2,Iris-setosa 103 | 4.8,3.1,1.6,0.2,Iris-setosa 104 | 5.4,3.4,1.5,0.4,Iris-setosa 105 | 5.2,4.1,1.5,0.1,Iris-setosa 106 | 5.5,4.2,1.4,0.2,Iris-setosa 107 | 4.9,3.1,1.5,0.1,Iris-setosa 108 | 5.0,3.2,1.2,0.2,Iris-setosa 109 | 5.5,3.5,1.3,0.2,Iris-setosa 110 | 4.9,3.1,1.5,0.1,Iris-setosa 111 | 4.4,3.0,1.3,0.2,Iris-setosa 112 | 5.1,3.4,1.5,0.2,Iris-setosa 113 | 5.0,3.5,1.3,0.3,Iris-setosa 114 | 4.5,2.3,1.3,0.3,Iris-setosa 115 | 4.4,3.2,1.3,0.2,Iris-setosa 116 | 5.0,3.5,1.6,0.6,Iris-setosa 117 | 5.1,3.8,1.9,0.4,Iris-setosa 118 | 4.8,3.0,1.4,0.3,Iris-setosa 119 | 5.1,3.8,1.6,0.2,Iris-setosa 120 | 4.6,3.2,1.4,0.2,Iris-setosa 121 | 5.3,3.7,1.5,0.2,Iris-setosa 122 | 5.0,3.3,1.4,0.2,Iris-setosa 123 | 7.0,3.2,4.7,1.4,Iris-versicolor 124 | 6.4,3.2,4.5,1.5,Iris-versicolor 125 | 6.9,3.1,4.9,1.5,Iris-versicolor 126 | 5.5,2.3,4.0,1.3,Iris-versicolor 127 | 6.5,2.8,4.6,1.5,Iris-versicolor 128 | 5.7,2.8,4.5,1.3,Iris-versicolor 129 | 6.3,3.3,4.7,1.6,Iris-versicolor 130 | 4.9,2.4,3.3,1.0,Iris-versicolor 131 | 6.6,2.9,4.6,1.3,Iris-versicolor 132 | 5.2,2.7,3.9,1.4,Iris-versicolor 133 | 5.0,2.0,3.5,1.0,Iris-versicolor 134 | 5.9,3.0,4.2,1.5,Iris-versicolor 135 | 6.0,2.2,4.0,1.0,Iris-versicolor 136 | 6.1,2.9,4.7,1.4,Iris-versicolor 137 | 5.6,2.9,3.6,1.3,Iris-versicolor 138 | 6.7,3.1,4.4,1.4,Iris-versicolor 139 | 5.6,3.0,4.5,1.5,Iris-versicolor 140 | 5.8,2.7,4.1,1.0,Iris-versicolor 141 | 6.2,2.2,4.5,1.5,Iris-versicolor 142 | 5.6,2.5,3.9,1.1,Iris-versicolor 143 | 5.9,3.2,4.8,1.8,Iris-versicolor 144 | 6.1,2.8,4.0,1.3,Iris-versicolor 145 | 6.3,2.5,4.9,1.5,Iris-versicolor 146 | 6.1,2.8,4.7,1.2,Iris-versicolor 147 | 6.4,2.9,4.3,1.3,Iris-versicolor 148 | 6.6,3.0,4.4,1.4,Iris-versicolor 149 | 6.8,2.8,4.8,1.4,Iris-versicolor 150 | 6.7,3.0,5.0,1.7,Iris-versicolor 151 | 6.0,2.9,4.5,1.5,Iris-versicolor 152 | 5.7,2.6,3.5,1.0,Iris-versicolor 153 | 5.5,2.4,3.8,1.1,Iris-versicolor 154 | 5.5,2.4,3.7,1.0,Iris-versicolor 155 | 5.8,2.7,3.9,1.2,Iris-versicolor 156 | 6.0,2.7,5.1,1.6,Iris-versicolor 157 | 5.4,3.0,4.5,1.5,Iris-versicolor 158 | 6.0,3.4,4.5,1.6,Iris-versicolor 159 | 6.7,3.1,4.7,1.5,Iris-versicolor 160 | 6.3,2.3,4.4,1.3,Iris-versicolor 161 | 5.6,3.0,4.1,1.3,Iris-versicolor 162 | 5.5,2.5,4.0,1.3,Iris-versicolor 163 | 5.5,2.6,4.4,1.2,Iris-versicolor 164 | 6.1,3.0,4.6,1.4,Iris-versicolor 165 | 5.8,2.6,4.0,1.2,Iris-versicolor 166 | 5.0,2.3,3.3,1.0,Iris-versicolor 167 | 5.6,2.7,4.2,1.3,Iris-versicolor 168 | 5.7,3.0,4.2,1.2,Iris-versicolor 169 | 5.7,2.9,4.2,1.3,Iris-versicolor 170 | 6.2,2.9,4.3,1.3,Iris-versicolor 171 | 5.1,2.5,3.0,1.1,Iris-versicolor 172 | 5.7,2.8,4.1,1.3,Iris-versicolor 173 | 6.3,3.3,6.0,2.5,Iris-virginica 174 | 5.8,2.7,5.1,1.9,Iris-virginica 175 | 7.1,3.0,5.9,2.1,Iris-virginica 176 | 6.3,2.9,5.6,1.8,Iris-virginica 177 | 6.5,3.0,5.8,2.2,Iris-virginica 178 | 7.6,3.0,6.6,2.1,Iris-virginica 179 | 4.9,2.5,4.5,1.7,Iris-virginica 180 | 7.3,2.9,6.3,1.8,Iris-virginica 181 | 6.7,2.5,5.8,1.8,Iris-virginica 182 | 7.2,3.6,6.1,2.5,Iris-virginica 183 | 6.5,3.2,5.1,2.0,Iris-virginica 184 | 6.4,2.7,5.3,1.9,Iris-virginica 185 | 6.8,3.0,5.5,2.1,Iris-virginica 186 | 5.7,2.5,5.0,2.0,Iris-virginica 187 | 5.8,2.8,5.1,2.4,Iris-virginica 188 | 6.4,3.2,5.3,2.3,Iris-virginica 189 | 6.5,3.0,5.5,1.8,Iris-virginica 190 | 7.7,3.8,6.7,2.2,Iris-virginica 191 | 7.7,2.6,6.9,2.3,Iris-virginica 192 | 6.0,2.2,5.0,1.5,Iris-virginica 193 | 6.9,3.2,5.7,2.3,Iris-virginica 194 | 5.6,2.8,4.9,2.0,Iris-virginica 195 | 7.7,2.8,6.7,2.0,Iris-virginica 196 | 6.3,2.7,4.9,1.8,Iris-virginica 197 | 6.7,3.3,5.7,2.1,Iris-virginica 198 | 7.2,3.2,6.0,1.8,Iris-virginica 199 | 6.2,2.8,4.8,1.8,Iris-virginica 200 | 6.1,3.0,4.9,1.8,Iris-virginica 201 | 6.4,2.8,5.6,2.1,Iris-virginica 202 | 7.2,3.0,5.8,1.6,Iris-virginica 203 | 7.4,2.8,6.1,1.9,Iris-virginica 204 | 7.9,3.8,6.4,2.0,Iris-virginica 205 | 6.4,2.8,5.6,2.2,Iris-virginica 206 | 6.3,2.8,5.1,1.5,Iris-virginica 207 | 6.1,2.6,5.6,1.4,Iris-virginica 208 | 7.7,3.0,6.1,2.3,Iris-virginica 209 | 6.3,3.4,5.6,2.4,Iris-virginica 210 | 6.4,3.1,5.5,1.8,Iris-virginica 211 | 6.0,3.0,4.8,1.8,Iris-virginica 212 | 6.9,3.1,5.4,2.1,Iris-virginica 213 | 6.7,3.1,5.6,2.4,Iris-virginica 214 | 6.9,3.1,5.1,2.3,Iris-virginica 215 | 5.8,2.7,5.1,1.9,Iris-virginica 216 | 6.8,3.2,5.9,2.3,Iris-virginica 217 | 6.7,3.3,5.7,2.5,Iris-virginica 218 | 6.7,3.0,5.2,2.3,Iris-virginica 219 | 6.3,2.5,5.0,1.9,Iris-virginica 220 | 6.5,3.0,5.2,2.0,Iris-virginica 221 | 6.2,3.4,5.4,2.3,Iris-virginica 222 | 5.9,3.0,5.1,1.8,Iris-virginica 223 | % 224 | % 225 | % 226 | -------------------------------------------------------------------------------- /data/abalone.names: -------------------------------------------------------------------------------- 1 | 1. Title of Database: Abalone data 2 | 3 | 2. Sources: 4 | 5 | (a) Original owners of database: 6 | Marine Resources Division 7 | Marine Research Laboratories - Taroona 8 | Department of Primary Industry and Fisheries, Tasmania 9 | GPO Box 619F, Hobart, Tasmania 7001, Australia 10 | (contact: Warwick Nash +61 02 277277, wnash@dpi.tas.gov.au) 11 | 12 | (b) Donor of database: 13 | Sam Waugh (Sam.Waugh@cs.utas.edu.au) 14 | Department of Computer Science, University of Tasmania 15 | GPO Box 252C, Hobart, Tasmania 7001, Australia 16 | 17 | (c) Date received: December 1995 18 | 19 | 20 | 3. Past Usage: 21 | 22 | Sam Waugh (1995) "Extending and benchmarking Cascade-Correlation", PhD 23 | thesis, Computer Science Department, University of Tasmania. 24 | 25 | -- Test set performance (final 1044 examples, first 3133 used for training): 26 | 24.86% Cascade-Correlation (no hidden nodes) 27 | 26.25% Cascade-Correlation (5 hidden nodes) 28 | 21.5% C4.5 29 | 0.0% Linear Discriminate Analysis 30 | 3.57% k=5 Nearest Neighbour 31 | (Problem encoded as a classification task) 32 | 33 | -- Data set samples are highly overlapped. Further information is required 34 | to separate completely using affine combinations. Other restrictions 35 | to data set examined. 36 | 37 | David Clark, Zoltan Schreter, Anthony Adams "A Quantitative Comparison of 38 | Dystal and Backpropagation", submitted to the Australian Conference on 39 | Neural Networks (ACNN'96). Data set treated as a 3-category classification 40 | problem (grouping ring classes 1-8, 9 and 10, and 11 on). 41 | 42 | -- Test set performance (3133 training, 1044 testing as above): 43 | 64% Backprop 44 | 55% Dystal 45 | -- Previous work (Waugh, 1995) on same data set: 46 | 61.40% Cascade-Correlation (no hidden nodes) 47 | 65.61% Cascade-Correlation (5 hidden nodes) 48 | 59.2% C4.5 49 | 32.57% Linear Discriminate Analysis 50 | 62.46% k=5 Nearest Neighbour 51 | 52 | 53 | 4. Relevant Information Paragraph: 54 | 55 | Predicting the age of abalone from physical measurements. The age of 56 | abalone is determined by cutting the shell through the cone, staining it, 57 | and counting the number of rings through a microscope -- a boring and 58 | time-consuming task. Other measurements, which are easier to obtain, are 59 | used to predict the age. Further information, such as weather patterns 60 | and location (hence food availability) may be required to solve the problem. 61 | 62 | From the original data examples with missing values were removed (the 63 | majority having the predicted value missing), and the ranges of the 64 | continuous values have been scaled for use with an ANN (by dividing by 200). 65 | 66 | Data comes from an original (non-machine-learning) study: 67 | 68 | Warwick J Nash, Tracy L Sellers, Simon R Talbot, Andrew J Cawthorn and 69 | Wes B Ford (1994) "The Population Biology of Abalone (_Haliotis_ 70 | species) in Tasmania. I. Blacklip Abalone (_H. rubra_) from the North 71 | Coast and Islands of Bass Strait", Sea Fisheries Division, Technical 72 | Report No. 48 (ISSN 1034-3288) 73 | 74 | 75 | 5. Number of Instances: 4177 76 | 77 | 78 | 6. Number of Attributes: 8 79 | 80 | 81 | 7. Attribute information: 82 | 83 | Given is the attribute name, attribute type, the measurement unit and a 84 | brief description. The number of rings is the value to predict: either 85 | as a continuous value or as a classification problem. 86 | 87 | Name Data Type Meas. Description 88 | ---- --------- ----- ----------- 89 | Sex nominal M, F, and I (infant) 90 | Length continuous mm Longest shell measurement 91 | Diameter continuous mm perpendicular to length 92 | Height continuous mm with meat in shell 93 | Whole weight continuous grams whole abalone 94 | Shucked weight continuous grams weight of meat 95 | Viscera weight continuous grams gut weight (after bleeding) 96 | Shell weight continuous grams after being dried 97 | Rings integer +1.5 gives the age in years 98 | 99 | Statistics for numeric domains: 100 | 101 | Length Diam Height Whole Shucked Viscera Shell Rings 102 | Min 0.075 0.055 0.000 0.002 0.001 0.001 0.002 1 103 | Max 0.815 0.650 1.130 2.826 1.488 0.760 1.005 29 104 | Mean 0.524 0.408 0.140 0.829 0.359 0.181 0.239 9.934 105 | SD 0.120 0.099 0.042 0.490 0.222 0.110 0.139 3.224 106 | Correl 0.557 0.575 0.557 0.540 0.421 0.504 0.628 1.0 107 | 108 | 109 | 8. Missing Attribute Values: None 110 | 111 | 112 | 9. Class Distribution: 113 | 114 | Class Examples 115 | ----- -------- 116 | 1 1 117 | 2 1 118 | 3 15 119 | 4 57 120 | 5 115 121 | 6 259 122 | 7 391 123 | 8 568 124 | 9 689 125 | 10 634 126 | 11 487 127 | 12 267 128 | 13 203 129 | 14 126 130 | 15 103 131 | 16 67 132 | 17 58 133 | 18 42 134 | 19 32 135 | 20 26 136 | 21 14 137 | 22 6 138 | 23 9 139 | 24 2 140 | 25 1 141 | 26 1 142 | 27 2 143 | 29 1 144 | ----- ---- 145 | Total 4177 146 | -------------------------------------------------------------------------------- /data/abc-transporter.fasta: -------------------------------------------------------------------------------- 1 | ">gi|16759485|ref|NP_455102.1| ABC transporter ATP-binding protein YbbA [Salmonella enterica subsp. enterica serovar Typhi str. CT18] 2 | MPAENSVEVHRLRKSVGQGEHELSILTGVELVVKRGETIALIGESGSGKSTLLAILAGLDDGSSGEVSLV 3 | GKPLHQMDEEARAQLRAQHVGFVFQSFMLIPTLNALENVELPALLRGENSGQSKAGAKALLEQLGLGKRL 4 | DHLPAQLSGGEQQRVALARAFNGRPDVLFADEPTGNLDRQTGDKIADLLFSLNREHGTTLILVTHDPALA 5 | ARCDRRLRLVNGQLQEEA 6 | -------------------------------------------------------------------------------- /data/agaricus-lepiota.names: -------------------------------------------------------------------------------- 1 | 1. Title: Mushroom Database 2 | 3 | 2. Sources: 4 | (a) Mushroom records drawn from The Audubon Society Field Guide to North 5 | American Mushrooms (1981). G. H. Lincoff (Pres.), New York: Alfred 6 | A. Knopf 7 | (b) Donor: Jeff Schlimmer (Jeffrey.Schlimmer@a.gp.cs.cmu.edu) 8 | (c) Date: 27 April 1987 9 | 10 | 3. Past Usage: 11 | 1. Schlimmer,J.S. (1987). Concept Acquisition Through Representational 12 | Adjustment (Technical Report 87-19). Doctoral disseration, Department 13 | of Information and Computer Science, University of California, Irvine. 14 | --- STAGGER: asymptoted to 95% classification accuracy after reviewing 15 | 1000 instances. 16 | 2. Iba,W., Wogulis,J., & Langley,P. (1988). Trading off Simplicity 17 | and Coverage in Incremental Concept Learning. In Proceedings of 18 | the 5th International Conference on Machine Learning, 73-79. 19 | Ann Arbor, Michigan: Morgan Kaufmann. 20 | -- approximately the same results with their HILLARY algorithm 21 | 3. In the following references a set of rules (given below) were 22 | learned for this data set which may serve as a point of 23 | comparison for other researchers. 24 | 25 | Duch W, Adamczak R, Grabczewski K (1996) Extraction of logical rules 26 | from training data using backpropagation networks, in: Proc. of the 27 | The 1st Online Workshop on Soft Computing, 19-30.Aug.1996, pp. 25-30, 28 | available on-line at: http://www.bioele.nuee.nagoya-u.ac.jp/wsc1/ 29 | 30 | Duch W, Adamczak R, Grabczewski K, Ishikawa M, Ueda H, Extraction of 31 | crisp logical rules using constrained backpropagation networks - 32 | comparison of two new approaches, in: Proc. of the European Symposium 33 | on Artificial Neural Networks (ESANN'97), Bruge, Belgium 16-18.4.1997, 34 | pp. xx-xx 35 | 36 | Wlodzislaw Duch, Department of Computer Methods, Nicholas Copernicus 37 | University, 87-100 Torun, Grudziadzka 5, Poland 38 | e-mail: duch@phys.uni.torun.pl 39 | WWW http://www.phys.uni.torun.pl/kmk/ 40 | 41 | Date: Mon, 17 Feb 1997 13:47:40 +0100 42 | From: Wlodzislaw Duch 43 | Organization: Dept. of Computer Methods, UMK 44 | 45 | I have attached a file containing logical rules for mushrooms. 46 | It should be helpful for other people since only in the last year I 47 | have seen about 10 papers analyzing this dataset and obtaining quite 48 | complex rules. We will try to contribute other results later. 49 | 50 | With best regards, Wlodek Duch 51 | ________________________________________________________________ 52 | 53 | Logical rules for the mushroom data sets. 54 | 55 | Logical rules given below seem to be the simplest possible for the 56 | mushroom dataset and therefore should be treated as benchmark results. 57 | 58 | Disjunctive rules for poisonous mushrooms, from most general 59 | to most specific: 60 | 61 | P_1) odor=NOT(almond.OR.anise.OR.none) 62 | 120 poisonous cases missed, 98.52% accuracy 63 | 64 | P_2) spore-print-color=green 65 | 48 cases missed, 99.41% accuracy 66 | 67 | P_3) odor=none.AND.stalk-surface-below-ring=scaly.AND. 68 | (stalk-color-above-ring=NOT.brown) 69 | 8 cases missed, 99.90% accuracy 70 | 71 | P_4) habitat=leaves.AND.cap-color=white 72 | 100% accuracy 73 | 74 | Rule P_4) may also be 75 | 76 | P_4') population=clustered.AND.cap_color=white 77 | 78 | These rule involve 6 attributes (out of 22). Rules for edible 79 | mushrooms are obtained as negation of the rules given above, for 80 | example the rule: 81 | 82 | odor=(almond.OR.anise.OR.none).AND.spore-print-color=NOT.green 83 | 84 | gives 48 errors, or 99.41% accuracy on the whole dataset. 85 | 86 | Several slightly more complex variations on these rules exist, 87 | involving other attributes, such as gill_size, gill_spacing, 88 | stalk_surface_above_ring, but the rules given above are the simplest 89 | we have found. 90 | 91 | 92 | 4. Relevant Information: 93 | This data set includes descriptions of hypothetical samples 94 | corresponding to 23 species of gilled mushrooms in the Agaricus and 95 | Lepiota Family (pp. 500-525). Each species is identified as 96 | definitely edible, definitely poisonous, or of unknown edibility and 97 | not recommended. This latter class was combined with the poisonous 98 | one. The Guide clearly states that there is no simple rule for 99 | determining the edibility of a mushroom; no rule like ``leaflets 100 | three, let it be'' for Poisonous Oak and Ivy. 101 | 102 | 5. Number of Instances: 8124 103 | 104 | 6. Number of Attributes: 22 (all nominally valued) 105 | 106 | 7. Attribute Information: (classes: edible=e, poisonous=p) 107 | 1. cap-shape: bell=b,conical=c,convex=x,flat=f, 108 | knobbed=k,sunken=s 109 | 2. cap-surface: fibrous=f,grooves=g,scaly=y,smooth=s 110 | 3. cap-color: brown=n,buff=b,cinnamon=c,gray=g,green=r, 111 | pink=p,purple=u,red=e,white=w,yellow=y 112 | 4. bruises?: bruises=t,no=f 113 | 5. odor: almond=a,anise=l,creosote=c,fishy=y,foul=f, 114 | musty=m,none=n,pungent=p,spicy=s 115 | 6. gill-attachment: attached=a,descending=d,free=f,notched=n 116 | 7. gill-spacing: close=c,crowded=w,distant=d 117 | 8. gill-size: broad=b,narrow=n 118 | 9. gill-color: black=k,brown=n,buff=b,chocolate=h,gray=g, 119 | green=r,orange=o,pink=p,purple=u,red=e, 120 | white=w,yellow=y 121 | 10. stalk-shape: enlarging=e,tapering=t 122 | 11. stalk-root: bulbous=b,club=c,cup=u,equal=e, 123 | rhizomorphs=z,rooted=r,missing=? 124 | 12. stalk-surface-above-ring: fibrous=f,scaly=y,silky=k,smooth=s 125 | 13. stalk-surface-below-ring: fibrous=f,scaly=y,silky=k,smooth=s 126 | 14. stalk-color-above-ring: brown=n,buff=b,cinnamon=c,gray=g,orange=o, 127 | pink=p,red=e,white=w,yellow=y 128 | 15. stalk-color-below-ring: brown=n,buff=b,cinnamon=c,gray=g,orange=o, 129 | pink=p,red=e,white=w,yellow=y 130 | 16. veil-type: partial=p,universal=u 131 | 17. veil-color: brown=n,orange=o,white=w,yellow=y 132 | 18. ring-number: none=n,one=o,two=t 133 | 19. ring-type: cobwebby=c,evanescent=e,flaring=f,large=l, 134 | none=n,pendant=p,sheathing=s,zone=z 135 | 20. spore-print-color: black=k,brown=n,buff=b,chocolate=h,green=r, 136 | orange=o,purple=u,white=w,yellow=y 137 | 21. population: abundant=a,clustered=c,numerous=n, 138 | scattered=s,several=v,solitary=y 139 | 22. habitat: grasses=g,leaves=l,meadows=m,paths=p, 140 | urban=u,waste=w,woods=d 141 | 142 | 8. Missing Attribute Values: 2480 of them (denoted by "?"), all for 143 | attribute #11. 144 | 145 | 9. Class Distribution: 146 | -- edible: 4208 (51.8%) 147 | -- poisonous: 3916 (48.2%) 148 | -- total: 8124 instances 149 | -------------------------------------------------------------------------------- /data/all_160_in_51.P35.csv: -------------------------------------------------------------------------------- 1 | GEOID,SUMLEV,STATE,COUNTY,CBSA,CSA,NECTA,CNECTA,NAME,POP100,HU100,POP100.2000,HU100.2000,P035001,P035001.2000 2 | 5100148,160,51,,,,,,Abingdon town,8191,4271,7780,3788,2056,2091 3 | 5100180,160,51,,,,,,Accomac town,519,229,547,235,117,126 4 | 5100724,160,51,,,,,,Alberta town,298,163,306,158,77,86 5 | 5101000,160,51,,,,,,Alexandria city,139966,72376,128283,64251,30978,27749 6 | 5101256,160,51,,,,,,Allisonia CDP,117,107,,,32, 7 | 5101528,160,51,,,,,,Altavista town,3450,1669,3425,1650,928,940 8 | 5101640,160,51,,,,,,Amelia Court House CDP,1099,419,,,273, 9 | 5101672,160,51,,,,,,Amherst town,2231,1032,2251,1000,550,569 10 | 5101912,160,51,,,,,,Annandale CDP,41008,14715,54994,20243,9790,14090 11 | 5102040,160,51,,,,,,Appalachia town,1754,879,1839,891,482,515 12 | 5102064,160,51,,,,,,Apple Mountain Lake CDP,1396,501,,,355, 13 | 5102072,160,51,,,,,,Appomattox town,1733,849,1761,767,441,470 14 | 5102112,160,51,,,,,,Aquia Harbour CDP,6727,2300,7856,2622,1914,2228 15 | 5102248,160,51,,,,,,Arcola CDP,233,96,,,59, 16 | 5103208,160,51,,,,,,Arrington CDP,708,309,,,199, 17 | 5103320,160,51,,,,,,Ashburn CDP,43511,15795,,,11466, 18 | 5103368,160,51,,,,,,Ashland town,7225,2863,6619,2445,1540,1454 19 | 5103512,160,51,,,,,,Atkins CDP,1143,584,1138,571,323,330 20 | 5103528,160,51,,,,,,Atlantic CDP,862,419,,,248, 21 | 5103608,160,51,,,,,,Augusta Springs CDP,257,122,,,75, 22 | 5104088,160,51,,,,,,Bailey's Crossroads CDP,23643,9682,23166,8813,5102,4968 23 | 5104856,160,51,,,,,,Baskerville CDP,128,60,,,38, 24 | 5104872,160,51,,,,,,Bassett CDP,1100,607,1338,601,279,338 25 | 5104920,160,51,,,,,,Basye CDP,1253,1646,,,388, 26 | 5105200,160,51,,,,,,Bayside CDP,120,71,,,35, 27 | 5105336,160,51,,,,,,Bealeton CDP,4435,1549,,,1097, 28 | 5105544,160,51,,,,,,Bedford city,6222,2920,6299,2702,1592,1593 29 | 5105928,160,51,,,,,,Belle Haven CDP,6518,3240,6269,3220,1610,1571 30 | 5106216,160,51,,,,,,Bellwood CDP,6352,2705,5974,2448,1555,1598 31 | 5106275,160,51,,,,,,Belmont CDP,5966,1870,,,1615, 32 | 5106336,160,51,,,,,,Belmont Estates CDP,1263,507,,,409, 33 | 5106424,160,51,,,,,,Belspring CDP,256,121,,,69, 34 | 5106512,160,51,,,,,,Belview CDP,891,436,,,251, 35 | 5106712,160,51,,,,,,Benns Church CDP,872,361,,,239, 36 | 5106728,160,51,,,,,,Bensley CDP,5819,2381,5435,2368,1350,1408 37 | 5106968,160,51,,,,,,Berryville town,4185,1804,2963,1312,1073,783 38 | 5107160,160,51,,,,,,Bethel Manor CDP,3792,1222,,,1000, 39 | 5107400,160,51,,,,,,Big Island CDP,303,153,,,93, 40 | 5107480,160,51,,,,,,Big Stone Gap town,5614,2052,4856,2197,1194,1332 41 | 5107784,160,51,,,,,,Blacksburg town,42620,15342,39573,13732,4668,4779 42 | 5107944,160,51,,,,,,Blairs CDP,916,413,,,273, 43 | 5107976,160,51,,,,,,Bland CDP,409,222,,,115, 44 | 5108120,160,51,,,,,,Bloxom town,387,184,395,175,99,99 45 | 5108200,160,51,,,,,,Blue Ridge CDP,3084,1269,3188,1219,965,969 46 | 5108264,160,51,,,,,,Blue Ridge Shores CDP,813,566,,,231, 47 | 5108320,160,51,,,,,,Bobtown CDP,211,143,,,67, 48 | 5108675,160,51,,,,,,Boston CDP,504,229,,,128, 49 | 5108708,160,51,,,,,,Boswell's Corner CDP,1375,522,,,339, 50 | 5108984,160,51,,,,,,Boyce town,589,252,426,168,165,114 51 | 5109064,160,51,,,,,,Bracey CDP,1554,2072,,,495, 52 | 5109188,160,51,,,,,,Brambleton CDP,9845,3265,,,2541, 53 | 5109208,160,51,,,,,,Branchville town,114,52,123,56,34,36 54 | 5109248,160,51,,,,,,Brandermill CDP,13173,5747,,,3666, 55 | 5109656,160,51,,,,,,Bridgewater town,5644,2120,5203,1850,1278,1201 56 | 5109752,160,51,,,,,,Brightwood CDP,1001,409,,,295, 57 | 5109816,160,51,,,,,,Bristol city,17835,8831,17367,8469,4760,4795 58 | 5109952,160,51,,,,,,Broadlands CDP,12313,3823,,,3161, 59 | 5110040,160,51,,,,,,Broadway town,3691,1560,2192,976,1024,610 60 | 5110072,160,51,,,,,,Brodnax town,298,144,317,139,88,80 61 | 5110296,160,51,,,,,,Brookneal town,1112,567,1259,580,290,326 62 | 5110744,160,51,,,,,,Buchanan town,1178,608,1233,579,331,359 63 | 5110776,160,51,,,,,,Buckhall CDP,16293,5325,,,4261, 64 | 5110856,160,51,,,,,,Buckingham Courthouse CDP,133,72,,,37, 65 | 5111032,160,51,,,,,,Buena Vista city,6650,2936,6349,2716,1726,1749 66 | 5111230,160,51,,,,,,Bull Run CDP,14983,5946,11337,4948,3334,2711 67 | 5111245,160,51,,,,,,Bull Run Mountain Estates CDP,1251,484,,,349, 68 | 5111464,160,51,,,,,,Burke CDP,41055,13884,57737,19367,11528,15751 69 | 5111470,160,51,,,,,,Burke Centre CDP,17326,6460,,,4711, 70 | 5112136,160,51,,,,,,Callaghan CDP,348,183,,,74, 71 | 5112264,160,51,,,,,,Calverton CDP,239,119,,,61, 72 | 5112590,160,51,,,,,,Camptown CDP,766,356,,,193, 73 | 5112600,160,51,,,,,,Cana CDP,1254,624,1228,576,375,363 74 | 5112904,160,51,,,,,,Capron town,166,70,167,79,40,45 75 | 5112915,160,51,,,,,,Captains Cove CDP,1042,844,,,341, 76 | 5113160,160,51,,,,,,Carrollton CDP,4574,1895,,,1317, 77 | 5113192,160,51,,,,,,Carrsville CDP,359,172,,,99, 78 | 5113403,160,51,,,,,,Cascades CDP,11912,4495,,,3146, 79 | 5113512,160,51,,,,,,Castlewood CDP,2045,937,2036,950,587,637 80 | 5113624,160,51,,,,,,Catlett CDP,296,125,,,74, 81 | 5113635,160,51,,,,,,Cats Bridge CDP,229,122,,,63, 82 | 5113720,160,51,,,,,,Cave Spring CDP,24922,11832,24941,11556,6976,7085 83 | 5113784,160,51,,,,,,Cedar Bluff town,1137,573,1085,535,324,312 84 | 5114312,160,51,,,,,,Central Garage CDP,1318,520,,,383, 85 | 5114440,160,51,,,,,,Centreville CDP,71135,25516,48661,18176,18075,12099 86 | 5114544,160,51,,,,,,Chamberlayne CDP,5456,2345,4380,1916,1566,1353 87 | 5114744,160,51,,,,,,Chantilly CDP,23039,7403,41041,15173,5939,10519 88 | 5114904,160,51,,,,,,Charles City CDP,133,67,,,34, 89 | 5114984,160,51,,,,,,Chase City town,2351,1210,2457,1249,618,658 90 | 5114995,160,51,,,,,,Chase Crossing CDP,377,128,,,85, 91 | 5115048,160,51,,,,,,Chatmoss CDP,1698,784,1742,715,546,550 92 | 5115176,160,51,,,,,,Cherry Hill CDP,16000,5587,,,3872, 93 | 5116000,160,51,,,,,,Chesapeake city,222209,83196,199184,72672,59927,54158 94 | 5116096,160,51,,,,,,Chester CDP,20987,8320,17890,6951,5819,5116 95 | 5116240,160,51,,,,,,Chester Gap CDP,839,350,,,231, 96 | 5116480,160,51,,,,,,Chilhowie town,1781,790,1827,775,447,462 97 | 5116512,160,51,,,,,,Chincoteague town,2941,4517,4317,3970,867,1244 98 | 5116736,160,51,,,,,,Churchville CDP,194,90,,,54, 99 | 5116880,160,51,,,,,,Claremont town,378,217,343,240,110,100 100 | 5116992,160,51,,,,,,Clarksville town,1139,768,1329,753,314,380 101 | 5117120,160,51,,,,,,Claypool Hill CDP,1776,770,1719,760,540,565 102 | 5117296,160,51,,,,,,Cleveland town,202,116,148,113,47,44 103 | 5117440,160,51,,,,,,Clifton Forge town,3884,2004,4289,2069,982,1147 104 | 5117504,160,51,,,,,,Clinchco town,337,197,424,226,86,114 105 | 5117536,160,51,,,,,,Clinchport town,70,38,77,38,17,19 106 | 5117552,160,51,,,,,,Clintwood town,1414,710,1549,756,386,427 107 | 5117632,160,51,,,,,,Clover CDP,438,226,,,117, 108 | 5117776,160,51,,,,,,Cluster Springs CDP,811,387,,,238, 109 | 5117952,160,51,,,,,,Coeburn town,2139,962,1996,923,568,576 110 | 5118352,160,51,,,,,,Collinsville CDP,7335,3765,7777,3758,2017,2199 111 | 5118448,160,51,,,,,,Colonial Heights city,17411,7831,16897,7340,4682,4720 112 | 5118624,160,51,,,,,,Columbia town,83,30,49,22,19,13 113 | 5118880,160,51,,,,,,Concord CDP,1458,619,,,427, 114 | 5119560,160,51,,,,,,Countryside CDP,10072,3698,,,2609, 115 | 5119571,160,51,,,,,,County Center CDP,3270,1137,,,904, 116 | 5119728,160,51,,,,,,Covington city,5961,3067,6303,3195,1559,1742 117 | 5120160,160,51,,,,,,Crewe town,2326,1078,2378,1074,605,646 118 | 5120436,160,51,,,,,,Crosspointe CDP,5802,1806,,,1676, 119 | 5120560,160,51,,,,,,Crozet CDP,5565,2229,2820,1041,1522,757 120 | 5120752,160,51,,,,,,Culpeper town,16379,6271,9664,4139,3861,2444 121 | 5120768,160,51,,,,,,Cumberland CDP,393,178,,,108, 122 | 5121008,160,51,,,,,,Dahlgren CDP,2653,1184,997,510,702,261 123 | 5121016,160,51,,,,,,Dahlgren Center CDP,599,192,,,109, 124 | 5121088,160,51,,,,,,Dale City CDP,65969,20922,55971,18171,15888,14336 125 | 5121152,160,51,,,,,,Daleville CDP,2557,1154,1454,573,741,477 126 | 5121312,160,51,,,,,,Dante CDP,649,367,,,179, 127 | 5121344,160,51,,,,,,Danville city,43055,22438,48411,23108,11082,12931 128 | 5121776,160,51,,,,,,Deep Creek CDP,115,84,,,33, 129 | 5121872,160,51,,,,,,Deerfield CDP,132,78,,,39, 130 | 5122064,160,51,,,,,,Deltaville CDP,1119,1212,,,343, 131 | 5122976,160,51,,,,,,Dooms CDP,1327,629,1282,553,382,387 132 | 5123392,160,51,,,,,,Dranesville CDP,11921,3895,,,3351, 133 | 5123408,160,51,,,,,,Draper CDP,320,153,,,102, 134 | 5123584,160,51,,,,,,Dryden CDP,1208,518,1253,507,299,330 135 | 5123648,160,51,,,,,,Dublin town,2534,943,2288,969,493,538 136 | 5123680,160,51,,,,,,Duffield town,91,47,62,30,30,20 137 | 5123732,160,51,,,,,,Dulles Town Center CDP,4601,1797,,,1118, 138 | 5123744,160,51,,,,,,Dumbarton CDP,7879,3911,6674,3782,1730,1509 139 | 5123760,160,51,,,,,,Dumfries town,4961,1689,4937,1699,1146,1198 140 | 5123952,160,51,,,,,,Dungannon town,332,179,317,149,96,91 141 | 5124544,160,51,,,,,,East Lexington CDP,1463,688,,,318, 142 | 5124752,160,51,,,,,,Eastville town,305,79,203,75,46,43 143 | 5124816,160,51,,,,,,Ebony CDP,161,85,,,43, 144 | 5125008,160,51,,,,,,Edinburg town,1041,543,813,425,275,221 145 | 5125408,160,51,,,,,,Elkton town,2726,1314,2042,919,719,556 146 | 5125488,160,51,,,,,,Elliston CDP,902,386,,,238, 147 | 5125792,160,51,,,,,,Emory CDP,1251,310,,,179, 148 | 5125808,160,51,,,,,,Emporia city,5927,2565,5665,2412,1440,1406 149 | 5125877,160,51,,,,,,Enon CDP,3466,1626,,,980, 150 | 5125968,160,51,,,,,,Esmont CDP,528,243,,,142, 151 | 5126128,160,51,,,,,,Ettrick CDP,6682,1746,5627,1673,1010,989 152 | 5126496,160,51,,,,,,Fairfax city,22565,8680,21498,8204,5545,5407 153 | 5126592,160,51,,,,,,Fairfax Station CDP,12030,4140,,,3497, 154 | 5126701,160,51,,,,,,Fair Lakes CDP,7942,3358,,,1884, 155 | 5126736,160,51,,,,,,Fairlawn CDP,2367,1193,2211,1065,674,632 156 | 5126875,160,51,,,,,,Fair Oaks CDP,30223,14367,,,7331, 157 | 5126944,160,51,,,,,,Fairview CDP,240,69,,,39, 158 | 5127040,160,51,,,,,,Fairview Beach CDP,391,312,230,222,100,63 159 | 5127200,160,51,,,,,,Falls Church city,12332,5489,10377,4725,3199,2622 160 | 5128496,160,51,,,,,,Flint Hill CDP,209,124,,,61, 161 | 5128528,160,51,,,,,,Floris CDP,8375,2562,,,2308, 162 | 5128688,160,51,,,,,,Forest CDP,9106,3922,8006,3294,2586,2292 163 | 5129008,160,51,,,,,,Fort Belvoir CDP,7100,2018,7176,2056,1700,1867 164 | 5129040,160,51,,,,,,Fort Chiswell CDP,939,417,911,380,271,264 165 | 5129136,160,51,,,,,,Fort Hunt CDP,16045,6113,12923,5050,4695,3911 166 | 5129552,160,51,,,,,,Franconia CDP,18245,7627,31907,13509,4518,8186 167 | 5129628,160,51,,,,,,Franklin Farm CDP,19288,6197,,,5459, 168 | 5129744,160,51,,,,,,Fredericksburg city,24286,10467,19279,8888,4854,3925 169 | 5129840,160,51,,,,,,Free Union CDP,193,82,,,55, 170 | 5129920,160,51,,,,,,Fries town,484,340,614,337,144,177 171 | 5129968,160,51,,,,,,Front Royal town,14440,6184,13589,5752,3647,3584 172 | 5130208,160,51,,,,,,Galax city,7042,3252,6837,3217,1801,1845 173 | 5130384,160,51,,,,,,Gargatha CDP,381,187,,,109, 174 | 5130480,160,51,,,,,,Gasburg CDP,481,636,,,155, 175 | 5130496,160,51,,,,,,Gate City town,2034,1087,2159,1119,561,604 176 | 5130618,160,51,,,,,,George Mason CDP,9496,1730,,,1260, 177 | 5131056,160,51,,,,,,Glade Spring town,1456,670,1374,626,411,403 178 | 5131200,160,51,,,,,,Glen Allen CDP,14774,6241,12562,5297,4021,3505 179 | 5131376,160,51,,,,,,Glen Lyn town,115,58,151,62,27,39 180 | 5131488,160,51,,,,,,Glenvar CDP,976,459,,,174, 181 | 5131616,160,51,,,,,,Gloucester Point CDP,9402,4257,9429,4071,2674,2715 182 | 5131808,160,51,,,,,,Goochland CDP,861,338,,,232, 183 | 5131968,160,51,,,,,,Goshen town,361,192,406,214,98,108 184 | 5132320,160,51,,,,,,Gratton CDP,937,412,,,290, 185 | 5132496,160,51,,,,,,Great Falls CDP,15427,5179,8549,2852,4439,2466 186 | 5132560,160,51,,,,,,Greenbackville CDP,192,145,,,57, 187 | 5132592,160,51,,,,,,Greenbriar CDP,8166,3224,,,2145, 188 | 5132624,160,51,,,,,,Greenbush CDP,220,96,,,58, 189 | 5132944,160,51,,,,,,Greenville CDP,832,259,886,251,178,194 190 | 5133232,160,51,,,,,,Gretna town,1267,686,1257,635,332,326 191 | 5133488,160,51,,,,,,Grottoes town,2668,1135,2114,894,738,593 192 | 5133584,160,51,,,,,,Groveton CDP,14598,5634,21296,8275,3538,5297 193 | 5133648,160,51,,,,,,Grundy town,1021,465,1105,519,210,250 194 | 5133824,160,51,,,,,,Gwynn CDP,602,654,,,183, 195 | 5134064,160,51,,,,,,Halifax town,1309,605,1389,583,331,349 196 | 5134176,160,51,,,,,,Hallwood town,206,108,290,121,51,73 197 | 5134304,160,51,,,,,,Hampden-Sydney CDP,1450,197,1264,184,108,118 198 | 5135000,160,51,,,,,,Hampton city,137436,59566,146437,57311,35061,35911 199 | 5135160,160,51,,,,,,Hanover CDP,252,117,,,66, 200 | 5135240,160,51,,,,,,Harborton CDP,131,94,,,40, 201 | 5135624,160,51,,,,,,Harrisonburg city,48914,17444,40468,13689,7515,6442 202 | 5135640,160,51,,,,,,Harriston CDP,909,369,,,248, 203 | 5135912,160,51,,,,,,Hayfield CDP,3909,1465,,,1115, 204 | 5135976,160,51,,,,,,Haymarket town,1782,621,879,337,460,235 205 | 5136008,160,51,,,,,,Haysi town,498,128,186,99,65,56 206 | 5136216,160,51,,,,,,Heathsville CDP,142,102,,,41, 207 | 5136445,160,51,,,,,,Henry Fork CDP,1234,551,,,314, 208 | 5136648,160,51,,,,,,Herndon town,23292,7813,21655,7190,5357,4968 209 | 5137032,160,51,,,,,,Highland Springs CDP,15711,6621,15137,6040,4157,4132 210 | 5137288,160,51,,,,,,Hillsboro town,80,38,96,41,25,28 211 | 5137544,160,51,,,,,,Hiwassee CDP,264,192,,,77, 212 | 5138032,160,51,,,,,,Hollymead CDP,7690,3013,,,2077, 213 | 5138424,160,51,,,,,,Hopewell city,22591,10121,22354,9749,5877,6073 214 | 5138504,160,51,,,,,,Horntown CDP,574,1142,,,169, 215 | 5138552,160,51,,,,,,Horse Pasture CDP,2227,1026,2255,1021,629,674 216 | 5138632,160,51,,,,,,Hot Springs CDP,738,571,,,176, 217 | 5139224,160,51,,,,,,Hurt town,1304,642,1276,592,387,386 218 | 5139304,160,51,,,,,,Hybla Valley CDP,15801,6060,16721,6515,3672,4214 219 | 5139448,160,51,,,,,,Idylwood CDP,17288,7138,16005,6727,4177,3833 220 | 5139544,160,51,,,,,,Independent Hill CDP,7419,2286,,,2023, 221 | 5139920,160,51,,,,,,Innsbrook CDP,7753,3332,,,1969, 222 | 5140024,160,51,,,,,,Iron Gate town,388,183,404,197,107,122 223 | 5140088,160,51,,,,,,Irvington town,432,374,673,325,142,175 224 | 5140216,160,51,,,,,,Ivanhoe CDP,551,263,,,154, 225 | 5140232,160,51,,,,,,Ivor town,339,156,320,152,99,100 226 | 5140248,160,51,,,,,,Ivy CDP,905,378,,,262, 227 | 5140536,160,51,,,,,,Jarratt town,638,304,589,293,176,176 228 | 5141144,160,51,,,,,,Jolivue CDP,1129,601,1037,594,269,249 229 | 5141272,160,51,,,,,,Jonesville town,1034,606,995,565,268,262 230 | 5142104,160,51,,,,,,Keokee CDP,416,188,316,147,110,89 231 | 5142264,160,51,,,,,,Keysville town,832,401,817,398,192,195 232 | 5142424,160,51,,,,,,Kilmarnock town,1487,810,1244,607,343,305 233 | 5142536,160,51,,,,,,King and Queen Court House CDP,85,54,,,24, 234 | 5142568,160,51,,,,,,King George CDP,4457,1681,,,1155, 235 | 5142664,160,51,,,,,,Kings Park CDP,4333,1453,,,1132, 236 | 5142680,160,51,,,,,,Kings Park West CDP,13390,4439,,,3533, 237 | 5142746,160,51,,,,,,Kingstowne CDP,15556,7048,,,3979, 238 | 5142792,160,51,,,,,,King William CDP,252,111,,,69, 239 | 5143176,160,51,,,,,,La Crosse town,604,299,618,314,148,161 240 | 5143224,160,51,,,,,,Lafayette CDP,449,210,,,127, 241 | 5143352,160,51,,,,,,Lake Barcroft CDP,9558,3731,8906,3673,2457,2416 242 | 5143359,160,51,,,,,,Lake Caroline CDP,2260,1035,,,621, 243 | 5143392,160,51,,,,,,Lake Holiday CDP,1905,844,,,551, 244 | 5143420,160,51,,,,,,Lake Land'Or CDP,4223,1639,,,1120, 245 | 5143424,160,51,,,,,,Lake Monticello CDP,9920,4265,6852,2950,2993,2196 246 | 5143430,160,51,,,,,,Lake of the Woods CDP,7177,3631,,,2253, 247 | 5143432,160,51,,,,,,Lake Ridge CDP,41058,15678,30404,11265,10745,8102 248 | 5143464,160,51,,,,,,Lakeside CDP,11849,5680,11157,5177,2871,2908 249 | 5143600,160,51,,,,,,Lake Wilderness CDP,2669,899,,,698, 250 | 5144048,160,51,,,,,,Lansdowne CDP,11253,4421,,,2956, 251 | 5144280,160,51,,,,,,Laurel CDP,16713,7268,14875,6522,3858,3633 252 | 5144430,160,51,,,,,,Laurel Hill CDP,6855,2312,,,1759, 253 | 5144476,160,51,,,,,,Laurel Park CDP,675,332,781,342,198,231 254 | 5144620,160,51,,,,,,Laymantown CDP,1979,787,2034,794,615,653 255 | 5144952,160,51,,,,,,Lee Mont CDP,125,60,,,32, 256 | 5144984,160,51,,,,,,Leesburg town,42616,15119,28311,10671,10522,7258 257 | 5145512,160,51,,,,,,Lexington city,7042,2546,6867,2376,1028,1080 258 | 5145784,160,51,,,,,,Lincolnia CDP,22855,8555,15788,5255,5407,3705 259 | 5145957,160,51,,,,,,Linton Hall CDP,35725,10633,8620,2851,9021,2349 260 | 5146328,160,51,,,,,,Loch Lomond CDP,3701,1081,3411,1063,817,866 261 | 5146760,160,51,,,,,,Long Branch CDP,7593,2652,,,2084, 262 | 5147064,160,51,,,,,,Lorton CDP,18610,6726,17786,5892,4637,3883 263 | 5147136,160,51,,,,,,Loudoun Valley Estates CDP,3656,1025,,,948, 264 | 5147144,160,51,,,,,,Louisa town,1555,750,1401,620,343,331 265 | 5147208,160,51,,,,,,Lovettsville town,1613,599,853,325,424,230 266 | 5147224,160,51,,,,,,Lovingston CDP,520,262,,,114, 267 | 5147296,160,51,,,,,,Lowes Island CDP,10756,3627,,,2968, 268 | 5147352,160,51,,,,,,Low Moor CDP,258,133,367,161,77,106 269 | 5147496,160,51,,,,,,Lunenburg CDP,165,69,,,52, 270 | 5147528,160,51,,,,,,Luray town,4895,2270,4871,2191,1287,1332 271 | 5147672,160,51,,,,,,Lynchburg city,75568,31992,65269,27640,16368,15588 272 | 5147720,160,51,,,,,,Lyndhurst CDP,1490,633,1527,602,427,447 273 | 5148376,160,51,,,,,,McLean CDP,48115,17756,38929,14735,13453,11051 274 | 5148445,160,51,,,,,,McMullin CDP,464,208,,,144, 275 | 5148450,160,51,,,,,,McNair CDP,17513,7823,,,4332, 276 | 5148488,160,51,,,,,,Madison town,229,107,210,115,54,57 277 | 5148520,160,51,,,,,,Madison Heights CDP,11285,4840,11584,4656,3040,3181 278 | 5148776,160,51,,,,,,Makemie Park CDP,155,72,,,38, 279 | 5148952,160,51,,,,,,Manassas city,37821,13123,35135,12114,8895,8437 280 | 5148968,160,51,,,,,,Manassas Park city,14273,4904,10290,3365,3212,2558 281 | 5148996,160,51,,,,,,Manchester CDP,10804,4821,,,2767, 282 | 5149144,160,51,,,,,,Mantua CDP,7135,2766,7485,2723,1936,1938 283 | 5149320,160,51,,,,,,Mappsburg CDP,60,28,,,19, 284 | 5149336,160,51,,,,,,Mappsville CDP,440,167,,,93, 285 | 5149464,160,51,,,,,,Marion town,5968,2822,6349,2865,1484,1614 286 | 5149656,160,51,,,,,,Marshall CDP,1480,578,,,359, 287 | 5149792,160,51,,,,,,Marumsco CDP,35036,11975,,,7794, 288 | 5149998,160,51,,,,,,Mason Neck CDP,2005,800,,,584, 289 | 5150020,160,51,,,,,,Massanetta Springs CDP,4833,1999,,,1336, 290 | 5150030,160,51,,,,,,Massanutten CDP,2291,2692,1945,1051,676,583 291 | 5150104,160,51,,,,,,Mathews CDP,555,272,,,123, 292 | 5150136,160,51,,,,,,Matoaca CDP,2403,991,2273,911,656,651 293 | 5150200,160,51,,,,,,Maurertown CDP,770,337,,,203, 294 | 5150312,160,51,,,,,,Max Meadows CDP,562,261,512,235,171,154 295 | 5150568,160,51,,,,,,Meadowbrook CDP,18312,7103,,,4842, 296 | 5150776,160,51,,,,,,Meadow View CDP,967,455,,,262, 297 | 5150856,160,51,,,,,,Mechanicsville CDP,36348,14267,30464,11915,10189,8831 298 | 5151192,160,51,,,,,,Merrifield CDP,15212,6477,11170,4534,3588,2725 299 | 5151208,160,51,,,,,,Merrimac CDP,2133,1142,1751,934,426,354 300 | 5151362,160,51,,,,,,Metompkin CDP,551,291,,,117, 301 | 5151432,160,51,,,,,,Middlebrook CDP,213,101,,,65, 302 | 5151512,160,51,,,,,,Middletown town,1265,556,1015,432,332,281 303 | 5151544,160,51,,,,,,Midland CDP,218,94,,,51, 304 | 5152120,160,51,,,,,,Mineral town,467,204,424,196,119,116 305 | 5152408,160,51,,,,,,Modest Town CDP,149,78,,,42, 306 | 5152658,160,51,,,,,,Montclair CDP,19570,6831,15728,5184,5467,4326 307 | 5152680,160,51,,,,,,Monterey town,147,121,158,141,46,44 308 | 5152904,160,51,,,,,,Montrose CDP,7993,3579,7018,3081,2048,1851 309 | 5152968,160,51,,,,,,Montvale CDP,698,328,,,195, 310 | 5153031,160,51,,,,,,Moorefield Station CDP,77,91,,,20, 311 | 5153480,160,51,,,,,,Motley CDP,1015,490,,,303, 312 | 5153584,160,51,,,,,,Mountain Road CDP,1100,529,,,331, 313 | 5153864,160,51,,,,,,Mount Crawford town,433,201,254,109,124,74 314 | 5153944,160,51,,,,,,Mount Hermon CDP,3966,1676,,,1228, 315 | 5154120,160,51,,,,,,Mount Sidney CDP,663,288,,,193, 316 | 5154904,160,51,,,,,,Narrows town,2029,941,2111,971,582,601 317 | 5154984,160,51,,,,,,Nassawadox town,499,239,572,207,106,121 318 | 5155000,160,51,,,,,,Nathalie CDP,183,93,,,50, 319 | 5155272,160,51,,,,,,Neabsco CDP,12068,4114,,,3061, 320 | 5155400,160,51,,,,,,Nellysford CDP,1076,702,,,396, 321 | 5155448,160,51,,,,,,Nelsonia CDP,523,215,,,131, 322 | 5155528,160,51,,,,,,New Baltimore CDP,8119,2772,,,2299, 323 | 5155592,160,51,,,,,,New Castle town,153,84,179,93,39,51 324 | 5155608,160,51,,,,,,New Church CDP,205,112,,,64, 325 | 5155720,160,51,,,,,,New Hope CDP,797,318,,,243, 326 | 5155758,160,51,,,,,,Newington Forest CDP,12442,4338,,,3374, 327 | 5155800,160,51,,,,,,New Kent CDP,239,83,,,73, 328 | 5156000,160,51,,,,,,Newport News city,180719,76198,180150,74117,44887,46358 329 | 5156048,160,51,,,,,,New River CDP,244,130,,,78, 330 | 5156096,160,51,,,,,,Newsoms town,321,163,282,141,90,78 331 | 5156304,160,51,,,,,,Nickelsville town,383,204,448,210,114,118 332 | 5156464,160,51,,,,,,Nokesville CDP,1354,511,1236,462,382,364 333 | 5157000,160,51,,,,,,Norfolk city,242803,95018,234403,94416,50756,51915 334 | 5157531,160,51,,,,,,North Shore CDP,3094,2950,2112,1919,1078,748 335 | 5157560,160,51,,,,,,North Springfield CDP,7274,2480,9173,3291,1791,2471 336 | 5157688,160,51,,,,,,Norton city,3958,1945,3904,1946,999,1067 337 | 5157870,160,51,,,,,,Nottoway Court House CDP,84,40,,,23, 338 | 5158104,160,51,,,,,,Oak Grove CDP,1777,540,,,397, 339 | 5158184,160,51,,,,,,Oak Hall CDP,255,124,,,74, 340 | 5158312,160,51,,,,,,Oak Level CDP,857,439,885,465,253,278 341 | 5158472,160,51,,,,,,Oakton CDP,34166,13691,29348,11392,8882,7648 342 | 5159336,160,51,,,,,,Onancock town,1263,753,1525,733,334,393 343 | 5159416,160,51,,,,,,Opal CDP,691,232,,,185, 344 | 5159496,160,51,,,,,,Orange town,4721,1991,4123,1712,1058,1010 345 | 5160296,160,51,,,,,,Painter town,229,113,246,117,56,70 346 | 5160392,160,51,,,,,,Palmyra CDP,104,55,,,28, 347 | 5160500,160,51,,,,,,Pantops CDP,3027,1860,,,664, 348 | 5160840,160,51,,,,,,Parrott CDP,435,228,,,131, 349 | 5160888,160,51,,,,,,Passapatanzy CDP,1283,439,,,329, 350 | 5160920,160,51,,,,,,Pastoria CDP,649,295,,,173, 351 | 5161208,160,51,,,,,,Pearisburg town,2786,1349,2729,1279,775,790 352 | 5161336,160,51,,,,,,Pembroke town,1128,555,1134,520,319,317 353 | 5161464,160,51,,,,,,Penhook CDP,801,961,726,694,266,244 354 | 5161832,160,51,,,,,,Petersburg city,32420,16326,33740,15955,7697,8508 355 | 5161896,160,51,,,,,,Phenix town,226,117,200,94,64,62 356 | 5162738,160,51,,,,,,Piney Mountain CDP,1130,452,,,297, 357 | 5163190,160,51,,,,,,Plum Creek CDP,1524,664,,,418, 358 | 5163768,160,51,,,,,,Poquoson city,12150,4726,11566,4300,3582,3370 359 | 5164000,160,51,,,,,,Portsmouth city,95535,40806,100565,41605,23987,25482 360 | 5164152,160,51,,,,,,Potomac Mills CDP,5614,1763,,,1335, 361 | 5164272,160,51,,,,,,Pound town,1037,502,1089,516,298,322 362 | 5164512,160,51,,,,,,Prices Fork CDP,1066,470,,,280, 363 | 5164560,160,51,,,,,,Prince George CDP,2066,892,,,564, 364 | 5164976,160,51,,,,,,Pungoteague CDP,347,160,,,97, 365 | 5165120,160,51,,,,,,Quantico town,480,308,561,359,105,108 366 | 5165128,160,51,,,,,,Quantico Base CDP,4452,1071,,,1033, 367 | 5165280,160,51,,,,,,Quinby CDP,282,205,,,85, 368 | 5165744,160,51,,,,,,Raven CDP,2270,1081,2593,1219,653,775 369 | 5165776,160,51,,,,,,Ravensworth CDP,2466,857,,,648, 370 | 5166672,160,51,,,,,,Reston CDP,58404,26787,56407,24210,14809,14489 371 | 5166896,160,51,,,,,,Rich Creek town,774,326,665,312,184,187 372 | 5166928,160,51,,,,,,Richlands town,5823,2860,4144,2137,1632,1223 373 | 5167000,160,51,,,,,,Richmond city,204214,98349,197790,92282,41304,43649 374 | 5167256,160,51,,,,,,Riner CDP,859,353,,,258, 375 | 5167331,160,51,,,,,,Rivanna CDP,1860,780,,,606, 376 | 5167352,160,51,,,,,,Riverdale CDP,956,486,,,283, 377 | 5167704,160,51,,,,,,Riverview CDP,782,325,,,219, 378 | 5168000,160,51,,,,,,Roanoke city,97032,47453,94911,45257,23487,24255 379 | 5168470,160,51,,,,,,Rockwood CDP,8431,3423,,,2457, 380 | 5168880,160,51,,,,,,Rose Hill CDP,20226,7447,15058,5783,5172,4081 381 | 5168885,160,51,,,,,,Rose Hill CDP,799,391,714,344,229,198 382 | 5169168,160,51,,,,,,Round Hill town,539,218,500,177,155,140 383 | 5169360,160,51,,,,,,Ruckersville CDP,1141,512,,,316, 384 | 5169456,160,51,,,,,,Rural Retreat town,1483,695,1350,629,438,399 385 | 5169472,160,51,,,,,,Rushmere CDP,1018,533,1083,529,290,313 386 | 5169536,160,51,,,,,,Rustburg CDP,1431,584,1271,518,367,322 387 | 5169792,160,51,,,,,,St. Charles town,128,66,159,72,33,44 388 | 5169936,160,51,,,,,,St. Paul town,970,475,1000,496,281,302 389 | 5170000,160,51,,,,,,Salem city,24802,10832,24747,10403,6309,6544 390 | 5170112,160,51,,,,,,Saluda CDP,769,236,,,144, 391 | 5170256,160,51,,,,,,Sandston CDP,7571,3345,,,1981, 392 | 5170296,160,51,,,,,,Sandy Level CDP,484,280,689,277,131,187 393 | 5170352,160,51,,,,,,Sanford CDP,212,127,,,61, 394 | 5170520,160,51,,,,,,Savage Town CDP,78,42,,,22, 395 | 5170528,160,51,,,,,,Savageville CDP,175,94,,,47, 396 | 5170704,160,51,,,,,,Schuyler CDP,298,159,,,82, 397 | 5170715,160,51,,,,,,Scotland CDP,203,155,,,54, 398 | 5170800,160,51,,,,,,Scottsville town,566,308,555,300,136,146 399 | 5171040,160,51,,,,,,Sedley CDP,470,216,,,136, 400 | 5171072,160,51,,,,,,Selma CDP,529,235,485,217,135,135 401 | 5171216,160,51,,,,,,Seven Corners CDP,9255,3767,8701,3378,1981,1894 402 | 5171264,160,51,,,,,,Seven Mile Ford CDP,783,400,,,197, 403 | 5171625,160,51,,,,,,Shawneeland CDP,1873,839,,,524, 404 | 5171632,160,51,,,,,,Shawsville CDP,1310,635,1029,443,355,299 405 | 5171810,160,51,,,,,,Shenandoah Farms CDP,3033,1396,,,780, 406 | 5171825,160,51,,,,,,Shenandoah Retreat CDP,518,270,,,141, 407 | 5171826,160,51,,,,,,Shenandoah Shores CDP,934,355,,,229, 408 | 5171904,160,51,,,,,,Sherando CDP,688,310,665,281,188,207 409 | 5172080,160,51,,,,,,Shipman CDP,507,261,,,127, 410 | 5172272,160,51,,,,,,Short Pump CDP,24729,9795,182,77,6483,44 411 | 5172935,160,51,,,,,,Skyland Estates CDP,830,409,,,212, 412 | 5173376,160,51,,,,,,Snowville CDP,149,65,,,43, 413 | 5173760,160,51,,,,,,Southern Gateway CDP,2805,1240,,,659, 414 | 5173894,160,51,,,,,,Southampton Meadows CDP,592,221,,,140, 415 | 5173904,160,51,,,,,,South Hill town,4650,2227,4403,1988,1209,1191 416 | 5174100,160,51,,,,,,South Riding CDP,24256,7653,,,6228, 417 | 5174120,160,51,,,,,,South Run CDP,6389,2113,,,1936, 418 | 5174160,160,51,,,,,,Southside Chesconessex CDP,131,99,,,43, 419 | 5174384,160,51,,,,,,Sperryville CDP,342,179,,,100, 420 | 5174470,160,51,,,,,,Spotsylvania Courthouse CDP,4239,1525,3833,1268,1138,1010 421 | 5174592,160,51,,,,,,Springfield CDP,30484,10630,30417,10832,6884,7476 422 | 5174848,160,51,,,,,,Springville CDP,1371,618,,,394, 423 | 5174916,160,51,,,,,,Stafford Courthouse CDP,4320,1188,,,749, 424 | 5175216,160,51,,,,,,Staunton city,23746,11738,23853,10427,5982,5766 425 | 5175344,160,51,,,,,,Stephens City town,1829,835,1146,546,447,291 426 | 5175376,160,51,,,,,,Sterling CDP,27822,9603,,,6476, 427 | 5175702,160,51,,,,,,Stone Ridge CDP,7214,2450,,,1896, 428 | 5175840,160,51,,,,,,Stony Creek town,198,108,202,118,54,56 429 | 5176000,160,51,,,,,,Strasburg town,6398,2950,4017,1877,1670,1087 430 | 5176272,160,51,,,,,,Stuarts Draft CDP,9235,3962,8367,3279,2649,2438 431 | 5176416,160,51,,,,,,Sudley CDP,16203,5377,7719,2703,3610,1998 432 | 5176432,160,51,,,,,,Suffolk city,84585,33035,63677,24704,23135,17730 433 | 5176464,160,51,,,,,,Sugarland Run CDP,11799,3716,,,2864, 434 | 5176880,160,51,,,,,,Surry town,244,118,262,119,67,80 435 | 5176912,160,51,,,,,,Sussex CDP,256,71,,,48, 436 | 5177520,160,51,,,,,,Tangier town,727,377,604,270,234,181 437 | 5177568,160,51,,,,,,Tappahannock town,2375,1131,2068,946,552,495 438 | 5177648,160,51,,,,,,Tasley CDP,300,147,,,73, 439 | 5177856,160,51,,,,,,Temperanceville CDP,358,167,,,95, 440 | 5177925,160,51,,,,,,Templeton CDP,431,189,,,121, 441 | 5178192,160,51,,,,,,The Plains town,217,105,266,118,57,71 442 | 5178532,160,51,,,,,,Thynedale CDP,197,85,,,52, 443 | 5178688,160,51,,,,,,Timberlake CDP,12183,5487,10683,4707,3354,3151 444 | 5178736,160,51,,,,,,Timberville town,2522,1166,1739,770,681,465 445 | 5179024,160,51,,,,,,Toms Brook town,258,111,255,103,71,70 446 | 5179360,160,51,,,,,,Triangle CDP,8188,3143,5500,2318,1964,1341 447 | 5179472,160,51,,,,,,Troutville town,431,226,432,202,126,135 448 | 5179560,160,51,,,,,,Tuckahoe CDP,44990,19679,43242,18647,12064,11957 449 | 5179768,160,51,,,,,,Twin Lakes CDP,1647,553,,,416, 450 | 5179952,160,51,,,,,,Tysons Corner CDP,19627,10637,18540,9474,4754,4512 451 | 5180016,160,51,,,,,,Union Level CDP,188,77,,,51, 452 | 5180120,160,51,,,,,,University Center CDP,3586,1720,,,835, 453 | 5180165,160,51,,,,,,University of Virginia CDP,7704,1379,,,386, 454 | 5180272,160,51,,,,,,Urbanna town,476,368,543,354,133,161 455 | 5180608,160,51,,,,,,Vansant CDP,470,282,989,500,145,309 456 | 5181024,160,51,,,,,,Victoria town,1725,888,1821,903,460,517 457 | 5181072,160,51,,,,,,Vienna town,15687,5686,14453,5438,4215,3980 458 | 5181152,160,51,,,,,,Villa Heights CDP,717,350,845,358,194,229 459 | 5181280,160,51,,,,,,Vinton town,8098,3774,7782,3471,2174,2178 460 | 5181312,160,51,,,,,,Virgilina town,154,87,159,86,42,43 461 | 5182371,160,51,,,,,,Wakefield CDP,11275,3931,,,3262, 462 | 5182384,160,51,,,,,,Wakefield town,927,455,1038,485,244,285 463 | 5183056,160,51,,,,,,Warfield CDP,115,61,,,32, 464 | 5183088,160,51,,,,,,Warm Springs CDP,123,108,,,30, 465 | 5183136,160,51,,,,,,Warrenton town,9611,3966,6670,2856,2307,1591 466 | 5183168,160,51,,,,,,Warsaw town,1512,555,1375,468,248,233 467 | 5183568,160,51,,,,,,Wattsville CDP,1128,582,,,325, 468 | 5183600,160,51,,,,,,Waverly town,2149,936,2309,960,546,570 469 | 5183680,160,51,,,,,,Waynesboro city,21006,9717,19520,8863,5589,5434 470 | 5183808,160,51,,,,,,Weber City town,1327,683,1333,689,362,383 471 | 5184366,160,51,,,,,,West Falls Church CDP,29207,10586,,,6775, 472 | 5184632,160,51,,,,,,Westlake Corner CDP,976,663,899,515,333,322 473 | 5184960,160,51,,,,,,West Point town,3306,1379,2866,1151,908,810 474 | 5184976,160,51,,,,,,West Springfield CDP,22460,8556,28378,10425,6105,7839 475 | 5185184,160,51,,,,,,Weyers Cave CDP,2473,910,1225,490,663,355 476 | 5185608,160,51,,,,,,Whitesville CDP,219,114,,,60, 477 | 5186160,160,51,,,,,,Williamsburg city,14068,5176,11998,3880,2252,1787 478 | 5186720,160,51,,,,,,Winchester city,26203,11872,23585,10587,5957,5649 479 | 5186784,160,51,,,,,,Windsor town,2626,1059,916,422,710,270 480 | 5187008,160,51,,,,,,Wintergreen CDP,165,2291,,,58, 481 | 5187240,160,51,,,,,,Wolf Trap CDP,16131,5361,14001,4606,4739,4172 482 | 5187312,160,51,,,,,,Woodbridge CDP,4055,1806,31941,11026,1079,7769 483 | 5187333,160,51,,,,,,Woodburn CDP,8480,3234,,,2203, 484 | 5187380,160,51,,,,,,Woodlake CDP,7319,2688,,,2164, 485 | 5187408,160,51,,,,,,Woodlawn CDP,2343,1017,2249,926,613,597 486 | 5187430,160,51,,,,,,Woodlawn CDP,20804,7491,,,4771, 487 | 5187712,160,51,,,,,,Woodstock town,5097,2421,3952,1840,1282,1030 488 | 5187960,160,51,,,,,,Wyndham CDP,9785,3266,6176,2190,2721,1734 489 | 5188000,160,51,,,,,,Wytheville town,8211,4258,7804,3776,2175,2113 490 | 5188145,160,51,,,,,,Yogaville CDP,226,141,,,41, 491 | 5188240,160,51,,,,,,Yorktown CDP,195,126,203,129,56,46 492 | 5109016,160,51,,,,,,Boydton town,431,159,454,165,83,96 493 | 5116608,160,51,,,,,,Christiansburg town,21041,9556,16947,7430,5609,4764 494 | 5123376,160,51,,,,,,Drakes Branch town,530,267,504,262,126,135 495 | 5124496,160,51,,,,,,East Highland Park CDP,14796,6295,12488,5226,3913,3314 496 | 5131936,160,51,,,,,,Gordonsville town,1496,710,1498,688,388,401 497 | 5137880,160,51,,,,,,Hollins CDP,14673,6435,14309,5947,3800,3783 498 | 5144696,160,51,,,,,,Lebanon town,3424,1681,3273,1548,884,886 499 | 5150984,160,51,,,,,,Melfa town,408,202,450,205,107,131 500 | 5153992,160,51,,,,,,Mount Jackson town,1994,843,1664,718,525,440 501 | 5155752,160,51,,,,,,Newington CDP,12943,4439,19784,6793,3434,5322 502 | 5155848,160,51,,,,,,New Market town,2146,1048,1637,808,522,432 503 | 5161560,160,51,,,,,,Pennington Gap town,1781,962,1781,950,464,480 504 | 5162264,160,51,,,,,,Pimmit Hills CDP,6094,2324,6152,2299,1461,1532 505 | 5165392,160,51,,,,,,Radford city,16408,6427,15859,6137,2496,2644 506 | 5170096,160,51,,,,,,Saltville town,2077,967,2204,1003,593,661 507 | 5173712,160,51,,,,,,South Boston town,8142,3866,8491,3946,1990,2185 508 | 5175040,160,51,,,,,,Stanleytown CDP,1422,745,1515,723,413,443 509 | 5179456,160,51,,,,,,Troutdale town,178,107,1230,111,50,56 510 | 5100468,160,51,,,,,,Adwolf CDP,1530,677,1457,617,467,459 511 | 5103000,160,51,,,,,,Arlington CDP,207627,105404,189453,90426,41607,39322 512 | 5105912,160,51,,,,,,Belle Haven town,532,256,480,248,143,139 513 | 5107832,160,51,,,,,,Blackstone town,3621,1698,3675,1581,868,886 514 | 5108152,160,51,,,,,,Bluefield town,5444,2451,5078,2349,1471,1423 515 | 5108472,160,51,,,,,,Bon Air CDP,16366,7017,16213,6502,4403,4458 516 | 5108584,160,51,,,,,,Boones Mill town,239,127,285,138,67,77 517 | 5108888,160,51,,,,,,Bowling Green town,1111,482,936,425,290,213 518 | 5109032,160,51,,,,,,Boykins town,564,270,620,287,151,180 519 | 5111560,160,51,,,,,,Burkeville town,432,223,489,248,113,135 520 | 5112808,160,51,,,,,,Cape Charles town,1009,958,1134,740,264,278 521 | 5114952,160,51,,,,,,Charlotte Court House town,543,230,404,177,118,105 522 | 5114968,160,51,,,,,,Charlottesville city,43475,19189,45049,17591,7518,7626 523 | 5115000,160,51,,,,,,Chatham town,1269,619,1338,612,306,350 524 | 5115112,160,51,,,,,,Cheriton town,487,243,499,239,127,135 525 | 5117376,160,51,,,,,,Clifton town,282,93,185,70,78,53 526 | 5117680,160,51,,,,,,Cloverdale CDP,3119,1336,2986,1204,916,858 527 | 5118400,160,51,,,,,,Colonial Beach town,3542,2382,3228,2030,940,863 528 | 5119600,160,51,,,,,,Courtland town,1284,520,1270,498,315,301 529 | 5119904,160,51,,,,,,Craigsville town,923,450,979,474,253,272 530 | 5120240,160,51,,,,,,Crimora CDP,2209,920,1796,761,617,516 531 | 5121184,160,51,,,,,,Damascus town,814,523,981,543,215,269 532 | 5121648,160,51,,,,,,Dayton town,1530,662,1344,565,425,384 533 | 5122160,160,51,,,,,,Dendron town,272,136,297,121,68,75 534 | 5122560,160,51,,,,,,Dillwyn town,447,197,447,200,110,115 535 | 5123984,160,51,,,,,,Dunn Loring CDP,8803,3027,7861,2711,2382,2039 536 | 5126384,160,51,,,,,,Ewing CDP,439,222,436,216,123,128 537 | 5126416,160,51,,,,,,Exmore town,1460,769,1136,524,359,318 538 | 5127264,160,51,,,,,,Falmouth CDP,4274,1692,3624,1412,1133,997 539 | 5127296,160,51,,,,,,Fancy Gap CDP,237,152,260,156,68,82 540 | 5127440,160,51,,,,,,Farmville town,8216,2885,6845,2294,1162,1074 541 | 5127712,160,51,,,,,,Ferrum CDP,2043,534,1313,307,264,170 542 | 5127744,160,51,,,,,,Fieldale CDP,879,455,929,473,247,275 543 | 5127824,160,51,,,,,,Fincastle town,353,143,359,142,71,84 544 | 5127968,160,51,,,,,,Fishersville CDP,7462,3077,4998,1931,2034,1433 545 | 5128544,160,51,,,,,,Floyd town,425,277,432,264,111,117 546 | 5129152,160,51,,,,,,Fort Lee CDP,3393,866,7269,1445,780,1223 547 | 5129600,160,51,,,,,,Franklin city,8582,3901,8346,3767,2336,2279 548 | 5130176,160,51,,,,,,Gainesville CDP,11481,3959,4382,1842,3038,1305 549 | 5131136,160,51,,,,,,Glasgow town,1133,532,1046,494,304,296 550 | 5131608,160,51,,,,,,Gloucester Courthouse CDP,2951,1149,2269,907,691,561 551 | 5134240,160,51,,,,,,Hamilton town,506,232,562,224,141,158 552 | 5137336,160,51,,,,,,Hillsville town,2681,1474,2607,1352,728,732 553 | 5138280,160,51,,,,,,Honaker town,1449,684,945,445,408,271 554 | 5139064,160,51,,,,,,Huntington CDP,11267,6409,8325,4860,2335,1677 555 | 5139528,160,51,,,,,,Independence town,947,534,971,497,208,226 556 | 5141656,160,51,,,,,,Keller town,178,87,173,90,50,46 557 | 5141832,160,51,,,,,,Kenbridge town,1257,596,1253,579,334,320 558 | 5144520,160,51,,,,,,Lawrenceville town,1438,538,1275,459,265,209 559 | 5148344,160,51,,,,,,McKenney town,483,215,441,183,121,105 560 | 5149784,160,51,,,,,,Martinsville city,13821,7205,15416,7249,3565,4025 561 | 5151448,160,51,,,,,,Middleburg town,673,414,632,364,173,172 562 | 5152952,160,51,,,,,,Montross town,384,207,315,164,91,95 563 | 5154144,160,51,,,,,,Mount Vernon CDP,12416,4773,28582,10926,3483,7488 564 | 5158696,160,51,,,,,,Occoquan town,934,569,759,443,225,187 565 | 5159384,160,51,,,,,,Onley town,516,288,496,271,140,144 566 | 5160488,160,51,,,,,,Pamplin City town,219,104,199,89,52,51 567 | 5160680,160,51,,,,,,Parksley town,842,407,837,405,220,227 568 | 5160984,160,51,,,,,,Patrick Springs CDP,1845,937,2068,966,547,623 569 | 5163288,160,51,,,,,,Pocahontas town,389,215,441,230,97,123 570 | 5163928,160,51,,,,,,Port Royal town,126,75,170,90,32,44 571 | 5164880,160,51,,,,,,Pulaski town,9086,4511,9473,4517,2399,2670 572 | 5165008,160,51,,,,,,Purcellville town,7727,2491,3584,1292,1940,956 573 | 5166512,160,51,,,,,,Remington town,598,256,624,255,156,163 574 | 5167208,160,51,,,,,,Ridgeway town,742,361,775,327,210,222 575 | 5168496,160,51,,,,,,Rocky Mount town,4799,2249,4066,1796,1191,1018 576 | 5170576,160,51,,,,,,Saxis town,241,179,337,193,68,101 577 | 5170752,160,51,,,,,,Scottsburg town,119,63,145,64,34,40 578 | 5171776,160,51,,,,,,Shenandoah town,2373,1076,1878,812,648,542 579 | 5173200,160,51,,,,,,Smithfield town,8089,3323,6324,2552,2331,1831 580 | 5175008,160,51,,,,,,Stanardsville town,367,182,476,196,91,116 581 | 5175024,160,51,,,,,,Stanley town,1689,769,1326,598,455,363 582 | 5176256,160,51,,,,,,Stuart town,1408,731,961,516,315,247 583 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-------------------------------------------------------------------------------- /data/companions.clj: -------------------------------------------------------------------------------- 1 | 2 | (require '[clojure.string :as string]) 3 | 4 | (def input-data 5 | [{:given-name "Susan", :surname "Forman", :doctors [1]} 6 | {:given-name "Barbara", :surname "Wright", :doctors [1]} 7 | {:given-name "Ian", :surname "Chesterton", :doctors [1]} 8 | {:given-name "Vicki", :surname nil, :doctors [1]} 9 | {:given-name "Steven", :surname "Taylor", :doctors [1]} 10 | {:given-name "Katarina", :surname nil, :doctors [1]} 11 | {:given-name "Sara", :surname "Kingdom", :doctors [1]} 12 | {:given-name "Dodo", :surname "Chaplet", :doctors [1]} 13 | {:given-name "Polly", :surname nil, :doctors [1 2]} 14 | {:given-name "Ben", :surname "Jackson", :doctors [1 2]} 15 | {:given-name "Jamie", :surname "McCrimmon", :doctors [2]} 16 | {:given-name "Victoria", :surname "Waterfield", :doctors [2]} 17 | {:given-name "Zoe", :surname "Heriot", :doctors [2]} 18 | {:given-name "Brigadier", :surname "Lethbridge-Stewart", :doctors [2]} 19 | {:given-name "Liz", :surname "Shaw", :doctors [3]} 20 | {:given-name "Jo", :surname "Grant", :doctors [3]} 21 | {:given-name "Sarah Jane", :surname "Smith", :doctors [3 4 10]} 22 | {:given-name "Harry", :surname "Sullivan", :doctors [4]} 23 | {:given-name "Leela", :surname nil, :doctors [4]} 24 | {:given-name "K-9 Mark I", :surname nil, :doctors [4]} 25 | {:given-name "K-9 Mark II", :surname nil, :doctors [4]} 26 | {:given-name "Romana", :surname nil, :doctors [4]} 27 | {:given-name "Adric", :surname nil, :doctors [4 5]} 28 | {:given-name "Nyssa", :surname nil, :doctors [4 5]} 29 | {:given-name "Tegan", :surname "Jovanka", :doctors [4 5]} 30 | {:given-name "Vislor", :surname "Turlough", :doctors [5]} 31 | {:given-name "Kamelion", :surname nil, :doctors [5]} 32 | {:given-name "Peri", :surname "Brown", :doctors [5 6]} 33 | {:given-name "Melanie", :surname "Bush", :doctors [6 7]} 34 | {:given-name "Ace", :surname nil, :doctors [7]} 35 | {:given-name "Grace", :surname "Holloway", :doctors [8]} 36 | {:given-name "Rose", :surname "Tyler", :doctors [9 10]} 37 | {:given-name "Adam", :surname "Mitchell", :doctors [9]} 38 | {:given-name "Jack", :surname "Harkness", :doctors [9 10]} 39 | {:given-name "Mickey", :surname "Smith", :doctors [10]} 40 | {:given-name "Donna", :surname "Noble", :doctors [10]} 41 | {:given-name "Martha", :surname "Jones", :doctors [10]} 42 | {:given-name "Astrid", :surname "Peth", :doctors [10]} 43 | {:given-name "Jackson", :surname "Lake", :doctors [10]} 44 | {:given-name "Rosita", :surname "Farisi", :doctors [10]} 45 | {:given-name "Christina", :surname "de Souza", :doctors [10]} 46 | {:given-name "Adelaide", :surname "Brooke", :doctors [10]} 47 | {:given-name "Wilfred", :surname "Mott", :doctors [10]} 48 | {:given-name "Amy", :surname "Pond", :doctors [11]} 49 | {:given-name "Rory", :surname "Williams", :doctors [11]} 50 | {:given-name "River", :surname "Song", :doctors [11]} 51 | {:given-name "Craig", :surname "Owens", :doctors [11]} 52 | {:given-name "Clara", :surname "Oswald", :doctors [11]}]) 53 | 54 | (def companion (map string/lower-case 55 | (map :given-name input-data))) 56 | (def full-name 57 | (map (fn [{:keys [given-name surname]}] 58 | [(string/lower-case given-name) 59 | (string/trim 60 | (string/join \space [given-name surname]))]) 61 | input-data)) 62 | (def doctor 63 | (mapcat #(map (fn [d] [(string/lower-case (:given-name %)) d]) 64 | (:doctors %)) 65 | input-data)) 66 | 67 | (def actor 68 | [[1 "William Hartnell" "1963–66"] 69 | [2 "Patrick Troughton" "1966–69"] 70 | [3 "Jon Pertwee" "1970–74"] 71 | [4 "Tom Baker" "1974–81"] 72 | [5 "Peter Davison" "1981–84"] 73 | [6 "Colin Baker" "1984–86"] 74 | [7 "Sylvester McCoy" "1987–89, 1996"] 75 | [8 "Paul McGann" "1996"] 76 | [9 "Christopher Eccleston" "2005"] 77 | [10 "David Tennant" "2005–10"] 78 | [11 "Matt Smith" "2010–present"]]) 79 | 80 | -------------------------------------------------------------------------------- /data/companions.txt: -------------------------------------------------------------------------------- 1 | susan,Susan Forman 2 | barbara,Barbara Wright 3 | ian,Ian Chesterton 4 | vicki,Vicki 5 | steven,Steven Taylor 6 | katarina,Katarina 7 | sara,Sara Kingdom 8 | dodo,Dodo Chaplet 9 | polly,Polly 10 | ben,Ben Jackson 11 | jamie,Jamie McCrimmon 12 | victoria,Victoria Waterfield 13 | zoe,Zoe Heriot 14 | brigadier,Brigadier Lethbridge-Stewart 15 | liz,Liz Shaw 16 | jo,Jo Grant 17 | sarah jane,Sarah Jane Smith 18 | harry,Harry Sullivan 19 | leela,Leela 20 | k-9 mark i,K-9 Mark I 21 | k-9 mark ii,K-9 Mark II 22 | romana,Romana 23 | adric,Adric 24 | nyssa,Nyssa 25 | tegan,Tegan Jovanka 26 | vislor,Vislor Turlough 27 | kamelion,Kamelion 28 | peri,Peri Brown 29 | melanie,Melanie Bush 30 | ace,Ace 31 | grace,Grace Holloway 32 | rose,Rose Tyler 33 | adam,Adam Mitchell 34 | jack,Jack Harkness 35 | mickey,Mickey Smith 36 | donna,Donna Noble 37 | martha,Martha Jones 38 | astrid,Astrid Peth 39 | jackson,Jackson Lake 40 | rosita,Rosita Farisi 41 | christina,Christina de Souza 42 | adelaide,Adelaide Brooke 43 | wilfred,Wilfred Mott 44 | amy,Amy Pond 45 | rory,Rory Williams 46 | river,River Song 47 | craig,Craig Owens 48 | clara,Clara Oswald 49 | -------------------------------------------------------------------------------- /data/dehydratase.fasta: -------------------------------------------------------------------------------- 1 | >gi|190014205|emb|CAQ47849.1| putative dihydroxyacid dehydratase [Stenotrophomonas maltophilia K279a] 2 | MPEYRSRTSTAGRNMAGARALWRATGMKDGDFHKPIIAIANSFTQFVPGHVHLKDLGQLVAREIEQVGGV 3 | AKEFNTIAVDDGIAMGHDGMLYSLPSREIIADAVEYMVNAHCADALVCISNCDKITPGMLMAALRLNIPV 4 | VFVSGGPMEAGKTKLSEHKLDLVDAMVVAADDSASDEKVAAFERSACPTCGSCSGMFTANSMNCLTEALG 5 | LSLPGNGTTLATHADREALFRRAGRLIVELCHRWYGGEDPSALPRGIATQAAFANAMTLDIAMGGSTNTI 6 | LHLLAAAQEAEVDFDLTHIDALSRRVPQLCKVAPNTPKYHIEDVHRAGGVFGILGELDRAGLLETTVPTV 7 | HSASLADALERWDVVRSDNDTLHTFFKAGPAGIPTQEAFSQATRWPTLDVDRAEGCIRSLQHAYSLEGGL 8 | AVLRGNLAVDGCVVKTAGVDESIHVFEGPARVYESQDAAVAGILADEVQPGEVVVIRYEGPKGGPGMQEM 9 | LYPTSYLKSKGLGKQCALLTDGRFSGGTSGLSIGHVSPEAASGGVIGLVEDGDRIRIDIPARRIDLLLDE 10 | AVLAQRRSDADARGWKPRAPRPRKVTSALKAYALLATSADKGAVRNTALLGD 11 | -------------------------------------------------------------------------------- /data/delicious-rss-214k.json.xz: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/erochest/clj-data-analysis/59cd5a881c3715c66b71e61188f9484e796e960c/data/delicious-rss-214k.json.xz -------------------------------------------------------------------------------- /data/elephas.fasta: -------------------------------------------------------------------------------- 1 | >gi|5524211|gb|AAD44166.1| cytochrome b [Elephas maximus maximus] 2 | LCLYTHIGRNIYYGSYLYSETWNTGIMLLLITMATAFMGYVLPWGQMSFWGATVITNLFSAIPYIGTNLV 3 | EWIWGGFSVDKATLNRFFAFHFILPFTMVALAGVHLTFLHETGSNNPLGLTSDSDKIPFHPYYTIKDFLG 4 | LLILILLLLLLALLSPDMLGDPDNHMPADPLNTPLHIKPEWYFLFAYAILRSVPNKLGGVLALFLSIVIL 5 | GLMPFLHTSKHRSMMLRPLSQALFWTLTMDLLTLTWIGSQPVEYPYTIIGQMASILYFSIILAFLPIAGX 6 | IENY 7 | -------------------------------------------------------------------------------- /data/flights_with_colnames.csv.gz: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/erochest/clj-data-analysis/59cd5a881c3715c66b71e61188f9484e796e960c/data/flights_with_colnames.csv.gz -------------------------------------------------------------------------------- /data/maltophilia.fasta: -------------------------------------------------------------------------------- 1 | >gi|190014208|emb|CAQ47852.1| putative shikimate dehydrogenase [Stenotrophomonas maltophilia K279a] 2 | MTDRYAVFGHPVAHSKSPQIHATFGRQEGIAVDYRAIDLAPEAFLAGLEAFAADGGVGANVTSPHKEAAF 3 | SVCTTLTARARRAGSVNTLLRKGDRWHGDTTDGIGLVRDLTDRHGLDLRGRRMLLIGAGGSARSVAPALL 4 | DAGITELVVVNRTPERADELIDAMGEPGRAISRYWEDLRDLGDFELIVNATSAGRDRDIEFKLPLSLVNS 5 | MTTAVDLNYGEAAIAFLAWARAAECRNTVDGLGMLVEQAAESFLQWHGVRPQTDEVYQSLRQGSAVLAGE 6 | D 7 | -------------------------------------------------------------------------------- /data/mchu.fasta: -------------------------------------------------------------------------------- 1 | >MCHU - Calmodulin - Human, rabbit, bovine, rat, and chicken 2 | ADQLTEEQIAEFKEAFSLFDKDGDGTITTKELGTVMRSLGQNPTEAELQDMINEVDADGNGTID 3 | FPEFLTMMARKMKDTDSEEEIREAFRVFDKDGNGYISAAELRHVMTNLGEKLTDEEVDEMIREA 4 | DIDGDGQVNYEEFVQMMTAK* 5 | -------------------------------------------------------------------------------- /data/ovax-chick.fasta: -------------------------------------------------------------------------------- 1 | >gi|129295|sp|P01013|OVAX_CHICK GENE X PROTEIN (OVALBUMIN-RELATED) 2 | QIKDLLVSSSTDLDTTLVLVNAIYFKGMWKTAFNAEDTREMPFHVTKQESKPVQMMCMNNSFNVATLPAE 3 | KMKILELPFASGDLSMLVLLPDEVSDLERIEKTINFEKLTEWTNPNTMEKRRVKVYLPQMKIEEKYNLTS 4 | VLMALGMTDLFIPSANLTGISSAESLKISQAVHGAFMELSEDGIEMAGSTGVIEDIKHSPESEQFRADHP 5 | FLFLIKHNPTNTIVYFGRYWSP 6 | -------------------------------------------------------------------------------- /data/salmonella.fasta: -------------------------------------------------------------------------------- 1 | ">gi|16759485|ref|NP_455102.1| ABC transporter ATP-binding protein YbbA [Salmonella enterica subsp. enterica serovar Typhi str. CT18] 2 | MPAENSVEVHRLRKSVGQGEHELSILTGVELVVKRGETIALIGESGSGKSTLLAILAGLDDGSSGEVSLV 3 | GKPLHQMDEEARAQLRAQHVGFVFQSFMLIPTLNALENVELPALLRGENSGQSKAGAKALLEQLGLGKRL 4 | DHLPAQLSGGEQQRVALARAFNGRPDVLFADEPTGNLDRQTGDKIADLLFSLNREHGTTLILVTHDPALA 5 | ARCDRRLRLVNGQLQEEA 6 | -------------------------------------------------------------------------------- /data/seqeuence-1.fasta: -------------------------------------------------------------------------------- 1 | >SEQUENCE_1 2 | MTEITAAMVKELRESTGAGMMDCKNALSETNGDFDKAVQLLREKGLGKAAKKADRLAAEG 3 | LVSVKVSDDFTIAAMRPSYLSYEDLDMTFVENEYKALVAELEKENEERRRLKDPNKPEHK 4 | IPQFASRKQLSDAILKEAEEKIKEELKAQGKPEKIWDNIIPGKMNSFIADNSQLDSKLTL 5 | MGQFYVMDDKKTVEQVIAEKEKEFGGKIKIVEFICFEVGEGLEKKTEDFAAEVAAQL 6 | >SEQUENCE_2 7 | SATVSEINSETDFVAKNDQFIALTKDTTAHIQSNSLQSVEELHSSTINGVKFEEYLKSQI 8 | ATIGENLVVRRFATLKAGANGVVNGYIHTNGRVGVVIAAACDSAEVASKSRDLLRQICMH 9 | -------------------------------------------------------------------------------- /data/sequences.fasta: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/erochest/clj-data-analysis/59cd5a881c3715c66b71e61188f9484e796e960c/data/sequences.fasta -------------------------------------------------------------------------------- /data/small-sample-header.csv: -------------------------------------------------------------------------------- 1 | given-name,surname,relation 2 | Gomez,Addams,father 3 | Morticia,Addams,mother 4 | Pugsley,Addams,brother 5 | Wednesday,Addams,sister 6 | Pubert,Addams,brother 7 | Fester,Addams,uncle 8 | Grandmama,,grandmother 9 | Thing,,hand 10 | Lurch,,butler 11 | Itt,,cousin 12 | Cackle,,cousin 13 | -------------------------------------------------------------------------------- /data/small-sample-header.xls: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/erochest/clj-data-analysis/59cd5a881c3715c66b71e61188f9484e796e960c/data/small-sample-header.xls -------------------------------------------------------------------------------- /data/small-sample-list.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | Small Sample List 10 | 11 | 12 | 13 | 14 | 17 | 18 |
19 |

Small Sample List

20 |
21 | 22 | 29 | 30 |
31 |
32 |

Addam's Family

33 |
34 |

Here's some information about the Addam's Family.

35 | 48 |
49 | 50 |
51 |
52 |

The Munsters

53 |
54 |

A different take.

55 | 63 |
64 | 65 | 71 | 72 | 73 | -------------------------------------------------------------------------------- /data/small-sample-table.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | Example data table 5 | 6 | 7 |

A Header

8 |

This contains a bunch of people.

9 |

Tonight we're going to code HTML like it's 1999!

10 | 11 | 12 | 13 | 30 | 31 | 32 | 44 | 45 |
Menu Here 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 |
Given Name Surname Relation
Gomez Addams father
Morticia Addams mother
Pugsley Addams brother
Wednesday Addams sister
Pubert Addams brother
Fester Addams uncle
Grandmama grandmother
Thing hand
Lurch butler
Itt cousin
Cackle cousin
29 |
33 | 34 | 35 | 38 | 41 | 42 | 43 |
46 | 47 | 48 | 49 | -------------------------------------------------------------------------------- /data/small-sample.csv: -------------------------------------------------------------------------------- 1 | Gomez,Addams,father 2 | Morticia,Addams,mother 3 | Pugsley,Addams,brother 4 | Wednesday,Addams,sister 5 | Pubert,Addams,brother 6 | Fester,Addams,uncle 7 | Grandmama,,grandmother 8 | Thing,,hand 9 | Lurch,,butler 10 | Itt,,cousin 11 | Cackle,,cousin 12 | -------------------------------------------------------------------------------- /data/small-sample.json: -------------------------------------------------------------------------------- 1 | [ 2 | { 3 | "given_name": "Gomez", 4 | "surname": "Addams", 5 | "relation": "father" 6 | }, 7 | { 8 | "given_name": "Morticia", 9 | "surname": "Addams", 10 | "relation": "mother" 11 | }, 12 | { 13 | "given_name": "Pugsley", 14 | "surname": "Addams", 15 | "relation": "brother" 16 | }, 17 | { 18 | "given_name": "Wednesday", 19 | "surname": "Addams", 20 | "relation": "sister" 21 | }, 22 | { 23 | "given_name": "Pubert", 24 | "surname": "Addams", 25 | "relation": "brother" 26 | }, 27 | { 28 | "given_name": "Fester", 29 | "surname": "Addams", 30 | "relation": "uncle" 31 | }, 32 | { 33 | "given_name": "Grandmama", 34 | "surname": "", 35 | "relation": "grandmother" 36 | }, 37 | { 38 | "given_name": "Thing", 39 | "surname": "", 40 | "relation": "hand" 41 | }, 42 | { 43 | "given_name": "Lurch", 44 | "surname": "", 45 | "relation": "butler" 46 | }, 47 | { 48 | "given_name": "Itt", 49 | "surname": "", 50 | "relation": "cousin" 51 | }, 52 | { 53 | "given_name": "Cackle", 54 | "surname": "", 55 | "relation": "cousin" 56 | } 57 | ] 58 | -------------------------------------------------------------------------------- /data/small-sample.sqlite: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/erochest/clj-data-analysis/59cd5a881c3715c66b71e61188f9484e796e960c/data/small-sample.sqlite -------------------------------------------------------------------------------- /data/small-sample.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | Gomez 5 | Addams 6 | father 7 | 8 | 9 | Morticia 10 | Addams 11 | mother 12 | 13 | 14 | Pugsley 15 | Addams 16 | brother 17 | 18 | 19 | Wednesday 20 | Addams 21 | sister 22 | 23 | 24 | Pubert 25 | Addams 26 | brother 27 | 28 | 29 | Fester 30 | Addams 31 | uncle 32 | 33 | 34 | Grandmama 35 | grandmother 36 | 37 | 38 | Thing 39 | hand 40 | 41 | 42 | Lurch 43 | butler 44 | 45 | 46 | Itt 47 | cousin 48 | 49 | 50 | Cackle 51 | cousin 52 | 53 | 54 | -------------------------------------------------------------------------------- /data/sotu.tar.gz: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/erochest/clj-data-analysis/59cd5a881c3715c66b71e61188f9484e796e960c/data/sotu.tar.gz -------------------------------------------------------------------------------- /data/transferase.fasta: -------------------------------------------------------------------------------- 1 | >gi|190576272|ref|YP_001974117.1| transferase [Stenotrophomonas maltophilia K279a] 2 | MNPLRPFRDKMPVLGERVYIDPSCTIIGDVELGDDVSVWPGTVIRGDVNYVRIGARTNVQDGTIIHVSHH 3 | SPYNKAGYPTLIGEGVTVGHGCIIHACTIGDYSLIGMGACILDGARVERHGFVGAGAVIGPGKVVGEGEL 4 | WVGNPARPARTLSDKEIESLHYSADHYVQLKDEYRG 5 | -------------------------------------------------------------------------------- /data/world-bank-filtered.csv: -------------------------------------------------------------------------------- 1 | SP.POP.TOTL,NY.GDP.MKTP.KD,SI.DST.04TH.20,SI.POV.GINI,year,SI.DST.FRST.20,NY.GNP.MKTP.KD,SI.DST.05TH.20,VC.IHR.PSRC.P5,cname,ccode,SI.DST.10TH.10,SI.DST.02ND.20,SI.DST.FRST.10,SI.DST.03RD.20,IC.FRM.CRIM.ZS 2 | 3065954,3400246575,20.33,36.16,2005,7.98,3494281476,44.63,1.793895147,Armenia,ARM,30.8,11.79,3.33,15.27,0.01 3 | 3061067,2370398385,20.78,35.66,2002,7.93,2459769230,44,2.254115967,Armenia,ARM,29.86,11.8,3.32,15.49,0.61 4 | 10158608,50275293599,22.35,26.82,2002,9.5,47614633047,36.55,1.998174476,Hungary,HUN,22.29,13.92,4.08,17.68,0.2 5 | 141910000,3.9821E11,21.29,40.11,2009,6.46,3.84673E11,47.13,11.2,Russian Federation,RUS,31.68,10.35,2.75,14.77,0.77 6 | 143150000,3.4971E11,22.35,37.51,2005,6.52,3.40577E11,44.43,24.9,Russian Federation,RUS,28.59,10.98,2.68,15.72,0.53 7 | 1.452996903E8,2.8588E11,22.65,35.7,2002,6.88,2.80764E11,42.91,30.7,Russian Federation,RUS,27.07,11.42,2.84,16.14,0.86 8 | 2056769,4494737198,21.98,43.17,2009,5.13,4455616246,48.87,1.750318096,"Macedonia, FYR",MKD,32.4,9.49,2.03,14.53,0.69 9 | 2038109,3877087656,22.74,39.13,2005,5.83,3803650942,45.34,2.600449731,"Macedonia, FYR",MKD,28.93,10.51,2.32,15.58,0.28 10 | 2022255,3453793697,22.34,38.75,2002,6.04,3412220087,45.21,3.461482355,"Macedonia, FYR",MKD,29.33,10.77,2.39,15.64,0.76 11 | 47105150,45231599857,22.61,28.21,2005,9.02,44816989449,37.43,8.611811198,Ukraine,UKR,22.73,13.45,3.87,17.49,0.46 12 | 46258200,53572110088,22.46,27.51,2008,9.36,53185919860,37.08,7.00128093,Ukraine,UKR,22.55,13.61,4.07,17.49,0.63 13 | 48202500,35912742450,22.58,28.28,2002,8.93,35472874982,37.43,10.00575279,Ukraine,UKR,22.8,13.52,3.79,17.54,0.73 14 | 27031000,1.46006E11,22.18,44.77,2006,4.28,1.45022E11,49.42,45.18089887,"Venezuela, RB",VEN,33.17,9.52,1.2,14.6,1.51 15 | 70923730,3.75074E11,22.42,38.95,2008,5.7,3.70751E11,45.06,3.3,Turkey,TUR,29.35,10.93,2.11,15.89,0.39 16 | 38151603,2.41613E11,22.03,34.07,2009,7.68,2.32304E11,42.11,1.3,Poland,POL,27.05,11.95,3.26,16.23,0.48 17 | 38165445,1.99364E11,22.38,34.92,2005,7.34,1.94877E11,42.38,1.45421045,Poland,POL,27.2,11.7,3.03,16.2,0.3 18 | 38230364,1.75843E11,22.17,34.05,2002,7.57,1.7525E11,41.98,1.872850358,Poland,POL,26.82,11.97,3.19,16.31,0.58 19 | 3435591,15435325000,22.36,35.81,2004,6.79,14992214940,42.97,8.42,Lithuania,LTU,27.59,11.63,2.72,16.25,2.7 20 | 3469070,13042025000,22.59,32.33,2002,7.68,12882053949,40.29,7.22,Lithuania,LTU,25.18,12.51,3.14,16.93,0.65 21 | 43696540,1.27917E11,0,58.66,2006,0,1.23171E11,100,40.00087879,Colombia,COL,100,0,0,0,0.68 22 | 46294841,1.49691E11,18.79,55.91,2010,3,1.43023E11,60.15,33.4,Colombia,COL,44.43,6.83,0.87,11.23,0.27 23 | 27866387,70497520780,20.41,50.87,2006,3.78,68232061393,55.55,2.7,Peru,PER,39.18,7.69,1.37,12.57,0.4 24 | 26579252,56085932802,19.17,55.64,2002,3,54652956637,59.67,2.7,Peru,PER,43.99,6.76,1.01,11.4,5.31 25 | 3294583,15573098990,20.17,55.06,2006,2.53,14385766978,58.83,11.2609092,Panama,PAN,41.61,6.79,0.74,11.68,0.54 26 | 3516820,21486310530,20.06,51.92,2010,3.3,19996912761,56.38,21.6,Panama,PAN,40.08,7.75,1.1,12.51,0.32 27 | 193246610,8.5507E11,19.04,54.69,2009,2.85,8.37864E11,58.57,22.7,Brazil,BRA,42.93,7.13,0.77,12.41,1.69 28 | 181633074,6.78218E11,18.65,58.78,2003,2.27,6.56136E11,62.41,33.1,Brazil,BRA,46.32,6.02,0.57,10.65,0.39 29 | 5383300,2058575694,22.37,36.19,2009,6.82,1979894266,43.38,8.1,Kyrgyz Republic,KGZ,27.79,11.4,2.8,16.03,0.34 30 | 5162600,1649306468,22.42,39.49,2005,6,1591124080,45.93,9.737463313,Kyrgyz Republic,KGZ,29.61,10.37,2.45,15.28,0.75 31 | 4990700,1442330936,22.43,31.67,2002,8.35,1388562993,40.29,8.215578376,Kyrgyz Republic,KGZ,25.02,12.35,3.65,16.58,2.57 32 | 6074487,15329111295,20.72,46.19,2006,4.61,14968132485,51.65,64.66389672,El Salvador,SLV,35.94,9.23,1.63,13.79,2.58 33 | 6008523,13985703810,21.47,50.72,2003,2.74,13586130065,54.32,55.85399274,El Salvador,SLV,37.42,8.09,0.58,13.38,3.85 34 | 67276383,1.654E11,20.97,42.35,2006,6.08,1.59261E11,49.15,6.966783574,Thailand,THA,33.3,9.78,2.5,14.02,0.11 35 | 78323298,1.45592E11,21.03,30.77,2008,9.24,1.4676E11,40.34,1.012470134,"Egypt, Arab Rep.",EGY,26.58,13.02,3.96,16.37,3.03 36 | 2338624,9010898599,22,35.91,2002,6.94,9037158560,43.24,10.82,Latvia,LVA,28.21,11.68,2.8,16.14,0.43 37 | 7440769,7888605693,22.47,33.4,2005,7.45,7792903607,41.05,1.89,Serbia,SRB,26.13,12.33,2.89,16.7,0.41 38 | 7480591,6847617227,22.19,32.81,2003,7.79,6799867375,40.93,2.2,Serbia,SRB,26.07,12.42,3.23,16.67,1.96 39 | 7500031,6669246165,22.1,32.74,2002,7.97,6636900444,40.9,2.1,Serbia,SRB,26.25,12.46,3.23,16.57,0.61 40 | 25567700,15538140015,21.48,36.72,2003,7.14,15350453855,44.19,3.778027432,Uzbekistan,UZB,29.47,11.52,2.85,15.67,0 41 | 25271800,14911842625,21.45,34.55,2002,7.8,14686773889,42.66,4.185949863,Uzbekistan,UZB,28.23,12.08,3.17,16.01,0.37 42 | 5537000,12459768320,20.99,37.72,2006,7.28,12793706076,45.48,1.8,Jordan,JOR,30.77,11.08,3.15,15.17,0.14 43 | 1358644,6427372284,22.19,36.81,2002,6.72,6157890585,43.94,10.46700535,Estonia,EST,28.41,11.27,2.75,15.88,0.13 44 | 1994530,21353851323,22.9,29.15,2002,8.65,21234138754,37.76,1.80784696,Slovenia,SVN,23.05,13.22,3.58,17.47,0.29 45 | 16468677,96486092629,18.67,51.84,2006,4.22,83927698499,57.45,5.6,Chile,CHL,41.98,7.85,1.55,11.81,0.55 46 | 3565603,1984642726,22.87,34.02,2009,7.29,2097930410,41.57,6.661387517,Moldova,MDA,25.76,11.8,3.05,16.47,0.41 47 | 3595182,1813877409,21.92,36.28,2005,7.01,2038692893,43.7,7.11464885,Moldova,MDA,28.52,11.47,2.9,15.9,0.17 48 | 3612869,1570901239,21.66,35.55,2003,7.5,1769841939,43.48,9.136617845,Moldova,MDA,28.48,11.57,3.22,15.79,0.02 49 | 3623059,1473640937,22.23,36.87,2002,6.82,1575359869,44.09,10.10377917,Moldova,MDA,28.39,11.13,2.85,15.73,0.74 50 | 107835259,6.69865E11,20.03,48.11,2006,4.8,6.56557E11,53.64,11.2,Mexico,MEX,38.28,8.51,1.96,13.02,0.69 51 | 31011199,52239577756,20.61,40.88,2007,6.52,51558797564,47.88,1.667139668,Morocco,MAR,33.22,10.45,2.66,14.54,0.02 52 | 39023850,3.40178E11,22.27,47.72,2006,3.59,3.31684E11,51.82,5.258322795,Argentina,ARG,34.59,8.38,1.13,13.94,1.25 53 | 9775591,18293979126,22.89,27.92,2005,8.76,18301047416,36.85,8.396859391,Belarus,BLR,22.13,13.68,3.63,17.82,0.27 54 | 9602000,24103693966,22.89,27.22,2008,9.17,23719637132,36.35,5.588444625,Belarus,BLR,21.9,13.77,3.8,17.82,0.42 55 | 9925000,14011685603,22.54,29.97,2002,8.35,13984063046,38.58,9.926347306,Belarus,BLR,23.86,13.18,3.45,17.35,0.51 56 | 6454548,10463076859,19.78,52.42,2010,3.26,10284915857,56.43,11.5,Paraguay,PRY,41.11,7.76,0.98,12.77,1.29 57 | 7017769,9505547333,19.74,57.56,2006,2.11,9068113372,60.69,43.00512029,Honduras,HND,44.06,6.12,0.57,11.34,2.16 58 | 6609337,7917422408,19.12,58.71,2003,2.21,7576321946,62.18,33.64936604,Honduras,HND,45.71,5.84,0.64,10.65,3.1 59 | 4361200,4354805817,22.13,41.05,2005,5.38,,46.9,9.001551483,Georgia,GEO,31.03,10.3,2.03,15.29,0.25 60 | 4383700,5475261546,22.05,41.34,2008,5.32,,47.15,5.985410164,Georgia,GEO,31.31,10.25,2,15.23,0.73 61 | 4357000,3379780412,22.03,40.31,2002,5.63,,46.4,6.312102332,Georgia,GEO,30.73,10.53,2.15,15.41,0.51 62 | 91703090,1.19869E11,21.04,42.98,2009,5.98,1.19734E11,49.69,5.4,Philippines,PHL,33.62,9.42,2.59,13.87,1.1 63 | 82293990,90705750112,21.17,44.48,2003,5.44,90394597904,50.68,7.820741223,Philippines,PHL,34.29,9.03,2.31,13.68,0.87 64 | 13034904,23597025901,18.46,55.89,2006,3.08,23083868461,60.26,45.14801183,Guatemala,GTM,44.92,6.85,1.06,11.35,1.5 65 | 12098576,21022740913,20.67,56.08,2003,2,20736423987,59.02,35.02065036,Guatemala,GTM,41.2,6.41,0.49,11.9,5.31 66 | 9264267,28536865195,19.9,51.06,2005,3.82,26964003324,56.05,25.84122414,Dominican Republic,DOM,39.7,7.84,1.32,12.39,0.72 67 | 7659764,19101459236,23.08,28.19,2007,8.5,17577433492,36.74,2.21195995,Bulgaria,BGR,22.17,13.74,3.28,17.94,0.24 68 | 5418590,43924489377,22,26,2009,10.12,41608493971,36.23,1.5,Slovak 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27 | 28 | #### [2010 US Census Data][ire] 29 | 30 | This data is downloaded from the [Investigative Reporters and Editors 31 | Census dataset][ire] site. You can also download raw census data from the 32 | [US Census Bureau][census]. 33 | 34 | - [all_160.P3.csv](data/all_160.P3.csv): This is race data (P3) from the 35 | census. This is a place-level summary (160), and I've merged this data 36 | for all states. 37 | - [all_160_in_51.P3.csv](data/all_160_in_51.P3.csv): This is race data 38 | (P3) from the census. This is a place-level summary (160) for Virginia 39 | (51). 40 | - [all_160_in_51.P35.csv](data/all_160_in_51.P35.csv): This is family 41 | counts (P35) from the census. This is a place level summary (160) for 42 | Virginia (51). 43 | - [census-race.json](data/census-race.json): This is the data from 44 | `all_160.P3.csv`, mentioned above, translated into JSON. 45 | - [clusters.json](data/clusters.json): This is a graph of the clusters of 46 | the data from `all_160.P3.csv`, mentioned above. The clusters were 47 | generated K-means clusters from that dataset aggregated by state. The 48 | JSON data structure represents the nodes and links (edges) in the graph, 49 | along with the aggregated data. 50 | 51 |
52 | 53 | #### [Abalone][abalone] 54 | 55 | This dataset is from the [UCI Machine Learning Repository][uci]. It 56 | contains sex, age, and measurements of abalone. This can be used to 57 | predict the age from the fish's physical measurements. 58 | 59 | - [abalone.data](data/abalone.data): This is the data in CSV format. 60 | - [abalone.json](data/abalone.json): The data from `abalone.data` 61 | formatted as JSON. 62 | - [abalone.names](data/abalone.names): This is information about the data, 63 | including the fields and their ranges of values. 64 | 65 |
66 | 67 | #### Accident Fatalities 68 | 69 | This dataset was selected and downloaded from the US [National Highway 70 | Traffic Safety Administration][nhtsa]. This dataset includes the speed 71 | limit and other factors related to the accidents. 72 | 73 | - [accident-fatalities.tsv](data/accident-fatalities.tsv) 74 | 75 |
76 | 77 | #### Chick Weights 78 | 79 | This is from the [Incanter datasets package][datasets]. It's also found in 80 | the R datasets package. 81 | 82 | - [chick-weight.json](data/chick-weight.json): This is the Incanter 83 | dataset converted to JSON. 84 | 85 |
86 | 87 | #### Currencies and Exchange Rates 88 | 89 | This is a couple of datasets used to illustrate working with semantic web 90 | data and web scraping. 91 | 92 | - [currencies.ttl](data/currencies.ttl): This dataset is from 93 | [Telegraphis][telegraphis], and it contains linked data with information 94 | about various currencies, such as the name, ISO codes, symbols. 95 | 96 | - [x-rates-usd.html](data/x-rates-usd.html): This is a snapshot of a rates 97 | table from [X-Rates][xrates]. 98 | 99 |
100 | 101 | #### Doctor Who Companions 102 | 103 | This is a dataset that I've pulled together from [Wikipedia][wikip] 104 | listing the actors and companions from the British television program 105 | [Doctor Who][drwho]. 106 | 107 | - [companions.clj](data/companions.clj): This is a set of Clojure forms 108 | that define the in-memory data for this information. 109 | - [companions.txt](data/companions.txt): This is a list of the companions 110 | as CSV. It lists an identifier (usually the first name) for each and 111 | their first name. 112 | 113 |
114 | 115 | #### FASTA datasets 116 | 117 | FASTA files are used in bioinformatics to exchange nucleotide and peptide 118 | sequences. This is a small collection of them to use for testing a custom 119 | FASTA parser. 120 | 121 | - [abc-transporter.fasta](data/abc-transporter.fasta) 122 | - [dehydratase.fasta](data/dehydratase.fasta) 123 | - [elephas.fasta](data/elephas.fasta) 124 | - [maltophilia.fasta](data/maltophilia.fasta) 125 | - [mchu.fasta](data/mchu.fasta) 126 | - [ovax-chick.fasta](data/ovax-chick.fasta) 127 | - [salmonella.fasta](data/salmonella.fasta) 128 | - [seqeuence-1.fasta](data/seqeuence-1.fasta) 129 | - [sequences.fasta](data/sequences.fasta) 130 | - [transferase.fasta](data/transferase.fasta) 131 | 132 |
133 | 134 | #### IBM stock prices 135 | 136 | This dataset was downloaded from [Google Finance][gfinance]. It contains 137 | the prices of IBM stock for the decade between 138 | and . 139 | 140 | - [ibm.csv](data/ibm.csv) 141 | 142 |
143 | 144 | #### [Ionosphere data][ionosphere] 145 | 146 | This dataset is from an antenna array in Labrador. It contains a number of 147 | measurements of free electrons in the ionosphere. This dataset can be 148 | found in the [UCI Machine Learning Repository][uci], but this dataset is 149 | in [Attribute-Relation File Format (ARFF)][arff] format for use with 150 | [Weka][weka]. 151 | 152 | - [ionosphere.arff](data/UCI/ionosphere.arff): This is pulled from the 153 | [Weka][weka] distribution for easier access. 154 | 155 |
156 | 157 | #### [Iris][iris] 158 | 159 | This is a standard dataset that's almost everywhere. We also use the copy 160 | that ships with Incanter several times in the book. For more information 161 | about this dataset, see [its page][iris] at the [UCI Machine Learning 162 | Repository][uci]. 163 | 164 | - [iris.arff](data/UCI/iris.arff): This is pulled from the [Weka][weka] 165 | distribution for easier access. 166 | 167 |
168 | 169 | #### [Mushroom][mushroom] 170 | 171 | This is another standard dataset from the [UCI Machine Learning 172 | Repository][uci]. This contains categorical data on mushrooms, including 173 | whether they're edible or poisonous. 174 | 175 | - [agaricus-lepiota.data](data/agaricus-lepiota.data): The data file from 176 | the UCI web site. 177 | - [agaricus-lepiota.names](data/agaricus-lepiota.names): Information about 178 | the data, including field names. 179 | - [mushroom.arff](data/mushroom.arff): The same dataset packages as an 180 | ARFF file for [Weka][weka]. 181 | 182 |
183 | 184 | #### TV-Related Sample Datasets 185 | 186 | These are a series of datasets I threw together to illustrate loading 187 | different data formats. 188 | 189 | - [small-sample-header.csv](data/small-sample-header.csv) 190 | - [small-sample-header.xls](data/small-sample-header.xls) 191 | - [small-sample-list.html](data/small-sample-list.html) 192 | - [small-sample-table.html](data/small-sample-table.html) 193 | - [small-sample.csv](data/small-sample.csv) 194 | - [small-sample.json](data/small-sample.json) 195 | - [small-sample.sqlite](data/small-sample.sqlite) 196 | - [small-sample.xml](data/small-sample.xml) 197 | 198 |
199 | 200 | #### *The Adventures of Sherlock Holmes* 201 | 202 | This text is from [Project Gutenberg][gutenberg]. It's a collection of 203 | Sherlock Holmes short stories written by Sir Arthur Conan Doyle. 204 | 205 | - [pg1661.txt](data/pg1661.txt) 206 | 207 |
208 | 209 | #### Spelling Training Corpus 210 | 211 | This is the training corpus used in [Peter Norvig's article, "How to Write 212 | a Spelling Corrector."][norvig] 213 | 214 | - [big.txt](data/big.txt) 215 | 216 |
217 | 218 | #### World Bank dataset 219 | 220 | I downloaded this dataset about income inequality from the [World 221 | Bank][worldbank]. It need to be filtered and pivoted, and here is the 222 | final result. 223 | 224 | - [world-bank-filtered.csv](data/world-bank-filtered.csv) 225 | 226 | This is a dataset on how much land is used for agriculture in China. 227 | 228 | - [chn-land.csv](data/chn-land.csv) 229 | 230 |
231 | 232 | #### Delicious RSS Feed 233 | 234 | This is a compressed subset of a delicious RSS feed scraping. I can't find 235 | the original online anywhere anymore, so I'm putting it here. 236 | 237 | - [delicious-rss-214k.json.xz](data/delicious-rss-214k.json.xz) 238 | 239 |
240 | 241 | #### State of the Union dataset 242 | 243 | This is a scraping of US Presidents' State of the Union (SOTU) addresses. 244 | 245 | - [sotu.tar.gz](data/sotu.tar.gz) 246 | 247 |
248 | 249 | #### Flight Data 250 | 251 | This is a compressed copy of data on US domestic flights from 1990–2009. 252 | 253 | - [flights_with_colnames.csv.gz](data/flights_with_colnames.csv.gz) 254 | 255 |
256 | 257 |
258 | 259 | [packt]: http://www.packtpub.com/ 260 | [packtclj]: http://www.packtpub.com/clojure-data-analysis-cookbook/book 261 | [amazon]: http://www.amazon.com/gp/product/B00BECVV9C/ref=as_li_ss_tl?ie=UTF8&camp=1789&creative=390957&creativeASIN=B00BECVV9C&linkCode=as2&tag=httpwwwericro-20 262 | 263 | [incanter]: http://incanter.org/ 264 | [d3]: http://d3js.org/ 265 | [cljs]: https://github.com/clojure/clojurescript 266 | 267 | [weka]: http://www.cs.waikato.ac.nz/ml/weka/ 268 | [arff]: http://www.cs.waikato.ac.nz/ml/weka/arff.html 269 | [datasets]: http://liebke.github.com/incanter/datasets-api.html 270 | 271 | [uci]: http://archive.ics.uci.edu/ml/datasets.html 272 | [abalone]: http://archive.ics.uci.edu/ml/datasets/Abalone 273 | [ionosphere]: http://archive.ics.uci.edu/ml/datasets/Ionosphere 274 | [iris]: http://archive.ics.uci.edu/ml/datasets/Iris 275 | [mushroom]: http://archive.ics.uci.edu/ml/datasets/Mushroom 276 | 277 | [ire]: http://census.ire.org/ 278 | [census]: http://www.census.gov/ 279 | 280 | [nhtsa]: http://www-fars.nhtsa.dot.gov/QueryTool/QuerySection/selectyear.aspx 281 | 282 | [telegraphis]: http://telegraphis.net/data/currencies/currencies.ttl 283 | [xrates]: http://www.x-rates.com/ 284 | 285 | [wikip]: http://en.wikipedia.org/wiki/Doctor_Who_companions 286 | [drwho]: http://www.bbc.co.uk/programmes/b006q2x0 287 | 288 | [fasta]: http://blast.ncbi.nlm.nih.gov/blastcgihelp.shtml 289 | 290 | [gfinance]: https://www.google.com/finance 291 | 292 | [gutenberg]: http://www.gutenberg.org/ 293 | [holmes]: http://www.gutenberg.org/ebooks/1661 294 | 295 | [norvig]: http://norvig.com/spell-correct.html 296 | 297 | [worldbank]: http://data.worldbank.org/ 298 | 299 | --------------------------------------------------------------------------------