{"id":3614,"date":"2023-07-16T12:37:36","date_gmt":"2023-07-16T12:37:36","guid":{"rendered":"https:\/\/statorials.org\/ja\/r-%e3%81%ae%e3%83%86%e3%82%99%e3%83%bc%e3%82%bf-%e3%83%86%e3%83%bc%e3%83%95%e3%82%99%e3%83%ab%e3%81%a8%e3%83%86%e3%82%99%e3%83%bc%e3%82%bf-%e3%83%95%e3%83%ac%e3%83%bc%e3%83%a0\/"},"modified":"2023-07-16T12:37:36","modified_gmt":"2023-07-16T12:37:36","slug":"r-%e3%81%ae%e3%83%86%e3%82%99%e3%83%bc%e3%82%bf-%e3%83%86%e3%83%bc%e3%83%95%e3%82%99%e3%83%ab%e3%81%a8%e3%83%86%e3%82%99%e3%83%bc%e3%82%bf-%e3%83%95%e3%83%ac%e3%83%bc%e3%83%a0","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/r-%e3%81%ae%e3%83%86%e3%82%99%e3%83%bc%e3%82%bf-%e3%83%86%e3%83%bc%e3%83%95%e3%82%99%e3%83%ab%e3%81%a8%e3%83%86%e3%82%99%e3%83%bc%e3%82%bf-%e3%83%95%e3%83%ac%e3%83%bc%e3%83%a0\/","title":{"rendered":"Data.table \u3068 r \u306e\u30c7\u30fc\u30bf \u30d5\u30ec\u30fc\u30e0: 3 \u3064\u306e\u4e3b\u306a\u9055\u3044"},"content":{"rendered":"

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R \u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u8a00\u8a9e\u3067\u306f\u3001 data.frame \u306f<\/strong>R \u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u306e\u4e00\u90e8\u3067\u3059\u3002<\/span><\/p>\n

data.table<\/strong>\u30d1\u30c3\u30b1\u30fc\u30b8\u306esetDF<\/strong>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001\u4efb\u610f\u306edata.frame<\/strong>\u3092data.table<\/strong>\u306b\u5909\u63db\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n

data.table \u306b\u306f\u3001R \u306e data.frame \u306b\u6bd4\u3079\u3066\u6b21\u306e\u5229\u70b9\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n

1.<\/strong> data.table \u30d1\u30c3\u30b1\u30fc\u30b8\u306efread<\/a>\u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b\u3068\u3001\u30d5\u30a1\u30a4\u30eb\u3092 data.frame \u306b\u8aad\u307f\u53d6\u308bread.csv<\/a>\u306a\u3069\u306e\u57fa\u672c\u7684\u306a R \u95a2\u6570\u3088\u308a\u3082\u306f\u308b\u304b\u306b\u9ad8\u901f<\/em>\u306b\u30d5\u30a1\u30a4\u30eb\u3092 data.table \u306b\u8aad\u307f\u53d6\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n

2.<\/strong> data.table \u3067\u306f\u3001data.frame \u3088\u308a\u3082\u306f\u308b\u304b\u306b<\/em>\u9ad8\u901f\u306b\u64cd\u4f5c (\u30b0\u30eb\u30fc\u30d7\u5316\u3084\u96c6\u8a08\u306a\u3069) \u3092\u5b9f\u884c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n

3.<\/strong> data.frame \u3092\u30b3\u30f3\u30bd\u30fc\u30eb\u306b\u51fa\u529b\u3059\u308b\u3068\u304d\u3001R \u306f data.frame \u5185\u306e\u5404\u884c\u3092\u51fa\u529b\u3057\u3088\u3046\u3068\u3057\u307e\u3059\u3002\u305f\u3060\u3057\u3001data.table \u306b\u306f\u6700\u521d\u306e 100 \u884c\u3057\u304b\u8868\u793a\u3055\u308c\u306a\u3044\u305f\u3081\u3001\u5927\u898f\u6a21\u306a\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u64cd\u4f5c\u3057\u3066\u3044\u308b\u5834\u5408\u306b\u30bb\u30c3\u30b7\u30e7\u30f3\u304c\u30cf\u30f3\u30b0\u3057\u305f\u308a\u30af\u30e9\u30c3\u30b7\u30e5\u3057\u305f\u308a\u3059\u308b\u3053\u3068\u304c\u306a\u304f\u306a\u308b\u53ef\u80fd\u6027\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n

\u6b21\u306e\u4f8b\u306f\u3001\u5b9f\u969b\u306e data.frames \u3068 data.tables \u306e\u9055\u3044\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n

\u9055\u3044 #1: fread \u3092\u4f7f\u7528\u3057\u305f\u30a4\u30f3\u30dd\u30fc\u30c8\u306e\u9ad8\u901f\u5316<\/strong><\/span><\/h2>\n

\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001data.table \u30d1\u30c3\u30b1\u30fc\u30b8\u306efread<\/strong>\u95a2\u6570\u3068 R \u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u306eread.csv<\/strong>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u300110,000 \u884c\u3068 100 \u5217\u306e\u30c7\u30fc\u30bf \u30d5\u30ec\u30fc\u30e0\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n

 library<\/span> (microbenchmark)\nlibrary<\/span> (data.table)\n\n#make this example reproducible\n<\/span>set. seeds<\/span> (1)\n\n#create data frame with 10,000 rows and 100 columns\n<\/span>df <- as. data<\/span> . frame<\/span> (matrix(runif(10^4 * 100), nrow = 10^4))\n\n#export CSV to current working directory\n<\/span>write.write. csv<\/span> (df, \" test.csv<\/span> \", quote = FALSE<\/span> )\n\n#import CSV file using fread and read.csv and time how long it takes\n<\/span>results <- microbenchmark(\n  read.csv = read. csv<\/span> (\" test.csv<\/span> \", header = TRUE<\/span> , stringsAsFactors = FALSE<\/span> ),\n  fread = fread(\" test.csv<\/span> \", sep = \",\", stringsAsFactors = FALSE<\/span> ),\n  times = 10)\n\n#view results\n<\/span>results\n\nUnit: milliseconds\n     expr min lq mean median uq max neval cld\n read.csv 817.1867 892.8748 1026.7071 899.5755 926.9120 1964.0540 10 b\n    fread 113.5889 116.2735 136.4079 124.3816 136.0534 211.7484 10 a<\/strong><\/pre>\n
\u7d50\u679c\u304b\u3089\u3001 fread \u306f<\/strong>read.csv<\/strong>\u95a2\u6570\u3068\u6bd4\u8f03\u3057\u3066\u3001\u3053\u306e CSV \u30d5\u30a1\u30a4\u30eb\u306e\u30a4\u30f3\u30dd\u30fc\u30c8\u304c\u7d04 10 \u500d\u9ad8\u901f\u3067\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n
\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u304c\u5927\u304d\u3044\u5834\u5408\u3001\u3053\u306e\u9055\u3044\u306f\u3055\u3089\u306b\u5927\u304d\u304f\u306a\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n
\u9055\u3044 #2: data.table \u3092\u4f7f\u7528\u3057\u305f\u9ad8\u901f\u306a\u30c7\u30fc\u30bf\u64cd\u4f5c<\/strong><\/span><\/h2>\n
\u4e00\u822c\u306b\u3001 data.table \u306f<\/strong>\u3001 data.frame<\/strong>\u3088\u308a\u3082\u306f\u308b\u304b\u306b\u9ad8\u901f\u306b\u3042\u3089\u3086\u308b\u30c7\u30fc\u30bf\u64cd\u4f5c\u30bf\u30b9\u30af\u3092\u5b9f\u884c\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n
\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001data.table \u3068 data.frame \u306e\u4e21\u65b9\u3067\u5225\u306e\u5909\u6570\u306b\u3088\u3063\u3066\u30b0\u30eb\u30fc\u30d7\u5316\u3055\u308c\u305f\u5909\u6570\u306e\u5e73\u5747\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n
 library<\/span> (microbenchmark)\nlibrary<\/span> (data.table)\n\n#make this example reproducible\n<\/span>set.seed(1)\n\n#create data frame with 10,000 rows and 100 columns\nd_frame <- data. frame<\/span> (team=rep(c(' A<\/span> ', ' B<\/span> '), each=5000),\n                      points=c(rnorm(10000, mean=20, sd=3)))\n\n#create data.table from data.frame\n<\/span>d_table <- setDT(d_frame)\n\n#calculate mean of points grouped by team in data.frame and data.table\n<\/span>results <- microbenchmark(\n  mean_d_frame = aggregate(d_frame$points, list(d_frame$team), FUN=mean),\n  mean_d_table = d_table[ ,list(mean=mean(points)), by=team],\n  times = 10)\n\n#view results\n<\/span>results\n\nUnit: milliseconds\n         expr min lq mean median uq max neval cld\n mean_d_frame 2.9045 3.0077 3.11683 3.1074 3.1654 3.4824 10 b\n mean_d_table 1.0539 1.1140 1.52002 1.2075 1.2786 3.6084 10 a<\/strong><\/span><\/pre>\n
\u7d50\u679c\u304b\u3089\u3001 data.table \u306f<\/strong>data.frame<\/strong>\u3088\u308a\u3082\u7d04 3 \u500d\u9ad8\u901f\u3067\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n
\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u304c\u5927\u304d\u3044\u5834\u5408\u3001\u3053\u306e\u5dee\u306f\u3055\u3089\u306b\u5927\u304d\u304f\u306a\u308a\u307e\u3059\u3002<\/span><\/p>\n
\u9055\u3044 #3: data.table \u3067\u5370\u5237\u3055\u308c\u308b\u884c\u304c\u5c11\u306a\u304f\u306a\u308b<\/strong><\/span><\/h2>\n
data.frame \u3092<\/strong>\u30b3\u30f3\u30bd\u30fc\u30eb\u306b\u51fa\u529b\u3059\u308b\u3068\u304d\u3001R \u306f data.frame \u5185\u306e\u5404\u884c\u3092\u51fa\u529b\u3057\u3088\u3046\u3068\u3057\u307e\u3059\u3002<\/span><\/p>\n
\u305f\u3060\u3057\u3001 data.table \u306b<\/strong>\u306f\u6700\u521d\u306e 100 \u884c\u3057\u304b\u8868\u793a\u3055\u308c\u306a\u3044\u305f\u3081\u3001\u5927\u898f\u6a21\u306a\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u64cd\u4f5c\u3057\u3066\u3044\u308b\u5834\u5408\u306b\u30bb\u30c3\u30b7\u30e7\u30f3\u304c\u30cf\u30f3\u30b0\u3057\u305f\u308a\u30af\u30e9\u30c3\u30b7\u30e5\u3057\u305f\u308a\u3059\u308b\u3053\u3068\u304c\u306a\u304f\u306a\u308b\u53ef\u80fd\u6027\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n
\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u3067\u306f\u3001\u30c7\u30fc\u30bf \u30d5\u30ec\u30fc\u30e0\u3068 200 \u884c\u306e data.table \u306e\u4e21\u65b9\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002<\/span><\/p>\n
 data.frame \u3092\u5370\u5237\u3059\u308b\u3068\u304d\u3001R \u306f\u5404\u884c\u306e\u5370\u5237\u3092\u8a66\u307f\u307e\u3059\u304c\u3001data.table \u306f\u6700\u521d\u306e 5 \u884c\u3068\u6700\u5f8c\u306e 5 \u884c\u306e\u307f\u3092\u8868\u793a\u3057\u307e\u3059\u3002<\/span><\/p>\n
 library<\/span> (data.table)\n\n#make this example reproducible\n<\/span>set. seeds<\/span> (1)\n\n#create data frame\n<\/span>d_frame <- data. frame<\/span> (x=rnorm(200),\n                      y=rnorm(200),\n                      z=rnorm(200))\n#view data frame\n<\/span>d_frame\n\n               X Y Z\n1 -0.055303118 1.54858564 -2.065337e-02\n2 0.354143920 0.36706204 -3.743962e-01\n3 -0.999823809 -1.57842544 4.392027e-01\n4 2.586214840 0.17383147 -2.081125e+00\n5 -1.917692199 -2.11487401 4.073522e-01\n6 0.039614766 2.21644236 1.869164e+00\n7 -1.942259548 0.81566443 4.740712e-01\n8 -0.424913746 1.01081030 4.996065e-01\n9 -1.753210825 -0.98893038 -6.290307e-01\n10 0.232382655 -1.25229873 -1.324883e+00\n11 0.027278832 0.44209325 -3.221920e-01\n...\n#create data table\n<\/span>d_table <- setDT(d_frame)\n\n#view data table\n<\/span>d_table\n\n               X Y Z\n  1: -0.05530312 1.54858564 -0.02065337\n  2: 0.35414392 0.36706204 -0.37439617\n  3: -0.99982381 -1.57842544 0.43920275\n  4: 2.58621484 0.17383147 -2.08112491\n  5: -1.91769220 -2.11487401 0.40735218\n ---                                    \n196: -0.06196178 1.08164065 0.58609090\n197: 0.34160667 -0.01886703 1.61296255\n198: -0.38361957 -0.03890329 0.71377217\n199: -0.80719743 -0.89674205 -0.49615702\n200: -0.26502679 -0.15887435 -1.73781026<\/strong><\/pre>\n
\u3053\u308c\u306f\u3001\u7279\u306b\u8aa4\u3063\u3066\u30b3\u30f3\u30bd\u30fc\u30eb\u306b\u51fa\u529b\u3057\u305f\u304f\u306a\u3044\u5927\u898f\u6a21\u306a\u30c7\u30fc\u30bf \u30bb\u30c3\u30c8\u3092\u6271\u3046\u5834\u5408\u306b\u3001 data.table \u304c<\/strong>data.frame<\/strong>\u306b\u6bd4\u3079\u3066\u63d0\u4f9b\u3059\u308b\u5229\u70b9\u3067\u3059\u3002<\/span><\/p>\n
\u8ffd\u52a0\u30ea\u30bd\u30fc\u30b9<\/strong><\/span><\/h2>\n
\u6b21\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001R \u3067\u4ed6\u306e\u4e00\u822c\u7684\u306a\u30bf\u30b9\u30af\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u306b\u3064\u3044\u3066\u8aac\u660e\u3057\u307e\u3059\u3002<\/span><\/p>\n
 R \u3067\u30c7\u30fc\u30bf \u30d5\u30ec\u30fc\u30e0\u306b\u884c\u3092\u8ffd\u52a0\u3059\u308b\u65b9\u6cd5<\/a>
R \u3067\u7279\u5b9a\u306e\u5217\u3092\u4fdd\u5b58\u3059\u308b\u65b9\u6cd5<\/a>
R \u3067\u6570\u5024\u5217\u306e\u307f\u3092\u9078\u629e\u3059\u308b\u65b9\u6cd5<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
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