{"id":954,"date":"2023-07-28T04:49:24","date_gmt":"2023-07-28T04:49:24","guid":{"rendered":"https:\/\/statorials.org\/ja\/%e3%83%86%e3%82%a3%e3%83%95%e3%82%99%e3%83%ab-r-%e3%81%ae%e3%81%99%e3%81%b8%e3%82%99%e3%81%a6%e3%81%ae%e8%a1%8c%e3%82%92%e5%87%ba%e5%8a%9b%e3%81%97%e3%81%be%e3%81%99\/"},"modified":"2023-07-28T04:49:24","modified_gmt":"2023-07-28T04:49:24","slug":"%e3%83%86%e3%82%a3%e3%83%95%e3%82%99%e3%83%ab-r-%e3%81%ae%e3%81%99%e3%81%b8%e3%82%99%e3%81%a6%e3%81%ae%e8%a1%8c%e3%82%92%e5%87%ba%e5%8a%9b%e3%81%97%e3%81%be%e3%81%99","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/%e3%83%86%e3%82%a3%e3%83%95%e3%82%99%e3%83%ab-r-%e3%81%ae%e3%81%99%e3%81%b8%e3%82%99%e3%81%a6%e3%81%ae%e8%a1%8c%e3%82%92%e5%87%ba%e5%8a%9b%e3%81%97%e3%81%be%e3%81%99\/","title":{"rendered":"R \u3067 tibble \u306e\u3059\u3079\u3066\u306e\u884c\u3092\u5370\u5237\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"

<\/p>\n

\n

\u30c6\u30a3\u30d6\u30eb\u306f<\/strong>\u3001\u30c7\u30fc\u30bf \u30d5\u30ec\u30fc\u30e0\u306e\u6700\u521d\u306e 10 \u884c\u306e\u307f\u3092\u8868\u793a\u3059\u308b\u6d17\u7df4\u3055\u308c\u305f\u5370\u5237\u65b9\u6cd5\u3092\u5099\u3048\u305f R \u306e\u30c7\u30fc\u30bf \u30d5\u30ec\u30fc\u30e0\u3067\u3059\u3002\u3053\u308c\u306b\u3088\u308a\u3001\u5927\u898f\u6a21\u306a\u30c7\u30fc\u30bf\u306e\u64cd\u4f5c\u304c\u306f\u308b\u304b\u306b\u7c21\u5358\u306b\u306a\u308a\u3001R \u304c\u30c7\u30fc\u30bf \u30d5\u30ec\u30fc\u30e0\u5185\u306e\u3059\u3079\u3066\u306e\u884c\u3092\u8868\u793a\u3057\u3088\u3046\u3068\u3059\u308b\u3053\u3068\u304c\u306a\u304f\u306a\u308a\u307e\u3059\u3002<\/span><\/p>\n

\u305f\u3068\u3048\u3070\u300180 \u884c 2 \u5217\u306e\u6b21\u306e\u30c6\u30a3\u30d6\u30eb\u306b\u3064\u3044\u3066\u8003\u3048\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/span><\/p>\n

 #load dplyr\nlibrary(dplyr)<\/span>\n\n#make this example reproducible\nset.seed(1)<\/span>\n\n#create tibble<\/span>\ndata <- tibble(a = rnorm(80),\n               b = rnorm(80))\n<\/strong>\n#view tibble\n<\/span>data\n\n# A tibble: 80 x 2\n        ab\n      \n 1 -0.626 -0.569\n 2 0.184 -0.135\n 3 -0.836 1.18 \n 4 1.60 -1.52 \n 5 0.330 0.594\n 6 -0.820 0.333\n 7 0.487 1.06 \n 8 0.738 -0.304\n 9 0.576 0.370\n10 -0.305 0.267\n# ... with 70 more rows<\/strong><\/pre>\n
 R \u306b\u30c6\u30a3\u30d6\u30eb\u540d\u3092\u5165\u529b\u3059\u308b\u3068\u3001\u30c7\u30d5\u30a9\u30eb\u30c8\u3067\u306f\u6700\u521d\u306e 10 \u884c\u306e\u307f\u304c\u8868\u793a\u3055\u308c\u307e\u3059\u3002\u305f\u3060\u3057\u3001\u8868\u793a\u3055\u308c\u3066\u3044\u306a\u3044\u884c\u304c\u3055\u3089\u306b 70 \u884c<\/strong>\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n
\u305f\u3060\u3057\u3001\u5834\u5408\u306b\u3088\u3063\u3066\u306f\u300110 \u884c\u3092\u8d85\u3048\u308b\u30c6\u30a3\u30d6\u30eb\u3092\u8868\u793a\u3057\u305f\u3044\u5834\u5408\u3082\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n
\u6ce8:<\/strong>\u30c6\u30a3\u30d6\u30eb\u3092\u521d\u3081\u3066\u4f7f\u7528\u3059\u308b\u5834\u5408\u306f\u3001 R for Data Science<\/em>\u306e\u30c6\u30a3\u30d6\u30eb\u306e\u7ae0<\/a>\u304b\u3089\u59cb\u3081\u308b\u3068\u3088\u3044\u3067\u3057\u3087\u3046\u3002<\/span><\/p>\n
\u30c6\u30a3\u30d6\u30eb\u304b\u3089\u7279\u5b9a\u306e\u884c\u6570\u3092\u5370\u5237\u3059\u308b<\/strong><\/h3>\n
print()<\/strong>\u95a2\u6570\u3067\u6570\u5024\u3092\u6307\u5b9a\u3059\u308b\u3068\u3001\u30c6\u30a3\u30d6\u30eb\u306e\u7279\u5b9a\u306e\u884c\u6570\u3092\u5370\u5237\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n
 #print first 20 rows of tibble<\/span>\nprint(data, n= 20<\/span> )\n<\/strong>\n# A tibble: 80 x 2\n         ab\n       \n 1 -0.626 -0.569\n 2 0.184 -0.135\n 3 -0.836 1.18 \n 4 1.60 -1.52 \n 5 0.330 0.594\n 6 -0.820 0.333\n 7 0.487 1.06 \n 8 0.738 -0.304\n 9 0.576 0.370\n10 -0.305 0.267\n11 1.51 -0.543\n12 0.390 1.21 \n13 -0.621 1.16 \n14 -2.21 0.700\n15 1.12 1.59 \n16 -0.0449 0.558\n17 -0.0162 -1.28 \n18 0.944 -0.573\n19 0.821 -1.22 \n20 0.594 -0.473\n# ... with 60 more rows<\/strong><\/pre>\n
\u30d1\u30a4\u30d7\u6f14\u7b97\u5b50\u3092\u4f7f\u7528\u3057\u3066\u540c\u3058\u7d50\u679c\u3092\u9054\u6210\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n
 #print first 20 rows of tibble<\/span>\ndata %>% print(n= 20<\/span> )\n<\/strong>\n# A tibble: 80 x 2\n         ab\n       \n 1 -0.626 -0.569\n 2 0.184 -0.135\n 3 -0.836 1.18 \n 4 1.60 -1.52 \n 5 0.330 0.594\n 6 -0.820 0.333\n 7 0.487 1.06 \n 8 0.738 -0.304\n 9 0.576 0.370\n10 -0.305 0.267\n11 1.51 -0.543\n12 0.390 1.21 \n13 -0.621 1.16 \n14 -2.21 0.700\n15 1.12 1.59 \n16 -0.0449 0.558\n17 -0.0162 -1.28 \n18 0.944 -0.573\n19 0.821 -1.22 \n20 0.594 -0.473\n# ... with 60 more rows<\/strong><\/pre>\n
\u30c6\u30a3\u30d6\u30eb\u306e\u3059\u3079\u3066\u306e\u884c\u3092\u5370\u5237\u3057\u307e\u3059<\/strong><\/h3>\n
n = Inf<\/strong>\u3092\u6307\u5b9a\u3059\u308b\u3068\u3001\u30c6\u30a3\u30d6\u30eb\u306e\u5404\u884c\u3092\u5370\u5237\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n
 #print all rows of tibble<\/span>\ndata %>% print(n= Inf<\/span> )\n<\/strong>\n# A tibble: 80 x 2\n          ab\n         \n 1 -0.626 -0.569 \n 2 0.184 -0.135 \n 3 -0.836 1.18  \n 4 1.60 -1.52  \n 5 0.330 0.594 \n 6 -0.820 0.333 \n 7 0.487 1.06  \n 8 0.738 -0.304 \n 9 0.576 0.370 \n10 -0.305 0.267 \n11 1.51 -0.543 \n12 0.390 1.21  \n13 -0.621 1.16  \n14 -2.21 0.700 \n15 1.12 1.59  \n16 -0.0449 0.558 \n17 -0.0162 -1.28  \n18 0.944 -0.573 \n19 0.821 -1.22  \n20 0.594 -0.473 \n21 0.919 -0.620 \n22 0.782 0.0421\n23 0.0746 -0.911 \n24 -1.99 0.158 \n25 0.620 -0.655 \n26 -0.0561 1.77  \n27 -0.156 0.717 \n28 -1.47 0.910 \n29 -0.478 0.384 \n30 0.418 1.68  \n31 1.36 -0.636 \n32 -0.103 -0.462 \n33 0.388 1.43  \n34 -0.0538 -0.651 \n35 -1.38 -0.207 \n36 -0.415 -0.393 \n37 -0.394 -0.320 \n38 -0.0593 -0.279 \n39 1.10 0.494 \n40 0.763 -0.177 \n41 -0.165 -0.506 \n42 -0.253 1.34  \n43 0.697 -0.215 \n44 0.557 -0.180 \n45 -0.689 -0.100 \n46 -0.707 0.713 \n47 0.365 -0.0736\n48 0.769 -0.0376\n49 -0.112 -0.682 \n50 0.881 -0.324 \n51 0.398 0.0602\n52 -0.612 -0.589 \n53 0.341 0.531 \n54 -1.13 -1.52  \n55 1.43 0.307 \n56 1.98 -1.54  \n57 -0.367 -0.301 \n58 -1.04 -0.528 \n59 0.570 -0.652 \n60 -0.135 -0.0569\n61 2.40 -1.91  \n62 -0.0392 1.18  \n63 0.690 -1.66  \n64 0.0280 -0.464 \n65 -0.743 -1.12  \n66 0.189 -0.751 \n67 -1.80 2.09  \n68 1.47 0.0174\n69 0.153 -1.29  \n70 2.17 -1.64  \n71 0.476 0.450 \n72 -0.710 -0.0186\n73 0.611 -0.318 \n74 -0.934 -0.929 \n75 -1.25 -1.49  \n76 0.291 -1.08  \n77 -0.443 1.00  \n78 0.00111 -0.621 \n79 0.0743 -1.38  \n80 -0.590 1.87<\/strong><\/pre>\n
\u305d\u306e\u4ed6\u306e R \u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u306f\u3053\u3053\u3067<\/a>\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/em><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"
\u30c6\u30a3\u30d6\u30eb\u306f\u3001\u30c7\u30fc\u30bf \u30d5\u30ec\u30fc\u30e0\u306e\u6700\u521d\u306e 10 \u884c\u306e\u307f\u3092\u8868\u793a\u3059\u308b\u6d17\u7df4\u3055\u308c\u305f\u5370\u5237\u65b9\u6cd5\u3092\u5099\u3048\u305f R \u306e\u30c7\u30fc\u30bf \u30d5\u30ec\u30fc\u30e0\u3067\u3059\u3002\u3053\u308c\u306b\u3088\u308a\u3001\u5927\u898f\u6a21\u306a\u30c7\u30fc\u30bf\u306e\u64cd\u4f5c\u304c\u306f\u308b\u304b\u306b\u7c21\u5358\u306b\u306a\u308a\u3001R \u304c\u30c7\u30fc\u30bf \u30d5\u30ec\u30fc\u30e0\u5185\u306e\u3059\u3079\u3066\u306e\u884c\u3092\u8868\u793a\u3057\u3088\u3046\u3068 […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[],"class_list":["post-954","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"\nR \u3067 Tibble \u306e\u3059\u3079\u3066\u306e\u884c\u3092\u5370\u5237\u3059\u308b\u65b9\u6cd5 - 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