{"id":957,"date":"2023-07-28T04:49:24","date_gmt":"2023-07-28T04:49:24","guid":{"rendered":"https:\/\/statorials.org\/cn\/%e6%89%93%e5%8d%b0-tibble-r-%e7%9a%84%e6%89%80%e6%9c%89%e8%a1%8c\/"},"modified":"2023-07-28T04:49:24","modified_gmt":"2023-07-28T04:49:24","slug":"%e6%89%93%e5%8d%b0-tibble-r-%e7%9a%84%e6%89%80%e6%9c%89%e8%a1%8c","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/%e6%89%93%e5%8d%b0-tibble-r-%e7%9a%84%e6%89%80%e6%9c%89%e8%a1%8c\/","title":{"rendered":"\u5982\u4f55\u5728 r \u4e2d\u6253\u5370 tibble \u7684\u6240\u6709\u884c"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>tibble<\/strong>\u662f R \u4e2d\u7684\u6570\u636e\u5e27\uff0c\u5b83\u5177\u6709\u6539\u8fdb\u7684\u6253\u5370\u65b9\u6cd5\uff0c\u4ec5\u663e\u793a\u6570\u636e\u5e27\u7684\u524d 10 \u884c\u3002\u8fd9\u4f7f\u5f97\u5904\u7406\u5927\u6570\u636e\u53d8\u5f97\u66f4\u52a0\u5bb9\u6613\uff0c\u5e76\u9632\u6b62 R \u5c1d\u8bd5\u663e\u793a\u6570\u636e\u6846\u4e2d\u7684\u6bcf\u4e00\u884c\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4f8b\u5982\uff0c\u8003\u8651\u4ee5\u4e0b\u5177\u6709 80 \u884c\u548c 2 \u5217\u7684 tibble\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#load dplyr\n<span style=\"color: #000000;\">library(dplyr)<\/span>\n\n#make this example reproducible\n<span style=\"color: #000000;\">set.seed(1)<\/span>\n\n#create tibble<\/span>\ndata &lt;- tibble(a = rnorm(80),\n               b = rnorm(80))\n<\/strong>\n<strong><span style=\"color: #008080;\">#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<p><span style=\"color: #000000;\">\u5f53\u6211\u4eec\u5728 R \u4e2d\u8f93\u5165 tibble \u540d\u79f0\u65f6\uff0c\u9ed8\u8ba4\u60c5\u51b5\u4e0b\u5b83\u53ea\u4f1a\u663e\u793a\u524d 10 \u884c\u3002\u4f46\u662f\uff0c\u8fd9\u544a\u8bc9\u6211\u4eec\u8fd8\u6709<strong>70 \u884c<\/strong>\u672a\u663e\u793a\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4f46\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\uff0c\u60a8\u53ef\u80fd\u5e0c\u671b\u770b\u5230\u8d85\u8fc7 10 \u884c\u7684\u5c0f\u6807\u9898\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u6ce8\u610f\uff1a<\/strong>\u5982\u679c\u60a8\u662f tibbles \u65b0\u624b\uff0c\u6700\u597d\u4ece<em>R for Data Science<\/em>\u7684<a href=\"https:\/\/r4ds.had.co.nz\/tibbles.html\" target=\"_blank\" rel=\"noopener noreferrer\">tibbles \u7ae0\u8282<\/a>\u5f00\u59cb\u3002<\/span><\/p>\n<h3><strong>\u4ece Tibble \u6253\u5370\u7279\u5b9a\u884c\u6570<\/strong><\/h3>\n<p><span style=\"color: #000000;\">\u60a8\u53ef\u4ee5\u901a\u8fc7\u5728<strong>print()<\/strong>\u51fd\u6570\u4e2d\u6307\u5b9a\u6570\u5b57\u6765\u6253\u5370 tibble \u7684\u7279\u5b9a\u884c\u6570\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#print first 20 rows of tibble<\/span>\nprint(data, n= <span style=\"color: #008000;\">20<\/span> )\n<\/strong><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<p><span style=\"color: #000000;\">\u60a8\u8fd8\u53ef\u4ee5\u4f7f\u7528\u7ba1\u9053\u8fd0\u7b97\u7b26\u6765\u5b9e\u73b0\u76f8\u540c\u7684\u7ed3\u679c\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#print first 20 rows of tibble<\/span>\ndata %&gt;% print(n= <span style=\"color: #008000;\">20<\/span> )\n<\/strong><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<h3><strong>\u6253\u5370 Tible \u7684\u6240\u6709\u884c<\/strong><\/h3>\n<p><span style=\"color: #000000;\">\u60a8\u53ef\u4ee5\u901a\u8fc7\u6307\u5b9a<strong>n = Inf<\/strong>\u6765\u6253\u5370 tibble \u7684\u6bcf\u4e00\u884c\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#print all rows of tibble<\/span>\ndata %&gt;% print(n= <span style=\"color: #008000;\">Inf<\/span> )\n<\/strong><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<p><span style=\"color: #000000;\"><em>\u60a8\u53ef\u4ee5<a href=\"https:\/\/statorials.org\/cn\/\u7edf\u8ba1\u5b66\u4ee5\u7b80\u5355\u76f4\u63a5\u7684\u65b9\u5f0f\u89e3\u91ca\u6982\u5ff5\uff0c\u6211\u4eec\u4f7f\u5b66\u4e60\u7edf\u8ba1\u53d8\u5f97\u66f4\u5bb9\u6613\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u5728\u6b64\u5904<\/a>\u627e\u5230\u66f4\u591a R \u6559\u7a0b\u3002<\/em><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>tibble\u662f R \u4e2d\u7684\u6570\u636e\u5e27\uff0c\u5b83\u5177\u6709\u6539\u8fdb\u7684\u6253\u5370\u65b9\u6cd5\uff0c\u4ec5\u663e\u793a\u6570\u636e\u5e27\u7684\u524d 10 \u884c\u3002\u8fd9\u4f7f\u5f97\u5904\u7406\u5927\u6570\u636e\u53d8\u5f97\u66f4\u52a0\u5bb9\u6613 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-957","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\u5982\u4f55\u5728 R \u4e2d\u6253\u5370 Tibble \u7684\u6240\u6709\u884c - Statorials<\/title>\n<meta name=\"description\" content=\"\u5173\u4e8e\u5982\u4f55\u5728 R \u4e2d\u6253\u5370 tibble \u7684\u6240\u6709\u884c\u7684\u7b80\u5355\u8bf4\u660e\u3002\" \/>\n<meta name=\"robots\" content=\"index, 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