{"id":954,"date":"2023-07-28T04:49:24","date_gmt":"2023-07-28T04:49:24","guid":{"rendered":"https:\/\/statorials.org\/ar\/%d8%b7%d8%a8%d8%a7%d8%b9%d8%a9-%d8%ac%d9%85%d9%8a%d8%b9-%d8%ae%d8%b7%d9%88%d8%b7-tibble-r\/"},"modified":"2023-07-28T04:49:24","modified_gmt":"2023-07-28T04:49:24","slug":"%d8%b7%d8%a8%d8%a7%d8%b9%d8%a9-%d8%ac%d9%85%d9%8a%d8%b9-%d8%ae%d8%b7%d9%88%d8%b7-tibble-r","status":"publish","type":"post","link":"https:\/\/statorials.org\/ar\/%d8%b7%d8%a8%d8%a7%d8%b9%d8%a9-%d8%ac%d9%85%d9%8a%d8%b9-%d8%ae%d8%b7%d9%88%d8%b7-tibble-r\/","title":{"rendered":"\u0643\u064a\u0641\u064a\u0629 \u0637\u0628\u0627\u0639\u0629 \u062c\u0645\u064a\u0639 \u0623\u0633\u0637\u0631 tibble \u0641\u064a r"},"content":{"rendered":"

<\/p>\n

\n

Tibble<\/strong> \u0639\u0628\u0627\u0631\u0629 \u0639\u0646 \u0625\u0637\u0627\u0631 \u0628\u064a\u0627\u0646\u0627\u062a \u0641\u064a R \u064a\u062d\u062a\u0648\u064a \u0639\u0644\u0649 \u0637\u0631\u064a\u0642\u0629 \u0637\u0628\u0627\u0639\u0629 \u0645\u062d\u0633\u0646\u0629 \u062a\u0639\u0631\u0636 \u0641\u0642\u0637 \u0627\u0644\u0623\u0633\u0637\u0631 \u0627\u0644\u0639\u0634\u0631\u0629 \u0627\u0644\u0623\u0648\u0644\u0649 \u0645\u0646 \u0625\u0637\u0627\u0631 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a. \u0648\u0647\u0630\u0627 \u064a\u062c\u0639\u0644 \u0627\u0644\u0639\u0645\u0644 \u0645\u0639 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0627\u0644\u0643\u0628\u064a\u0631\u0629 \u0623\u0633\u0647\u0644 \u0628\u0643\u062b\u064a\u0631 \u0648\u064a\u0645\u0646\u0639 R \u0645\u0646 \u0645\u062d\u0627\u0648\u0644\u0629 \u0639\u0631\u0636 \u0643\u0644 \u0635\u0641 \u0641\u064a \u0625\u0637\u0627\u0631 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a.<\/span><\/p>\n

\u0639\u0644\u0649 \u0633\u0628\u064a\u0644 \u0627\u0644\u0645\u062b\u0627\u0644\u060c \u0641\u0643\u0631 \u0641\u064a \u0627\u0644\u062c\u062f\u0648\u0644 \u0627\u0644\u062a\u0627\u0644\u064a \u0627\u0644\u0630\u064a \u064a\u062d\u062a\u0648\u064a \u0639\u0644\u0649 80 \u0635\u0641\u064b\u0627 \u0648\u0639\u0645\u0648\u062f\u064a\u0646:<\/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
 \u0639\u0646\u062f\u0645\u0627 \u0646\u0643\u062a\u0628 \u0627\u0633\u0645 Tibble \u0641\u064a R\u060c \u0641\u0625\u0646\u0647 \u0633\u064a\u0638\u0647\u0631 \u0641\u0642\u0637 \u0627\u0644\u0623\u0633\u0637\u0631 \u0627\u0644\u0639\u0634\u0631\u0629 \u0627\u0644\u0623\u0648\u0644\u0649 \u0628\u0634\u0643\u0644 \u0627\u0641\u062a\u0631\u0627\u0636\u064a. \u0648\u0645\u0639 \u0630\u0644\u0643\u060c \u0641\u0647\u0630\u0627 \u064a\u062e\u0628\u0631\u0646\u0627 \u0628\u0648\u062c\u0648\u062f 70 \u0635\u0641\u064b\u0627 \u0625\u0636\u0627\u0641\u064a\u064b\u0627<\/strong> \u063a\u064a\u0631 \u0645\u0639\u0631\u0648\u0636\u0629.<\/span><\/p>\n
 \u0648\u0644\u0643\u0646 \u0641\u064a \u0628\u0639\u0636 \u0627\u0644\u062d\u0627\u0644\u0627\u062a \u0642\u062f \u062a\u0631\u063a\u0628 \u0641\u064a \u0631\u0624\u064a\u0629 \u0623\u0643\u062b\u0631 \u0645\u0646 10 \u0623\u0633\u0637\u0631 \u0645\u0646 \u0627\u0644\u062d\u0635\u0629.<\/span><\/p>\n
 \u0645\u0644\u0627\u062d\u0638\u0629:<\/strong> \u0625\u0630\u0627 \u0643\u0646\u062a \u062c\u062f\u064a\u062f\u064b\u0627 \u0641\u064a \u0645\u062c\u0627\u0644 tibbles\u060c \u0641\u0627\u0644\u0645\u0643\u0627\u0646 \u0627\u0644\u062c\u064a\u062f \u0644\u0644\u0628\u062f\u0621 \u0647\u0648 \u0641\u0635\u0644 tibbles<\/a> \u0645\u0646 R for Data Science<\/em> .<\/span><\/p>\n
 \u0637\u0628\u0627\u0639\u0629 \u0639\u062f\u062f \u0645\u062d\u062f\u062f \u0645\u0646 \u0627\u0644\u0623\u0633\u0637\u0631 \u0645\u0646 Tibble<\/strong><\/h3>\n
 \u064a\u0645\u0643\u0646\u0643 \u0637\u0628\u0627\u0639\u0629 \u0639\u062f\u062f \u0645\u062d\u062f\u062f \u0645\u0646 \u0623\u0633\u0637\u0631 tibble \u0639\u0646 \u0637\u0631\u064a\u0642 \u062a\u062d\u062f\u064a\u062f \u0631\u0642\u0645 \u0641\u064a \u0648\u0638\u064a\u0641\u0629 print()<\/strong> :<\/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
 \u064a\u0645\u0643\u0646\u0643 \u0623\u064a\u0636\u064b\u0627 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0645\u0634\u063a\u0644 \u0627\u0644\u0623\u0646\u0627\u0628\u064a\u0628 \u0644\u062a\u062d\u0642\u064a\u0642 \u0646\u0641\u0633 \u0627\u0644\u0646\u062a\u064a\u062c\u0629:<\/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
 \u0637\u0628\u0627\u0639\u0629 \u062c\u0645\u064a\u0639 \u0623\u0633\u0637\u0631 Tibble<\/strong><\/h3>\n
 \u064a\u0645\u0643\u0646\u0643 \u0637\u0628\u0627\u0639\u0629 \u0643\u0644 \u0633\u0637\u0631 \u0645\u0646 tibble \u0639\u0646 \u0637\u0631\u064a\u0642 \u062a\u062d\u062f\u064a\u062f n = Inf<\/strong> :<\/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
 \u064a\u0645\u0643\u0646\u0643 \u0627\u0644\u0639\u062b\u0648\u0631 \u0639\u0644\u0649 \u0627\u0644\u0645\u0632\u064a\u062f \u0645\u0646 \u062f\u0631\u0648\u0633 R \u0647\u0646\u0627 .<\/em><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"
Tibble \u0639\u0628\u0627\u0631\u0629 \u0639\u0646 \u0625\u0637\u0627\u0631 \u0628\u064a\u0627\u0646\u0627\u062a \u0641\u064a R \u064a\u062d\u062a\u0648\u064a \u0639\u0644\u0649 \u0637\u0631\u064a\u0642\u0629 \u0637\u0628\u0627\u0639\u0629 \u0645\u062d\u0633\u0646\u0629 \u062a\u0639\u0631\u0636 \u0641\u0642\u0637 \u0627\u0644\u0623\u0633\u0637\u0631 \u0627\u0644\u0639\u0634\u0631\u0629 \u0627\u0644\u0623\u0648\u0644\u0649 \u0645\u0646 \u0625\u0637\u0627\u0631 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a. \u0648\u0647\u0630\u0627 \u064a\u062c\u0639\u0644 \u0627\u0644\u0639\u0645\u0644 \u0645\u0639 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0627\u0644\u0643\u0628\u064a\u0631\u0629 \u0623\u0633\u0647\u0644 \u0628\u0643\u062b\u064a\u0631 \u0648\u064a\u0645\u0646\u0639 R \u0645\u0646 \u0645\u062d\u0627\u0648\u0644\u0629 \u0639\u0631\u0636 \u0643\u0644 \u0635\u0641 \u0641\u064a \u0625\u0637\u0627\u0631 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a. \u0639\u0644\u0649 \u0633\u0628\u064a\u0644 \u0627\u0644\u0645\u062b\u0627\u0644\u060c \u0641\u0643\u0631 \u0641\u064a \u0627\u0644\u062c\u062f\u0648\u0644 \u0627\u0644\u062a\u0627\u0644\u064a \u0627\u0644\u0630\u064a \u064a\u062d\u062a\u0648\u064a \u0639\u0644\u0649 80 \u0635\u0641\u064b\u0627 \u0648\u0639\u0645\u0648\u062f\u064a\u0646: #load dplyr library(dplyr) #make […]<\/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":[],"yoast_head":"\n\u0643\u064a\u0641\u064a\u0629 \u0637\u0628\u0627\u0639\u0629 \u062c\u0645\u064a\u0639 \u0623\u0633\u0637\u0631 Tibble \u0641\u064a R - 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