{"id":1978,"date":"2023-07-24T05:32:17","date_gmt":"2023-07-24T05:32:17","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%87%e1%85%a9%e1%86%a8%e1%84%89%e1%85%a1-%e1%84%80%e1%85%a7%e1%86%bc%e1%84%80%e1%85%a9%e1%84%80%e1%85%a1-%e1%84%8b%e1%85%b5%e1%86%bb%e1%84%82%e1%85%b3%e1%86%ab-%e1%84%91%e1%85%a2%e1%86%ab\/"},"modified":"2023-07-24T05:32:17","modified_gmt":"2023-07-24T05:32:17","slug":"%e1%84%87%e1%85%a9%e1%86%a8%e1%84%89%e1%85%a1-%e1%84%80%e1%85%a7%e1%86%bc%e1%84%80%e1%85%a9%e1%84%80%e1%85%a1-%e1%84%8b%e1%85%b5%e1%86%bb%e1%84%82%e1%85%b3%e1%86%ab-%e1%84%91%e1%85%a2%e1%86%ab","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%87%e1%85%a9%e1%86%a8%e1%84%89%e1%85%a1-%e1%84%80%e1%85%a7%e1%86%bc%e1%84%80%e1%85%a9%e1%84%80%e1%85%a1-%e1%84%8b%e1%85%b5%e1%86%bb%e1%84%82%e1%85%b3%e1%86%ab-%e1%84%91%e1%85%a2%e1%86%ab\/","title":{"rendered":"Pandas\uc5d0\uc11c \uc218\uc815\ud558\ub294 \ubc29\ubc95:settingwithcopywarning"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">Pandas\ub97c \uc0ac\uc6a9\ud560 \ub54c \ubc1c\uc0dd\ud560 \uc218 \uc788\ub294 \uacbd\uace0 \uc911 \ud558\ub098\ub294 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc774 \uacbd\uace0\ub294 \ud32c\ub354\uac00 \uccb4\uc778 \ud560\ub2f9(\uccb4\uc778 \ud560\ub2f9\uacfc \ud55c \ub2e8\uacc4\uc758 \uc870\ud569)\uc774\ub77c\ub294 \uac83\uc744 \ubc1c\uacac\ud560 \ub54c \ub098\ud0c0\ub0a9\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774\ub294 \ub2e8\uc9c0 <em>\uacbd\uace0\uc77c<\/em> \ubfd0\uc774\uba70 \uc624\ub958\uac00 \uc544\ub2c8\ub77c\ub294 \uc810\uc5d0 \uc720\uc758\ud558\ub294 \uac83\uc774 \uc911\uc694\ud569\ub2c8\ub2e4. \ucf54\ub4dc\ub294 \uacc4\uc18d \uc2e4\ud589\ub418\uc9c0\ub9cc \uacb0\uacfc\uac00 \ud56d\uc0c1 \uc608\uc0c1\ud55c \uac83\uacfc \ub2e4\ub97c \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774 \uacbd\uace0\ub97c \uc5b5\uc81c\ud558\ub294 \uac00\uc7a5 \uc26c\uc6b4 \ubc29\ubc95\uc740 \ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\ub294 \uac83\uc785\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>p.d. <span style=\"color: #3366ff;\">options<\/span> . <span style=\"color: #3366ff;\">fashion<\/span> . <span style=\"color: #3366ff;\">chained_assignment<\/span> = <span style=\"color: #008000;\">None<\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc2e4\uc81c\ub85c \uc774 \uacbd\uace0\uc5d0 \ub300\uc751\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\uacbd\uace0\ub97c \uc7ac\ud604\ud558\ub294 \ubc29\ubc95<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c\uacfc \uac19\uc740 pandas DataFrame\uc744 \uc0dd\uc131\ud55c\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame\n<span style=\"color: #000000;\">df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">A<\/span> ': [25, 12, 15, 14, 19, 23, 25, 29],\n                   ' <span style=\"color: #ff0000;\">B<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n                   ' <span style=\"color: #ff0000;\">C<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12]})<\/span>\n\n#view DataFrame\n<span style=\"color: #000000;\">df<\/span>\n<\/span>\n\tA B C\n0 25 5 11\n1 12 7 8\n2 15 7 10\n3 14 9 6\n4 19 12 6\n5 23 9 5\n6 25 9 9\n7 29 4 12<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc774\uc81c \uc6d0\ubcf8 DataFrame\uc758 &#8220;A&#8221; \uc5f4\ub9cc \ud3ec\ud568\ud558\ub294 \uc0c8 DataFrame\uc744 \ub9cc\ub4e4\uace0 &#8220;A&#8221; \uc5f4\uc758 \uac01 \uac12\uc744 2\ub85c \ub098\ub208\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#define new DataFrame\n<\/span>df2 = df[[' <span style=\"color: #ff0000;\">A<\/span> ']]\n\n<\/span>#divide all values in column 'A' by 2\n<span style=\"color: #000000;\">df2[' <span style=\"color: #ff0000;\">A<\/span> '] = df[' <span style=\"color: #ff0000;\">A<\/span> '] \/ 2<\/span>\n\n<span style=\"color: #000000;\">\/srv\/conda\/envs\/notebook\/lib\/python3.7\/site-packages\/ipykernel_launcher.py:2:\nSettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc6d0\ubcf8 DataFrame\uc758 &#8220;\uc2ac\ub77c\uc774\uc2a4&#8221;\uc5d0\uc11c \uc5f4 &#8220;A&#8221;\uc5d0 \ub300\ud55c \uc0c8 \uac12\uc744 \uc124\uc815\ud558\uace0 \uc788\uae30 \ub54c\ubb38\uc5d0 <strong>SettingWithCopyWarning<\/strong> \uba54\uc2dc\uc9c0\ub97c \ubc1b\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uadf8\ub7ec\ub098 \uc6b0\ub9ac\uac00 \ub9cc\ub4e0 \uc0c8 DataFrame\uc744 \uc0b4\ud3b4\ubcf4\uba74 \uac01 \uac12\uc774 \uc2e4\uc81c\ub85c \uc131\uacf5\uc801\uc73c\ub85c 2\ub85c \ub098\ub204\uc5b4\uc9c4 \uac83\uc744 \ubcfc \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#view new DataFrame\n<\/span>df2\n\n     HAS\n0 12.5\n1 6.0\n2 7.5\n3 7.0\n4 9.5\n5 11.5\n6 12.5\n7 14.5\n<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uacbd\uace0 \uba54\uc2dc\uc9c0\ub97c \ubc1b\uc558\uc74c\uc5d0\ub3c4 \ubd88\uad6c\ud558\uace0 \ud32c\ub354\ub294 \uc5ec\uc804\ud788 \uc6b0\ub9ac\uac00 \uc0dd\uac01\ud588\ub358 \ub300\ub85c \ud589\ub3d9\ud588\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\uacbd\uace0\ub97c \ud53c\ud558\ub294 \ubc29\ubc95<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\uc774 \uacbd\uace0\ub97c \ubc29\uc9c0\ud558\ub824\uba74 \ub2e4\uc74c\uacfc \uac19\uc774 <strong>.loc[row indexer, col indexer]<\/strong> \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 \uac83\uc774 \uc88b\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#define new DataFrame\n<\/span>df2 = df. <span style=\"color: #3366ff;\">loc<\/span> [:,[' <span style=\"color: #ff0000;\">A<\/span> ']]\n\n<span style=\"color: #008080;\">#divide each value in column 'A' by 2\n<\/span>df2[' <span style=\"color: #ff0000;\">A<\/span> '] = df[' <span style=\"color: #ff0000;\">A<\/span> '] \/ 2\n\n<span style=\"color: #008080;\">#view result\n<\/span>df2\n\n     HAS\n0 12.5\n1 6.0\n2 7.5\n3 7.0\n4 9.5\n5 11.5\n6 12.5\n7 14.5\n<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc0c8 DataFrame\uc5d0\ub294 \uc6d0\ubcf8 DataFrame\uc758 &#8220;A&#8221; \uc5f4\uc5d0 \uc788\ub294 \ubaa8\ub4e0 \uac12\uc774 2\ub85c \ub098\ub204\uc5b4 \ud3ec\ud568\ub418\uc5b4 \uc788\uc73c\uba70 \uacbd\uace0 \uba54\uc2dc\uc9c0\uac00 \ud45c\uc2dc\ub418\uc9c0 \uc54a\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uacbd\uace0 \uba54\uc2dc\uc9c0\uac00 \ud45c\uc2dc\ub418\ub294 \uac83\uc744 \ubc29\uc9c0\ud558\ub824\uba74 \ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#prevent SettingWithCopyWarning message from appearing\n<\/span>p.d. <span style=\"color: #3366ff;\">options<\/span> . <span style=\"color: #3366ff;\">fashion<\/span> . <span style=\"color: #3366ff;\">chained_assignment<\/span> = <span style=\"color: #008000;\">None<\/span>\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uccb4\uc778 \ud560\ub2f9\uc744 \ud53c\ud574\uc57c \ud558\ub294 \uc774\uc720\uc5d0 \ub300\ud55c \uc790\uc138\ud55c \uc124\uba85\uc740 <a href=\"https:\/\/pandas.pydata.org\/pandas-docs\/version\/0.22\/indexing.html\" target=\"_blank\" rel=\"noopener\">\uc628\ub77c\uc778 Pandas \uc124\uba85\uc11c\ub97c<\/a> \ucc38\uc870\ud558\uc138\uc694.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h3>\n<p> <a href=\"https:\/\/statorials.org\/ko\/pandas\u1105\u1161\u1102\u1173\u11ab-\u1106\u1169\u1103\u1172\u11af\u110b\u1175-\u110b\u1165\u11b9\u1109\u1173\u11b8\u1102\u1175\u1103\u1161.\/\" target=\"_blank\" rel=\"noopener\">\ud574\uacb0 \ubc29\ubc95: pandas\ub77c\ub294 \ubaa8\ub4c8\uc774 \uc5c6\uc2b5\ub2c8\ub2e4.<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/numpy\u1105\u1161\u1102\u1173\u11ab-\u1106\u1169\u1103\u1172\u11af\u110b\u1175-\u110b\u1165\u11b9\u1109\u1173\u11b8\u1102\u1175\u1103\u1161.\/\" target=\"_blank\" rel=\"noopener\">\ud574\uacb0 \ubc29\ubc95: numpy\ub77c\ub294 \ubaa8\ub4c8\uc774 \uc5c6\uc2b5\ub2c8\ub2e4.<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u110b\u1167\u11af\u110b\u1175-\u1100\u1167\u11b8\u110e\u1175\u110c\u1175\u1106\u1161\u11ab-\u110c\u1165\u11b8\u1106\u1175\u1109\u1161\u1100\u1161-\u110c\u1175\u110c\u1165\u11bc\u1103\u116c\u110c\u1175-\u110b\u1161\u11ad\u110b\u1161\u11bb\u1109\u1173\u11b8\u1102\u1175\u1103\u1161.\/\" target=\"_blank\" rel=\"noopener\">\uc218\uc815\ubc29\ubc95: \uc5f4\uc774 \uacb9\uce58\ub294\ub370 \uc811\ubbf8\uc0ac\uac00 \uc9c0\uc815\ub418\uc9c0 \uc54a\uc74c<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Pandas\ub97c \uc0ac\uc6a9\ud560 \ub54c \ubc1c\uc0dd\ud560 \uc218 \uc788\ub294 \uacbd\uace0 \uc911 \ud558\ub098\ub294 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4. SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. \uc774 \uacbd\uace0\ub294 \ud32c\ub354\uac00 \uccb4\uc778 \ud560\ub2f9(\uccb4\uc778 \ud560\ub2f9\uacfc \ud55c \ub2e8\uacc4\uc758 \uc870\ud569)\uc774\ub77c\ub294 \uac83\uc744 \ubc1c\uacac\ud560 \ub54c \ub098\ud0c0\ub0a9\ub2c8\ub2e4. \uc774\ub294 \ub2e8\uc9c0 \uacbd\uace0\uc77c \ubfd0\uc774\uba70 \uc624\ub958\uac00 \uc544\ub2c8\ub77c\ub294 \uc810\uc5d0 \uc720\uc758\ud558\ub294 \uac83\uc774 \uc911\uc694\ud569\ub2c8\ub2e4. \ucf54\ub4dc\ub294 \uacc4\uc18d \uc2e4\ud589\ub418\uc9c0\ub9cc \uacb0\uacfc\uac00 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[],"class_list":["post-1978","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - 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