{"id":3433,"date":"2023-07-17T12:20:03","date_gmt":"2023-07-17T12:20:03","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%84%82%e1%85%b3%e1%86%ab-%e1%84%8b%e1%85%b5%e1%84%85%e1%85%b3%e1%86%b7%e1%84%8b%e1%85%b3%e1%84%85%e1%85%a9-%e1%84%8b%e1%85%a7%e1%86%af%e1%84%8b%e1%85%b3\/"},"modified":"2023-07-17T12:20:03","modified_gmt":"2023-07-17T12:20:03","slug":"%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%84%82%e1%85%b3%e1%86%ab-%e1%84%8b%e1%85%b5%e1%84%85%e1%85%b3%e1%86%b7%e1%84%8b%e1%85%b3%e1%84%85%e1%85%a9-%e1%84%8b%e1%85%a7%e1%86%af%e1%84%8b%e1%85%b3","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5%e1%84%82%e1%85%b3%e1%86%ab-%e1%84%8b%e1%85%b5%e1%84%85%e1%85%b3%e1%86%b7%e1%84%8b%e1%85%b3%e1%84%85%e1%85%a9-%e1%84%8b%e1%85%a7%e1%86%af%e1%84%8b%e1%85%b3\/","title":{"rendered":"Pandas\uc5d0\uc11c \uc774\ub984\uc73c\ub85c \uc5f4\uc744 \uc120\ud0dd\ud558\ub294 \ubc29\ubc95(\uc608\uc81c 3\uac1c)"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\ub2e4\uc74c \ubc29\ubc95\uc744 \uc0ac\uc6a9\ud558\uc5ec Pandas DataFrame\uc5d0\uc11c \uc774\ub984\uc73c\ub85c \uc5f4\uc744 \uc120\ud0dd\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\ubc29\ubc95 1: \uc774\ub984\uc73c\ub85c \uc5f4 \uc120\ud0dd<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">loc<\/span> [:, ' <span style=\"color: #ff0000;\">column1<\/span> ']\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>\ubc29\ubc95 2: \uc774\ub984\uc73c\ub85c \uc5ec\ub7ec \uc5f4 \uc120\ud0dd<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">loc<\/span> [:,[' <span style=\"color: #ff0000;\">column1<\/span> ',' <span style=\"color: #ff0000;\">column3<\/span> ',' <span style=\"color: #ff0000;\">column4<\/span> ']]<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>\ubc29\ubc95 3: \uc774\ub984\ubcc4\ub85c \ubc94\uc704\uc758 \uc5f4 \uc120\ud0dd<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">loc<\/span> [:, ' <span style=\"color: #ff0000;\">column2<\/span> ':' <span style=\"color: #ff0000;\">column4<\/span> ']<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc2e4\uc81c\ub85c \ub2e4\uc74c pandas DataFrame\uc5d0\uc11c \uc774\ub7ec\ud55c \uac01 \uba54\uc11c\ub4dc\ub97c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">mavs<\/span> ': [10, 12, 14, 15, 19, 22, 27],\n                   ' <span style=\"color: #ff0000;\">cavs<\/span> ': [18, 22, 19, 14, 14, 11, 20],\n                   ' <span style=\"color: #ff0000;\">hornets<\/span> ': [5, 7, 7, 9, 12, 9, 14],\n                   ' <span style=\"color: #ff0000;\">spurs<\/span> ': [10, 12, 14, 13, 13, 19, 22],\n                   ' <span style=\"color: #ff0000;\">net<\/span> ': [10, 14, 25, 22, 25, 17, 12]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n   mavs cavs hornets spurs nets\n0 10 18 5 10 10\n1 12 22 7 12 14\n2 14 19 7 14 25\n3 15 14 9 13 22\n4 19 14 12 13 25\n5 22 11 9 19 17\n6 27 20 14 22 12\n<\/strong><\/span><\/pre>\n<h2> <span style=\"color: #000000;\"><strong>\uc608 1: \uc774\ub984\uc73c\ub85c \uc5f4 \uc120\ud0dd<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 DataFrame\uc5d0\uc11c &#8220;spurs&#8221; \uc5f4\uc744 \uc120\ud0dd\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\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;\">#select column with name 'spurs'\n<\/span>df. <span style=\"color: #3366ff;\">loc<\/span> [:, ' <span style=\"color: #ff0000;\">spurs<\/span> ']\n\n0 10\n1 12\n2 14\n3 13\n4 13\n5 19\n6 22\nName: spurs, dtype: int64<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">&#8220;spurs&#8221; \uc5f4\uc758 \uac12\ub9cc \ubc18\ud658\ub429\ub2c8\ub2e4.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\uc608 2: \uc774\ub984\uc73c\ub85c \uc5ec\ub7ec \uc5f4 \uc120\ud0dd<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 DataFrame\uc5d0\uc11c cavs, spur \ubc0f net \uc5f4\uc744 \uc120\ud0dd\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\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;\">#select columns with names cavs, spurs, and nets\n<\/span>df. <span style=\"color: #3366ff;\">loc<\/span> [:, [' <span style=\"color: #ff0000;\">cavs<\/span> ', ' <span style=\"color: #ff0000;\">spurs<\/span> ', ' <span style=\"color: #ff0000;\">nets<\/span> ']]\n\n        cavs spurs nets\n0 18 10 10\n1 22 12 14\n2 19 14 25\n3 14 13 22\n4 14 13 25\n5 11 19 17\n6 20 22 12<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">cavs, spurs \ubc0f net \uc5f4\uc758 \uac12\ub9cc \ubc18\ud658\ub429\ub2c8\ub2e4.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\uc608 3: \uc774\ub984\uc73c\ub85c \ubc94\uc704\uc758 \uc5f4 \uc120\ud0dd<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 DataFrame\uc5d0\uc11c &#8220;hornets&#8221;\uc640 &#8220;net&#8221; \uc774\ub984 \uc0ac\uc774\uc758 \ubaa8\ub4e0 \uc5f4\uc744 \uc120\ud0dd\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\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;\">#select all columns between hornets and nets\n<\/span>df. <span style=\"color: #3366ff;\">loc<\/span> [:, ' <span style=\"color: #ff0000;\">hornets<\/span> ': ' <span style=\"color: #ff0000;\">nets<\/span> ']\n\n        hornets spurs nets\n0 5 10 10\n1 7 12 14\n2 7 14 25\n3 9 13 22\n4 12 13 25\n5 9 19 17\n6 14 22 12<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uc774\ub984 &#8220;hornets&#8221;\uc640 &#8220;net&#8221; \uc0ac\uc774\uc758 \ubaa8\ub4e0 \uc5f4\uc774 \ubc18\ud658\ub429\ub2c8\ub2e4.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Pandas\uc5d0\uc11c \ub2e4\ub978 \uc77c\ubc18\uc801\uc778 \uc791\uc5c5\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1161\u11ab\u1103\u1161\u1102\u1173\u11ab-\u110e\u1165\u11a8\u110e\u116e\u110b\u1166\u1109\u1165-\u110b\u1161\u11c1\u110b\u1173\u1105\u1169-\u110b\u116e\u11b7\u110c\u1175\u11a8\u110b\u1175\u11ab\u1103\u1161\/\" target=\"_blank\" rel=\"noopener\">Pandas: DataFrame \uc55e\uc73c\ub85c \uc5f4\uc744 \uc774\ub3d9\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/pandas\u1102\u1173\u11ab-\u110b\u1167\u11af\u110b\u1166-\u1106\u116e\u11ab\u110c\u1161\u110b\u1167\u11af\u110b\u1175-\u1111\u1169\u1112\u1161\u11b7\u1103\u116c\u110b\u1165-\u110b\u1175\u11bb\u1102\u1173\u11ab\u110c\u1175-\u1112\u116a\u11a8\u110b\u1175\u11ab\u1112\u1161\u11b8\u1102\u1175\u1103\u1161.\/\" target=\"_blank\" rel=\"noopener\">Pandas:\uc5f4\uc5d0 \ubb38\uc790\uc5f4\uc774 \ud3ec\ud568\ub418\uc5b4 \uc788\ub294\uc9c0 \ud655\uc778\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165\u1102\u1173\u11ab-\u1107\u1175\u11ab-\u110b\u1167\u11af\u110b\u1173\u11af-\u110e\u116e\u1100\u1161\u1112\u1161\u11b8\u1102\u1175\u1103\u1161\/\" target=\"_blank\" rel=\"noopener\">Pandas: DataFrame\uc5d0 \ube48 \uc5f4\uc744 \ucd94\uac00\ud558\ub294 \ubc29\ubc95(\uc608\uc81c 3\uac1c)<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\ub2e4\uc74c \ubc29\ubc95\uc744 \uc0ac\uc6a9\ud558\uc5ec Pandas DataFrame\uc5d0\uc11c \uc774\ub984\uc73c\ub85c \uc5f4\uc744 \uc120\ud0dd\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ubc29\ubc95 1: \uc774\ub984\uc73c\ub85c \uc5f4 \uc120\ud0dd df. loc [:, &#8216; column1 &#8216;] \ubc29\ubc95 2: \uc774\ub984\uc73c\ub85c \uc5ec\ub7ec \uc5f4 \uc120\ud0dd df. loc [:,[&#8216; column1 &#8216;,&#8217; column3 &#8216;,&#8217; column4 &#8216;]] \ubc29\ubc95 3: \uc774\ub984\ubcc4\ub85c \ubc94\uc704\uc758 \uc5f4 \uc120\ud0dd df. loc [:, &#8216; column2 &#8216;:&#8217; column4 &#8216;] \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc2e4\uc81c\ub85c \ub2e4\uc74c pandas [&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-3433","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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