{"id":3856,"date":"2023-07-15T03:28:54","date_gmt":"2023-07-15T03:28:54","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%8d%e1%85%a1%e1%84%8c%e1%85%b3%e1%86%bc%e1%84%82%e1%85%a1%e1%84%8c%e1%85%b5-%e1%84%8b%e1%85%a1%e1%86%ad%e1%84%8b%e1%85%a1\/"},"modified":"2023-07-15T03:28:54","modified_gmt":"2023-07-15T03:28:54","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%8d%e1%85%a1%e1%84%8c%e1%85%b3%e1%86%bc%e1%84%82%e1%85%a1%e1%84%8c%e1%85%b5-%e1%84%8b%e1%85%a1%e1%86%ad%e1%84%8b%e1%85%a1","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%8d%e1%85%a1%e1%84%8c%e1%85%b3%e1%86%bc%e1%84%82%e1%85%a1%e1%84%8c%e1%85%b5-%e1%84%8b%e1%85%a1%e1%86%ad%e1%84%8b%e1%85%a1\/","title":{"rendered":"&quot;null\uc774 \uc544\ub2d8&quot;\uc744 \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc740 \ubb34\uc5c7\uc785\ub2c8\uae4c? pandas\uc5d0\uc11c(\uc608\uc81c \ud3ec\ud568)"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">pandas <strong>notnull()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec pandas DataFrame\uc758 \uc694\uc18c\uac00 null\uc778\uc9c0 \uc5ec\ubd80\ub97c \ud14c\uc2a4\ud2b8\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc694\uc18c\uac00 NaN \ub610\ub294 None\uacfc \uac19\uc73c\uba74 \ud568\uc218\ub294 <strong>False \ub97c<\/strong> \ubc18\ud658\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uadf8\ub807\uc9c0 \uc54a\uc73c\uba74 \ud568\uc218\ub294 <strong>True \ub97c<\/strong> \ubc18\ud658\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc2e4\uc81c\ub85c \uc774 \uae30\ub2a5\uc744 \uc0ac\uc6a9\ud558\ub294 \uba87 \uac00\uc9c0 \uc77c\ubc18\uc801\uc778 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\ubc29\ubc95 1: \ubaa8\ub4e0 \uc5f4\uc5d0 null \uac12\uc774 \uc5c6\ub294 \ud589 \ud544\ud130\ub9c1<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df[df. <span style=\"color: #3366ff;\">notnull<\/span> (). <span style=\"color: #3366ff;\">all<\/span> ( <span style=\"color: #008000;\">1<\/span> )]\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>\ubc29\ubc95 2: \ud2b9\uc815 \uc5f4\uc5d0\uc11c Null \uac12\uc774 \uc5c6\ub294 \ud589 \ud544\ud130\ub9c1<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df[df[[' <span style=\"color: #ff0000;\">this_column<\/span> ']]. <span style=\"color: #3366ff;\">notnull<\/span> (). <span style=\"color: #3366ff;\">all<\/span> ( <span style=\"color: #008000;\">1<\/span> )]<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>\ubc29\ubc95 3: \uac01 \uc5f4\uc5d0\uc11c 0\uc774 \uc544\ub2cc \uac12\uc758 \uac1c\uc218 \uacc4\uc0b0<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">notnull<\/span> (). <span style=\"color: #3366ff;\">sum<\/span> ()<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>\ubc29\ubc95 4: \uc804\uccb4 DataFrame\uc5d0\uc11c 0\uc774 \uc544\ub2cc \uac12\uc758 \uac1c\uc218 \uacc4\uc0b0<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">notnull<\/span> (). <span style=\"color: #3366ff;\">sum<\/span> (). <span style=\"color: #3366ff;\">sum<\/span> ()<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \ub2e4\uc74c pandas DataFrame\uc5d0\uc11c \uc2e4\uc81c\ub85c \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;\"> <strong><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n<span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np\n\n<span style=\"color: #008080;\">#createDataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">team<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],\n                   ' <span style=\"color: #ff0000;\">points<\/span> ': [18, 22, 19, 14, 14, 11, 20, np.nan],\n                   ' <span style=\"color: #ff0000;\">assists<\/span> ': [5, np.nan, 7, 9, 12, 9, 9, np.nan],\n                   ' <span style=\"color: #ff0000;\">rebounds<\/span> ': [11, 8, 10, 6, 6, 5, np.nan, 12]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n  team points assists rebounds\n0 A 18.0 5.0 11.0\n1 B 22.0 NaN 8.0\n2 C 19.0 7.0 10.0\n3D 14.0 9.0 6.0\n4 E 14.0 12.0 6.0\n5 F 11.0 9.0 5.0\n6G 20.0 9.0 NaN\n7 H NaN NaN 12.0\n<\/strong><\/pre>\n<h2> <span style=\"color: #000000;\"><strong>\uc608\uc2dc 1: \ubaa8\ub4e0 \uc5f4\uc5d0 Null \uac12\uc774 \uc5c6\ub294 \ud589 \ud544\ud130\ub9c1<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 \ubaa8\ub4e0 \uc5f4\uc5d0 null \uac12\uc774 \uc5c6\ub294 \ud589\ub9cc \ud45c\uc2dc\ud558\ub3c4\ub85d DataFrame\uc744 \ud544\ud130\ub9c1\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;\">#filter for rows with no null values in any column\n<\/span>df[df. <span style=\"color: #3366ff;\">notnull<\/span> (). <span style=\"color: #3366ff;\">all<\/span> ( <span style=\"color: #008000;\">1<\/span> )]\n\n\n        team points assists rebounds\n0 A 18.0 5.0 11.0\n2 C 19.0 7.0 10.0\n3D 14.0 9.0 6.0\n4 E 14.0 12.0 6.0\n5 F 11.0 9.0 5.0<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ud544\ud130\ub9c1\ub41c DataFrame\uc758 \uac01 \ud589\uc5d0\ub294 \uc5b4\ub5a4 \uc5f4\uc5d0\ub3c4 null \uac12\uc774 \uc5c6\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\uc608\uc2dc 2: \ud2b9\uc815 \uc5f4\uc5d0\uc11c null \uac12\uc774 \uc5c6\ub294 \ud589 \ud544\ud130\ub9c1<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 DataFrame\uc744 \ud544\ud130\ub9c1\ud558\uc5ec <strong>\ub3c4\uc6b0\ubbf8<\/strong> \uc5f4\uc5d0 null \uac12\uc774 \uc5c6\ub294 \ud589\ub9cc \ud45c\uc2dc\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;\">#filter for rows with no null values in the 'assists' column\n<\/span>df[df[[' <span style=\"color: #ff0000;\">assists<\/span> ']]. <span style=\"color: #3366ff;\">notnull<\/span> (). <span style=\"color: #3366ff;\">all<\/span> ( <span style=\"color: #008000;\">1<\/span> )]\n\n\tteam points assists rebounds\n0 A 18.0 5.0 11.0\n2 C 19.0 7.0 10.0\n3D 14.0 9.0 6.0\n4 E 14.0 12.0 6.0\n5 F 11.0 9.0 5.0\n6G 20.0 9.0 NaN<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ud544\ud130\ub9c1\ub41c DataFrame\uc758 \uac01 \ud589\uc5d0\ub294 <strong>Helper<\/strong> \uc5f4\uc5d0 null \uac12\uc774 \uc5c6\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\uc608\uc2dc 3: \uac01 \uc5f4\uc5d0\uc11c 0\uc774 \uc544\ub2cc \uac12\uc758 \uac1c\uc218 \uacc4\uc0b0<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 DataFrame\uc758 \uac01 \uc5f4\uc5d0\uc11c 0\uc774 \uc544\ub2cc \uac12\uc758 \uac1c\uc218\ub97c \uacc4\uc0b0\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;\">#count number of non-null values in each column<\/span>\ndf. <span style=\"color: #3366ff;\">notnull<\/span> (). <span style=\"color: #3366ff;\">sum<\/span> ()\n\nteam 8\npoints 7\nassists 6\nrebounds 7\ndtype: int64\n<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><span style=\"color: #000000;\">\uacb0\uacfc\uc5d0\uc11c \uc6b0\ub9ac\ub294 \ub2e4\uc74c\uc744 \ubcfc \uc218 \uc788\uc2b5\ub2c8\ub2e4:<\/span><\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>\ud300<\/strong> \uc5f4\uc5d0\ub294 0\uc774 \uc544\ub2cc \uac12\uc774 8\uac1c \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\"><b>\ud3ec\uc778\ud2b8<\/b> \uc5f4\uc5d0\ub294 0\uc774 \uc544\ub2cc \uac12\uc774 7\uac1c \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\"><b>\uc9c0\uc6d0<\/b> \uc5f4\uc5d0\ub294 0\uc774 \uc544\ub2cc \uac12\uc774 6\uac1c \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\"><b>\ubc18\uc1a1<\/b> \uc5f4\uc5d0\ub294 0\uc774 \uc544\ub2cc \uac12\uc774 7\uac1c \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/li>\n<\/ul>\n<h2> <span style=\"color: #000000;\"><strong>\uc608\uc2dc 4: \uc804\uccb4 DataFrame\uc5d0\uc11c 0\uc774 \uc544\ub2cc \uac12\uc758 \uac1c\uc218 \uacc4\uc0b0<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 \uc804\uccb4 DataFrame\uc5d0\uc11c 0\uc774 \uc544\ub2cc \uac12\uc758 \uac1c\uc218\ub97c \uacc4\uc0b0\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;\">#count number of non-null values in entire DataFrame\n<\/span>df. <span style=\"color: #3366ff;\">notnull<\/span> (). <span style=\"color: #3366ff;\">sum<\/span> (). <span style=\"color: #3366ff;\">sum<\/span> ()\n\n28\n<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\ucd9c\ub825 \uacb0\uacfc\ub97c \ubcf4\uba74 \uc804\uccb4 DataFrame\uc5d0 0\uc774 \uc544\ub2cc \uac12\uc774 <strong>28\uac1c<\/strong> \uc788\ub2e4\ub294 \uac83\uc744 \uc54c \uc218 \uc788\uc2b5\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 \ud544\ud130\ub9c1 \uc791\uc5c5\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> \uc5f4 \uac12\uc73c\ub85c Pandas DataFrame\uc744 \ud544\ud130\ub9c1\ud558\ub294 \ubc29\ubc95<br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165\u1102\u1173\u11ab-\u1111\u1169\u1112\u1161\u11b7\u1112\u1161\u110c\u1175-\u110b\u1161\u11ad\u1109\u1173\u11b8\u1102\u1175\u1103\u1161\/\" target=\"_blank\" rel=\"noopener\">Pandas\uc5d0\uc11c &#8216;\ud3ec\ud568\ud558\uc9c0 \uc54a\uc74c&#8217;\uc744 \ud544\ud130\ub9c1\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165\u1102\u1173\u11ab-\u110b\u1167\u1105\u1165-\u110c\u1169\u1100\u1165\u11ab\u110b\u1173\u11af-\u1111\u1175\u11af\u1110\u1165\u1105\u1175\u11bc\u1112\u1161\u11b8\u1102\u1175\u1103\u1161.\/\" target=\"_blank\" rel=\"noopener\">\uc5ec\ub7ec \uc870\uac74\uc5d0\uc11c Pandas DataFrame\uc744 \ud544\ud130\ub9c1\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>pandas notnull() \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec pandas DataFrame\uc758 \uc694\uc18c\uac00 null\uc778\uc9c0 \uc5ec\ubd80\ub97c \ud14c\uc2a4\ud2b8\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc694\uc18c\uac00 NaN \ub610\ub294 None\uacfc \uac19\uc73c\uba74 \ud568\uc218\ub294 False \ub97c \ubc18\ud658\ud569\ub2c8\ub2e4. \uadf8\ub807\uc9c0 \uc54a\uc73c\uba74 \ud568\uc218\ub294 True \ub97c \ubc18\ud658\ud569\ub2c8\ub2e4. \uc2e4\uc81c\ub85c \uc774 \uae30\ub2a5\uc744 \uc0ac\uc6a9\ud558\ub294 \uba87 \uac00\uc9c0 \uc77c\ubc18\uc801\uc778 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4. \ubc29\ubc95 1: \ubaa8\ub4e0 \uc5f4\uc5d0 null \uac12\uc774 \uc5c6\ub294 \ud589 \ud544\ud130\ub9c1 df[df. notnull (). all ( 1 )] \ubc29\ubc95 2: [&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-3856","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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