{"id":3227,"date":"2023-07-18T13:59:04","date_gmt":"2023-07-18T13:59:04","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab-%e1%84%8c%e1%85%a5%e1%86%bc%e1%84%80%e1%85%b2%e1%84%89%e1%85%a5%e1%86%bc-%e1%84%90%e1%85%a6%e1%84%89%e1%85%b3%e1%84%90%e1%85%b3\/"},"modified":"2023-07-18T13:59:04","modified_gmt":"2023-07-18T13:59:04","slug":"%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab-%e1%84%8c%e1%85%a5%e1%86%bc%e1%84%80%e1%85%b2%e1%84%89%e1%85%a5%e1%86%bc-%e1%84%90%e1%85%a6%e1%84%89%e1%85%b3%e1%84%90%e1%85%b3","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab-%e1%84%8c%e1%85%a5%e1%86%bc%e1%84%80%e1%85%b2%e1%84%89%e1%85%a5%e1%86%bc-%e1%84%90%e1%85%a6%e1%84%89%e1%85%b3%e1%84%90%e1%85%b3\/","title":{"rendered":"Python\uc5d0\uc11c \uc815\uaddc\uc131\uc744 \ud14c\uc2a4\ud2b8\ud558\ub294 \ubc29\ubc95(4\uac00\uc9c0 \ubc29\ubc95)"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\ub9ce\uc740 \ud1b5\uacc4 \ud14c\uc2a4\ud2b8\uc5d0\uc11c\ub294 \ub370\uc774\ud130 \uc138\ud2b8\uac00 \uc815\uaddc \ubd84\ud3ec\ub97c \ub530\ub978\ub2e4\uace0 <a href=\"https:\/\/statorials.org\/ko\/\u110c\u1165\u11bc\u1100\u1172\u1109\u1165\u11bc-\u1100\u1161\u1109\u1165\u11af\/\" target=\"_blank\" rel=\"noopener\">\uac00\uc815\ud569\ub2c8\ub2e4<\/a> .<\/span><\/p>\n<p> <span style=\"color: #000000;\">Python\uc5d0\uc11c \uc774 \uac00\uc124\uc744 \ud655\uc778\ud558\ub294 \ub124 \uac00\uc9c0 \uc77c\ubc18\uc801\uc778 \ubc29\ubc95\uc774 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>1. (\uc2dc\uac01\uc801 \ubc29\ubc95) \ud788\uc2a4\ud1a0\uadf8\ub7a8\uc744 \uc0dd\uc131\ud569\ub2c8\ub2e4.<\/strong><\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\ud788\uc2a4\ud1a0\uadf8\ub7a8\uc774 \ub300\ub7b5 &#8220;\uc885&#8221; \ubaa8\uc591\uc774\uba74 \ub370\uc774\ud130\uac00 \uc815\uaddc \ubd84\ud3ec\ub97c \ub530\ub974\ub294 \uac83\uc73c\ub85c \uac04\uc8fc\ub429\ub2c8\ub2e4.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\"><strong>2. (\uc2dc\uac01\uc801 \ubc29\ubc95) QQ \ud50c\ub86f\uc744 \uc0dd\uc131\ud569\ub2c8\ub2e4.<\/strong><\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\uadf8\ub9bc\uc758 \uc810\uc774 \ub300\ub7b5 \uc9c1\uc120 \ub300\uac01\uc120\uc744 \ub530\ub77c \uc788\uc73c\uba74 \ub370\uc774\ud130\uac00 \uc815\uaddc \ubd84\ud3ec\ub97c \ub530\ub974\ub294 \uac83\uc73c\ub85c \uac04\uc8fc\ub429\ub2c8\ub2e4.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\"><strong>3. (\uc815\uc2dd \ud1b5\uacc4 \uac80\uc815) Shapiro-Wilk \uac80\uc815\uc744 \uc218\ud589\ud569\ub2c8\ub2e4.<\/strong><\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\uac80\uc815\uc758 p-\uac12\uc774 \u03b1 = 0.05\ubcf4\ub2e4 \ud06c\uba74 \ub370\uc774\ud130\uac00 \uc815\uaddc \ubd84\ud3ec\ub97c \ub530\ub974\ub294 \uac83\uc73c\ub85c \uac00\uc815\ub429\ub2c8\ub2e4.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\"><strong>4. (\uacf5\uc2dd \ud1b5\uacc4 \uac80\uc815) Kolmogorov-Smirnov \uac80\uc815\uc744 \uc218\ud589\ud569\ub2c8\ub2e4.<\/strong><\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\uac80\uc815\uc758 p-\uac12\uc774 \u03b1 = 0.05\ubcf4\ub2e4 \ud06c\uba74 \ub370\uc774\ud130\uac00 \uc815\uaddc \ubd84\ud3ec\ub97c \ub530\ub974\ub294 \uac83\uc73c\ub85c \uac00\uc815\ub429\ub2c8\ub2e4.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc774\ub7ec\ud55c \uac01 \ubc29\ubc95\uc744 \uc2e4\uc81c\ub85c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<h3> <strong><span style=\"color: #000000;\">\ubc29\ubc95 1: \ud788\uc2a4\ud1a0\uadf8\ub7a8 \ub9cc\ub4e4\uae30<\/span><\/strong><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 <a href=\"https:\/\/statorials.org\/ko\/\u110b\u1175\u11af\u1107\u1161\u11ab-\u1105\u1169\u1100\u1173-\u1111\u1161\u110b\u1175\u110a\u1165\u11ab-\u1107\u1162\u1111\u1169\/\" target=\"_blank\" rel=\"noopener\">\ub85c\uadf8 \uc815\uaddc \ubd84\ud3ec\ub97c<\/a> \ub530\ub974\ub294 \ub370\uc774\ud130 \uc138\ud2b8\uc5d0 \ub300\ud55c \ud788\uc2a4\ud1a0\uadf8\ub7a8\uc744 \uc0dd\uc131\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: #008000;\">import<\/span> math\n<span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np\n<span style=\"color: #008000;\">from<\/span> scipy. <span style=\"color: #3366ff;\">stats<\/span> <span style=\"color: #008000;\">import<\/span> lognorm\n<span style=\"color: #008000;\">import<\/span> matplotlib. <span style=\"color: #3366ff;\">pyplot<\/span> <span style=\"color: #008000;\">as<\/span> plt\n\n<span style=\"color: #008080;\">#make this example reproducible\n<\/span>n.p. <span style=\"color: #3366ff;\">random<\/span> . <span style=\"color: #3366ff;\">seeds<\/span> (1)\n\n<span style=\"color: #008080;\">#generate dataset that contains 1000 log-normal distributed values\n<\/span>lognorm_dataset = lognorm. <span style=\"color: #3366ff;\">rvs<\/span> (s=.5, scale= <span style=\"color: #3366ff;\">math.exp<\/span> (1), size=1000)\n\n<span style=\"color: #008080;\">#create histogram to visualize values in dataset\n<\/span>plt. <span style=\"color: #3366ff;\">hist<\/span> (lognorm_dataset, edgecolor=' <span style=\"color: #ff0000;\">black<\/span> ', bins=20)<\/span><\/span><\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\" wp-image-27387 aligncenter\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/normalitepython1.jpg\" alt=\"\" width=\"559\" height=\"364\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p> <span style=\"color: #000000;\">\uc774 \ud788\uc2a4\ud1a0\uadf8\ub7a8\ub9cc \ubcf4\uba74 \ub370\uc774\ud130\uc138\ud2b8\uac00 &#8220;\uc885 \ubaa8\uc591&#8221;\uc744 \ub098\ud0c0\ub0b4\uc9c0 \uc54a\uace0 \uc815\uaddc \ubd84\ud3ec\ub97c \ub530\ub974\uc9c0 \uc54a\ub294\ub2e4\ub294 \uac83\uc744 \uc54c \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<h3> <strong><span style=\"color: #000000;\">\ubc29\ubc95 2: QQ \ud50c\ub86f \uc0dd\uc131<\/span><\/strong><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 \ub85c\uadf8 \uc815\uaddc \ubd84\ud3ec\ub97c \ub530\ub974\ub294 \ub370\uc774\ud130 \uc138\ud2b8\uc5d0 \ub300\ud55c QQ \ud50c\ub86f\uc744 \uc0dd\uc131\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: #008000;\">import<\/span> math\n<span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np\n<span style=\"color: #008000;\">from<\/span> scipy. <span style=\"color: #3366ff;\">stats<\/span> <span style=\"color: #008000;\">import<\/span> lognorm\n<span style=\"color: #008000;\">import<\/span> statsmodels. <span style=\"color: #3366ff;\">api<\/span> <span style=\"color: #008000;\">as<\/span> sm\n<span style=\"color: #008000;\">import<\/span> matplotlib. <span style=\"color: #3366ff;\">pyplot<\/span> <span style=\"color: #008000;\">as<\/span> plt\n\n<span style=\"color: #008080;\">#make this example reproducible\n<\/span>n.p. <span style=\"color: #3366ff;\">random<\/span> . <span style=\"color: #3366ff;\">seeds<\/span> (1)\n\n<span style=\"color: #008080;\">#generate dataset that contains 1000 log-normal distributed values\n<\/span>lognorm_dataset = lognorm. <span style=\"color: #3366ff;\">rvs<\/span> (s=.5, scale= <span style=\"color: #3366ff;\">math.exp<\/span> (1), size=1000)\n\n<span style=\"color: #008080;\">#create QQ plot with 45-degree line added to plot\n<\/span>fig = sm. <span style=\"color: #3366ff;\">qqplot<\/span> (lognorm_dataset, line=' <span style=\"color: #ff0000;\">45<\/span> ')\n\nplt. <span style=\"color: #3366ff;\">show<\/span> ()\n<\/span><\/span><\/strong><\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\" wp-image-27390 aligncenter\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/normalitepython2.jpg\" alt=\"\" width=\"533\" height=\"359\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p> <span style=\"color: #000000;\">\ud50c\ub86f \ud3ec\uc778\ud2b8\uac00 \ub300\ub7b5 \uc9c1\uc120 \ub300\uac01\uc120\uc744 \ub530\ub77c \uc788\ub294 \uacbd\uc6b0 \uc77c\ubc18\uc801\uc73c\ub85c \ub370\uc774\ud130 \uc138\ud2b8\uac00 \uc815\uaddc \ubd84\ud3ec\ub97c \ub530\ub978\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uadf8\ub7ec\ub098 \uc774 \uadf8\ub798\ud504\uc758 \uc810\uc740 \ube68\uac04\uc0c9 \uc120\uacfc \uba85\ud655\ud558\uac8c \uc77c\uce58\ud558\uc9c0 \uc54a\uc73c\ubbc0\ub85c \uc774 \ub370\uc774\ud130 \uc138\ud2b8\uac00 \uc815\uaddc \ubd84\ud3ec\ub97c \ub530\ub978\ub2e4\uace0 \uac00\uc815\ud560 \uc218 \uc5c6\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774\ub294 \ub85c\uadf8 \uc815\uaddc \ubd84\ud3ec \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub370\uc774\ud130\ub97c \uc0dd\uc131\ud588\ub2e4\ub294 \uc810\uc744 \uace0\ub824\ud558\uba74 \uc758\ubbf8\uac00 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<h3> <strong><span style=\"color: #000000;\">\ubc29\ubc95 3: Shapiro-Wilk \ud14c\uc2a4\ud2b8 \uc218\ud589<\/span><\/strong><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 \ub85c\uadf8 \uc815\uaddc \ubd84\ud3ec\ub97c \ub530\ub974\ub294 \ub370\uc774\ud130 \uc138\ud2b8\uc5d0 \ub300\ud574 Shapiro-Wilk\ub97c \uc218\ud589\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: #008000;\">import<\/span> math\n<span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np\n<span style=\"color: #008000;\">from<\/span> scipy.stats <span style=\"color: #008000;\">import<\/span> shapiro \n<span style=\"color: #008000;\">from<\/span> scipy. <span style=\"color: #3366ff;\">stats<\/span> <span style=\"color: #008000;\">import<\/span> lognorm\n\n<span style=\"color: #008080;\">#make this example reproducible\n<\/span>n.p. <span style=\"color: #3366ff;\">random<\/span> . <span style=\"color: #3366ff;\">seeds<\/span> (1)\n\n<span style=\"color: #008080;\">#generate dataset that contains 1000 log-normal distributed values\n<\/span>lognorm_dataset = lognorm. <span style=\"color: #3366ff;\">rvs<\/span> (s=.5, scale= <span style=\"color: #3366ff;\">math.exp<\/span> (1), size=1000)\n\n<span style=\"color: #008080;\">#perform Shapiro-Wilk test for normality\n<\/span>shapiro(lognorm_dataset)\n\nShapiroResult(statistic=0.8573324680328369, pvalue=3.880663073872444e-29)\n<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uacb0\uacfc\uc5d0\uc11c \uac80\uc815 \ud1b5\uacc4\ub7c9\uc740 <strong>0.857<\/strong> \uc774\uace0 \ud574\ub2f9 p-\uac12\uc740 <strong>3.88e-29<\/strong> (0\uc5d0 \ub9e4\uc6b0 \uac00\uae4c\uc6c0)\uc784\uc744 \uc54c \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">p-\uac12\uc774 0.05\ubcf4\ub2e4 \uc791\uc73c\ubbc0\ub85c Shapiro-Wilk \uac80\uc815\uc758 \uadc0\ubb34\uac00\uc124\uc744 \uae30\uac01\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774\ub294 \ud45c\ubcf8 \ub370\uc774\ud130\uac00 \uc815\uaddc \ubd84\ud3ec\uc5d0\uc11c \ub098\uc624\uc9c0 \uc54a\ub294\ub2e4\uace0 \ub9d0\ud560 \uc218 \uc788\ub294 \ucda9\ubd84\ud55c \uc99d\uac70\uac00 \uc788\uc74c\uc744 \uc758\ubbf8\ud569\ub2c8\ub2e4.<\/span><\/p>\n<h3> <strong><span style=\"color: #000000;\">\ubc29\ubc95 4: Kolmogorov-Smirnov \ud14c\uc2a4\ud2b8 \uc218\ud589<\/span><\/strong><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 \ub85c\uadf8 \uc815\uaddc \ubd84\ud3ec\ub97c \ub530\ub974\ub294 \ub370\uc774\ud130 \uc138\ud2b8\uc5d0 \ub300\ud574 Kolmogorov-Smirnov \ud14c\uc2a4\ud2b8\ub97c \uc218\ud589\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: #008000;\">import<\/span> math\n<span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np\n<span style=\"color: #008000;\">from<\/span> scipy.stats <span style=\"color: #008000;\">import<\/span> kstest\n<span style=\"color: #008000;\">from<\/span> scipy. <span style=\"color: #3366ff;\">stats<\/span> <span style=\"color: #008000;\">import<\/span> lognorm\n\n<span style=\"color: #008080;\">#make this example reproducible\n<\/span>n.p. <span style=\"color: #3366ff;\">random<\/span> . <span style=\"color: #3366ff;\">seeds<\/span> (1)\n\n<span style=\"color: #008080;\">#generate dataset that contains 1000 log-normal distributed values\n<\/span>lognorm_dataset = lognorm. <span style=\"color: #3366ff;\">rvs<\/span> (s=.5, scale= <span style=\"color: #3366ff;\">math.exp<\/span> (1), size=1000)\n\n<span style=\"color: #008080;\">#perform Kolmogorov-Smirnov test for normality\n<\/span>kstest(lognorm_dataset, ' <span style=\"color: #ff0000;\">norm<\/span> ')\n\nKstestResult(statistic=0.84125708308077, pvalue=0.0)\n<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uacb0\uacfc\uc5d0\uc11c \uac80\uc815 \ud1b5\uacc4\ub7c9\uc740 <strong>0.841<\/strong> \uc774\uace0 \ud574\ub2f9 p-\uac12\uc740 <strong>0.0<\/strong> \uc784\uc744 \uc54c \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">p-\uac12\uc774 0.05\ubcf4\ub2e4 \uc791\uc73c\ubbc0\ub85c Kolmogorov-Smirnov \uac80\uc815\uc758 \uadc0\ubb34\uac00\uc124\uc744 \uae30\uac01\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774\ub294 \ud45c\ubcf8 \ub370\uc774\ud130\uac00 \uc815\uaddc \ubd84\ud3ec\uc5d0\uc11c \ub098\uc624\uc9c0 \uc54a\ub294\ub2e4\uace0 \ub9d0\ud560 \uc218 \uc788\ub294 \ucda9\ubd84\ud55c \uc99d\uac70\uac00 \uc788\uc74c\uc744 \uc758\ubbf8\ud569\ub2c8\ub2e4.<\/span><\/p>\n<h3> <strong>\ube44\uc815\uaddc \ub370\uc774\ud130\ub97c \ucc98\ub9ac\ud558\ub294 \ubc29\ubc95<\/strong><\/h3>\n<p> <span style=\"color: #000000;\">\uc8fc\uc5b4\uc9c4 \ub370\uc774\ud130 \uc138\ud2b8\uac00 \uc815\uaddc \ubd84\ud3ec\ub97c <em>\ub530\ub974\uc9c0 \uc54a\ub294<\/em> \uacbd\uc6b0 \ub2e4\uc74c \ubcc0\ud658 \uc911 \ud558\ub098\ub97c \uc218\ud589\ud558\uc5ec \ubcf4\ub2e4 \uc815\uaddc \ubd84\ud3ec\ub97c \ub9cc\ub4e4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>1. \ub85c\uadf8 \ubcc0\ud658:<\/strong> x \uac12\uc744 <strong>log(x)<\/strong> \ub85c \ubcc0\ud658\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>2. \uc81c\uacf1\uadfc \ubcc0\ud658:<\/strong> x\uc758 \uac12\uc744 <strong><span style=\"border-top: 1px solid black;\">\u221ax<\/span><\/strong> \ub85c \ubcc0\ud658\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>3. \uc138\uc81c\uacf1\uadfc \ubcc0\ud658:<\/strong> x \uac12\uc744 <strong>x <sup>1\/3<\/sup><\/strong> \uc73c\ub85c \ubcc0\ud658\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774\ub7ec\ud55c \ubcc0\ud658\uc744 \uc218\ud589\ud568\uc73c\ub85c\uc368 \ub370\uc774\ud130\uc138\ud2b8\ub294 \uc77c\ubc18\uc801\uc73c\ub85c \ubcf4\ub2e4 \uc815\uaddc \ubd84\ud3ec\ub97c \ub744\uac8c \ub429\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Python\uc5d0\uc11c \uc774\ub7ec\ud55c \ubcc0\ud658\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc54c\uc544\ubcf4\ub824\uba74 <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1161\u110b\u1175\u110a\u1165\u11ab\u110b\u1173\u1105\u1169-\u1103\u1166\u110b\u1175\u1110\u1165-\u1107\u1167\u11ab\u1112\u116a\u11ab\/\" target=\"_blank\" rel=\"noopener noreferrer\">\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc744<\/a> \uc77d\uc5b4\ubcf4\uc138\uc694.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\ub9ce\uc740 \ud1b5\uacc4 \ud14c\uc2a4\ud2b8\uc5d0\uc11c\ub294 \ub370\uc774\ud130 \uc138\ud2b8\uac00 \uc815\uaddc \ubd84\ud3ec\ub97c \ub530\ub978\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4 . Python\uc5d0\uc11c \uc774 \uac00\uc124\uc744 \ud655\uc778\ud558\ub294 \ub124 \uac00\uc9c0 \uc77c\ubc18\uc801\uc778 \ubc29\ubc95\uc774 \uc788\uc2b5\ub2c8\ub2e4. 1. (\uc2dc\uac01\uc801 \ubc29\ubc95) \ud788\uc2a4\ud1a0\uadf8\ub7a8\uc744 \uc0dd\uc131\ud569\ub2c8\ub2e4. \ud788\uc2a4\ud1a0\uadf8\ub7a8\uc774 \ub300\ub7b5 &#8220;\uc885&#8221; \ubaa8\uc591\uc774\uba74 \ub370\uc774\ud130\uac00 \uc815\uaddc \ubd84\ud3ec\ub97c \ub530\ub974\ub294 \uac83\uc73c\ub85c \uac04\uc8fc\ub429\ub2c8\ub2e4. 2. (\uc2dc\uac01\uc801 \ubc29\ubc95) QQ \ud50c\ub86f\uc744 \uc0dd\uc131\ud569\ub2c8\ub2e4. \uadf8\ub9bc\uc758 \uc810\uc774 \ub300\ub7b5 \uc9c1\uc120 \ub300\uac01\uc120\uc744 \ub530\ub77c \uc788\uc73c\uba74 \ub370\uc774\ud130\uac00 \uc815\uaddc \ubd84\ud3ec\ub97c \ub530\ub974\ub294 \uac83\uc73c\ub85c \uac04\uc8fc\ub429\ub2c8\ub2e4. 3. (\uc815\uc2dd [&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-3227","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Python\uc5d0\uc11c \uc815\uaddc\uc131\uc744 \ud14c\uc2a4\ud2b8\ud558\ub294 \ubc29\ubc95(4\uac00\uc9c0 \ubc29\ubc95) - \ud1b5\uacc4\ud559<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uba87 \uac00\uc9c0 \uc608\ub97c \ud1b5\ud574 Python\uc5d0\uc11c \uc815\uaddc\uc131\uc744 \ud14c\uc2a4\ud2b8\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/ko\/\u1111\u1161\u110b\u1175\u110a\u1165\u11ab-\u110c\u1165\u11bc\u1100\u1172\u1109\u1165\u11bc-\u1110\u1166\u1109\u1173\u1110\u1173\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Python\uc5d0\uc11c \uc815\uaddc\uc131\uc744 \ud14c\uc2a4\ud2b8\ud558\ub294 \ubc29\ubc95(4\uac00\uc9c0 \ubc29\ubc95) - 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