{"id":825,"date":"2023-07-28T15:16:06","date_gmt":"2023-07-28T15:16:06","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%87%e1%85%ae%e1%84%87%e1%85%ae%e1%86%ab-%e1%84%89%e1%85%a1%e1%86%bc%e1%84%80%e1%85%aa%e1%86%ab-%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab\/"},"modified":"2023-07-28T15:16:06","modified_gmt":"2023-07-28T15:16:06","slug":"%e1%84%87%e1%85%ae%e1%84%87%e1%85%ae%e1%86%ab-%e1%84%89%e1%85%a1%e1%86%bc%e1%84%80%e1%85%aa%e1%86%ab-%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%87%e1%85%ae%e1%84%87%e1%85%ae%e1%86%ab-%e1%84%89%e1%85%a1%e1%86%bc%e1%84%80%e1%85%aa%e1%86%ab-%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab\/","title":{"rendered":"Python\uc5d0\uc11c \ubd80\ubd84 \uc0c1\uad00 \uad00\uacc4\ub97c \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"

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\ud1b5\uacc4\uc5d0\uc11c\ub294<\/span> \ub450 \ubcc0\uc218 \uac04\uc758 \uc120\ud615 \uad00\uacc4\ub97c \uce21\uc815\ud558\uae30 \uc704\ud574<\/span> Pearson \uc0c1\uad00 \uacc4\uc218\ub97c<\/a> \uc790\uc8fc \uc0ac\uc6a9\ud569\ub2c8\ub2e4. \uadf8\ub7ec\ub098 \ub54c\ub54c\ub85c \uc6b0\ub9ac\ub294 \uc138 \ubc88\uc9f8 \ubcc0\uc218\ub97c \uc81c\uc5b4\ud558\uba74\uc11c<\/strong> \ub450 \ubcc0\uc218 \uc0ac\uc774\uc758 \uad00\uacc4\ub97c \uc774\ud574\ud558\uace0 \uc2f6\uc744 \ub54c\uac00 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

\uc608\ub97c \ub4e4\uc5b4, \ud559\uc0dd\uc758 \ud604\uc7ac \uc218\uc5c5 \uc131\uc801\uc744 \ud1b5\uc81c\ud558\uba74\uc11c \ud559\uc0dd\uc758 \ud559\uc2b5 \uc2dc\uac04\uacfc \ucd5c\uc885 \uc2dc\ud5d8 \uc131\uc801 \uc0ac\uc774\uc758 \uc5f0\uad00\uc131\uc744 \uce21\uc815\ud55c\ub2e4\uace0 \uac00\uc815\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4. \uc774 \uacbd\uc6b0 \ubd80\ubd84 \uc0c1\uad00 \uad00\uacc4\ub97c<\/strong> \uc0ac\uc6a9\ud558\uc5ec \uacf5\ubd80 \uc2dc\uac04\uacfc \ucd5c\uc885 \uc2dc\ud5d8 \uc131\uc801 \uac04\uc758 \uad00\uacc4\ub97c \uce21\uc815\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Python\uc5d0\uc11c \ubd80\ubd84 \uc0c1\uad00 \uad00\uacc4\ub97c \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n

\uc608: Python\uc758 \ubd80\ubd84 \uc0c1\uad00\uad00\uacc4<\/strong><\/span><\/h3>\n

10\uba85\uc758 \ud559\uc0dd\uc5d0 \ub300\ud55c \ud604\uc7ac \uc131\uc801, \ucd1d \ud559\uc2b5 \uc2dc\uac04 \ubc0f \ucd5c\uc885 \uc2dc\ud5d8 \uc131\uc801\uc744 \ud45c\uc2dc\ud558\ub294 \ub2e4\uc74c Pandas DataFrame\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

 import<\/span> numpy as<\/span> np\nimport<\/span> panda as<\/span> pd\n\ndata = {'currentGrade': [82, 88, 75, 74, 93, 97, 83, 90, 90, 80],\n        'hours': [4, 3, 6, 5, 4, 5, 8, 7, 4, 6],\n        'examScore': [88, 85, 76, 70, 92, 94, 89, 85, 90, 93],\n        }\n\ndf = pd.DataFrame(data, columns = ['currentGrade','hours', 'examScore'])\ndf\n\n   currentGrade hours examScore\n0 82 4 88\n1 88 3 85\n2 75 6 76\n3 74 5 70\n4 93 4 92\n5 97 5 94\n6 83 8 89\n7 90 7 85\n8 90 4 90\n9 80 6 93\n<\/strong><\/pre>\n
 currentGrade\ub97c<\/strong> \uc81c\uc5b4\ud558\uba74\uc11c \uc2dc\uac04<\/strong> \uacfc ExamScore<\/strong> \uc0ac\uc774\uc758 \ubd80\ubd84 \uc0c1\uad00\uad00\uacc4\ub97c \uacc4\uc0b0\ud558\ub824\uba74 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 \ud3ad\uadc4 \ud328\ud0a4\uc9c0<\/a> \uc758 \ubd80\ubd84\uc801_corr()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \ubd80\ubd84_corr(\ub370\uc774\ud130, x, y, \ucf54\ubc14\ub974)<\/span><\/strong><\/p>\n
 \uae08:<\/span><\/p>\n