{"id":3555,"date":"2023-07-16T20:42:07","date_gmt":"2023-07-16T20:42:07","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%8b%e1%85%a7%e1%84%85%e1%85%a5-%e1%84%8b%e1%85%a7%e1%86%af%e1%84%8b%e1%85%b3%e1%86%af-%e1%84%8b%e1%85%b5%e1%86%ab%e1%84%8f%e1%85%a9%e1%84%83%e1%85%b5%e1%86%bc%e1%84%92%e1%85%a1%e1%84%82%e1%85%b3\/"},"modified":"2023-07-16T20:42:07","modified_gmt":"2023-07-16T20:42:07","slug":"%e1%84%8b%e1%85%a7%e1%84%85%e1%85%a5-%e1%84%8b%e1%85%a7%e1%86%af%e1%84%8b%e1%85%b3%e1%86%af-%e1%84%8b%e1%85%b5%e1%86%ab%e1%84%8f%e1%85%a9%e1%84%83%e1%85%b5%e1%86%bc%e1%84%92%e1%85%a1%e1%84%82%e1%85%b3","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%8b%e1%85%a7%e1%84%85%e1%85%a5-%e1%84%8b%e1%85%a7%e1%86%af%e1%84%8b%e1%85%b3%e1%86%af-%e1%84%8b%e1%85%b5%e1%86%ab%e1%84%8f%e1%85%a9%e1%84%83%e1%85%b5%e1%86%bc%e1%84%92%e1%85%a1%e1%84%82%e1%85%b3\/","title":{"rendered":"Scikit-learn: \ub2e4\uc911 \uc5f4 \ub808\uc774\ube14 \ucf54\ub529 \uc0ac\uc6a9"},"content":{"rendered":"

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\uae30\uacc4 \ud559\uc2b5\uc5d0\uc11c \ub808\uc774\ube14 \uc778\ucf54\ub529\uc740<\/strong> \ubc94\uc8fc\ud615 \ubcc0\uc218<\/a> \uc758 \uac12\uc744 \uc815\uc218 \uac12\uc73c\ub85c \ubcc0\ud658\ud558\ub294 \ud504\ub85c\uc138\uc2a4\uc785\ub2c8\ub2e4.<\/span><\/p>\n

\uc608\ub97c \ub4e4\uc5b4 \ub2e4\uc74c \uc2a4\ud06c\ub9b0\uc0f7\uc5d0\uc11c\ub294 Team<\/strong> \uc774\ub77c\ub294 \ubc94\uc8fc\ud615 \ubcc0\uc218\uc758 \uac01 \uace0\uc720 \uac12\uc744 \uc54c\ud30c\ubcb3 \uc21c\uc11c\uc5d0 \ub530\ub77c \uc815\uc218 \uac12\uc73c\ub85c \ubcc0\ud658\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span> <\/p>\n

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\ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec Python\uc5d0\uc11c \ub2e4\uc911 \uc5f4 \ub808\uc774\ube14 \uc778\ucf54\ub529\uc744 \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

 from<\/span> sklearn. preprocessing<\/span> import<\/span> LabelEncoder\n\n#perform label encoding on col1, col2 columns\n<\/span>df[[' col1<\/span> ', ' col2<\/span> ']] = df[[' col1<\/span> ', ' col2<\/span> ']]. apply<\/span> (LabelEncoder(). fit_transform<\/span> )\n<\/strong><\/pre>\n
 \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc2e4\uc81c\ub85c \uc774 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 \uc608: Python\uc758 \ub808\uc774\ube14 \uc778\ucf54\ub529<\/strong><\/span><\/h2>\n
 \ub2e4\uc591\ud55c \ub18d\uad6c \uc120\uc218\uc5d0 \ub300\ud55c \uc815\ubcf4\uac00 \ud3ec\ud568\ub41c \ub2e4\uc74c\uacfc \uac19\uc740 pandas DataFrame\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame<\/span>\ndf = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'A', 'B', 'B', 'B', 'C', 'C', 'D'],\n                   ' position<\/span> ': ['G', 'F', 'G', 'F', 'F', 'G', 'G', 'F'],\n                   ' all_star<\/span> ': ['Y', 'N', 'Y', 'Y', 'Y', 'N', 'Y', 'N'],\n                   ' points<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n  team position all_star points\n0 AGY 11\n1 AFN 8\n2 BGY 10\n3 BFY 6\n4 BFY 6\n5 CGN 5\n6 CGY 9\n7 DFN 12\n<\/strong><\/span><\/pre>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub808\uc774\ube14 \uc778\ucf54\ub529\uc744 \uc218\ud589\ud558\uc5ec team<\/strong> , position<\/strong> \ubc0f all_star<\/strong> \uc5f4\uc758 \uac01 \ubc94\uc8fc \uac12\uc744 \uc815\uc218 \uac12\uc73c\ub85c \ubcc0\ud658\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 from<\/span> sklearn. preprocessing<\/span> import<\/span> LabelEncoder\n\n#perform label encoding across team, position, and all_star columns\ndf[[' team<\/span> ', ' position<\/span> ', ' all_star<\/span> ']] = df[[' team<\/span> ', ' position<\/span> ', ' all_star<\/span> ']]. apply<\/span> (LabelEncoder(). fit_transform<\/span> )\n<\/span>\n#view udpated DataFrame\nprint<\/span> (df)\n\n   team position all_star points\n0 0 1 1 11\n1 0 0 0 8\n2 1 1 1 10\n3 1 0 1 6\n4 1 0 1 6\n5 2 1 0 5\n6 2 1 1 9\n7 3 0 0 12<\/span><\/span><\/strong><\/pre>\n
 \uadf8 \uacb0\uacfc, team<\/strong> , position<\/strong> , all_star<\/strong> \uceec\ub7fc\uc758 \uac01 \uac12\uc774 \uc815\uc218\uac12\uc73c\ub85c \ubcc0\ud658\ub41c \uac83\uc744 \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \uc608\ub97c \ub4e4\uc5b4 \ud300<\/strong> \uc5f4\uc5d0\uc11c \ub2e4\uc74c\uc744 \ubcfc \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n