{"id":908,"date":"2023-07-28T08:30:34","date_gmt":"2023-07-28T08:30:34","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%8b%e1%85%a7%e1%86%af%e1%84%8b%e1%85%b3%e1%86%af-%e1%84%80%e1%85%b5%e1%84%87%e1%85%a1%e1%86%ab%e1%84%8b%e1%85%b3%e1%84%85%e1%85%a9-%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%86\/"},"modified":"2023-07-28T08:30:34","modified_gmt":"2023-07-28T08:30:34","slug":"%e1%84%8b%e1%85%a7%e1%86%af%e1%84%8b%e1%85%b3%e1%86%af-%e1%84%80%e1%85%b5%e1%84%87%e1%85%a1%e1%86%ab%e1%84%8b%e1%85%b3%e1%84%85%e1%85%a9-%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%86","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%8b%e1%85%a7%e1%86%af%e1%84%8b%e1%85%b3%e1%86%af-%e1%84%80%e1%85%b5%e1%84%87%e1%85%a1%e1%86%ab%e1%84%8b%e1%85%b3%e1%84%85%e1%85%a9-%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%86\/","title":{"rendered":"Pandas\uc758 \uc870\uac74\uc744 \uae30\ubc18\uc73c\ub85c \uc0c8 \uc5f4\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95"},"content":{"rendered":"

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\ud2b9\uc815 \uc870\uac74\uc5d0 \ub530\ub77c Pandas DataFrame\uc5d0 \uc0c8 \uc5f4\uc744 \uc0dd\uc131\ud558\ub824\ub294 \uacbd\uc6b0\uac00 \uc885\uc885 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \ub2e4\uc74c DataFrame\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc774\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud55c \uba87 \uac00\uc9c0 \uc608\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4.<\/span><\/p>\n

 import<\/span> pandas as<\/span> pd\nimport<\/span> numpy as<\/span> np\n\n#createDataFrame<\/span>\ndf = pd. DataFrame<\/span> ({'rating': [90, 85, 82, 88, 94, 90, 76, 75, 87, 86],\n                   'points': [25, 20, 14, 16, 27, 20, 12, 15, 14, 19],\n                   'assists': [5, 7, 7, 8, 5, 7, 6, 9, 9, 5],\n                   'rebounds': [11, 8, 10, 6, 6, 9, 6, 10, 10, 7]})\n\n#view DataFrame\ndf\n<\/span>\n<\/span>rating points assists rebounds\n0 90 25 5 11\n1 85 20 7 8\n2 82 14 7 10\n3 88 16 8 6\n4 94 27 5 6\n5 90 20 7 9\n6 76 12 6 6\n7 75 15 9 10\n8 87 14 9 10\n9 86 19 5 7\n<\/strong><\/pre>\n
 \uc608 1: \uc774\uc9c4 \uac12\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc0c8 \uc5f4 \ub9cc\ub4e4\uae30<\/strong><\/span><\/h3>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub294 \uc8fc\uc5b4\uc9c4 \ud589\uc758 \ud3ec\uc778\ud2b8\uac00 20\ubcf4\ub2e4 \ud06c\uba74 \uac12\uc774 “yes”\uc774\uace0 \uadf8\ub807\uc9c0 \uc54a\uc73c\uba74 “no”\uc778 “Good”\uc774\ub77c\ub294 \uc0c8 \uc5f4\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 #create new column titled 'Good'<\/span>\ndf['Good'] = np. where<\/span> (df['points']>20, ' yes<\/span> ', ' no<\/span> ')\n\n#view DataFrame<\/span> \ndf\n\n        rating points assists rebounds Good\n0 90 25 5 11 yes\n1 85 20 7 8 no\n2 82 14 7 10 no\n3 88 16 8 6 no\n4 94 27 5 6 yes\n5 90 20 7 9 no\n6 76 12 6 6 no\n7 75 15 9 10 no\n8 87 14 9 10 no\n9 86 19 5 7 no\n<\/strong><\/pre>\n
 \uc608 2: \uc5ec\ub7ec \uac12\uc774 \ud3ec\ud568\ub41c \uc0c8 \uc5f4 \ub9cc\ub4e4\uae30<\/strong><\/span><\/h3>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub294 \uac12\uc774 \ub2e4\uc74c\uacfc \uac19\uc740 “Good”\uc774\ub77c\ub294 \uc0c8 \uc5f4\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n