{"id":3206,"date":"2023-07-18T16:36:45","date_gmt":"2023-07-18T16:36:45","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%83%e1%85%ae-%e1%84%8b%e1%85%a7%e1%86%af%e1%84%8b%e1%85%b4-%e1%84%80%e1%85%a9%e1%84%8b%e1%85%b2%e1%84%92%e1%85%a1\/"},"modified":"2023-07-18T16:36:45","modified_gmt":"2023-07-18T16:36:45","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%83%e1%85%ae-%e1%84%8b%e1%85%a7%e1%86%af%e1%84%8b%e1%85%b4-%e1%84%80%e1%85%a9%e1%84%8b%e1%85%b2%e1%84%92%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%83%e1%85%ae-%e1%84%8b%e1%85%a7%e1%86%af%e1%84%8b%e1%85%b4-%e1%84%80%e1%85%a9%e1%84%8b%e1%85%b2%e1%84%92%e1%85%a1\/","title":{"rendered":"Pandas: \ub450 \uc5f4\uc758 \uace0\uc720\ud55c \uc870\ud569\uc744 \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"

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\ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec Pandas DataFrame\uc758 \ub450 \uc5f4\uc5d0 \uac78\uccd0 \uace0\uc720\ud55c \uc870\ud569 \uc218\ub97c \uacc4\uc0b0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

 df[[' col1<\/span> ', ' col2<\/span> ']]. value_counts<\/span> (). reset_index<\/span> (name=' count<\/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: Pandas\uc5d0\uc11c \ub450 \uc5f4\uc758 \uace0\uc720\ud55c \uc870\ud569 \uacc4\uc0b0<\/strong><\/span><\/h3>\n
 \ub2e4\uc591\ud55c \ub18d\uad6c \uc120\uc218\uc758 \ud300<\/strong> \uacfc \uc704\uce58\ub97c<\/strong> \ubcf4\uc5ec\uc8fc\ub294 \ub2e4\uc74c\uacfc \uac19\uc740 \ud32c\ub354 DataFrame\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#create dataFrame<\/span>\ndf = pd. DataFrame<\/span> ({' team<\/span> ': ['Mavs', 'Mavs', 'Mavs', 'Mavs',\n                            'Heat', 'Heat', 'Heat', 'Heat'],\n                   ' position<\/span> ': ['Guard', 'Guard', 'Guard', 'Forward',\n                                'Guard', 'Forward', 'Forward', 'Guard']})\n#view DataFrame\n<\/span>df\n\n        team position\n0 Mavs Guard\n1 Mavs Guard\n2 Mavs Guard\n3 Mavs Forward\n4 Heat Guard\n5 Heat Forward\n6 Heat Forward\n7 Heat Guard<\/strong><\/pre>\n
 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec \uace0\uc720\ud55c \ud300<\/strong> \ubc0f \uc704\uce58<\/strong> \uc870\ud569\uc758 \uc218\ub97c \uacc4\uc0b0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 df[[' team<\/span> ', ' position<\/span> ']]. value_counts<\/span> (). reset_index<\/span> (name=' count<\/span> ')\n\n        team position count\n0 Mavs Guard 3\n1 Heat Forward 2\n2 Heat Guard 2\n3 Mavs Forward 1\n<\/strong><\/pre>\n
 \uacb0\uacfc\uc5d0\uc11c \uc6b0\ub9ac\ub294 \ub2e4\uc74c\uc744 \ubcfc \uc218 \uc788\uc2b5\ub2c8\ub2e4:<\/span><\/p>\n