{"id":2522,"date":"2023-07-21T21:45:15","date_gmt":"2023-07-21T21:45:15","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-html%e1%84%8b%e1%85%b3%e1%86%af-%e1%84%8b%e1%85%b5%e1%86%b0%e1%84%89%e1%85%b3%e1%86%b8%e1%84%82%e1%85%b5%e1%84%83%e1%85%a1\/"},"modified":"2023-07-21T21:45:15","modified_gmt":"2023-07-21T21:45:15","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-html%e1%84%8b%e1%85%b3%e1%86%af-%e1%84%8b%e1%85%b5%e1%86%b0%e1%84%89%e1%85%b3%e1%86%b8%e1%84%82%e1%85%b5%e1%84%83%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-html%e1%84%8b%e1%85%b3%e1%86%af-%e1%84%8b%e1%85%b5%e1%86%b0%e1%84%89%e1%85%b3%e1%86%b8%e1%84%82%e1%85%b5%e1%84%83%e1%85%a1\/","title":{"rendered":"Pandas\ub85c html \ud14c\uc774\ube14\uc744 \uc77d\ub294 \ubc29\ubc95(\uc608\uc81c \ud3ec\ud568)"},"content":{"rendered":"

<\/p>\n

\n

pandas read_html()<\/a> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec HTML \ud14c\uc774\ube14\uc744 pandas DataFrame\uc73c\ub85c \uc77d\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

\uc774 \ud568\uc218\ub294 \ub2e4\uc74c \uae30\ubcf8 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud569\ub2c8\ub2e4.<\/span><\/p>\n

 df = pd. read_html<\/span> (' https:\/\/en.wikipedia.org\/wiki\/National_Basketball_Association<\/span> ')\n<\/strong><\/pre>\n
 \ub2e4\uc74c \uc608\ub294 \uc774 \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc774 Wikipedia \ud398\uc774\uc9c0<\/a> \uc5d0\uc11c NBA \ud300 \uc774\ub984 \ud14c\uc774\ube14\uc744 \uc77d\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 \uc608: Pandas\ub85c HTML \ud14c\uc774\ube14 \uc77d\uae30<\/strong><\/span><\/h3>\n
 read_html()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uae30 \uc804\uc5d0 lxml\uc744 \uc124\uce58\ud574\uc57c \ud560 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4:<\/span><\/p>\n
 pip install<\/span> lxml<\/strong><\/span><\/pre>\n
 \ucc38\uace0<\/strong> : Jupyter \ub178\ud2b8\ubd81\uc744 \uc0ac\uc6a9\ud558\ub294 \uacbd\uc6b0 \uc774 \uc124\uce58\ub97c \uc218\ud589\ud55c \ud6c4 \ucee4\ub110\uc744 \ub2e4\uc2dc \uc2dc\uc791\ud574\uc57c \ud569\ub2c8\ub2e4.<\/span><\/p>\n
 \ub2e4\uc74c\uc73c\ub85c, read_html()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc774 Wikipedia \ud398\uc774\uc9c0<\/a> \uc758 \uac01 HTML \ud14c\uc774\ube14\uc744 \uc77d\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\nimport<\/span> numpy as<\/span> np\nimport<\/span> matplotlib. pyplot<\/span> as<\/span> plt\nfrom<\/span> unicodedata import<\/span> normalize\n\n#read all HTML tables from specific URL\n<\/span>tabs = pd. read_html<\/span> (' https:\/\/en.wikipedia.org\/wiki\/National_Basketball_Association<\/span> ')\n\n#display total number of tables read\n<\/span>len<\/span> (tabs)\n\n44<\/span><\/span><\/strong><\/pre>\n
 \uc774 \ud398\uc774\uc9c0\uc5d0\uc11c \ucd1d 44\uac1c\uc758 HTML \ud14c\uc774\ube14\uc774 \ubc1c\uacac\ub418\uc5c8\uc74c\uc744 \uc54c \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \uad00\uc2ec \uc788\ub294 \ud14c\uc774\ube14\uc5d0 “Division”\uc774\ub77c\ub294 \ub2e8\uc5b4\uac00 \ud3ec\ud568\ub418\uc5b4 \uc788\ub2e4\ub294 \uac83\uc744 \uc54c\uace0 \uc788\uc73c\ubbc0\ub85c match<\/strong> \uc778\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc774 \ub2e8\uc5b4\uac00 \ud3ec\ud568\ub41c HTML \ud14c\uc774\ube14\ub9cc \uac80\uc0c9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 #read HTML tables from specific URL with the word \"Division\" in them\n<\/span>tabs = pd. read_html<\/span> (' https:\/\/en.wikipedia.org\/wiki\/National_Basketball_Association<\/span> ',\n                    match=' Division<\/span> ')\n\n#display total number of tables read\n<\/span>len<\/span> (tabs)\n\n1<\/span><\/span><\/strong><\/pre>\n
 #define table\ndf = tabs[0]<\/span>\n\n#list all column names of table\nlist<\/span> (df)\n\n[('Division', 'Eastern Conference'),\n ('Team', 'Eastern Conference'),\n ('Location', 'Eastern Conference'),\n ('Arena', 'Eastern Conference'),\n ('Capacity', 'Eastern Conference'),\n ('Coordinates', 'Eastern Conference'),\n ('Founded', 'Eastern Conference'),\n ('Joined', 'Eastern Conference'),\n ('Unnamed: 8_level_0', 'Eastern Conference')]<\/span><\/span><\/strong><\/pre>\n
 #filter DataFrame to only contain first two columns\n<\/span>df_final = df. iloc<\/span> [:, 0:2]\n\n#rename columns\n<\/span>df_final. columns<\/span> = [' Division<\/span> ', ' Team<\/span> ']\n\n#view first few rows of final DataFrame\n<\/span>print<\/span> ( df_final.head<\/span> ())\n\n   Division Team\n0 Atlantic Boston Celtics\n1 Atlantic Brooklyn Nets\n2 Atlantic New York Knicks\n3 Atlantic Philadelphia 76ers\n4 Atlantic Toronto Raptors\n<\/strong><\/span><\/pre>\n
 \ucd5c\uc885 \ud14c\uc774\ube14\uc5d0\ub294 “Division” \ubc0f “Team” \uc5f4\ub9cc \ud3ec\ud568\ub429\ub2c8\ub2e4.<\/span><\/p>\n
 \ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h3>\n
 \ub2e4\uc74c \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Pandas\uc5d0\uc11c \ub2e4\ub978 \ud30c\uc77c \ud615\uc2dd\uc744 \uc77d\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 Pandas\ub85c \ud14d\uc2a4\ud2b8 \ud30c\uc77c\uc744 \uc77d\ub294 \ubc29\ubc95<\/a>
 Pandas\ub85c Excel \ud30c\uc77c\uc744 \uc77d\ub294 \ubc29\ubc95<\/a>
 Pandas\ub85c CSV \ud30c\uc77c\uc744 \uc77d\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
pandas read_html() \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec HTML \ud14c\uc774\ube14\uc744 pandas DataFrame\uc73c\ub85c \uc77d\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \ud568\uc218\ub294 \ub2e4\uc74c \uae30\ubcf8 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud569\ub2c8\ub2e4. df = pd. read_html (‘ https:\/\/en.wikipedia.org\/wiki\/National_Basketball_Association ‘) \ub2e4\uc74c \uc608\ub294 \uc774 \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc774 Wikipedia \ud398\uc774\uc9c0 \uc5d0\uc11c NBA \ud300 \uc774\ub984 \ud14c\uc774\ube14\uc744 \uc77d\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4. \uc608: Pandas\ub85c HTML \ud14c\uc774\ube14 \uc77d\uae30 read_html() \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uae30 \uc804\uc5d0 lxml\uc744 \uc124\uce58\ud574\uc57c \ud560 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4: pip […]<\/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-2522","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"\nPandas\ub85c HTML \ud14c\uc774\ube14\uc744 \uc77d\ub294 \ubc29\ubc95(\uc608\uc81c \ud3ec\ud568) - 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