{"id":3407,"date":"2023-07-17T15:39:31","date_gmt":"2023-07-17T15:39:31","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%8c%e1%85%a5%e1%86%b7%e1%84%91%e1%85%b3-%e1%84%89%e1%85%ae%e1%86%ab%e1%84%8b%e1%85%b1\/"},"modified":"2023-07-17T15:39:31","modified_gmt":"2023-07-17T15:39:31","slug":"%e1%84%91%e1%85%a2%e1%86%ab%e1%84%83%e1%85%a5-%e1%84%8c%e1%85%a5%e1%86%b7%e1%84%91%e1%85%b3-%e1%84%89%e1%85%ae%e1%86%ab%e1%84%8b%e1%85%b1","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%8c%e1%85%a5%e1%86%b7%e1%84%91%e1%85%b3-%e1%84%89%e1%85%ae%e1%86%ab%e1%84%8b%e1%85%b1\/","title":{"rendered":"Pandas: csv \ud30c\uc77c\uc744 \uc77d\uc744 \ub54c \uc904\uc744 \uac74\ub108\ub6f0\ub294 \ubc29\ubc95"},"content":{"rendered":"

<\/p>\n

\n

CSV \ud30c\uc77c\uc744 Pandas DataFrame\uc73c\ub85c \uc77d\uc744 \ub54c \ub2e4\uc74c \ubc29\ubc95\uc744 \uc0ac\uc6a9\ud558\uc5ec \ud589\uc744 \uac74\ub108\ub6f8 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

\ubc29\ubc95 1: \ud2b9\uc815 \ud589 \uac74\ub108\ub6f0\uae30<\/strong><\/span><\/p>\n

 #import DataFrame and skip 2nd row\n<\/span>df = pd. read_csv<\/span> ('my_data.csv', skiprows=[ 2<\/span> ])\n<\/strong><\/pre>\n
 \ubc29\ubc95 2: \uc5ec\ub7ec \ud2b9\uc815 \ud589 \ubb34\uc2dc<\/strong><\/span><\/p>\n
 #import DataFrame and skip 2nd and 4th row\n<\/span>df = pd. read_csv<\/span> (' my_data.csv', skiprows=[2,4<\/span> ]<\/span> )<\/strong><\/pre>\n
 \ubc29\ubc95 3: \ucc98\uc74c N \uc904\uc744 \ubb34\uc2dc\ud569\ub2c8\ub2e4.<\/strong><\/span><\/p>\n
 #import DataFrame and skip first 2 rows\n<\/span>df = pd. read_csv<\/span> ('my_data.csv', skiprows= 2<\/span> )<\/strong><\/pre>\n
 \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 Basketball_data.csv<\/strong> \ub77c\ub294 CSV \ud30c\uc77c\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc2e4\uc81c\ub85c \uac01 \ubc29\ubc95\uc744 \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span> <\/p>\n
\"\"<\/p>\n
 \uc608\uc2dc 1: \ud2b9\uc815 \ud589 \ubb34\uc2dc<\/strong><\/span><\/h2>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec CSV \ud30c\uc77c\uc744 \uac00\uc838\uc624\uace0 \ub450 \ubc88\uc9f8 \uc904\uc744 \ubb34\uc2dc\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#import DataFrame and skip 2nd row\n<\/span>df = pd. read_csv<\/span> ('basketball_data.csv', skiprows=[ 2<\/span> ])\n\n#view DataFrame\n<\/span>df\n\n        team points rebounds\n0 to 22 10\n1 C 29 6\n2 D 30 2\n<\/b><\/pre>\n
 CSV \ud30c\uc77c\uc744 pandas DataFrame\uc73c\ub85c \uac00\uc838\uc62c \ub54c \ub450 \ubc88\uc9f8 \uc904(\ud300 “B” \ud3ec\ud568)\uc740 \ubb34\uc2dc\ub418\uc5c8\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \ucc38\uace0<\/strong> : CSV \ud30c\uc77c\uc758 \uccab \ubc88\uc9f8 \uc904\uc740 0\uc904\ub85c \uac04\uc8fc\ub429\ub2c8\ub2e4.<\/span><\/p>\n
 \uc608\uc2dc 2: \uc5ec\ub7ec \ud2b9\uc815 \uc904 \ubb34\uc2dc<\/strong><\/span><\/h2>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec CSV \ud30c\uc77c\uc744 \uac00\uc838\uc624\uace0 \ub450 \ubc88\uc9f8\uc640 \ub124 \ubc88\uc9f8 \uc904\uc744 \uac74\ub108\ub6f8 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#import DataFrame and skip 2nd and 4th rows\n<\/span>df = pd. read_csv<\/span> ('basketball_data.csv', skiprows=[ 2<\/span> , 4<\/span> ])\n\n#view DataFrame\n<\/span>df\n\n        team points rebounds\n0 to 22 10\n1 C 29 6\n<\/b><\/pre>\n
 CSV \ud30c\uc77c\uc744 pandas DataFrame\uc73c\ub85c \uac00\uc838\uc62c \ub54c \ub450 \ubc88\uc9f8 \ubc0f \ub124 \ubc88\uc9f8 \uc904(\ud300 “B” \ubc0f “D” \ud3ec\ud568)\uc740 \ubb34\uc2dc\ub418\uc5c8\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \uc608\uc2dc 3: \ucc98\uc74c N \uc904 \ubb34\uc2dc<\/strong><\/span><\/h2>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec CSV \ud30c\uc77c\uc744 \uac00\uc838\uc624\uace0 \ucc98\uc74c \ub450 \uc904\uc744 \uac74\ub108\ub6f8 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#import DataFrame and skip first 2 rows\n<\/span>df = pd. read_csv<\/span> ('basketball_data.csv', skiprows= 2<\/span> )\n\n#view DataFrame\n<\/span>df\n\n        B 14 9\n0 C 29 6\n1 D 30 2\n<\/b><\/pre>\n
 CSV \ud30c\uc77c\uc758 \ucc98\uc74c \ub450 \uc904\uc740 \uac74\ub108\ub6f0\uc5c8\uace0 \uc0ac\uc6a9 \uac00\ub2a5\ud55c \ub2e4\uc74c \uc904(\ud300 “B” \ud3ec\ud568)\uc774 DataFrame\uc758 \ud5e4\ub354 \uc904\uc774 \ub418\uc5c8\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h2>\n
 \ub2e4\uc74c \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Python\uc5d0\uc11c \ub2e4\ub978 \uc77c\ubc18\uc801\uc778 \uc791\uc5c5\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 Pandas\ub85c Excel \ud30c\uc77c\uc744 \uc77d\ub294 \ubc29\ubc95<\/a>
 Pandas DataFrame\uc744 Excel\ub85c \ub0b4\ubcf4\ub0b4\ub294 \ubc29\ubc95<\/a>
 NumPy \ubc30\uc5f4\uc744 CSV \ud30c\uc77c\ub85c \ub0b4\ubcf4\ub0b4\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
CSV \ud30c\uc77c\uc744 Pandas DataFrame\uc73c\ub85c \uc77d\uc744 \ub54c \ub2e4\uc74c \ubc29\ubc95\uc744 \uc0ac\uc6a9\ud558\uc5ec \ud589\uc744 \uac74\ub108\ub6f8 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ubc29\ubc95 1: \ud2b9\uc815 \ud589 \uac74\ub108\ub6f0\uae30 #import DataFrame and skip 2nd row df = pd. read_csv (‘my_data.csv’, skiprows=[ 2 ]) \ubc29\ubc95 2: \uc5ec\ub7ec \ud2b9\uc815 \ud589 \ubb34\uc2dc #import DataFrame and skip 2nd and 4th row df = pd. read_csv (‘ my_data.csv’, skiprows=[2,4 ] ) […]<\/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-3407","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"\nPandas: CSV \ud30c\uc77c\uc744 \uc77d\uc744 \ub54c \uc904\uc744 \uac74\ub108\ub6f0\ub294 \ubc29\ubc95 - Statorials<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Pandas\uc5d0\uc11c CSV \ud30c\uc77c\uc744 \uc77d\uc744 \ub54c \uc904\uc744 \uac74\ub108\ub6f0\ub294 \ubc29\ubc95\uc744 \uc608\uc2dc\uc640 \ud568\uaed8 \uc124\uba85\ud569\ub2c8\ub2e4.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/ko\/\u1111\u1162\u11ab\u1103\u1165-\u110c\u1165\u11b7\u1111\u1173-\u1109\u116e\u11ab\u110b\u1171\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Pandas: CSV \ud30c\uc77c\uc744 \uc77d\uc744 \ub54c \uc904\uc744 \uac74\ub108\ub6f0\ub294 \ubc29\ubc95 - 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