{"id":1730,"date":"2023-07-25T05:15:38","date_gmt":"2023-07-25T05:15:38","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%80%e1%85%a2%e1%84%8b%e1%85%b4-%e1%84%8b%e1%85%a7%e1%86%af%e1%84%8b%e1%85%b3%e1%86%af-%e1%84%80\/"},"modified":"2023-07-25T05:15:38","modified_gmt":"2023-07-25T05:15:38","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%80%e1%85%a2%e1%84%8b%e1%85%b4-%e1%84%8b%e1%85%a7%e1%86%af%e1%84%8b%e1%85%b3%e1%86%af-%e1%84%80","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%80%e1%85%a2%e1%84%8b%e1%85%b4-%e1%84%8b%e1%85%a7%e1%86%af%e1%84%8b%e1%85%b3%e1%86%af-%e1%84%80\/","title":{"rendered":"Pandas\uc5d0\uc11c \ub450 \uc5f4\uc744 \uacb0\ud569\ud558\ub294 \ubc29\ubc95(\uc608\uc81c \ud3ec\ud568)"},"content":{"rendered":"

<\/p>\n

\n

\ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec Pandas DataFrame\uc5d0\uc11c \ub450 \uac1c\uc758 \ud14d\uc2a4\ud2b8 \uc5f4\uc744 \ud558\ub098\ub85c \uacb0\ud569\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

 df[' new_column<\/span> '] = df[' column1<\/span> '] + df[' column2<\/span> ']\n<\/strong><\/pre>\n
 \uc5f4 \uc911 \ud558\ub098\uac00 \uc544\uc9c1 \ubb38\uc790\uc5f4\uc774 \uc544\ub2cc \uacbd\uc6b0 astype(str)<\/strong> \uba85\ub839\uc744 \uc0ac\uc6a9\ud558\uc5ec \ubcc0\ud658\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 df[' new_column<\/span> '] = df[' column1<\/span> ']. astype<\/span> ( str<\/span> )+df[' column2<\/span> ']<\/strong><\/pre>\n
 \uadf8\ub9ac\uace0 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc5ec\ub7ec \ud14d\uc2a4\ud2b8 \uc5f4\uc744 \ud558\ub098\ub85c \uacb0\ud569\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 df[' new_column<\/span> '] = df[[' col1<\/span> ', ' col2<\/span> ', ' col3<\/span> ', ...]]. agg<\/span> (' '. join<\/span> , axis= 1<\/span> )<\/strong><\/pre>\n
 \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc2e4\uc81c\ub85c \ud14d\uc2a4\ud2b8 \uc5f4\uc744 \uacb0\ud569\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 \uc608\uc2dc 1: \ub450 \uc5f4 \uacb0\ud569<\/strong><\/span><\/h3>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub294 Pandas DataFrame\uc5d0\uc11c \ub450 \uac1c\uc758 \ud14d\uc2a4\ud2b8 \uc5f4\uc744 \ud558\ub098\ub85c \uacb0\ud569\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#create dataFrame<\/span>\ndf = pd. DataFrame<\/span> ({' team<\/span> ': ['Mavs', 'Lakers', 'Spurs', 'Cavs'],\n                   ' first<\/span> ': ['Dirk', 'Kobe', 'Tim', 'Lebron'],\n                   ' last<\/span> ': ['Nowitzki', 'Bryant', 'Duncan', 'James'],\n                   ' points<\/span> ': [26, 31, 22, 29]})\n\n#combine first and last name column into new column, with space in between<\/span>\ndf[' full_name<\/span> '] = df[' first<\/span> '] + ' ' + df[' last<\/span> ']\n\n#view resulting dataFrame\ndf<\/span>\n\nteam first last<\/span> points full_name\n0 Mavs Dirk Nowitzki<\/span> 26 Dirk Nowitzki\n1 Lakers Kobe Bryant<\/span> 31 Kobe Bryant\n2 Spurs Tim Duncan<\/span> 22 Tim Duncan\n3 Cavs LeBron James<\/span> 29 LeBron James\n<\/span><\/span><\/strong><\/pre>\n
 \uc774\ub984\uacfc \uc131 \uc5f4\uc744 \uc0ac\uc774\uc5d0 \uacf5\ubc31\uc73c\ub85c \uacb0\ud569\ud588\uc9c0\ub9cc \ud558\uc774\ud508\uacfc \uac19\uc740 \ub2e4\ub978 \uad6c\ubd84 \uae30\ud638\ub97c \uc0ac\uc6a9\ud560 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 #combine first and last name column into new column, with dash in between<\/span>\ndf[' full_name<\/span> '] = df[' first<\/span> '] + ' -<\/span> ' + df[' last<\/span> ']\n\n#view resulting dataFrame\ndf<\/span>\n\nteam first last<\/span> points full_name\n0 Mavs Dirk Nowitzki<\/span> 26 Dirk<\/span> - Nowitzki\n1 Lakers Kobe Bryant<\/span> 31 Kobe<\/span> - Bryant\n2 Spurs Tim Duncan<\/span> 22 Tim<\/span> - Duncan\n3 Cavs Lebron James<\/span> 29 Lebron<\/span> - James<\/span><\/span><\/strong><\/pre>\n
 \uc608 2: \ud14d\uc2a4\ud2b8\ub85c \ubcc0\ud658\ud558\uace0 \ub450 \uc5f4 \uacb0\ud569<\/strong><\/span><\/h3>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub294 \uc5f4\uc744 \ud14d\uc2a4\ud2b8\ub85c \ubcc0\ud658\ud55c \ud6c4 \ub2e4\ub978 \uc5f4\uc5d0 \uacb0\ud569\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#create dataFrame<\/span>\ndf = pd. DataFrame<\/span> ({' team<\/span> ': ['Mavs', 'Lakers', 'Spurs', 'Cavs'],\n                   ' first<\/span> ': ['Dirk', 'Kobe', 'Tim', 'Lebron'],\n                   ' last<\/span> ': ['Nowitzki', 'Bryant', 'Duncan', 'James'],\n                   ' points<\/span> ': [26, 31, 22, 29]})\n\n#convert points to text, then join to last name column<\/span>\ndf[' name_points<\/span> '] = df[' last<\/span> '] + df[' points<\/span> ']. astype<\/span> ( str<\/span> )\n\n#view resulting dataFrame\ndf<\/span>\n\n        team first last<\/span> points name_points\n0 Mavs Dirk Nowitzki<\/span> 26 Nowitzki26\n1 Lakers Kobe Bryant<\/span> 31 Bryant31\n2 Spurs Tim Duncan<\/span> 22 Duncan22\n3 Cavs LeBron James<\/span> 29 James29<\/span><\/span><\/strong><\/pre>\n
 \uc608\uc2dc 3: 2\uac1c \uc774\uc0c1\uc758 \uc5f4 \uacb0\ud569<\/strong><\/span><\/h3>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub294 \uc5ec\ub7ec \uc5f4\uc744 \ud558\ub098\ub85c \uacb0\ud569\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#create dataFrame<\/span>\ndf = pd. DataFrame<\/span> ({' team<\/span> ': ['Mavs', 'Lakers', 'Spurs', 'Cavs'],\n                   ' first<\/span> ': ['Dirk', 'Kobe', 'Tim', 'Lebron'],\n                   ' last<\/span> ': ['Nowitzki', 'Bryant', 'Duncan', 'James'],\n                   ' points<\/span> ': [26, 31, 22, 29]})\n\n#join team, first name, and last name into one column<\/span>\ndf[' team_and_name<\/span> '] = df[[' team<\/span> ', ' first<\/span> ', ' last<\/span> ']]. agg<\/span> (' '. join<\/span> , axis= 1<\/span> )\n\n#view resulting dataFrame\ndf<\/span>\n\nteam first last points team_name\n0 Mavs Dirk Nowitzki 26 Mavs Dirk Nowitzki\n1 Lakers Kobe Bryant 31 Lakers Kobe Bryant\n2 Spurs Tim Duncan 22 Spurs Tim Duncan\n3 Cavs Lebron James 29 Cavs Lebron James<\/span><\/span><\/strong><\/pre>\n
 \ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h3>\n
 Pandas: \ub450 \uc5f4\uc758 \ucc28\uc774\uc810\uc744 \ucc3e\ub294 \ubc29\ubc95<\/a>
 Pandas: \ub450 \uc904\uc758 \ucc28\uc774\uc810\uc744 \ucc3e\ub294 \ubc29\ubc95<\/a>
 Pandas: \uc774\ub984\ubcc4\ub85c \uc5f4\uc744 \uc815\ub82c\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec Pandas DataFrame\uc5d0\uc11c \ub450 \uac1c\uc758 \ud14d\uc2a4\ud2b8 \uc5f4\uc744 \ud558\ub098\ub85c \uacb0\ud569\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. df[‘ new_column ‘] = df[‘ column1 ‘] + df[‘ column2 ‘] \uc5f4 \uc911 \ud558\ub098\uac00 \uc544\uc9c1 \ubb38\uc790\uc5f4\uc774 \uc544\ub2cc \uacbd\uc6b0 astype(str) \uba85\ub839\uc744 \uc0ac\uc6a9\ud558\uc5ec \ubcc0\ud658\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. df[‘ new_column ‘] = df[‘ column1 ‘]. astype ( str )+df[‘ column2 ‘] \uadf8\ub9ac\uace0 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc5ec\ub7ec […]<\/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-1730","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"\nPandas\uc5d0\uc11c \ub450 \uc5f4\uc744 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