{"id":1729,"date":"2023-07-25T05:15:38","date_gmt":"2023-07-25T05:15:38","guid":{"rendered":"https:\/\/statorials.org\/ja\/%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%af-2-%e3%81%a4%e3%81%ae%e5%88%97%e3%82%92%e7%b5%90%e5%90%88%e3%81%97%e3%81%be%e3%81%99\/"},"modified":"2023-07-25T05:15:38","modified_gmt":"2023-07-25T05:15:38","slug":"%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%af-2-%e3%81%a4%e3%81%ae%e5%88%97%e3%82%92%e7%b5%90%e5%90%88%e3%81%97%e3%81%be%e3%81%99","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%af-2-%e3%81%a4%e3%81%ae%e5%88%97%e3%82%92%e7%b5%90%e5%90%88%e3%81%97%e3%81%be%e3%81%99\/","title":{"rendered":"Pandas \u3067 2 \u3064\u306e\u5217\u3092\u7d50\u5408\u3059\u308b\u65b9\u6cd5 (\u4f8b\u4ed8\u304d)"},"content":{"rendered":"

<\/p>\n

\n

\u6b21\u306e\u69cb\u6587\u3092\u4f7f\u7528\u3057\u3066\u3001pandas DataFrame \u3067 2 \u3064\u306e\u30c6\u30ad\u30b9\u30c8\u5217\u3092 1 \u3064\u306b\u7d50\u5408\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n

 df[' new_column<\/span> '] = df[' column1<\/span> '] + df[' column2<\/span> ']\n<\/strong><\/pre>\n
\u3044\u305a\u308c\u304b\u306e\u5217\u304c\u307e\u3060\u6587\u5b57\u5217\u3067\u306a\u3044\u5834\u5408\u306f\u3001 astype(str)<\/strong>\u30b3\u30de\u30f3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u5909\u63db\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n
 df[' new_column<\/span> '] = df[' column1<\/span> ']. astype<\/span> ( str<\/span> )+df[' column2<\/span> ']<\/strong><\/pre>\n
\u307e\u305f\u3001\u6b21\u306e\u69cb\u6587\u3092\u4f7f\u7528\u3059\u308b\u3068\u3001\u8907\u6570\u306e\u30c6\u30ad\u30b9\u30c8\u5217\u3092 1 \u3064\u306b\u7d50\u5408\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n
 df[' new_column<\/span> '] = df[[' col1<\/span> ', ' col2<\/span> ', ' col3<\/span> ', ...]]. agg<\/span> (' '. join<\/span> , axis= 1<\/span> )<\/strong><\/pre>\n
\u6b21\u306e\u4f8b\u306f\u3001\u5b9f\u969b\u306b\u30c6\u30ad\u30b9\u30c8\u5217\u3092\u7d50\u5408\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n
\u4f8b 1: 2 \u3064\u306e\u5217\u3092\u7d50\u5408\u3059\u308b<\/strong><\/span><\/h3>\n
\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001pandas DataFrame \u3067 2 \u3064\u306e\u30c6\u30ad\u30b9\u30c8\u5217\u3092 1 \u3064\u306b\u7d50\u5408\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/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
\u59d3\u540d\u5217\u3092\u9593\u306b\u30b9\u30da\u30fc\u30b9\u3092\u5165\u308c\u3066\u7d50\u5408\u3057\u307e\u3057\u305f\u304c\u3001\u30cf\u30a4\u30d5\u30f3\u306a\u3069\u306e\u5225\u306e\u533a\u5207\u308a\u6587\u5b57\u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002<\/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
\u4f8b 2: \u30c6\u30ad\u30b9\u30c8\u306b\u5909\u63db\u3057\u3066 2 \u3064\u306e\u5217\u3092\u7d50\u5408\u3059\u308b<\/strong><\/span><\/h3>\n
\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u5217\u3092\u30c6\u30ad\u30b9\u30c8\u306b\u5909\u63db\u3057\u3001\u305d\u308c\u3092\u5225\u306e\u5217\u306b\u7d50\u5408\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/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
\u4f8b 3: 3 \u3064\u4ee5\u4e0a\u306e\u5217\u3092\u7d50\u5408\u3059\u308b<\/strong><\/span><\/h3>\n
\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u8907\u6570\u306e\u5217\u3092 1 \u3064\u306b\u7d50\u5408\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/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
\u8ffd\u52a0\u30ea\u30bd\u30fc\u30b9<\/strong><\/span><\/h3>\n
\u30d1\u30f3\u30c0: 2 \u3064\u306e\u5217\u306e\u9055\u3044\u3092\u898b\u3064\u3051\u308b\u65b9\u6cd5<\/a>
\u30d1\u30f3\u30c0: 2 \u3064\u306e\u7dda\u306e\u9055\u3044\u3092\u898b\u3064\u3051\u308b\u65b9\u6cd5<\/a>
\u30d1\u30f3\u30c0: \u5217\u3092\u540d\u524d\u3067\u4e26\u3079\u66ff\u3048\u308b\u65b9\u6cd5<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u6b21\u306e\u69cb\u6587\u3092\u4f7f\u7528\u3057\u3066\u3001pandas DataFrame \u3067 2 \u3064\u306e\u30c6\u30ad\u30b9\u30c8\u5217\u3092 1 \u3064\u306b\u7d50\u5408\u3067\u304d\u307e\u3059\u3002 df[‘ new_column ‘] = df[‘ column1 ‘] + df[‘ column2 ‘] \u3044\u305a\u308c […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[],"class_list":["post-1729","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"\nPandas \u3067 2 \u3064\u306e\u5217\u3092\u7d50\u5408\u3059\u308b\u65b9\u6cd5 (\u4f8b\u4ed8\u304d)<\/title>\n<meta name=\"description\" content=\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001pandas DataFrame \u3067 2 \u3064\u306e\u5217\u3092\u7d50\u5408\u3059\u308b\u65b9\u6cd5\u3092\u3044\u304f\u3064\u304b\u306e\u4f8b\u3068\u3068\u3082\u306b\u8aac\u660e\u3057\u307e\u3059\u3002\" 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