{"id":75442,"date":"2018-10-09T17:26:14","date_gmt":"2018-10-09T08:26:14","guid":{"rendered":"https:\/\/www.sejuku.net\/blog\/?p=75442"},"modified":"2024-05-06T11:52:48","modified_gmt":"2024-05-06T02:52:48","slug":"pandas%e3%81%aedataframe%e3%81%ab%e8%a1%8c%e3%82%92%e8%bf%bd%e5%8a%a0%e3%81%99%e3%82%8bappend%e9%96%a2%e6%95%b0%e3%82%92%e3%83%9e%e3%82%b9%e3%82%bf%e3%83%bc%e3%81%97%e3%82%88%e3%81%86%ef%bc%81","status":"publish","type":"post","link":"https:\/\/www.sejuku.net\/blog\/75442","title":{"rendered":"Pandas\u306eDataFrame\u306b\u884c\u3092\u8ffd\u52a0\u3059\u308bappend\u30e1\u30bd\u30c3\u30c9\u3092\u30de\u30b9\u30bf\u30fc\u3057\u3088\u3046\uff01"},"content":{"rendered":"

\u3053\u3093\u306b\u3061\u306f\uff01\u30a4\u30f3\u30b9\u30c8\u30e9\u30af\u30bf\u30fc\u306e\u30d5\u30af\u30ed\u30a6<\/a>\u3067\u3059\uff01<\/p>\n

\u3053\u306e\u8a18\u4e8b\u3067\u306f\u3001Pandas\u306e\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u306b\u65b0\u3057\u3044\u8981\u7d20\u3092\u884c\u65b9\u5411\u306b\u8ffd\u52a0<\/strong><\/span>\u3059\u308bDataFrame\u306eappend\u30e1\u30bd\u30c3\u30c9<\/strong><\/span>\u3092\u7d39\u4ecb\u3057\u307e\u3059\u3002<\/p>\n

append\u95a2\u6570\u3001Python\u306elist<\/strong><\/span>\u3084NumPy\u306enp.array<\/strong><\/span>\u306b\u3082\u3042\u308a\u307e\u3057\u305f\u306d\u3002<\/p>\n

\u540c\u69d8\u306e\u95a2\u6570\u304cPandas\u306b\u3082\u3042\u308a\u307e\u3059\u3002<\/p>\n

\u3088\u304f\u4f7f\u3046\u95a2\u6570\u306a\u306e\u3067\u3001\u4f7f\u3044\u65b9\u3092\u899a\u3048\u3066\u304a\u304d\u307e\u3057\u3087\u3046\uff01<\/p>\n

\u958b\u767a\u74b0\u5883<\/h2>\n

\u3053\u306e\u8a18\u4e8b\u3092\u66f8\u304f\u305f\u3081\u306b\u4f7f\u3063\u305f\u958b\u767a\u74b0\u5883\u306f\u4ee5\u4e0b\u306e\u3068\u304a\u308a\u3067\u3059\u3002
\n<\/p>\n

\u30e9\u30a4\u30d6\u30e9\u30ea\u306e\u30d0\u30fc\u30b8\u30e7\u30f3\u306a\u3069<\/p>\n

    \n
  • OS=”Ubuntu 18.04.1 LTS”<\/li>\n
  • Python 3.7.0<\/li>\n
  • Pandas 0.23.4<\/li>\n<\/ul>\n


    \nOS\u304c\u7570\u306a\u3063\u3066\u3082\u57fa\u672c\u7684\u306b\u306f\u540c\u3058<\/strong><\/span>\u64cd\u4f5c\u3067\u8a18\u4e8b\u4e2d\u306e\u30d7\u30ed\u30b0\u30e9\u30e0\u306f\u518d\u73fe\u3067\u304d\u308b\u306e\u3067\u3001\u8a66\u3057\u3066\u307f\u3066\u304f\u3060\u3055\u3044\uff01<\/p>\n

    append\u306eAPI<\/h2>\n

    append\u306fpandas.DataFrame\u306e\u30e1\u30bd\u30c3\u30c9<\/strong><\/span>\u3067\u3059\u3002<\/p>\n

    DataFrame.append(other,  # \u5927\u5207\u306a\u306e\u306f\u3053\u306e\u5f15\u6570\r\n\u3000\u3000\u3000\u3000\u3000\u3000\u3000\u3000\u3000\u3000ignore_index=False, \r\n\u3000\u3000\u3000\u3000\u3000\u3000\u3000\u3000\u3000\u3000verify_integrity=False, \r\n\u3000\u3000\u3000\u3000\u3000\u3000\u3000\u3000\u3000\u3000sort=None)<\/pre>\n
    \u57fa\u672c\u7684\u306b\u306f\u30aa\u30ea\u30b8\u30ca\u30eb\u306eDataFrame\u306e\u30e1\u30bd\u30c3\u30c9\u3068\u3057\u3066\u547c\u3073\u51fa\u3057\u3001\u8ffd\u52a0\u3057\u305f\u3044DataFrame\u3092\u7b2c\u4e00\u5f15\u6570<\/strong><\/span>\u306b\u3059\u308b\u3053\u3068\u3067\u4f7f\u3048\u307e\u3059\u3088\uff01<\/p>\n
    \u5f15\u6570\u3084\u8fd4\u308a\u5024\u306e\u8a73\u3057\u3044\u89e3\u8aac\u306f\u4ee5\u4e0b\u306e\u516c\u5f0f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3092\u53c2\u7167\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n\n
    \u6b21\u306e\u7ae0\u3067\u7279\u306b\u5927\u5207\u306a\u90e8\u5206\u306e\u4f7f\u3044\u65b9\u3092\u7d39\u4ecb\u3057\u3066\u3044\u304d\u307e\u3059\uff01<\/p>\n
    append\u306e\u4f7f\u3044\u65b9<\/h2>\n
    \n
    \n
    \n
    append\u306e\u57fa\u672c\u64cd\u4f5c<\/h3>\n
    \u307e\u305a\u306f\u30b7\u30f3\u30d7\u30eb\u306a\u7d50\u5408\u3092\u884c\u3063\u3066\u307f\u307e\u3059\u3002<\/p>\n
    \u540c\u3058\u5217\u6570\u306eDataFrame\u3092\uff12\u3064<\/strong><\/span>\u7528\u610f\u3057\u3066\u3001\u3053\u308c\u3089\u3092\u3064\u306a\u3052\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n
    \n
    \n
    In\u00a0[1]:<\/div>\n
    \n
    \n
    \n
    import pandas as pd\r\nimport numpy as np\r\n\r\n# DataFrame\u306b\u5165\u308c\u308b\u30c7\u30fc\u30bf\r\nx1 = np.arange(0,10).reshape((2,5))\r\nx2 = np.arange(10,20).reshape((2,5))\r\n\r\nprint(\"x1:\")\r\nprint(x1)\r\nprint(\"x2:\")\r\nprint(x2)<\/pre>\n
    Out[1]<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
    \n
    \n
    \n
    \n
    x1:\r\n[[0 1 2 3 4]\r\n [5 6 7 8 9]]\r\nx2:\r\n[[10 11 12 13 14]\r\n [15 16 17 18 19]]\r\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
    \n
    \n
    In\u00a0[2]:<\/div>\n
    \n
    \n
    \n
    # x1, x2\u304b\u3089DataFrame\u3092\u4f5c\u6210\r\n\r\ndf1 = pd.DataFrame(x1)\r\ndf2 = pd.DataFrame(x2)\r\n\r\ndf1.head()<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
    \n
    \n
    \n
    Out[2]:<\/div>\n
    \n
    \n\n\n\n\n\n\n
    <\/th>\n0<\/th>\n1<\/th>\n2<\/th>\n3<\/th>\n4<\/th>\n<\/tr>\n<\/thead>\n
    0<\/th>\n0<\/td>\n1<\/td>\n2<\/td>\n3<\/td>\n4<\/td>\n<\/tr>\n
    1<\/th>\n5<\/td>\n6<\/td>\n7<\/td>\n8<\/td>\n9<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
    \n
    \n
    In\u00a0[3]:<\/div>\n
    \n
    \n
    \n
    df2.head()<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
    \n
    \n
    \n
    Out[3]:<\/div>\n
    \n
    \n\n\n\n\n\n\n
    <\/th>\n0<\/th>\n1<\/th>\n2<\/th>\n3<\/th>\n4<\/th>\n<\/tr>\n<\/thead>\n
    0<\/th>\n10<\/td>\n11<\/td>\n12<\/td>\n13<\/td>\n14<\/td>\n<\/tr>\n
    1<\/th>\n15<\/td>\n16<\/td>\n17<\/td>\n18<\/td>\n19<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
    \n
    <\/div>\n
    \n
    \n
    \u3053\u3053\u307e\u3067\u3067DataFrame\u306e\u6e96\u5099\u304c\u3067\u304d\u307e\u3057\u305f\u3002<\/p>\n
    df1\u306bdf2\u3092\u8ffd\u52a0<\/strong><\/span>\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n
    \n
    \n
    In\u00a0[4]:<\/div>\n
    \n
    \n
    \n
    df1.append(df2)<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
    \n
    \n
    \n
    Out[4]:<\/div>\n
    \n
    \n\n\n\n\n\n\n\n\n
    <\/th>\n0<\/th>\n1<\/th>\n2<\/th>\n3<\/th>\n4<\/th>\n<\/tr>\n<\/thead>\n
    0<\/th>\n0<\/td>\n1<\/td>\n2<\/td>\n3<\/td>\n4<\/td>\n<\/tr>\n
    1<\/th>\n5<\/td>\n6<\/td>\n7<\/td>\n8<\/td>\n9<\/td>\n<\/tr>\n
    0<\/th>\n10<\/td>\n11<\/td>\n12<\/td>\n13<\/td>\n14<\/td>\n<\/tr>\n
    1<\/th>\n15<\/td>\n16<\/td>\n17<\/td>\n18<\/td>\n19<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
    \n
    <\/div>\n
    \n
    \n
    \u7d50\u5408\u3067\u304d\u307e\u3057\u305f\uff01<\/p>\n
    \u3053\u306e\u64cd\u4f5c\u3067\u306f\u30e1\u30bd\u30c3\u30c9\u3092\u547c\u3073\u51fa\u3057\u305fDataFrame\uff08\u3053\u3053\u3067\u306fdf1\uff09\u306e\u5f8c\u308d\u306b\u5f15\u6570\u306eDataFrame\u304c\u8ffd\u52a0\u3055\u308c\u308b\u5f62\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n
    \n
    \n
    \n
    \u5217\u6570\u304c\u9055\u3046DataFrame\u3092\u7d50\u5408<\/h3>\n
    \u3061\u306a\u307f\u306b\u5217\u6570\u304c\u9055\u3046\u5834\u5408<\/strong><\/span>\u306f\u3001\u7d50\u5408\u3057\u305f\u3068\u304d\u306b\u5024\u304c\u306a\u3044\u8981\u7d20\u304cNaN\uff08Non a Number\uff09<\/strong><\/span>\u306b\u306a\u308a\u307e\u3059\u304c\u3001\u4e00\u5fdc\u7d50\u5408\u3067\u304d\u307e\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n
    \n
    \n
    In\u00a0[5]:<\/div>\n
    \n
    \n
    \n
    # \u5217\u6570\u304c\u9055\u3046\u7d50\u5408\u306e\u4f8b\u306b\u4f7f\u3046DataFrame\u3067\u3059\u3002 \r\ndf2.T<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
    \n
    \n
    \n
    Out[5]:<\/div>\n
    \n
    \n\n\n\n\n\n\n\n\n\n
    <\/th>\n0<\/th>\n1<\/th>\n<\/tr>\n<\/thead>\n
    0<\/th>\n10<\/td>\n15<\/td>\n<\/tr>\n
    1<\/th>\n11<\/td>\n16<\/td>\n<\/tr>\n
    2<\/th>\n12<\/td>\n17<\/td>\n<\/tr>\n
    3<\/th>\n13<\/td>\n18<\/td>\n<\/tr>\n
    4<\/th>\n14<\/td>\n19<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
    \n
    \n
    In\u00a0[6]:<\/div>\n
    \n
    \n
    \n
    # \u9055\u3046\u5217\u6570\u306eDataFrame\u540c\u58eb\u3092\u7d50\u5408 \r\ndf1.append(df2.T)<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
    \n
    \n
    \n
    Out[6]:<\/div>\n
    \n
    \n\n\n\n\n\n\n\n\n\n\n\n
    <\/th>\n0<\/th>\n1<\/th>\n2<\/th>\n3<\/th>\n4<\/th>\n<\/tr>\n<\/thead>\n
    0<\/th>\n0<\/td>\n1<\/td>\n2.0<\/td>\n3.0<\/td>\n4.0<\/td>\n<\/tr>\n
    1<\/th>\n5<\/td>\n6<\/td>\n7.0<\/td>\n8.0<\/td>\n9.0<\/td>\n<\/tr>\n
    0<\/th>\n10<\/td>\n15<\/td>\nNaN<\/td>\nNaN<\/td>\nNaN<\/td>\n<\/tr>\n
    1<\/th>\n11<\/td>\n16<\/td>\nNaN<\/td>\nNaN<\/td>\nNaN<\/td>\n<\/tr>\n
    2<\/th>\n12<\/td>\n17<\/td>\nNaN<\/td>\nNaN<\/td>\nNaN<\/td>\n<\/tr>\n
    3<\/th>\n13<\/td>\n18<\/td>\nNaN<\/td>\nNaN<\/td>\nNaN<\/td>\n<\/tr>\n
    4<\/th>\n14<\/td>\n19<\/td>\nNaN<\/td>\nNaN<\/td>\nNaN<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
    \n
    <\/div>\n
    \n
    \n
    [\u304a\u307e\u3051]append\u3067\u4f5c\u3063\u305fDataFrame\u306e\u884cindex\u3092\u66f4\u65b0<\/h3>\n
    append\u3067\uff12\u3064\u306eDataFrame\u3092\u7d50\u5408\u3057\u305f\u5834\u5408\u3001\u884c\u306eindex\u306f\u5143\u306b\u306a\u3063\u305fDataFrame\u306e\u3082\u306e\u3092\u5f15\u304d\u7d99\u304e<\/strong><\/span>\u307e\u3059\u3002<\/p>\n
    \u3082\u3057\u30820\u884c\u76ee\u304b\u3089\u30ad\u30ec\u30a4\u306b\u30ca\u30f3\u30d0\u30ea\u30f3\u30b0\u3057\u305f\u3044\u5834\u5408<\/strong><\/span>\u306f\u3001DataFrame\u306eindex\u5c5e\u6027<\/strong><\/span>\u306b\u65b0\u3057\u3044index\u3092\u4ee3\u5165\u3057\u307e\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n
    \n
    \n
    In\u00a0[7]:<\/div>\n
    \n
    \n
    \n
    df3 = df1.append(df2.T) \r\ndf3.index = [0,1,2,3,4,5,6] \r\n\r\n# DataFrame\u306e\u8868\u793a\r\ndf3<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
    \n
    \n
    \n
    Out[7]:<\/div>\n
    \n
    \n\n\n\n\n\n\n\n\n\n\n\n
    <\/th>\n0<\/th>\n1<\/th>\n2<\/th>\n3<\/th>\n4<\/th>\n<\/tr>\n<\/thead>\n
    0<\/th>\n0<\/td>\n1<\/td>\n2.0<\/td>\n3.0<\/td>\n4.0<\/td>\n<\/tr>\n
    1<\/th>\n5<\/td>\n6<\/td>\n7.0<\/td>\n8.0<\/td>\n9.0<\/td>\n<\/tr>\n
    2<\/th>\n10<\/td>\n15<\/td>\nNaN<\/td>\nNaN<\/td>\nNaN<\/td>\n<\/tr>\n
    3<\/th>\n11<\/td>\n16<\/td>\nNaN<\/td>\nNaN<\/td>\nNaN<\/td>\n<\/tr>\n
    4<\/th>\n12<\/td>\n17<\/td>\nNaN<\/td>\nNaN<\/td>\nNaN<\/td>\n<\/tr>\n
    5<\/th>\n13<\/td>\n18<\/td>\nNaN<\/td>\nNaN<\/td>\nNaN<\/td>\n<\/tr>\n
    6<\/th>\n14<\/td>\n19<\/td>\nNaN<\/td>\nNaN<\/td>\nNaN<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
    \u307e\u3068\u3081<\/h2>\n
    \u3053\u306e\u8a18\u4e8b\u3067\u306f\u3001DataFrame\u306b\u884c\u65b9\u5411\u306e\u8981\u7d20\u3092\u8ffd\u52a0\u3059\u308bdf.append<\/strong><\/span>\u3092\u7d39\u4ecb\u3057\u307e\u3057\u305f\uff01<\/p>\n
    append\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u3048\u3070\u7528\u610f\u3057\u305f\uff12\u3064\u306eDataFrame\u3092\u7c21\u5358\u306b\u7d50\u5408\u3059\u308b\u4e8b\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n
    \u8981\u70b9<\/p>\n
      \n
    • df.append\u3092\u4f7f\u3048\u3070\uff12\u3064\u306eDataFrame\u3092\u884c\u65b9\u5411\u306b\u7d50\u5408<\/strong><\/span>\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u308b<\/li>\n
    • \u884c\u306eindex\u306f\u5143\u306eDataFrame\u306e\u307e\u307e<\/strong><\/span><\/li>\n
    • \u5217\u6570\u304c\u7570\u306a\u3063\u3066\u3044\u3066\u3082\u7d50\u5408\u3067\u304d\u308b<\/strong><\/span><\/li>\n<\/ul>\n
      \u7c21\u5358\u3060\u3051\u3069\u5f37\u529b\u306aappend\u30e1\u30bd\u30c3\u30c9\u3001list\u3084np.array\u3068\u540c\u69d8\u306b\u983b\u7e41\u306b\u4f7f\u3046\u3053\u3068\u306b\u306a\u308b\u3068\u601d\u3044\u307e\u3059\u3002<\/p>\n
      \u662f\u975e\u4f7f\u3044\u3053\u306a\u3057\u3066\u304f\u3060\u3055\u3044\uff01<\/p>\n","protected":false},"excerpt":{"rendered":"
      \u3053\u3093\u306b\u3061\u306f\uff01\u30a4\u30f3\u30b9\u30c8\u30e9\u30af\u30bf\u30fc\u306e\u30d5\u30af\u30ed\u30a6\u3067\u3059\uff01 \u3053\u306e\u8a18\u4e8b\u3067\u306f\u3001Pandas\u306e\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u306b\u65b0\u3057\u3044\u8981\u7d20\u3092\u884c\u65b9\u5411\u306b\u8ffd\u52a0\u3059\u308bDataFrame\u306eappend\u30e1\u30bd\u30c3\u30c9\u3092\u7d39\u4ecb\u3057\u307e\u3059\u3002 append\u95a2\u6570\u3001Python\u306elist\u3084Nu […]<\/p>\n","protected":false},"author":4,"featured_media":75454,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"swell_btn_cv_data":"","footnotes":""},"categories":[2350],"tags":[2016],"class_list":["post-75442","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-python-study","tag-ai-python-pandas"],"acf":[],"yoast_head":"\nPandas\u306eDataFrame\u306b\u884c\u3092\u8ffd\u52a0\u3059\u308bappend\u30e1\u30bd\u30c3\u30c9\u3092\u30de\u30b9\u30bf\u30fc\u3057\u3088\u3046\uff01 | \u4f8d\u30a8\u30f3\u30b8\u30cb\u30a2\u30d6\u30ed\u30b0<\/title>\n<meta name=\"description\" content=\"\u3053\u306e\u8a18\u4e8b\u3067\u306f\u300c Pandas\u306eDataFrame\u306b\u884c\u3092\u8ffd\u52a0\u3059\u308bappend\u30e1\u30bd\u30c3\u30c9\u3092\u30de\u30b9\u30bf\u30fc\u3057\u3088\u3046\uff01 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