{"id":50788,"date":"2022-03-23T00:00:00","date_gmt":"2022-03-23T07:00:00","guid":{"rendered":"https:\/\/griddb-linux-hte8hndjf8cka8ht.westus-01.azurewebsites.net\/%e6%9c%aa%e5%88%86%e9%a1%9e\/modelling-sp-500-index-price-based-on-u-s-economic-indicators-using-python-and-griddb\/"},"modified":"2025-11-14T07:55:15","modified_gmt":"2025-11-14T15:55:15","slug":"modelling-sp-500-index-price-based-on-u-s-economic-indicators-using-python-and-griddb","status":"publish","type":"post","link":"https:\/\/griddb.net\/ja\/%e6%9c%aa%e5%88%86%e9%a1%9e\/modelling-sp-500-index-price-based-on-u-s-economic-indicators-using-python-and-griddb\/","title":{"rendered":"Python\u3068GridDB\u3092\u7528\u3044\u305f\u7c73\u56fd\u7d4c\u6e08\u6307\u6a19\u306b\u57fa\u3065\u304fS&P500\u6307\u6570\u4fa1\u683c\u306e\u30e2\u30c7\u30eb\u5316"},"content":{"rendered":"

\u7d4c\u6e08\u6307\u6a19\u3068\u5e83\u304f\u77e5\u3089\u308c\u305f\u7d71\u8a08\u7684\u624b\u6cd5\u3092\u4f7f\u3063\u3066\u682a\u4fa1\u3092\u4e88\u6e2c\u3059\u308b\u6570\u591a\u304f\u306e\u7814\u7a76\u304c\u3053\u308c\u307e\u3067\u306b\u884c\u308f\u308c\u3066\u304d\u307e\u3057\u305f\u3002\u305d\u3057\u30662010\u5e74\u4ee5\u964d\u306e\u30b3\u30f3\u30d4\u30e5\u30fc\u30bf\u306e\u6027\u80fd\u306e\u4e0a\u6607\u306b\u3088\u308a\u3001\u6a5f\u68b0\u5b66\u7fd2\u306b\u3088\u308b\u65b0\u3057\u3044\u624b\u6cd5\u304c\u958b\u767a\u3055\u308c\u308b\u3053\u3068\u306b\u306a\u308a\u307e\u3057\u305f\u3002\u305d\u308c\u3089\u306e\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u304c\u3001\u69d8\u3005\u306a\u6570\u5b66\u7684\u30fb\u7d71\u8a08\u7684\u624b\u6cd5\u3092\u7528\u3044\u3066\u682a\u5f0f\u5e02\u5834\u3092\u4e88\u6e2c\u3067\u304d\u308b\u304b\u3069\u3046\u304b\u3092\u767a\u898b\u3059\u308b\u3053\u3068\u306f\u3001\u8208\u5473\u6df1\u3044\u3053\u3068\u3067\u3059\u3002\u672c\u30d6\u30ed\u30b0\u306e\u76ee\u7684\u306f\u3001GridDB\u3092\u4f7f\u3063\u3066\u30c7\u30fc\u30bf\u3092\u62bd\u51fa\u3057\u3001\u6b21\u306b\u7d71\u8a08\u7684\u691c\u5b9a\u3092\u884c\u3044\u3001\u6700\u5f8c\u306b\u6a5f\u68b0\u5b66\u7fd2\u30e2\u30c7\u30eb\u3092\u69cb\u7bc9\u3057\u3066\u3001\u7c73\u56fd\u306e\u7d4c\u6e08\u6307\u6a19\u306b\u57fa\u3065\u304fS&P500\u6307\u6570\u306e\u6708\u6b21\u4fa1\u683c\u3092\u30e2\u30c7\u30eb\u5316\u3059\u308b\u3053\u3068\u3067\u3059\u3002<\/p>\n

\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u306e\u6982\u8981\u306f\u4ee5\u4e0b\u306e\u901a\u308a\u3067\u3059\u3002<\/p>\n

    \n
  1. \u524d\u63d0\u6761\u4ef6\u3068\u74b0\u5883\u8a2d\u5b9a<\/li>\n
  2. \u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u6982\u8981<\/li>\n
  3. \u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u306e\u30a4\u30f3\u30dd\u30fc\u30c8<\/li>\n
  4. \u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u8aad\u307f\u8fbc\u307f<\/li>\n
  5. \u63a2\u7d22\u7684\u30c7\u30fc\u30bf\u89e3\u6790\u3068\u7279\u5fb4\u91cf\u306e\u9078\u629e<\/li>\n
  6. \u6a5f\u68b0\u5b66\u7fd2\u30e2\u30c7\u30eb\u306e\u69cb\u7bc9\u3068\u5b66\u7fd2<\/li>\n
  7. \u307e\u3068\u3081<\/li>\n<\/ol>\n

    \u524d\u63d0\u6761\u4ef6\u3068\u74b0\u5883\u8a2d\u5b9a<\/h1>\n

    \u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u306f\u3001Windows \u30aa\u30da\u30ec\u30fc\u30c6\u30a3\u30f3\u30b0\u30b7\u30b9\u30c6\u30e0\u4e0a\u306e Anaconda Navigator (Python \u30d0\u30fc\u30b8\u30e7\u30f3 – 3.8.3) \u3067\u5b9f\u65bd\u3055\u308c\u307e\u3059\u3002\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3092\u7d9a\u3051\u308b\u524d\u306b\u3001\u4ee5\u4e0b\u306e\u30d1\u30c3\u30b1\u30fc\u30b8\u304c\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3055\u308c\u3066\u3044\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n

      \n
    1. \n

      Pandas<\/p>\n<\/li>\n

    2. \n

      NumPy<\/p>\n<\/li>\n

    3. \n

      Scikit-learn<\/p>\n<\/li>\n

    4. \n

      Matplotlib<\/p>\n<\/li>\n

    5. \n

      Statsmodels<\/p>\n<\/li>\n

    6. \n

      griddb_python<\/p>\n<\/li>\n<\/ol>\n

      \u3053\u308c\u3089\u306e\u30d1\u30c3\u30b1\u30fc\u30b8\u3092Conda\u306e\u4eee\u60f3\u74b0\u5883\u306b\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3059\u308b\u306b\u306f\u3001conda install package-name<\/code>\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002\u30bf\u30fc\u30df\u30ca\u30eb\u3084\u30b3\u30de\u30f3\u30c9\u30d7\u30ed\u30f3\u30d7\u30c8\u304b\u3089\u76f4\u63a5Python\u3092\u4f7f\u7528\u3059\u308b\u5834\u5408\u306f\u3001 pip install package-name<\/code> \u3067\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3067\u304d\u307e\u3059\u3002<\/p>\n

      GridDB\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb<\/h3>\n

      \u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u30ed\u30fc\u30c9\u3059\u308b\u969b\u3001\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001GridDB \u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u3068 Pandas \u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u306e 2 \u3064\u3092\u53d6\u308a\u4e0a\u3052\u307e\u3059\u3002Python\u3092\u4f7f\u7528\u3057\u3066GridDB\u306b\u30a2\u30af\u30bb\u30b9\u3059\u308b\u305f\u3081\u306b\u306f\u3001\u4ee5\u4e0b\u306e\u30d1\u30c3\u30b1\u30fc\u30b8\u3082\u4e88\u3081\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u3066\u304a\u304f\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n

        \n
      1. GridDB C-client<\/a><\/li>\n
      2. SWIG (Simplified Wrapper and Interface Generator)<\/li>\n
      3. GridDB Python Client<\/a><\/li>\n<\/ol>\n

        1. \u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u6982\u8981<\/h1>\n

        \u4e00\u822c\u7684\u306b\u682a\u5f0f\u5e02\u5834\u306e\u30ea\u30bf\u30fc\u30f3\u3001\u7279\u306bS&P500\u306b\u6700\u3082\u5927\u304d\u306a\u5f71\u97ff\u3092\u4e0e\u3048\u308b\u3068\u8a8d\u8b58\u3055\u308c\u3066\u3044\u308b\u6307\u6a19\u306f\u3001\u4ee5\u4e0b\u306e\u30ab\u30c6\u30b4\u30ea\u30fc\u306b\u5206\u985e\u3055\u308c\u307e\u3059\uff1a\u4e00\u822c\u7684\u306a\u30de\u30af\u30ed\u7d4c\u6e08\u6307\u6a19\u3001\u52b4\u50cd\u5e02\u5834\u6307\u6a19\uff08\u5931\u696d\u7387\u3084\u96c7\u7528\u7d71\u8a08\uff09\u3001\u4e0d\u52d5\u7523\u6307\u6a19\u3001\u4fe1\u7528\u5e02\u5834\u6307\u6a19\u3001\u91d1\u878d\u4f9b\u7d66\u6307\u6a19\u3001\u6d88\u8cbb\u8005\uff08\u5bb6\u8a08\uff09\u91d1\u878d\u884c\u52d5\u6307\u6a19\u3001\u5546\u54c1\u5e02\u5834\u6307\u6a19\u306a\u3069\u3067\u3059\u3002<\/p>\n

        \u3053\u306e\u30d6\u30ed\u30b0\u3067\u306f\u3001S&P500\u6307\u6570\u306e\u7d42\u5024\u3092\u30e2\u30c7\u30eb\u5316\u3057\u307e\u3057\u305f\u3002\u3053\u3053\u3067\u306f\u3001Google Colab\u74b0\u5883\u3067\u3001\u591a\u304f\u306e\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u542b\u3080Python\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u8a00\u8a9e\u3092\u4f7f\u7528\u3057\u3066\u3044\u307e\u3059\u3002\u5206\u6790\u671f\u9593\u306f1970-01-01 \/ 2018-04-01\u3067\u3001S&P500\u6307\u6570\u7d42\u5024\u3068\u7c73\u56fd\u7d4c\u6e08\u6307\u6a19\u30c7\u30fc\u30bf\u306e\u983b\u5ea6\u306f\u3044\u305a\u308c\u3082\u6708\u6b21\u3067\u3059\u3002<\/p>\n

        \u7279\u5fb4\u306e\u8aac\u660e\uff1a<\/p>\n

        1) SP500<\/code> – \u5404\u6708\u306eS&P500\u306e\u4fa1\u683c (\u5358\u4f4d\u306f\u7c73\u30c9\u30eb)<\/p>\n

        2) INTDSRUSM193N<\/code> – \u7c73\u56fd\u306e\u91d1\u5229\u3001\u5272\u5f15\u7387 (\u5358\u4f4d: \u30d1\u30fc\u30bb\u30f3\u30c8\/\u5e74)<\/p>\n

        3) BUSLOANS<\/code> – \u5546\u5de5\u696d\u30ed\u30fc\u30f3\u3001\u5168\u5546\u696d\u9280\u884c (\u5358\u4f4d: 10\u5104\u7c73\u30c9\u30eb)<\/p>\n

        4) MPRIME<\/code> – \u9280\u884c\u30d7\u30e9\u30a4\u30e0\u30ed\u30fc\u30f3\u91d1\u5229 (\u5358\u4f4d: \u30d1\u30fc\u30bb\u30f3\u30c8)<\/p>\n

        5) FEDFUNDS<\/code> – \u30d5\u30a7\u30c7\u30e9\u30eb\u30d5\u30a1\u30f3\u30c9\u5b9f\u52b9\u91d1\u5229 (\u30d5\u30a7\u30c7\u30e9\u30eb\u30d5\u30a1\u30f3\u30c9\u91d1\u5229\u3068\u306f\u3001\u9810\u91d1\u53d6\u6271\u6a5f\u95a2\u304c\u30d5\u30a7\u30c7\u30e9\u30eb\u30d5\u30a1\u30f3\u30c9\u3092\u591c\u9593\u306b\u53d6\u5f15\u3059\u308b\u969b\u306e\u91d1\u5229\u306e\u3053\u3068\u3002) (\u5358\u4f4d: \u30d1\u30fc\u30bb\u30f3\u30c8)<\/p>\n

        6) CURRCIR<\/code> – \u6d41\u901a\u901a\u8ca8 (\u5358\u4f4d: \u5104\u30c9\u30eb)<\/p>\n

        7) PSAVERT<\/code> – \u500b\u4eba\u8caf\u84c4\u7387 (\u53ef\u51e6\u5206\u500b\u4eba\u6240\u5f97(DPI)\u306b\u5bfe\u3059\u308b\u500b\u4eba\u8caf\u84c4\u306e\u5272\u5408\u3067\u3001\u3057\u3070\u3057\u3070\u300c\u500b\u4eba\u8caf\u84c4\u7387\u300d\u3068\u547c\u3070\u308c\u308b)(\u5358\u4f4d:\u767e\u5206\u7387)<\/p>\n

        8) PERMIT<\/code> – \u8a31\u53ef\u767a\u884c\u5730\u306b\u304a\u3051\u308b\u6c11\u9593\u65b0\u7bc9\u4f4f\u5b85\u8a31\u53ef\u6238\u6570: \u7dcf\u6238\u6570 (\u5358\u4f4d: \u5104\u30c9\u30eb)<\/p>\n

        9) INDPRO<\/code> – \u9271\u5de5\u696d\u751f\u7523\u3002\u5de5\u696d\u751f\u7523\u6307\u6570\uff08INDPRO\uff09\u306f\u3001\u7c73\u56fd\u306e\u88fd\u9020\u696d\u3001\u9271\u696d\u3001\u96fb\u6c17\u30fb\u30ac\u30b9\u4e8b\u696d\u8005\u306b\u7acb\u5730\u3059\u308b\u3059\u3079\u3066\u306e\u65bd\u8a2d\u306e\u5b9f\u8cea\u751f\u7523\u9ad8\u3092\u6e2c\u5b9a\u3059\u308b\u7d4c\u6e08\u6307\u6a19\uff09\uff08\u5358\u4f4d\uff1a\u6307\u65702017=100<\/p>\n

        10) PMSAVE<\/code> – \u500b\u4eba\u8caf\u84c4 (\u5358\u4f4d: \u5104\u30c9\u30eb)<\/p>\n

        11) DAUTOSAAR<\/code> – \u81ea\u52d5\u8eca\u5c0f\u58f2\u8ca9\u58f2\u53f0\u6570: \u56fd\u5185\u81ea\u52d5\u8eca\u8ca9\u58f2\u53f0\u6570 (\u5358\u4f4d: \u767e\u4e07\u53f0)<\/p>\n

        12) UNEMPLOY<\/code> – \u5931\u696d\u6c34\u6e96 (\u5358\u4f4d: \u5343\u4eba)<\/p>\n

        13) CPIAUCSL<\/code> – \u3059\u3079\u3066\u306e\u90fd\u5e02\u6d88\u8cbb\u8005\u5411\u3051\u6d88\u8cbb\u8005\u7269\u4fa1\u6307\u6570\u3002\u5168\u7c73\u90fd\u5e02\u5e73\u5747\u306e\u5168\u54c1\u76ee\uff08\u5358\u4f4d\uff1a\u6307\u6570 1982-1984=100\uff09\u3002<\/p>\n

        \u3053\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306f\u4e00\u822c\u306b\u516c\u958b\u3055\u308c\u3066\u304a\u308a\u3001finance.yahoo.com<\/code> \u3068 fred.stlouisfed.org<\/code> \u306e\u30a6\u30a7\u30d6\u30b5\u30a4\u30c8\u304b\u3089\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u5f97\u3089\u308c\u305f\u30c7\u30fc\u30bf\u306f1\u3064\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u307e\u3068\u3081\u3089\u308c\u3001\u6b20\u640d\u5024\u306b\u3064\u3044\u3066\u3082\u30c1\u30a7\u30c3\u30af\u6e08\u307f\u3067\u3059\u3002<\/p>\n

        2. \u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u306e\u30a4\u30f3\u30dd\u30fc\u30c8<\/h1>\n
        \n
        import griddb_python as griddb\n\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport datetime\n\nimport statsmodels.api as sm\nfrom statsmodels.stats.outliers_influence import variance_inflation_factor\n\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.linear_model import LinearRegression\nfrom sklearn.ensemble import RandomForestRegressor\nfrom sklearn.metrics import r2_score\nfrom sklearn.metrics import mean_squared_error\n\nimport warnings\nwarnings.filterwarnings('ignore')\n%matplotlib inline<\/code><\/pre>\n<\/div>\n
        3. \u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u8aad\u307f\u8fbc\u307f<\/h1>\n
        \u305d\u308c\u3067\u306f\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306b\u8aad\u307f\u8fbc\u3093\u3067\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n
        3.a GridDB\u306e\u5229\u7528<\/h2>\n
        \u6771\u829dGridDB\u2122\u306f\u3001IoT\u3084\u30d3\u30c3\u30b0\u30c7\u30fc\u30bf\u306b\u6700\u9069\u306a\u62e1\u5f35\u6027\u306e\u9ad8\u3044NoSQL\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u3067\u3059\u3002GridDB\u306e\u7406\u5ff5\u306e\u6839\u5e79\u306f\u3001IoT\u306b\u6700\u9069\u5316\u3055\u308c\u305f\u6c4e\u7528\u6027\u306e\u9ad8\u3044\u30c7\u30fc\u30bf\u30b9\u30c8\u30a2\u306e\u63d0\u4f9b\u3001\u9ad8\u3044\u30b9\u30b1\u30fc\u30e9\u30d3\u30ea\u30c6\u30a3\u3001\u9ad8\u6027\u80fd\u306a\u30c1\u30e5\u30fc\u30cb\u30f3\u30b0\u3001\u9ad8\u3044\u4fe1\u983c\u6027\u306e\u78ba\u4fdd\u306b\u3042\u308a\u307e\u3059\u3002<\/p>\n
        \u5927\u91cf\u306e\u30c7\u30fc\u30bf\u3092\u4fdd\u5b58\u3059\u308b\u305f\u3081\u306b\u3001CSV\u30d5\u30a1\u30a4\u30eb\u306f\u9762\u5012\u3067\u3059\u3002GridDB\u306f\u3001\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u3067\u62e1\u5f35\u6027\u306e\u9ad8\u3044\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u3067\u3042\u308b\u305f\u3081\u3001\u5b8c\u74a7\u306a\u4ee3\u66ff\u54c1\u3068\u3057\u3066\u6a5f\u80fd\u3057\u307e\u3059\u3002GridDB\u306f\u3001\u30b9\u30b1\u30fc\u30e9\u30d6\u30eb\u3067\u30a4\u30f3\u30e1\u30e2\u30ea\u306aNoSQL\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u3067\u3042\u308a\u3001\u5927\u91cf\u306e\u30c7\u30fc\u30bf\u3092\u7c21\u5358\u306b\u4fdd\u5b58\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002GridDB\u3092\u521d\u3081\u3066\u4f7f\u3046\u5834\u5408\u306f\u3001\u3053\u3061\u3089\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb<\/a>\u304c\u53c2\u8003\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n
        \u3059\u3067\u306b\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u306e\u30bb\u30c3\u30c8\u30a2\u30c3\u30d7\u304c\u5b8c\u4e86\u3057\u3066\u3044\u308b\u3068\u4eee\u5b9a\u3057\u3066\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u30ed\u30fc\u30c9\u3059\u308b\u305f\u3081\u306eSQL\u30af\u30a8\u30ea\u3092python\u3067\u8a18\u8ff0\u3057\u3066\u3044\u304d\u307e\u3059\u3002<\/p>\n
        \n
        sql_statement = ('SELECT * FROM us_economic_data')\ndataset = pd.read_sql_query(sql_statement, cont)<\/code><\/pre>\n<\/div>\n
        \u5909\u6570 cont<\/code> \u306b\u306f\u3001\u30c7\u30fc\u30bf\u304c\u683c\u7d0d\u3055\u308c\u3066\u3044\u308b\u30b3\u30f3\u30c6\u30ca\u60c5\u5831\u304c\u683c\u7d0d\u3055\u308c\u3066\u3044\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002credit_card_dataset` \u3092\u30b3\u30f3\u30c6\u30ca\u306e\u540d\u524d\u306b\u7f6e\u304d\u63db\u3048\u3066\u304f\u3060\u3055\u3044\u3002\u8a73\u7d30\u306f\u3001\u3053\u3061\u3089\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30ebGridDB\u3078\u306e\u8aad\u307f\u66f8\u304d<\/a>\u3092\u53c2\u7167\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n
        IoT\u3084\u30d3\u30c3\u30b0\u30c7\u30fc\u30bf\u306e\u30e6\u30fc\u30b9\u30b1\u30fc\u30b9\u306b\u95a2\u3057\u3066\u8a00\u3048\u3070\u3001GridDB\u306f\u30ea\u30ec\u30fc\u30b7\u30e7\u30ca\u30eb\u3084NoSQL\u306e\u9818\u57df\u306e\u4ed6\u306e\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u306e\u4e2d\u3067\u660e\u3089\u304b\u306b\u969b\u7acb\u3063\u3066\u3044\u307e\u3059\u3002\u5168\u4f53\u3068\u3057\u3066\u3001GridDB\u306f\u9ad8\u53ef\u7528\u6027\u3068\u30c7\u30fc\u30bf\u4fdd\u6301\u3092\u5fc5\u8981\u3068\u3059\u308b\u30df\u30c3\u30b7\u30e7\u30f3\u30af\u30ea\u30c6\u30a3\u30ab\u30eb\u306a\u30a2\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3\u306e\u305f\u3081\u306b\u3001\u8907\u6570\u306e\u4fe1\u983c\u6027\u6a5f\u80fd\u3092\u63d0\u4f9b\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n
        3.b Pandas\u306e\u5229\u7528<\/h2>\n
        \u307e\u305f\u3001Pandas\u306e read_csv<\/code> \u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u30c7\u30fc\u30bf\u3092\u8aad\u307f\u8fbc\u3080\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002\u4e0a\u8a18\u306e\u3069\u3061\u3089\u306e\u65b9\u6cd5\u3092\u4f7f\u3063\u3066\u3082\u3001\u30c7\u30fc\u30bf\u306fpandas\u306edataframe\u306e\u5f62\u3067\u8aad\u307f\u8fbc\u307e\u308c\u308b\u305f\u3081\u3001\u540c\u3058\u51fa\u529b\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n
        \n
        us_economic_data = pd.read_csv('us_economic_data.csv')<\/code><\/pre>\n<\/div>\n
        4. \u63a2\u7d22\u7684\u30c7\u30fc\u30bf\u89e3\u6790\u3068\u7279\u5fb4\u91cf\u306e\u9078\u629e<\/h1>\n
        \u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u304c\u8aad\u307f\u8fbc\u307e\u308c\u305f\u3089\u3001\u4eca\u5ea6\u306f\u305d\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u63a2\u7d22\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002head()\u95a2\u6570\u3092\u4f7f\u3063\u3066\u3001\u3053\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u6700\u521d\u306e10\u884c\u3092\u8868\u793a\u3057\u3066\u307f\u307e\u3059\u3002<\/p>\n
        \n
        us_economic_data.head()<\/code><\/pre>\n<\/div>\n
        \n