{"id":6950,"date":"2023-07-10T13:33:33","date_gmt":"2023-07-10T04:33:33","guid":{"rendered":"https:\/\/bocek.co.jp\/media\/?p=6950"},"modified":"2023-07-10T13:33:37","modified_gmt":"2023-07-10T04:33:37","slug":"chatgpt%e3%81%aecode-interpreter%e3%82%92%e6%b4%bb%e7%94%a8%e3%81%97%e3%81%a6python%e3%82%b3%e3%83%bc%e3%83%89%e3%82%92%e5%ae%9f%e8%a1%8c%e3%81%99%e3%82%8b","status":"publish","type":"post","link":"https:\/\/taskhub.jp\/magazine\/exercise\/chatgpt\/6950\/","title":{"rendered":"ChatGPT\u306eCode Interpreter\u3092\u6d3b\u7528\u3057\u3066Python\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u3059\u308b"},"content":{"rendered":"\n

\u300cChatGPT Code Interpreter\u306e\u6d3b\u7528\u65b9\u6cd5\u3092\u77e5\u308a\u305f\u3044\u2026\u300d\u300cChatGPT\u3067Python\u306e\u5b9f\u884c\u3067\u304d\u308b\u306e\uff1f\u300d\u305d\u3046\u601d\u3046\u65b9\u3082\u591a\u3044\u306e\u3067\u306f\u306a\u3044\u3067\u3057\u3087\u3046\u304b\u3002<\/p>\n\n\n\n

\u5b9f\u306f\u3001ChatGPT Code Interpreter\u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u3067\u3001\u7c21\u5358\u304b\u3064\u8fc5\u901f\u306b\u30b0\u30e9\u30d5\u3092\u4f5c\u6210\u3059\u308b\u3053\u3068\u304c\u53ef\u80fd\u3067\u3059\u3002<\/p>\n\n\n\n

\u4eca\u56dePROMPTY\u3067\u306f\u3001ChatGPT Code Interpreter\u3092\u7528\u3044\u305f\u30b0\u30e9\u30d5\u4f5c\u6210\u306e\u5b9f\u4f8b\u3092\u307e\u3068\u3081\u3066\u3054\u7d39\u4ecb\u3057\u307e\u3059\u3002<\/p>\n\n\n\n

Code Interpreter\u306e\u6982\u8981\u306b\u3064\u3044\u3066\u77e5\u308a\u305f\u3044\u65b9\u306f\u3001\u3053\u3061\u3089\u306e\u8a18\u4e8b\u3092\u3054\u89a7\u304f\u3060\u3055\u3044\u3002<\/p>\n\n\n\n\n\n\n

\u306f\u3058\u3081\u306b<\/h2>\n\n\n\n

\u3053\u3061\u3089\u306eCode Interpreter\u3067\u306f\u8cea\u554f\u6587\u3067\u6307\u5b9a\u3057\u305f\u51e6\u7406\u5185\u5bb9\u3092Python\u3067\u5b9f\u884c\u3057\u307e\u3059\u3002<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Python\u306e\u30d0\u30fc\u30b8\u30e7\u30f3\u306f\u30013.8.10\u3092\u4f7f\u7528\u3057\u3066\u3044\u307e\u3059\u3002\u5c11\u3057\u53e4\u3044\u30d0\u30fc\u30b8\u30e7\u30f3\u3067\u3059\u304c\u3001ChatGPT\u306e\u5b66\u7fd2\u30c7\u30fc\u30bf\u304c2021\u5e74\u307e\u3067\u3067\u3042\u308b\u3053\u3068\u3092\u8e0f\u307e\u3048\u308b\u3068\u3001\u59a5\u5f53\u306a\u30d0\u30fc\u30b8\u30e7\u30f3\u3067\u3059\u3002<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

ChatGPT Code Interpreter\u3067\u306f\u3001numpy, scipy, pandas, matplotlib, seaborn, sklearn, statsmodels, math, datetime, collections\u306a\u3069\u4e3b\u8981\u306a\u6a19\u6e96\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u63c3\u3048\u3066\u3044\u307e\u3059\u3002<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\u3084\u5b89\u5168\u6027\u306e\u89b3\u70b9\u304b\u3089\u3001\u73fe\u5728\u306e\u5b9f\u884c\u74b0\u5883\u3067\u306f\u3001OpenAI\u306b\u3088\u3063\u3066\u4f7f\u7528\u3067\u304d\u308b\u30e9\u30a4\u30d6\u30e9\u30ea\u304c\u5236\u9650\u3055\u308c\u3066\u3044\u307e\u3059\u3002<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

\u5b9f\u969b\u306bChat GPT Code Interpreter\u3067Python\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u3059\u308b<\/h2>\n\n\n\n

\u2460 \u6f14\u7b97\u3068\u30b0\u30e9\u30d5\u306e\u4f5c\u6210\u3059\u308b\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u3059\u308b<\/h3>\n\n\n\n

Chat GPT Code Interpreter\u306bpy\u30d5\u30a1\u30a4\u30eb\u3092\u8aad\u307f\u3053\u3093\u3067\u5b9f\u884c\u3057\u307e\u3059\u3002\u4eca\u56de\u306f\u4e8c\u6b21\u95a2\u6570\u306e\u30b0\u30e9\u30d5\u306e\u63cf\u753b\u3068\u7a4d\u5206\u306e\u8a08\u7b97\u3092\u884c\u3044\u307e\u3059\u3002<\/p>\n\n\n\n

\u30d7\u30ed\u30f3\u30d7\u30c8\uff1a<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

\u3053\u3061\u3089\u306ePython\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u3057\u307e\u3059\u3002<\/p>\n\n\n\n

import numpy as np\nimport matplotlib.pyplot as plt\nfrom scipy import integrate\n\n# \u95a2\u6570\u306e\u5b9a\u7fa9\ndef f(x):\n    return x**2\n\n# x\u306e\u7bc4\u56f2\nx = np.linspace(1, 5, 1000)\n\n# y\u306e\u8a08\u7b97\ny = f(x)\n\n# \u30b0\u30e9\u30d5\u306e\u63cf\u753b\nplt.plot(x, y, label='y=x^2')\nplt.fill_between(x, y, color='skyblue', alpha=0.5)  # \u9762\u7a4d\u3092\u5857\u308a\u3064\u3076\u3059\nplt.legend()\nplt.show()\n\n# \u9762\u7a4d\uff08\u6570\u5024\u7a4d\u5206\uff09\u306e\u8a08\u7b97\narea, error = integrate.quad(f, 1, 5)\nprint(f\"The area is: {area}\")\n<\/code><\/pre>\n\n\n\n
<\/p>\n\n\n\n
GPT-4\u306e\u51fa\u529b\uff08Code Interpreter\uff09\uff1a<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
\u3053\u306e\u3088\u3046\u306b\u3001\u8aad\u307f\u8fbc\u3093\u3060Python\u30b3\u30fc\u30c9\u306e\u51e6\u7406\u5185\u5bb9\u3092\u89e3\u8aac\u3057\u306a\u304c\u3089\u3001\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u3057\u3066\u304f\u308c\u307e\u3059\u3002<\/p>\n\n\n\n
\u30b0\u30e9\u30d5\u3084\u7a4d\u5206\u5024\u3082\u554f\u984c\u306a\u304f\u51fa\u529b\u3055\u308c\u307e\u3057\u305f\u3002<\/p>\n\n\n\n
\u2461 \u7d20\u6570\u3092\u5224\u5b9a\u3059\u308b\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u3059\u308b<\/h3>\n\n\n\n
\u6307\u5b9a\u3057\u305f\u6570\u5b57\u304c\u7d20\u6570\u3067\u3042\u308b\u304b\u3092\u5224\u5b9a\u3059\u308b\u30b3\u30fc\u30c9\u8aad\u307f\u8fbc\u3093\u3067\u5b9f\u884c\u3057\u307e\u3059.<\/p>\n\n\n\n
\u30d7\u30ed\u30f3\u30d7\u30c8\uff1a<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
\u3053\u3061\u3089\u306ePython\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
def is_prime(n):\n    if n <= 1:\n        return False\n    elif n <= 3:\n        return True\n    elif n % 2 == 0 or n % 3 == 0:\n        return False\n    i = 5\n    while i * i <= n:\n        if n % i == 0 or n % (i + 2) == 0:\n            return False\n        i += 6\n    return True\n\nnum = int(input(\"Enter a number: \"))\nif is_prime(num):\n    print(num, \"is a prime number.\")\nelse:\n    print(num, \"is not a prime number.\")\n<\/code><\/pre>\n\n\n\n
GPT-4\u306e\u51fa\u529b\uff08Code Interpreter\uff09\uff1a<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
Code Interpreter\u3067\u5229\u7528\u3067\u304d\u308b\u3088\u3046\u306b\u30b3\u30fc\u30c9\u3092\u4fee\u6b63\u3057\u3066\u304b\u3089\u3001\u7d20\u6570\u306e\u5224\u5b9a\u3092\u5b9f\u884c\u3057\u3066\u304f\u308c\u307e\u3057\u305f\u3002<\/p>\n\n\n\n
\u2462 \u753b\u50cf\u306e\u8f2a\u90ed\u3092\u691c\u51fa\u3059\u308b\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u3059\u308b<\/h3>\n\n\n\n
\u30a2\u30c3\u30d7\u30ed\u30fc\u30c9\u3057\u305f\u753b\u50cf\u304b\u3089\u7269\u4f53\u306e\u30a8\u30c3\u30b8\uff08\u5883\u754c\uff09\u3092\u691c\u51fa\u3057\u3001\u305d\u306e\u8f2a\u90ed\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u3057\u307e\u3059\u3002\u5177\u4f53\u7684\u306b\u306f\u3001\u753b\u50cf\u5185\u306e\u6025\u6fc0\u306a\u8f1d\u5ea6\u306e\u5909\u5316\u3092\u30a8\u30c3\u30b8\u3068\u307f\u306a\u3059Canny\u6cd5\u3068\u547c\u3070\u308c\u308b\u624b\u6cd5\u3092\u7528\u3044\u3066\u30a8\u30c3\u30b8\uff08\u5883\u754c\uff09\u3092\u691c\u51fa\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
\u30d7\u30ed\u30f3\u30d7\u30c8\uff1a<\/p>\n\n\n\n
\u30a2\u30c3\u30d7\u30ed\u30fc\u30c9\u753b\u50cf\u306b\u5bfe\u3057\u3066\u3001\u4ee5\u4e0b\u306e\u51e6\u7406\u3092\u5b9f\u884c\u3057\u3066\u304f\u3060\u3055\u3044\u3002\nfrom skimage import io, filters, measure\nfrom skimage.color import rgb2gray\nfrom skimage.feature import canny\nfrom skimage.segmentation import clear_border\nfrom skimage.measure import label, regionprops\nimport matplotlib.pyplot as plt\nimport matplotlib.patches as mpatches\n\n# \u753b\u50cf\u3092\u8aad\u307f\u8fbc\u3080\nimage = io.imread('your_image_path')\n\n# \u30b0\u30ec\u30fc\u30b9\u30b1\u30fc\u30eb\u306b\u5909\u63db\u3059\u308b\ngray_image = rgb2gray(image)\n\n# \u30a8\u30c3\u30b8\u691c\u51fa\uff08Canny\u6cd5\uff09\u3092\u884c\u3046\nedges = canny(gray_image)\n\n# \u8f2a\u90ed\u3092\u691c\u51fa\u3059\u308b\ncontours = measure.find_contours(edges, 0.8)\n\n# \u5143\u306e\u753b\u50cf\u306b\u8f2a\u90ed\u3092\u63cf\u753b\u3059\u308b\nfig, ax = plt.subplots()\nax.imshow(edges, cmap=plt.cm.gray)\n\nfor contour in contours:\n    ax.plot(contour[:, 1], contour[:, 0], linewidth=2)\n\nplt.show()<\/code><\/pre>\n\n\n\n
\u30a2\u30c3\u30d7\u30ed\u30fc\u30c9\u3057\u305f\u753b\u50cf\uff1a<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
GPT-4\u306e\u51fa\u529b\uff08Code Interpreter\uff09\uff1a<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
\u554f\u984c\u306a\u304f\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u3057\u3001\u753b\u50cf\u5185\u306e\u7269\u4f53\uff08\u6587\u5b57\u306e\uff09\u8f2a\u90ed\u3092\u691c\u51fa\u3057\u3066\u30d7\u30ed\u30c3\u30c8\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n\n\n\n
\u307e\u3068\u3081<\/h2>\n\n\n\n
\u4eca\u56dePROMPTY\u3067\u306f\u3001ChatGPT\u306eCode Interpreter\u3067\u3044\u304f\u3064\u304b\u306ePython\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u3057\u307e\u3057\u305f\u3002\u3053\u306eCode Interpreter\u3092\u6d3b\u7528\u3059\u308b\u3053\u3068\u3067\u3001Python\u30b3\u30fc\u30c9\u306e\u5b9f\u884c\u3092\u7c21\u5358\u306b\u884c\u3046\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
\u4eca\u56de\u306e\u4f8b\u3092\u53c2\u8003\u306b\u3001\u7686\u3055\u307e\u3082ChatGPT\u306eCode Interpreter\u3092\u4f7f\u3063\u305fPython\u30b3\u30fc\u30c9\u306e\u5b9f\u884c\u3092\u3057\u3066\u307f\u3066\u306f\u3044\u304b\u304c\u3067\u3057\u3087\u3046\u304b\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
\u300cChatGPT Code Interpreter\u306e\u6d3b\u7528\u65b9\u6cd5\u3092\u77e5\u308a\u305f\u3044\u2026\u300d\u300cChatGPT\u3067Python\u306e\u5b9f\u884c\u3067\u304d\u308b\u306e\uff1f\u300d\u305d\u3046\u601d\u3046\u65b9\u3082\u591a\u3044\u306e\u3067\u306f\u306a\u3044\u3067\u3057\u3087\u3046\u304b\u3002 \u5b9f\u306f\u3001ChatGPT Code Int […]<\/p>\n","protected":false},"author":9,"featured_media":7050,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_eb_attr":""},"categories":[46],"tags":[],"_links":{"self":[{"href":"https:\/\/taskhub.jp\/magazine\/wp-json\/wp\/v2\/posts\/6950"}],"collection":[{"href":"https:\/\/taskhub.jp\/magazine\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/taskhub.jp\/magazine\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/taskhub.jp\/magazine\/wp-json\/wp\/v2\/users\/9"}],"replies":[{"embeddable":true,"href":"https:\/\/taskhub.jp\/magazine\/wp-json\/wp\/v2\/comments?post=6950"}],"version-history":[{"count":5,"href":"https:\/\/taskhub.jp\/magazine\/wp-json\/wp\/v2\/posts\/6950\/revisions"}],"predecessor-version":[{"id":7045,"href":"https:\/\/taskhub.jp\/magazine\/wp-json\/wp\/v2\/posts\/6950\/revisions\/7045"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/taskhub.jp\/magazine\/wp-json\/wp\/v2\/media\/7050"}],"wp:attachment":[{"href":"https:\/\/taskhub.jp\/magazine\/wp-json\/wp\/v2\/media?parent=6950"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/taskhub.jp\/magazine\/wp-json\/wp\/v2\/categories?post=6950"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/taskhub.jp\/magazine\/wp-json\/wp\/v2\/tags?post=6950"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}