笔记本验证失败:不允许附加属性(“id”是意外的):

时间:2021-04-09 05:46:03

标签: python jupyter-notebook

打开我的笔记本时出现以下验证错误:

{ “元数据”:{ “信任”:真实 }, "id": "比较导入", "cell_type": "代码", "source": "import numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nimport nltk\nimport re\nimport gensim \nfrom gensim.utils import simple_preprocess\nfrom gensim.models.word2vec import Word2Vec\nfrom nltk.stem.porter import PorterStemmer\nfrom nltk.corpus import stopwords\nfrom sklearn.decomposition import PCA,TruncatedSVD\nfrom sklearn.manifold import TSNE\nfrom sklearn.model_selection import train_test_split\nfrom sklearnisticRelinear_model from wordpress\nfrom sklearn.decomposition import PCA\nfrom导入 WordCloud、STOPWORDS、ImageColorGenerator\n", "execution_count": 10, “输出”:[] }

2 个答案:

答案 0 :(得分:0)

你的笔记本只是一堆导入你可以很容易地重新创建这次我为你做的:

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Untitled5.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "CRAF2wibMCRq"
      },
      "source": [
        "import numpy as np \n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import nltk\n",
        "import re\n",
        "import gensim \n",
        "from gensim.utils import simple_preprocess\n",
        "from gensim.models.word2vec import Word2Vec\n",
        "from nltk.stem.porter import PorterStemmer\n",
        "from nltk.corpus import stopwords\n",
        "from sklearn.decomposition import PCA,TruncatedSVD\n",
        "from sklearn.manifold import TSNE\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.linear_model import LogisticRegression \n",
        "from wordcloud import WordCloud, STOPWORDS, ImageColorGenerator"
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}

答案 1 :(得分:0)

我通过复制单元格的内容而不是单元格本身来解决上述问题。我一直在使用多个笔记本,出现了一些应付粘贴问题