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‎src/.ipynb_checkpoints/Untitled-checkpoint.ipynb‎

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"ename": "FileNotFoundError",
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"evalue": "[Errno 2] No such file or directory: './data/movietweetings/movies.dat'",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[1;31mFileNotFoundError\u001b[0m Traceback (most recent call last)",
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"\u001b[1;32m<ipython-input-1-7efaf53b7077>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m movies = pd.read_csv('./data/movietweetings/movies.dat', delimiter='::',\n\u001b[1;32m----> 5\u001b[1;33m engine='python', header=None, names=['Movie ID', 'Movie Title', 'Genre'])\n\u001b[0m\u001b[0;32m 6\u001b[0m users = pd.read_csv('./data/movietweetings/users.dat', delimiter='::',\n\u001b[0;32m 7\u001b[0m engine='python', header=None, names=['User ID', 'Twitter ID'])\n",
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"\u001b[1;32mD:\\ProgramData\\conda3.05\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36mparser_f\u001b[1;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, escapechar, comment, encoding, dialect, tupleize_cols, error_bad_lines, warn_bad_lines, skipfooter, skip_footer, doublequote, delim_whitespace, as_recarray, compact_ints, use_unsigned, low_memory, buffer_lines, memory_map, float_precision)\u001b[0m\n\u001b[0;32m 653\u001b[0m skip_blank_lines=skip_blank_lines)\n\u001b[0;32m 654\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 655\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 656\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 657\u001b[0m \u001b[0mparser_f\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
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"\u001b[1;32mD:\\ProgramData\\conda3.05\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36m_read\u001b[1;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[0;32m 403\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 404\u001b[0m \u001b[1;31m# Create the parser.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 405\u001b[1;33m \u001b[0mparser\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 406\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 407\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mchunksize\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0miterator\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
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"\u001b[1;32mD:\\ProgramData\\conda3.05\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[0;32m 762\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'has_index_names'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mkwds\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'has_index_names'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 763\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 764\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 765\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 766\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
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"\u001b[1;32mD:\\ProgramData\\conda3.05\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36m_make_engine\u001b[1;34m(self, engine)\u001b[0m\n\u001b[0;32m 993\u001b[0m ' \"c\", \"python\", or' ' \"python-fwf\")'.format(\n\u001b[0;32m 994\u001b[0m engine=engine))\n\u001b[1;32m--> 995\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_engine\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mklass\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 996\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 997\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_failover_to_python\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
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"\u001b[1;32mD:\\ProgramData\\conda3.05\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, f, **kwds)\u001b[0m\n\u001b[0;32m 1983\u001b[0m f, handles = _get_handle(f, mode, encoding=self.encoding,\n\u001b[0;32m 1984\u001b[0m \u001b[0mcompression\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcompression\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1985\u001b[1;33m memory_map=self.memory_map)\n\u001b[0m\u001b[0;32m 1986\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mhandles\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mextend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mhandles\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1987\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
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"\u001b[1;32mD:\\ProgramData\\conda3.05\\lib\\site-packages\\pandas\\io\\common.py\u001b[0m in \u001b[0;36m_get_handle\u001b[1;34m(path_or_buf, mode, encoding, compression, memory_map, is_text)\u001b[0m\n\u001b[0;32m 383\u001b[0m \u001b[1;32melif\u001b[0m \u001b[0mis_text\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 384\u001b[0m \u001b[1;31m# Python 3 and no explicit encoding\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 385\u001b[1;33m \u001b[0mf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpath_or_buf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmode\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'replace'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 386\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 387\u001b[0m \u001b[1;31m# Python 3 and binary mode\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
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"\u001b[1;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: './data/movietweetings/movies.dat'"
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]
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}
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],
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"source": [
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"import pandas as pd\n",
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"import numpy as np\n",
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"\n",
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"movies = pd.read_csv('./data/movietweetings/movies.dat', delimiter='::',\n",
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" engine='python', header=None, names=['Movie ID', 'Movie Title', 'Genre'])\n",
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"users = pd.read_csv('./data/movietweetings/users.dat', delimiter='::',\n",
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" engine='python', header=None, names=['User ID', 'Twitter ID'])\n",
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"ratings = pd.read_csv('./data/movietweetings/ratings.dat', delimiter='::', engine='python',\n",
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" header=None, names=['User ID', 'Movie ID', 'Rating', 'Rating Timestamp'])\n",
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"\n",
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"print(movies.head(10))\n",
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"mask = movies.Genre.str.contains('comedy', case=False, na=False)\n",
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"print(mask.head(10))\n",
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"comedy = movies[mask]\n",
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"comedy_ids = comedy['Movie ID']\n",
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"print(comedy_ids.head(10))\n",
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"\n",
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"combine = ratings.join(comedy, on='Movie ID', rsuffix='right')\n",
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"print(combine.head(50))\n",
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"result = combine[combine['Movie IDright'] != np.NaN]\n",
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"print(result)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎src/Descend.py‎

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from collections.abc import Iterator
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#编写一个迭代器，通过循环语句，实现对某个正整数的依次递减1，直到0.
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class Descend(Iterator):
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def __init__(self,N):
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self.N=N
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self.a=0
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def __next__(self):
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while self.a<self.N:
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self.N-=1
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return self.N
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raise StopIteration
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descend_iter=Descend(10)
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try:
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for i in descend_iter:
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print(i)
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except StopIteration as e:
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print('迭代结束')
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‎src/Untitled.ipynb‎

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"ename": "FileNotFoundError",
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"evalue": "[Errno 2] No such file or directory: './data/movietweetings/movies.dat'",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[1;31mFileNotFoundError\u001b[0m Traceback (most recent call last)",
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"\u001b[1;32m<ipython-input-1-7efaf53b7077>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m movies = pd.read_csv('./data/movietweetings/movies.dat', delimiter='::',\n\u001b[1;32m----> 5\u001b[1;33m engine='python', header=None, names=['Movie ID', 'Movie Title', 'Genre'])\n\u001b[0m\u001b[0;32m 6\u001b[0m users = pd.read_csv('./data/movietweetings/users.dat', delimiter='::',\n\u001b[0;32m 7\u001b[0m engine='python', header=None, names=['User ID', 'Twitter ID'])\n",
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"\u001b[1;32mD:\\ProgramData\\conda3.05\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36mparser_f\u001b[1;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, escapechar, comment, encoding, dialect, tupleize_cols, error_bad_lines, warn_bad_lines, skipfooter, skip_footer, doublequote, delim_whitespace, as_recarray, compact_ints, use_unsigned, low_memory, buffer_lines, memory_map, float_precision)\u001b[0m\n\u001b[0;32m 653\u001b[0m skip_blank_lines=skip_blank_lines)\n\u001b[0;32m 654\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 655\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 656\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 657\u001b[0m \u001b[0mparser_f\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
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"\u001b[1;32mD:\\ProgramData\\conda3.05\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36m_read\u001b[1;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[0;32m 403\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 404\u001b[0m \u001b[1;31m# Create the parser.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 405\u001b[1;33m \u001b[0mparser\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 406\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 407\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mchunksize\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0miterator\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
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"\u001b[1;32mD:\\ProgramData\\conda3.05\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[0;32m 762\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'has_index_names'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mkwds\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'has_index_names'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 763\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 764\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 765\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 766\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
19+
"\u001b[1;32mD:\\ProgramData\\conda3.05\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36m_make_engine\u001b[1;34m(self, engine)\u001b[0m\n\u001b[0;32m 993\u001b[0m ' \"c\", \"python\", or' ' \"python-fwf\")'.format(\n\u001b[0;32m 994\u001b[0m engine=engine))\n\u001b[1;32m--> 995\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_engine\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mklass\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 996\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 997\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_failover_to_python\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
20+
"\u001b[1;32mD:\\ProgramData\\conda3.05\\lib\\site-packages\\pandas\\io\\parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, f, **kwds)\u001b[0m\n\u001b[0;32m 1983\u001b[0m f, handles = _get_handle(f, mode, encoding=self.encoding,\n\u001b[0;32m 1984\u001b[0m \u001b[0mcompression\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcompression\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1985\u001b[1;33m memory_map=self.memory_map)\n\u001b[0m\u001b[0;32m 1986\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mhandles\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mextend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mhandles\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1987\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
21+
"\u001b[1;32mD:\\ProgramData\\conda3.05\\lib\\site-packages\\pandas\\io\\common.py\u001b[0m in \u001b[0;36m_get_handle\u001b[1;34m(path_or_buf, mode, encoding, compression, memory_map, is_text)\u001b[0m\n\u001b[0;32m 383\u001b[0m \u001b[1;32melif\u001b[0m \u001b[0mis_text\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 384\u001b[0m \u001b[1;31m# Python 3 and no explicit encoding\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 385\u001b[1;33m \u001b[0mf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpath_or_buf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmode\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'replace'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 386\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 387\u001b[0m \u001b[1;31m# Python 3 and binary mode\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
22+
"\u001b[1;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: './data/movietweetings/movies.dat'"
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]
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}
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],
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"source": [
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"import pandas as pd\n",
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"import numpy as np\n",
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"\n",
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"movies = pd.read_csv('./data/movietweetings/movies.dat', delimiter='::',\n",
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" engine='python', header=None, names=['Movie ID', 'Movie Title', 'Genre'])\n",
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"users = pd.read_csv('./data/movietweetings/users.dat', delimiter='::',\n",
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" engine='python', header=None, names=['User ID', 'Twitter ID'])\n",
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"ratings = pd.read_csv('./data/movietweetings/ratings.dat', delimiter='::', engine='python',\n",
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" header=None, names=['User ID', 'Movie ID', 'Rating', 'Rating Timestamp'])\n",
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"\n",
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"print(movies.head(10))\n",
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"mask = movies.Genre.str.contains('comedy', case=False, na=False)\n",
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"print(mask.head(10))\n",
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"comedy = movies[mask]\n",
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"comedy_ids = comedy['Movie ID']\n",
42+
"print(comedy_ids.head(10))\n",
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"\n",
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"combine = ratings.join(comedy, on='Movie ID', rsuffix='right')\n",
45+
"print(combine.head(50))\n",
46+
"result = combine[combine['Movie IDright'] != np.NaN]\n",
47+
"print(result)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎src/add_or_sub.py‎

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from operator import (add, sub)
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3+
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def add_or_sub(a, b, oper):
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return (add if oper == '+' else sub)(a, b)
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add_or_sub(1, 2, '-') # -1

‎src/anagram.py‎

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from collections import Counter
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# 检查两个字符串是否 相同字母异序词，简称：互为变位词
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def anagram(str1, str2):
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return Counter(str1) == Counter(str2)
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anagram('eleven+two', 'twelve+one') # True 这是一对神器的变位词
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anagram('eleven', 'twelve') # False

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