のWebスクレイピング（jupyterを使用しているときにエラーを取得）

Question

これが私の初めて私はここthis lecture に記載されている例を実行しようとしているのpythonとすべての関連パッケージとtools.Soでの作業は、コード

import pandas as pd 

# pass in column names for each CSV 
u_cols = ['user_id', 'age', 'sex', 'occupation', 'zip_code'] 

users = pd.read_csv(
    'http://files.grouplens.org/datasets/movielens/ml-100k/u.user', 
    sep='|', names=u_cols) 

users.head() 

です

結果はlike thisあるべき講義によるとjupyter

URLErrorTraceback (most recent call last) 
<ipython-input-4-cd2489d7386f> in <module>() 
     6 users = pd.read_csv(
     7  'http://files.grouplens.org/datasets/movielens/ml-100k/u.user', 
----> 8  sep='|', names=u_cols) 
     9 
    10 users.head() 

/opt/conda/envs/python2/lib/python2.7/site-packages/pandas/io/parsers.pyc in parser_f(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, 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, skip_footer, doublequote, delim_whitespace, as_recarray, compact_ints, use_unsigned, low_memory, buffer_lines, memory_map, float_precision) 
    560      skip_blank_lines=skip_blank_lines) 
    561 
--> 562   return _read(filepath_or_buffer, kwds) 
    563 
    564  parser_f.__name__ = name 

/opt/conda/envs/python2/lib/python2.7/site-packages/pandas/io/parsers.pyc in _read(filepath_or_buffer, kwds) 
    299  filepath_or_buffer, _, compression = get_filepath_or_buffer(
    300   filepath_or_buffer, encoding, 
--> 301   compression=kwds.get('compression', None)) 
    302  kwds['compression'] = (inferred_compression if compression == 'infer' 
    303       else compression) 

/opt/conda/envs/python2/lib/python2.7/site-packages/pandas/io/common.pyc in get_filepath_or_buffer(filepath_or_buffer, encoding, compression) 
    306 
    307  if _is_url(filepath_or_buffer): 
--> 308   req = _urlopen(str(filepath_or_buffer)) 
    309   if compression == 'infer': 
    310    content_encoding = req.headers.get('Content-Encoding', None) 

/opt/conda/envs/python2/lib/python2.7/urllib2.pyc in urlopen(url, data, timeout, cafile, capath, cadefault, context) 
    152  else: 
    153   opener = _opener 
--> 154  return opener.open(url, data, timeout) 
    155 
    156 def install_opener(opener): 

/opt/conda/envs/python2/lib/python2.7/urllib2.pyc in open(self, fullurl, data, timeout) 
    427    req = meth(req) 
    428 
--> 429   response = self._open(req, data) 
    430 
    431   # post-process response 

/opt/conda/envs/python2/lib/python2.7/urllib2.pyc in _open(self, req, data) 
    445   protocol = req.get_type() 
    446   result = self._call_chain(self.handle_open, protocol, protocol + 
--> 447         '_open', req) 
    448   if result: 
    449    return result 

/opt/conda/envs/python2/lib/python2.7/urllib2.pyc in _call_chain(self, chain, kind, meth_name, *args) 
    405    func = getattr(handler, meth_name) 
    406 
--> 407    result = func(*args) 
    408    if result is not None: 
    409     return result 

/opt/conda/envs/python2/lib/python2.7/urllib2.pyc in http_open(self, req) 
    1226 
    1227  def http_open(self, req): 
-> 1228   return self.do_open(httplib.HTTPConnection, req) 
    1229 
    1230  http_request = AbstractHTTPHandler.do_request_ 

/opt/conda/envs/python2/lib/python2.7/urllib2.pyc in do_open(self, http_class, req, **http_conn_args) 
    1196   except socket.error, err: # XXX what error? 
    1197    h.close() 
-> 1198    raise URLError(err) 
    1199   else: 
    1200    try: 

URLError: <urlopen error [Errno -2] Name or service not known> 

を使用してコードを実行しながら、私はエラーのみを取得します。

Answer 1

ネットワークの問題のようです（インターネット接続を確認してください）。コードは私のためにうまく働いた：

>>> users.head() 
    user_id age sex occupation zip_code 
0  1 24 M technician 85711 
1  2 53 F  other 94043 
2  3 23 M  writer 32067 
3  4 24 M technician 43537 
4  5 33 F  other 15213 

それはあなたのマシン（http://files.grouplens.org/datasets/movielens/ml-100k/u.user）からロードすることができるかどうかを確認するには、ブラウザでURLを開くようにしてください。