Remote Data Access

Warning

In pandas 0.17.0, the sub-package pandas.io.data will be removed in favor of a separately installable pandas-datareader package. This will allow the data modules to be independently updated to your pandas installation. The API for pandas-datareader v0.1.1 is the same as in pandas v0.16.1. (GH8961)

You should replace the imports of the following:

from pandas.io import data, wb

With:

from pandas_datareader import data, wb

Functions from pandas.io.data and pandas.io.ga extract data from various Internet sources into a DataFrame. Currently the following sources are supported:

It should be noted, that various sources support different kinds of data, so not all sources implement the same methods and the data elements returned might also differ.

Yahoo! Finance

In [1]: import pandas.io.data as web

In [2]: import datetime

In [3]: start = datetime.datetime(2010, 1, 1)

In [4]: end = datetime.datetime(2013, 1, 27)

In [5]: f = web.DataReader("F", 'yahoo', start, end)
---------------------------------------------------------------------------
IOError                                   Traceback (most recent call last)
<ipython-input-5-679b50ab962b> in <module>()
----> 1 f = web.DataReader("F", 'yahoo', start, end)

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in DataReader(name, data_source, start, end, retry_count, pause)
     75         return get_data_yahoo(symbols=name, start=start, end=end,
     76                               adjust_price=False, chunksize=25,
---> 77                               retry_count=retry_count, pause=pause)
     78     elif data_source == "google":
     79         return get_data_google(symbols=name, start=start, end=end,

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in get_data_yahoo(symbols, start, end, retry_count, pause, adjust_price, ret_index, chunksize, interval)
    422         raise ValueError("Invalid interval: valid values are 'd', 'w', 'm' and 'v'")
    423     return _get_data_from(symbols, start, end, interval, retry_count, pause,
--> 424                           adjust_price, ret_index, chunksize, 'yahoo')
    425 
    426 

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in _get_data_from(symbols, start, end, interval, retry_count, pause, adjust_price, ret_index, chunksize, source)
    363     # If a single symbol, (e.g., 'GOOG')
    364     if isinstance(symbols, (compat.string_types, int)):
--> 365         hist_data = src_fn(symbols, start, end, interval, retry_count, pause)
    366     # Or multiple symbols, (e.g., ['GOOG', 'AAPL', 'MSFT'])
    367     elif isinstance(symbols, DataFrame):

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in _get_hist_yahoo(sym, start, end, interval, retry_count, pause)
    206            '&g=%s' % interval +
    207            '&ignore=.csv')
--> 208     return _retry_read_url(url, retry_count, pause, 'Yahoo!')
    209 
    210 

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in _retry_read_url(url, retry_count, pause, name)
    183 
    184     raise IOError("after %d tries, %s did not "
--> 185                   "return a 200 for url %r" % (retry_count, name, url))
    186 
    187 

IOError: after 3 tries, Yahoo! did not return a 200 for url 'http://ichart.finance.yahoo.com/table.csv?s=F&a=0&b=1&c=2010&d=0&e=27&f=2013&g=d&ignore=.csv'

In [6]: f.ix['2010-01-04']
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-6-a881e6f45410> in <module>()
----> 1 f.ix['2010-01-04']

AttributeError: 'file' object has no attribute 'ix'

Yahoo! Finance Options

*Experimental*

The Options class allows the download of options data from Yahoo! Finance.

The get_all_data method downloads and caches option data for all expiry months and provides a formatted DataFrame with a hierarchical index, so it is easy to get to the specific option you want.

In [7]: from pandas.io.data import Options

In [8]: aapl = Options('aapl', 'yahoo')

In [9]: data = aapl.get_all_data()
---------------------------------------------------------------------------
RemoteDataError                           Traceback (most recent call last)
<ipython-input-9-a2dc6d91ec5f> in <module>()
----> 1 data = aapl.get_all_data()

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in get_all_data(self, call, put)
   1113 
   1114         try:
-> 1115             expiry_dates = self.expiry_dates
   1116         except AttributeError:
   1117             expiry_dates, _ = self._get_expiry_dates_and_links()

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in expiry_dates(self)
   1144             expiry_dates = self._expiry_dates
   1145         except AttributeError:
-> 1146             expiry_dates, _ = self._get_expiry_dates_and_links()
   1147         return expiry_dates
   1148 

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in _get_expiry_dates_and_links(self)
   1159 
   1160         url = self._OPTIONS_BASE_URL.format(sym=self.symbol)
-> 1161         root = self._parse_url(url)
   1162 
   1163         try:

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in _parse_url(self, url)
   1191         except _network_error_classes:
   1192             raise RemoteDataError("Unable to parse URL "
-> 1193                                   "{0!r}".format(url))
   1194         else:
   1195             root = doc.getroot()

RemoteDataError: Unable to parse URL 'http://finance.yahoo.com/q/op?s=AAPL'

In [10]: data.iloc[0:5, 0:5]
Out[10]: 
   id       Date Col_1  Col_2  Col_3
0  26 2010-10-18     X  27.50   True
1  42 2010-10-19     Y -12.50  False
2  63 2010-10-20     Z   5.73   True

# Show the $100 strike puts at all expiry dates:
In [11]: data.loc[(100, slice(None), 'put'),:].iloc[0:5, 0:5]
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-11-b8b1bd8f16d0> in <module>()
----> 1 data.loc[(100, slice(None), 'put'),:].iloc[0:5, 0:5]

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/core/indexing.pyc in __getitem__(self, key)
   1185     def __getitem__(self, key):
   1186         if type(key) is tuple:
-> 1187             return self._getitem_tuple(key)
   1188         else:
   1189             return self._getitem_axis(key, axis=0)

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/core/indexing.pyc in _getitem_tuple(self, tup)
    698     def _getitem_tuple(self, tup):
    699         try:
--> 700             return self._getitem_lowerdim(tup)
    701         except IndexingError:
    702             pass

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/core/indexing.pyc in _getitem_lowerdim(self, tup)
    823         for i, key in enumerate(tup):
    824             if is_label_like(key) or isinstance(key, tuple):
--> 825                 section = self._getitem_axis(key, axis=i)
    826 
    827                 # we have yielded a scalar ?

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/core/indexing.pyc in _getitem_axis(self, key, axis)
   1321                     raise ValueError('Cannot index with multidimensional key')
   1322 
-> 1323                 return self._getitem_iterable(key, axis=axis)
   1324 
   1325             # nested tuple slicing

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/core/indexing.pyc in _getitem_iterable(self, key, axis)
    931     def _getitem_iterable(self, key, axis=0):
    932         if self._should_validate_iterable(axis):
--> 933             self._has_valid_type(key, axis)
    934 
    935         labels = self.obj._get_axis(axis)

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/core/indexing.pyc in _has_valid_type(self, key, axis)
   1266 
   1267             # TODO: don't check the entire key unless necessary
-> 1268             if len(key) and np.all(ax.get_indexer_for(key) < 0):
   1269 
   1270                 raise KeyError("None of [%s] are in the [%s]" %

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/core/index.pyc in get_indexer_for(self, target, **kwargs)
   1778         """ guaranteed return of an indexer even when non-unique """
   1779         if self.is_unique:
-> 1780             return self.get_indexer(target, **kwargs)
   1781         indexer, _ = self.get_indexer_non_unique(target, **kwargs)
   1782         return indexer

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/core/index.pyc in get_indexer(self, target, method, limit)
   1683             this = self.astype(object)
   1684             target = target.astype(object)
-> 1685             return this.get_indexer(target, method=method, limit=limit)
   1686 
   1687         if not self.is_unique:

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/core/index.pyc in get_indexer(self, target, method, limit)
   1694             indexer = self._get_nearest_indexer(target, limit)
   1695         else:
-> 1696             indexer = self._engine.get_indexer(target.values)
   1697 
   1698         return com._ensure_platform_int(indexer)

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/index.so in pandas.index.IndexEngine.get_indexer (pandas/index.c:5500)()

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/hashtable.so in pandas.hashtable.PyObjectHashTable.lookup (pandas/hashtable.c:12155)()

TypeError: unhashable type

# Show the volume traded of $100 strike puts at all expiry dates:
In [12]: data.loc[(100, slice(None), 'put'),'Vol'].head()
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-12-12ae0bf819cc> in <module>()
----> 1 data.loc[(100, slice(None), 'put'),'Vol'].head()

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/core/indexing.pyc in __getitem__(self, key)
   1185     def __getitem__(self, key):
   1186         if type(key) is tuple:
-> 1187             return self._getitem_tuple(key)
   1188         else:
   1189             return self._getitem_axis(key, axis=0)

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/core/indexing.pyc in _getitem_tuple(self, tup)
    698     def _getitem_tuple(self, tup):
    699         try:
--> 700             return self._getitem_lowerdim(tup)
    701         except IndexingError:
    702             pass

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/core/indexing.pyc in _getitem_lowerdim(self, tup)
    823         for i, key in enumerate(tup):
    824             if is_label_like(key) or isinstance(key, tuple):
--> 825                 section = self._getitem_axis(key, axis=i)
    826 
    827                 # we have yielded a scalar ?

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/core/indexing.pyc in _getitem_axis(self, key, axis)
   1321                     raise ValueError('Cannot index with multidimensional key')
   1322 
-> 1323                 return self._getitem_iterable(key, axis=axis)
   1324 
   1325             # nested tuple slicing

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/core/indexing.pyc in _getitem_iterable(self, key, axis)
    931     def _getitem_iterable(self, key, axis=0):
    932         if self._should_validate_iterable(axis):
--> 933             self._has_valid_type(key, axis)
    934 
    935         labels = self.obj._get_axis(axis)

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/core/indexing.pyc in _has_valid_type(self, key, axis)
   1266 
   1267             # TODO: don't check the entire key unless necessary
-> 1268             if len(key) and np.all(ax.get_indexer_for(key) < 0):
   1269 
   1270                 raise KeyError("None of [%s] are in the [%s]" %

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/core/index.pyc in get_indexer_for(self, target, **kwargs)
   1778         """ guaranteed return of an indexer even when non-unique """
   1779         if self.is_unique:
-> 1780             return self.get_indexer(target, **kwargs)
   1781         indexer, _ = self.get_indexer_non_unique(target, **kwargs)
   1782         return indexer

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/core/index.pyc in get_indexer(self, target, method, limit)
   1683             this = self.astype(object)
   1684             target = target.astype(object)
-> 1685             return this.get_indexer(target, method=method, limit=limit)
   1686 
   1687         if not self.is_unique:

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/core/index.pyc in get_indexer(self, target, method, limit)
   1694             indexer = self._get_nearest_indexer(target, limit)
   1695         else:
-> 1696             indexer = self._engine.get_indexer(target.values)
   1697 
   1698         return com._ensure_platform_int(indexer)

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/index.so in pandas.index.IndexEngine.get_indexer (pandas/index.c:5500)()

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/hashtable.so in pandas.hashtable.PyObjectHashTable.lookup (pandas/hashtable.c:12155)()

TypeError: unhashable type

If you don’t want to download all the data, more specific requests can be made.

In [13]: import datetime

In [14]: expiry = datetime.date(2016, 1, 1)

In [15]: data = aapl.get_call_data(expiry=expiry)
---------------------------------------------------------------------------
RemoteDataError                           Traceback (most recent call last)
<ipython-input-15-15c0ecd77bfd> in <module>()
----> 1 data = aapl.get_call_data(expiry=expiry)

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in get_call_data(self, month, year, expiry)
    817         for the expiry of the options.
    818         """
--> 819         expiry = self._try_parse_dates(year, month, expiry)
    820         return self._get_data_in_date_range(expiry, call=True, put=False)
    821 

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in _try_parse_dates(self, year, month, expiry)
    977                 expiry = [self._validate_expiry(exp) for exp in expiry]
    978             else:
--> 979                 expiry = [self._validate_expiry(expiry)]
    980 
    981             if len(expiry) == 0:

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in _validate_expiry(self, expiry)
   1001         If the expiry date does not have options that expire on that day, return next expiry"""
   1002 
-> 1003         expiry_dates = self.expiry_dates
   1004         expiry = to_datetime(expiry)
   1005         if hasattr(expiry, 'date'):

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in expiry_dates(self)
   1144             expiry_dates = self._expiry_dates
   1145         except AttributeError:
-> 1146             expiry_dates, _ = self._get_expiry_dates_and_links()
   1147         return expiry_dates
   1148 

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in _get_expiry_dates_and_links(self)
   1159 
   1160         url = self._OPTIONS_BASE_URL.format(sym=self.symbol)
-> 1161         root = self._parse_url(url)
   1162 
   1163         try:

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in _parse_url(self, url)
   1191         except _network_error_classes:
   1192             raise RemoteDataError("Unable to parse URL "
-> 1193                                   "{0!r}".format(url))
   1194         else:
   1195             root = doc.getroot()

RemoteDataError: Unable to parse URL 'http://finance.yahoo.com/q/op?s=AAPL'

In [16]: data.iloc[0:5:, 0:5]
Out[16]: 
   id       Date Col_1  Col_2  Col_3
0  26 2010-10-18     X  27.50   True
1  42 2010-10-19     Y -12.50  False
2  63 2010-10-20     Z   5.73   True

Note that if you call get_all_data first, this second call will happen much faster, as the data is cached.

If a given expiry date is not available, data for the next available expiry will be returned (January 15, 2015 in the above example).

Available expiry dates can be accessed from the expiry_dates property.

In [17]: aapl.expiry_dates
---------------------------------------------------------------------------
RemoteDataError                           Traceback (most recent call last)
<ipython-input-17-c392ccd6fc72> in <module>()
----> 1 aapl.expiry_dates

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in expiry_dates(self)
   1144             expiry_dates = self._expiry_dates
   1145         except AttributeError:
-> 1146             expiry_dates, _ = self._get_expiry_dates_and_links()
   1147         return expiry_dates
   1148 

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in _get_expiry_dates_and_links(self)
   1159 
   1160         url = self._OPTIONS_BASE_URL.format(sym=self.symbol)
-> 1161         root = self._parse_url(url)
   1162 
   1163         try:

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in _parse_url(self, url)
   1191         except _network_error_classes:
   1192             raise RemoteDataError("Unable to parse URL "
-> 1193                                   "{0!r}".format(url))
   1194         else:
   1195             root = doc.getroot()

RemoteDataError: Unable to parse URL 'http://finance.yahoo.com/q/op?s=AAPL'

In [18]: data = aapl.get_call_data(expiry=aapl.expiry_dates[0])
---------------------------------------------------------------------------
RemoteDataError                           Traceback (most recent call last)
<ipython-input-18-110cc070174a> in <module>()
----> 1 data = aapl.get_call_data(expiry=aapl.expiry_dates[0])

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in expiry_dates(self)
   1144             expiry_dates = self._expiry_dates
   1145         except AttributeError:
-> 1146             expiry_dates, _ = self._get_expiry_dates_and_links()
   1147         return expiry_dates
   1148 

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in _get_expiry_dates_and_links(self)
   1159 
   1160         url = self._OPTIONS_BASE_URL.format(sym=self.symbol)
-> 1161         root = self._parse_url(url)
   1162 
   1163         try:

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in _parse_url(self, url)
   1191         except _network_error_classes:
   1192             raise RemoteDataError("Unable to parse URL "
-> 1193                                   "{0!r}".format(url))
   1194         else:
   1195             root = doc.getroot()

RemoteDataError: Unable to parse URL 'http://finance.yahoo.com/q/op?s=AAPL'

In [19]: data.iloc[0:5:, 0:5]
Out[19]: 
   id       Date Col_1  Col_2  Col_3
0  26 2010-10-18     X  27.50   True
1  42 2010-10-19     Y -12.50  False
2  63 2010-10-20     Z   5.73   True

A list-like object containing dates can also be passed to the expiry parameter, returning options data for all expiry dates in the list.

In [20]: data = aapl.get_near_stock_price(expiry=aapl.expiry_dates[0:3])
---------------------------------------------------------------------------
RemoteDataError                           Traceback (most recent call last)
<ipython-input-20-c65c968dea4d> in <module>()
----> 1 data = aapl.get_near_stock_price(expiry=aapl.expiry_dates[0:3])

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in expiry_dates(self)
   1144             expiry_dates = self._expiry_dates
   1145         except AttributeError:
-> 1146             expiry_dates, _ = self._get_expiry_dates_and_links()
   1147         return expiry_dates
   1148 

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in _get_expiry_dates_and_links(self)
   1159 
   1160         url = self._OPTIONS_BASE_URL.format(sym=self.symbol)
-> 1161         root = self._parse_url(url)
   1162 
   1163         try:

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in _parse_url(self, url)
   1191         except _network_error_classes:
   1192             raise RemoteDataError("Unable to parse URL "
-> 1193                                   "{0!r}".format(url))
   1194         else:
   1195             root = doc.getroot()

RemoteDataError: Unable to parse URL 'http://finance.yahoo.com/q/op?s=AAPL'

In [21]: data.iloc[0:5:, 0:5]
Out[21]: 
   id       Date Col_1  Col_2  Col_3
0  26 2010-10-18     X  27.50   True
1  42 2010-10-19     Y -12.50  False
2  63 2010-10-20     Z   5.73   True

The month and year parameters can be used to get all options data for a given month.

Google Finance

In [22]: import pandas.io.data as web

In [23]: import datetime

In [24]: start = datetime.datetime(2010, 1, 1)

In [25]: end = datetime.datetime(2013, 1, 27)

In [26]: f = web.DataReader("F", 'google', start, end)
---------------------------------------------------------------------------
IOError                                   Traceback (most recent call last)
<ipython-input-26-514f2d6b98c6> in <module>()
----> 1 f = web.DataReader("F", 'google', start, end)

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in DataReader(name, data_source, start, end, retry_count, pause)
     79         return get_data_google(symbols=name, start=start, end=end,
     80                                adjust_price=False, chunksize=25,
---> 81                                retry_count=retry_count, pause=pause)
     82     elif data_source == "fred":
     83         return get_data_fred(name, start, end)

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in get_data_google(symbols, start, end, retry_count, pause, adjust_price, ret_index, chunksize)
    456     """
    457     return _get_data_from(symbols, start, end, None, retry_count, pause,
--> 458                           adjust_price, ret_index, chunksize, 'google')
    459 
    460 

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in _get_data_from(symbols, start, end, interval, retry_count, pause, adjust_price, ret_index, chunksize, source)
    363     # If a single symbol, (e.g., 'GOOG')
    364     if isinstance(symbols, (compat.string_types, int)):
--> 365         hist_data = src_fn(symbols, start, end, interval, retry_count, pause)
    366     # Or multiple symbols, (e.g., ['GOOG', 'AAPL', 'MSFT'])
    367     elif isinstance(symbols, DataFrame):

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in _get_hist_google(sym, start, end, interval, retry_count, pause)
    227                                "enddate": end.strftime('%b %d, %Y'),
    228                                "output": "csv"}))
--> 229     return _retry_read_url(url, retry_count, pause, 'Google')
    230 
    231 

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in _retry_read_url(url, retry_count, pause, name)
    183 
    184     raise IOError("after %d tries, %s did not "
--> 185                   "return a 200 for url %r" % (retry_count, name, url))
    186 
    187 

IOError: after 3 tries, Google did not return a 200 for url 'http://www.google.com/finance/historical?q=F&startdate=Jan+01%2C+2010&enddate=Jan+27%2C+2013&output=csv'

In [27]: f.ix['2010-01-04']
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-27-a881e6f45410> in <module>()
----> 1 f.ix['2010-01-04']

AttributeError: 'file' object has no attribute 'ix'

FRED

In [28]: import pandas.io.data as web

In [29]: import datetime

In [30]: start = datetime.datetime(2010, 1, 1)

In [31]: end = datetime.datetime(2013, 1, 27)

In [32]: gdp=web.DataReader("GDP", "fred", start, end)
---------------------------------------------------------------------------
URLError                                  Traceback (most recent call last)
<ipython-input-32-ee552a87dd44> in <module>()
----> 1 gdp=web.DataReader("GDP", "fred", start, end)

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in DataReader(name, data_source, start, end, retry_count, pause)
     81                                retry_count=retry_count, pause=pause)
     82     elif data_source == "fred":
---> 83         return get_data_fred(name, start, end)
     84     elif data_source == "famafrench":
     85         return get_data_famafrench(name)

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in get_data_fred(name, start, end)
    495                               "a valid FRED series.".format(name))
    496             raise
--> 497     df = concat([fetch_data(url, n) for url, n in zip(urls, names)],
    498                 axis=1, join='outer')
    499     return df

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in fetch_data(url, name)
    484 
    485     def fetch_data(url, name):
--> 486         with urlopen(url) as resp:
    487             data = read_csv(resp, index_col=0, parse_dates=True,
    488                             header=None, skiprows=1, names=["DATE", name],

/usr/lib/python2.7/contextlib.pyc in __enter__(self)
     15     def __enter__(self):
     16         try:
---> 17             return self.gen.next()
     18         except StopIteration:
     19             raise RuntimeError("generator didn't yield")

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/common.pyc in urlopen(*args, **kwargs)
     32     @contextmanager
     33     def urlopen(*args, **kwargs):
---> 34         with closing(_urlopen(*args, **kwargs)) as f:
     35             yield f
     36 

/usr/lib/python2.7/urllib2.pyc in urlopen(url, data, timeout)
    125     if _opener is None:
    126         _opener = build_opener()
--> 127     return _opener.open(url, data, timeout)
    128 
    129 def install_opener(opener):

/usr/lib/python2.7/urllib2.pyc in open(self, fullurl, data, timeout)
    402             req = meth(req)
    403 
--> 404         response = self._open(req, data)
    405 
    406         # post-process response

/usr/lib/python2.7/urllib2.pyc in _open(self, req, data)
    420         protocol = req.get_type()
    421         result = self._call_chain(self.handle_open, protocol, protocol +
--> 422                                   '_open', req)
    423         if result:
    424             return result

/usr/lib/python2.7/urllib2.pyc in _call_chain(self, chain, kind, meth_name, *args)
    380             func = getattr(handler, meth_name)
    381 
--> 382             result = func(*args)
    383             if result is not None:
    384                 return result

/usr/lib/python2.7/urllib2.pyc in http_open(self, req)
   1197 
   1198     def http_open(self, req):
-> 1199         return self.do_open(httplib.HTTPConnection, req)
   1200 
   1201     http_request = AbstractHTTPHandler.do_request_

/usr/lib/python2.7/urllib2.pyc in do_open(self, http_class, req)
   1167         except socket.error, err: # XXX what error?
   1168             h.close()
-> 1169             raise URLError(err)
   1170         else:
   1171             try:

URLError: <urlopen error [Errno 111] Connection refused>

In [33]: gdp.ix['2013-01-01']
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-33-4fda7a1657eb> in <module>()
----> 1 gdp.ix['2013-01-01']

NameError: name 'gdp' is not defined

# Multiple series:
In [34]: inflation = web.DataReader(["CPIAUCSL", "CPILFESL"], "fred", start, end)
---------------------------------------------------------------------------
URLError                                  Traceback (most recent call last)
<ipython-input-34-c7b3843168f6> in <module>()
----> 1 inflation = web.DataReader(["CPIAUCSL", "CPILFESL"], "fred", start, end)

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in DataReader(name, data_source, start, end, retry_count, pause)
     81                                retry_count=retry_count, pause=pause)
     82     elif data_source == "fred":
---> 83         return get_data_fred(name, start, end)
     84     elif data_source == "famafrench":
     85         return get_data_famafrench(name)

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in get_data_fred(name, start, end)
    495                               "a valid FRED series.".format(name))
    496             raise
--> 497     df = concat([fetch_data(url, n) for url, n in zip(urls, names)],
    498                 axis=1, join='outer')
    499     return df

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in fetch_data(url, name)
    484 
    485     def fetch_data(url, name):
--> 486         with urlopen(url) as resp:
    487             data = read_csv(resp, index_col=0, parse_dates=True,
    488                             header=None, skiprows=1, names=["DATE", name],

/usr/lib/python2.7/contextlib.pyc in __enter__(self)
     15     def __enter__(self):
     16         try:
---> 17             return self.gen.next()
     18         except StopIteration:
     19             raise RuntimeError("generator didn't yield")

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/common.pyc in urlopen(*args, **kwargs)
     32     @contextmanager
     33     def urlopen(*args, **kwargs):
---> 34         with closing(_urlopen(*args, **kwargs)) as f:
     35             yield f
     36 

/usr/lib/python2.7/urllib2.pyc in urlopen(url, data, timeout)
    125     if _opener is None:
    126         _opener = build_opener()
--> 127     return _opener.open(url, data, timeout)
    128 
    129 def install_opener(opener):

/usr/lib/python2.7/urllib2.pyc in open(self, fullurl, data, timeout)
    402             req = meth(req)
    403 
--> 404         response = self._open(req, data)
    405 
    406         # post-process response

/usr/lib/python2.7/urllib2.pyc in _open(self, req, data)
    420         protocol = req.get_type()
    421         result = self._call_chain(self.handle_open, protocol, protocol +
--> 422                                   '_open', req)
    423         if result:
    424             return result

/usr/lib/python2.7/urllib2.pyc in _call_chain(self, chain, kind, meth_name, *args)
    380             func = getattr(handler, meth_name)
    381 
--> 382             result = func(*args)
    383             if result is not None:
    384                 return result

/usr/lib/python2.7/urllib2.pyc in http_open(self, req)
   1197 
   1198     def http_open(self, req):
-> 1199         return self.do_open(httplib.HTTPConnection, req)
   1200 
   1201     http_request = AbstractHTTPHandler.do_request_

/usr/lib/python2.7/urllib2.pyc in do_open(self, http_class, req)
   1167         except socket.error, err: # XXX what error?
   1168             h.close()
-> 1169             raise URLError(err)
   1170         else:
   1171             try:

URLError: <urlopen error [Errno 111] Connection refused>

In [35]: inflation.head()
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-35-7b22de5ccbc6> in <module>()
----> 1 inflation.head()

NameError: name 'inflation' is not defined

Fama/French

Dataset names are listed at Fama/French Data Library.

In [36]: import pandas.io.data as web

In [37]: ip = web.DataReader("5_Industry_Portfolios", "famafrench")
---------------------------------------------------------------------------
URLError                                  Traceback (most recent call last)
<ipython-input-37-5a3e59d5b894> in <module>()
----> 1 ip = web.DataReader("5_Industry_Portfolios", "famafrench")

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in DataReader(name, data_source, start, end, retry_count, pause)
     83         return get_data_fred(name, start, end)
     84     elif data_source == "famafrench":
---> 85         return get_data_famafrench(name)
     86 
     87 

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/data.pyc in get_data_famafrench(name)
    507     zip_file_path = '{0}/{1}.zip'.format(_FAMAFRENCH_URL, name)
    508 
--> 509     with urlopen(zip_file_path) as url:
    510         raw = url.read()
    511 

/usr/lib/python2.7/contextlib.pyc in __enter__(self)
     15     def __enter__(self):
     16         try:
---> 17             return self.gen.next()
     18         except StopIteration:
     19             raise RuntimeError("generator didn't yield")

/tmp/buildd/pandas-0.16.2+git65-g054821d/debian/python-pandas/usr/lib/python2.7/dist-packages/pandas/io/common.pyc in urlopen(*args, **kwargs)
     32     @contextmanager
     33     def urlopen(*args, **kwargs):
---> 34         with closing(_urlopen(*args, **kwargs)) as f:
     35             yield f
     36 

/usr/lib/python2.7/urllib2.pyc in urlopen(url, data, timeout)
    125     if _opener is None:
    126         _opener = build_opener()
--> 127     return _opener.open(url, data, timeout)
    128 
    129 def install_opener(opener):

/usr/lib/python2.7/urllib2.pyc in open(self, fullurl, data, timeout)
    402             req = meth(req)
    403 
--> 404         response = self._open(req, data)
    405 
    406         # post-process response

/usr/lib/python2.7/urllib2.pyc in _open(self, req, data)
    420         protocol = req.get_type()
    421         result = self._call_chain(self.handle_open, protocol, protocol +
--> 422                                   '_open', req)
    423         if result:
    424             return result

/usr/lib/python2.7/urllib2.pyc in _call_chain(self, chain, kind, meth_name, *args)
    380             func = getattr(handler, meth_name)
    381 
--> 382             result = func(*args)
    383             if result is not None:
    384                 return result

/usr/lib/python2.7/urllib2.pyc in http_open(self, req)
   1197 
   1198     def http_open(self, req):
-> 1199         return self.do_open(httplib.HTTPConnection, req)
   1200 
   1201     http_request = AbstractHTTPHandler.do_request_

/usr/lib/python2.7/urllib2.pyc in do_open(self, http_class, req)
   1167         except socket.error, err: # XXX what error?
   1168             h.close()
-> 1169             raise URLError(err)
   1170         else:
   1171             try:

URLError: <urlopen error [Errno 111] Connection refused>

In [38]: ip[4].ix[192607]
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-38-1cb52c705436> in <module>()
----> 1 ip[4].ix[192607]

NameError: name 'ip' is not defined

World Bank

pandas users can easily access thousands of panel data series from the World Bank’s World Development Indicators by using the wb I/O functions.

Indicators

Either from exploring the World Bank site, or using the search function included, every world bank indicator is accessible.

For example, if you wanted to compare the Gross Domestic Products per capita in constant dollars in North America, you would use the search function:

In [1]: from pandas.io import wb

In [2]: wb.search('gdp.*capita.*const').iloc[:,:2]
Out[2]:
                     id                                               name
3242            GDPPCKD             GDP per Capita, constant US$, millions
5143     NY.GDP.PCAP.KD                 GDP per capita (constant 2005 US$)
5145     NY.GDP.PCAP.KN                      GDP per capita (constant LCU)
5147  NY.GDP.PCAP.PP.KD  GDP per capita, PPP (constant 2005 internation...

Then you would use the download function to acquire the data from the World Bank’s servers:

In [3]: dat = wb.download(indicator='NY.GDP.PCAP.KD', country=['US', 'CA', 'MX'], start=2005, end=2008)

In [4]: print(dat)
                      NY.GDP.PCAP.KD
country       year
Canada        2008  36005.5004978584
              2007  36182.9138439757
              2006  35785.9698172849
              2005  35087.8925933298
Mexico        2008  8113.10219480083
              2007  8119.21298908649
              2006  7961.96818458178
              2005  7666.69796097264
United States 2008  43069.5819857208
              2007  43635.5852068142
              2006   43228.111147107
              2005  42516.3934699993

The resulting dataset is a properly formatted DataFrame with a hierarchical index, so it is easy to apply .groupby transformations to it:

In [6]: dat['NY.GDP.PCAP.KD'].groupby(level=0).mean()
Out[6]:
country
Canada           35765.569188
Mexico            7965.245332
United States    43112.417952
dtype: float64

Now imagine you want to compare GDP to the share of people with cellphone contracts around the world.

In [7]: wb.search('cell.*%').iloc[:,:2]
Out[7]:
                     id                                               name
3990  IT.CEL.SETS.FE.ZS  Mobile cellular telephone users, female (% of ...
3991  IT.CEL.SETS.MA.ZS  Mobile cellular telephone users, male (% of po...
4027      IT.MOB.COV.ZS  Population coverage of mobile cellular telepho...

Notice that this second search was much faster than the first one because pandas now has a cached list of available data series.

In [13]: ind = ['NY.GDP.PCAP.KD', 'IT.MOB.COV.ZS']
In [14]: dat = wb.download(indicator=ind, country='all', start=2011, end=2011).dropna()
In [15]: dat.columns = ['gdp', 'cellphone']
In [16]: print(dat.tail())
                        gdp  cellphone
country   year
Swaziland 2011  2413.952853       94.9
Tunisia   2011  3687.340170      100.0
Uganda    2011   405.332501      100.0
Zambia    2011   767.911290       62.0
Zimbabwe  2011   419.236086       72.4

Finally, we use the statsmodels package to assess the relationship between our two variables using ordinary least squares regression. Unsurprisingly, populations in rich countries tend to use cellphones at a higher rate:

In [17]: import numpy as np
In [18]: import statsmodels.formula.api as smf
In [19]: mod = smf.ols("cellphone ~ np.log(gdp)", dat).fit()
In [20]: print(mod.summary())
                            OLS Regression Results
==============================================================================
Dep. Variable:              cellphone   R-squared:                       0.297
Model:                            OLS   Adj. R-squared:                  0.274
Method:                 Least Squares   F-statistic:                     13.08
Date:                Thu, 25 Jul 2013   Prob (F-statistic):            0.00105
Time:                        15:24:42   Log-Likelihood:                -139.16
No. Observations:                  33   AIC:                             282.3
Df Residuals:                      31   BIC:                             285.3
Df Model:                           1
===============================================================================
                  coef    std err          t      P>|t|      [95.0% Conf. Int.]
-------------------------------------------------------------------------------
Intercept      16.5110     19.071      0.866      0.393       -22.384    55.406
np.log(gdp)     9.9333      2.747      3.616      0.001         4.331    15.535
==============================================================================
Omnibus:                       36.054   Durbin-Watson:                   2.071
Prob(Omnibus):                  0.000   Jarque-Bera (JB):              119.133
Skew:                          -2.314   Prob(JB):                     1.35e-26
Kurtosis:                      11.077   Cond. No.                         45.8
==============================================================================

Country Codes

New in version 0.15.1.

The country argument accepts a string or list of mixed two or three character ISO country codes, as well as dynamic World Bank exceptions to the ISO standards.

For a list of the the hard-coded country codes (used solely for error handling logic) see pandas.io.wb.country_codes.

Problematic Country Codes & Indicators

Note

The World Bank’s country list and indicators are dynamic. As of 0.15.1, wb.download() is more flexible. To achieve this, the warning and exception logic changed.

The world bank converts some country codes in their response, which makes error checking by pandas difficult. Retired indicators still persist in the search.

Given the new flexibility of 0.15.1, improved error handling by the user may be necessary for fringe cases.

To help identify issues:

There are at least 4 kinds of country codes:

  1. Standard (2/3 digit ISO) - returns data, will warn and error properly.
  2. Non-standard (WB Exceptions) - returns data, but will falsely warn.
  3. Blank - silently missing from the response.
  4. Bad - causes the entire response from WB to fail, always exception inducing.

There are at least 3 kinds of indicators:

  1. Current - Returns data.
  2. Retired - Appears in search results, yet won’t return data.
  3. Bad - Will not return data.

Use the errors argument to control warnings and exceptions. Setting errors to ignore or warn, won’t stop failed responses. (ie, 100% bad indicators, or a single “bad” (#4 above) country code).

See docstrings for more info.

Google Analytics

The ga module provides a wrapper for Google Analytics API to simplify retrieving traffic data. Result sets are parsed into a pandas DataFrame with a shape and data types derived from the source table.

Configuring Access to Google Analytics

The first thing you need to do is to setup accesses to Google Analytics API. Follow the steps below:

  1. In the Google Developers Console
    1. enable the Analytics API
    2. create a new project
    3. create a new Client ID for an “Installed Application” (in the “APIs & auth / Credentials section” of the newly created project)
    4. download it (JSON file)
  2. On your machine
    1. rename it to client_secrets.json
    2. move it to the pandas/io module directory

The first time you use the read_ga() funtion, a browser window will open to ask you to authentify to the Google API. Do proceed.

Using the Google Analytics API

The following will fetch users and pageviews (metrics) data per day of the week, for the first semester of 2014, from a particular property.

import pandas.io.ga as ga
ga.read_ga(
    account_id  = "2360420",
    profile_id  = "19462946",
    property_id = "UA-2360420-5",
    metrics     = ['users', 'pageviews'],
    dimensions  = ['dayOfWeek'],
    start_date  = "2014-01-01",
    end_date    = "2014-08-01",
    index_col   = 0,
    filters     = "pagePath=~aboutus;ga:country==France",
)

The only mandatory arguments are metrics, dimensions and start_date. We strongly recommend that you always specify the account_id, profile_id and property_id to avoid accessing the wrong data bucket in Google Analytics.

The index_col argument indicates which dimension(s) has to be taken as index.

The filters argument indicates the filtering to apply to the query. In the above example, the page URL has to contain aboutus AND the visitors country has to be France.

Detailed information in the following: