CLN: FamaFrenchReader

pandas_datareader/data.py

@@ -14,14 +14,17 @@
 from pandas_datareader.yahoo.options import Options as YahooOptions
 
 from pandas_datareader.fred import FredReader
-from pandas_datareader.famafrench import _get_data as get_data_famafrench
+from pandas_datareader.famafrench import FamaFrenchReader
 from pandas_datareader.oecd import OECDReader
 
 
 # ToDo: deprecate
 def get_data_fred(*args, **kwargs):
     return FredReader(*args, **kwargs).read()
 
+def get_data_famafrench(*args, **kwargs):
+    return FamaFrenchReader(*args, **kwargs).read()
+
 def get_data_google(*args, **kwargs):
     return GoogleDailyReader(*args, **kwargs).read()
 
@@ -88,21 +91,28 @@ def DataReader(name, data_source=None, start=None, end=None,
                                 adjust_price=False, chunksize=25,
                                 retry_count=retry_count, pause=pause,
                                 session=session).read()
+
     elif data_source == "yahoo-actions":
         return YahooActionReader(symbol=name, start=start, end=end,
                                  retry_count=retry_count, pause=pause,
                                  session=session).read()
+
     elif data_source == "google":
         return GoogleDailyReader(symbols=name, start=start, end=end,
                                  chunksize=25,
                                  retry_count=retry_count, pause=pause,
                                  session=session).read()
+
     elif data_source == "fred":
         return FredReader(symbols=name, start=start, end=end,
                           retry_count=retry_count, pause=pause,
                           session=session).read()
+
     elif data_source == "famafrench":
-        return get_data_famafrench(name)
+        return FamaFrenchReader(symbols=name, start=start, end=end,
+                                retry_count=retry_count, pause=pause,
+                                session=session).read()
+
     elif data_source == "oecd":
         return OECDReader(symbols=name, start=start, end=end,
                           retry_count=retry_count, pause=pause,

pandas_datareader/famafrench.py

@@ -1,10 +1,11 @@
 import tempfile
 import re
 import datetime as dt
-from pandas.io.common import urlopen, ZipFile
+from pandas.io.common import ZipFile
 from pandas.compat import lmap, StringIO
 from pandas import read_csv, to_datetime
 
+from pandas_datareader.base import _BaseReader
 
 _URL = 'http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/'
 _URL_PREFIX = 'ftp/'
@@ -33,28 +34,17 @@ def get_available_datasets():
     return lmap(lambda x: x[len(_URL_PREFIX):-len(_URL_SUFFIX)], l)
 
 
-def _download_data_famafrench(name):
-    url = ''.join([_URL, _URL_PREFIX, name, _URL_SUFFIX])
-    with urlopen(url) as socket:
-        raw = socket.read()
-
-    with tempfile.TemporaryFile() as tmpf:
-        tmpf.write(raw)
-
-        with ZipFile(tmpf, 'r') as zf:
-            data = zf.open(zf.namelist()[0]).read().decode()
-
-    return data
-
-
 def _parse_date_famafrench(x):
     x = x.strip()
-    try: return dt.datetime.strptime(x, '%Y%m')
-    except: pass
+    try:
+        return dt.datetime.strptime(x, '%Y%m')
+    except:
+        pass
     return to_datetime(x)
 
 
-def _get_data(name):
+class FamaFrenchReader(_BaseReader):
+
     """
     Get data for the given name from the Fama/French data library.
 
@@ -66,43 +56,75 @@ def _get_data(name):
     df : a dictionary of pandas.DataFrame. Tables are accessed by integer keys.
          See df['DESCR'] for a description of the dataset
     """
-    params = {'index_col': 0,
-              'parse_dates': [0],
-              'date_parser': _parse_date_famafrench}
-
-    # headers in these files are not valid
-    if name.endswith('_Breakpoints'):
-        c = ['<=0', '>0'] if name.find('-') > -1 else ['Count']
-        r = list(range(0, 105, 5))
-        params['names'] = ['Date'] + c + list(zip(r, r[1:]))
-        params['skiprows'] = 1 if name != 'Prior_2-12_Breakpoints' else 3
-
-    doc_chunks, tables = [], []
-    data = _download_data_famafrench(name)
-    for chunk in data.split(2 * '\r\n'):
-        if len(chunk) < 800:
-            doc_chunks.append(chunk.replace('\r\n', ' ').strip())
-        else:
-            tables.append(chunk)
-
-    datasets, table_desc = {}, []
-    for i, src in enumerate(tables):
-        match = re.search('^\s*,', src, re.M)  # the table starts there
-        start = 0 if not match else match.start()
-
-        df = read_csv(StringIO('Date' + src[start:]), **params)
-        try: df = df.to_period(df.index.inferred_freq[:1])
-        except: pass
-        datasets[i] = df
-
-        title = src[:start].replace('\r\n', ' ').strip()
-        shape = '({0} rows x {1} cols)'.format(*df.shape)
-        table_desc.append('{0} {1}'.format(title, shape).strip())
-
-    descr = '{0}\n{1}\n\n'.format(name.replace('_', ' '), len(name) * '-')
-    if doc_chunks: descr += ' '.join(doc_chunks).replace(2 * ' ', ' ') + '\n\n'
-
-    table_descr = map(lambda x: '{0:3} : {1}'.format(*x), enumerate(table_desc))
-
-    datasets['DESCR'] = descr + '\n'.join(table_descr)
-    return datasets
+
+    @property
+    def url(self):
+        return ''.join([_URL, _URL_PREFIX, self.symbols, _URL_SUFFIX])
+
+    def _read_zipfile(self, url):
+        raw = self._get_response(url).content
+
+        with tempfile.TemporaryFile() as tmpf:
+            tmpf.write(raw)
+
+            with ZipFile(tmpf, 'r') as zf:
+                data = zf.open(zf.namelist()[0]).read().decode()
+
+        return data
+
+    def _read_one_data(self, url, params):
+
+        params = {'index_col': 0,
+                  'parse_dates': [0],
+                  'date_parser': _parse_date_famafrench}
+
+        # headers in these files are not valid
+        if self.symbols.endswith('_Breakpoints'):
+
+            if self.symbols.find('-') > -1:
+                c = ['<=0', '>0']
+            else:
+                c = ['Count']
+            r = list(range(0, 105, 5))
+            params['names'] = ['Date'] + c + list(zip(r, r[1:]))
+
+            if self.symbols != 'Prior_2-12_Breakpoints':
+                params['skiprows'] = 1
+            else:
+                params['skiprows'] = 3
+
+        doc_chunks, tables = [], []
+        data = self._read_zipfile(url)
+
+        for chunk in data.split(2 * '\r\n'):
+            if len(chunk) < 800:
+                doc_chunks.append(chunk.replace('\r\n', ' ').strip())
+            else:
+                tables.append(chunk)
+
+        datasets, table_desc = {}, []
+        for i, src in enumerate(tables):
+            match = re.search('^\s*,', src, re.M)  # the table starts there
+            start = 0 if not match else match.start()
+
+            df = read_csv(StringIO('Date' + src[start:]), **params)
+            try:
+                idx_name = df.index.name # hack for pandas 0.16.2
+                df = df.to_period(df.index.inferred_freq[:1])
+                df.index.name = idx_name
+            except:
+                pass
+            df = df.truncate(self.start, self.end)
+            datasets[i] = df
+
+            title = src[:start].replace('\r\n', ' ').strip()
+            shape = '({0} rows x {1} cols)'.format(*df.shape)
+            table_desc.append('{0} {1}'.format(title, shape).strip())
+
+        descr = '{0}\n{1}\n\n'.format(self.symbols.replace('_', ' '), len(self.symbols) * '-')
+        if doc_chunks:
+            descr += ' '.join(doc_chunks).replace(2 * ' ', ' ') + '\n\n'
+        table_descr = map(lambda x: '{0:3} : {1}'.format(*x), enumerate(table_desc))
+        datasets['DESCR'] = descr + '\n'.join(table_descr)
+
+        return datasets

pandas_datareader/oecd.py

@@ -6,8 +6,6 @@
 from pandas import concat, read_csv
 
 from pandas_datareader.io import read_jsdmx
-
-
 from pandas_datareader.base import _BaseReader
 
 
@@ -18,6 +16,7 @@ class OECDReader(_BaseReader):
     @property
     def url(self):
         url = 'http://stats.oecd.org/SDMX-JSON/data'
+
         if not isinstance(self.symbols, compat.string_types):
             raise ValueError('data name must be string')
 

pandas_datareader/tests/test_famafrench.py

@@ -1,4 +1,5 @@
 import nose
+import pandas as pd
 import pandas.util.testing as tm
 
 import pandas_datareader.data as web
@@ -27,6 +28,55 @@ def test_index(self):
         assert ff[0].index.freq == 'M'
         assert ff[1].index.freq == 'A-DEC'
 
+    def test_f_f_research(self):
+        results = web.DataReader("F-F_Research_Data_Factors", "famafrench",
+                                 start='2010-01-01', end='2010-12-01')
+        self.assertTrue(isinstance(results, dict))
+        self.assertEqual(len(results), 3)
+
+        exp = pd.DataFrame({'Mkt-RF': [-3.36, 3.4, 6.31, 2., -7.89, -5.56,
+                                       6.93, -4.77, 9.54, 3.88, 0.6, 6.82],
+                            'SMB': [0.2, 1.44, 1.57, 4.92, -0.09, -2.15,
+                                    0.24, -3.03, 3.84, 1.01, 3.69, 0.85],
+                            'HML': [0.61, 2.74, 2.01, 3.12, -2.32, -4.27,
+                                    0.04, -1.51, -2.94, -2.23, -0.58, 3.47],
+                            'RF': [0., 0., 0.01, 0.01, 0.01, 0.01, 0.01,
+                                   0.01, 0.01, 0.01, 0.01, 0.01]},
+                           index=pd.period_range('2010-01-01', '2010-12-01', freq='M', name='Date'),
+                           columns=['Mkt-RF', 'SMB', 'HML', 'RF'])
+        tm.assert_frame_equal(results[0], exp)
+
+    def test_me_breakpoints(self):
+        results = web.DataReader("ME_Breakpoints", "famafrench",
+                                 start='2010-01-01', end='2010-12-01')
+        self.assertTrue(isinstance(results, dict))
+        self.assertEqual(len(results), 2)
+        self.assertEqual(results[0].shape, (12, 21))
+
+        exp_columns = pd.Index(['Count', (0, 5), (5, 10), (10, 15), (15, 20), (20, 25),
+                                (25, 30), (30, 35), (35, 40), (40, 45), (45, 50), (50, 55),
+                                (55, 60), (60, 65), (65, 70), (70, 75), (75, 80), (80, 85),
+                                (85, 90), (90, 95), (95, 100)], dtype='object')
+        tm.assert_index_equal(results[0].columns, exp_columns)
+
+        exp_index = pd.period_range('2010-01-01', '2010-12-01', freq='M', name='Date')
+        tm.assert_index_equal(results[0].index, exp_index)
+
+    def test_prior_2_12_breakpoints(self):
+        results = web.DataReader("Prior_2-12_Breakpoints", "famafrench",
+                                 start='2010-01-01', end='2010-12-01')
+        self.assertTrue(isinstance(results, dict))
+        self.assertEqual(len(results), 2)
+        self.assertEqual(results[0].shape, (12, 22))
+
+        exp_columns = pd.Index(['<=0', '>0', (0, 5), (5, 10), (10, 15), (15, 20), (20, 25),
+                                (25, 30), (30, 35), (35, 40), (40, 45), (45, 50), (50, 55),
+                                (55, 60), (60, 65), (65, 70), (70, 75), (75, 80), (80, 85),
+                                (85, 90), (90, 95), (95, 100)], dtype='object')
+        tm.assert_index_equal(results[0].columns, exp_columns)
+
+        exp_index = pd.period_range('2010-01-01', '2010-12-01', freq='M', name='Date')
+        tm.assert_index_equal(results[0].index, exp_index)
 
 
 if __name__ == '__main__':