Bug in df.pct_change()
df.pct_change incorrectly calculates a value when it shouldn't.

```
#!/usr/bin/env python

import numpy as np
import pandas as pd
from datetime import datetime


"""
Notice that the two nonmissing data points are 8 days apart, not 7.
Therefore, any attempt to calculate a 7-day (week-over-week) percent change
should result in NaN, not an actual numeric value.
The bug is that pct_change does calculate an (erroneous) actual numeric value.
(The value it calculates is 414.53/430.30 - 1 = -0.036649.)
"""
idx = pd.DatetimeIndex(start=datetime(2013, 9, 12),
                       end=datetime(2013, 9, 21),
                       freq='D')
df = pd.DataFrame(data={'Series': [430.30,
                                   np.NaN,
                                   np.NaN,
                                   np.NaN,
                                   np.NaN,
                                   np.NaN,
                                   np.NaN,
                                   np.NaN,
                                   414.53,
                                   np.NaN]}, index=idx)
pd.show_versions()
print('\n\nInput data:')
print(df)
print("\n\nThe bug is the pct_change for 09-20 should be NaN, but it isn't:\n")
print(df.pct_change(periods=7))
```

Here is the output:

```
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.6.final.0
python-bits: 64
OS: Darwin
OS-release: 12.5.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.13.1
Cython: 0.19.2
numpy: 1.8.0
scipy: 0.13.3
statsmodels: 0.5.0
IPython: 1.1.0
sphinx: 1.1.3
patsy: 0.2.1
scikits.timeseries: None
dateutil: 1.5
pytz: 2013b
bottleneck: None
tables: 3.0.0
numexpr: 2.2.2
matplotlib: 1.3.1
openpyxl: 1.6.2
xlrd: 0.9.2
xlwt: 0.7.5
xlsxwriter: None
sqlalchemy: 0.8.3
lxml: 3.2.3
bs4: 4.3.1
html5lib: None
bq: None
apiclient: None


Input data:
            Series
2013-09-12  430.30
2013-09-13     NaN
2013-09-14     NaN
2013-09-15     NaN
2013-09-16     NaN
2013-09-17     NaN
2013-09-18     NaN
2013-09-19     NaN
2013-09-20  414.53
2013-09-21     NaN

[10 rows x 1 columns]


The bug is the pct_change for 09-20 should be NaN, but it isn't:

              Series
2013-09-12       NaN
2013-09-13       NaN
2013-09-14       NaN
2013-09-15       NaN
2013-09-16       NaN
2013-09-17       NaN
2013-09-18       NaN
2013-09-19       NaN
2013-09-20 -0.036649
2013-09-21       NaN

[10 rows x 1 columns]
```
