pct_change computes incorrect values
[btc_nvt.txt](https://github.com/pandas-dev/pandas/files/1584094/btc_nvt.txt)
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
import numpy as np

def to_weekly(dataframe, field=None):
    dataframe.index = pd.to_datetime(dataframe.index)
    if field:
        dataframe = dataframe[field]
    return dataframe.resample('W').mean()

btc_frame = pd.read_csv('btc_nvt.csv')
btc_frame = btc_frame.shift(periods=1, freq=None, axis=1)
btc_frame = btc_frame.drop(['Date'], axis=1)
btc_frame['nvt'] = btc_frame['marketcap(USD)'] / btc_frame['txVolume(USD)']
btc_frame['price(%)'] = btc_frame['price(USD)'].pct_change(1)
btc_frame['% man'] = (btc_frame['price(USD)'] - btc_frame['price(USD)'].shift(1)) / btc_frame['price(USD)'].shift(1)
btc_frame['1 shift'] = btc_frame['price(USD)'].shift(1)

btc_frame = to_weekly(btc_frame)
print(btc_frame[['price(USD)', 'price(%)', '% man', '1 shift']])

```
#### Problem description
The values in `price(%)` and in `% man` are incorrect. It not clear how those values are computed because they do not align with pct_change. Another issue is the `1 shift` column does not seem to be `price(USD)` shifted by 1.

I have tried using the latest version of Pandas as well via a pip install with the same result. Perhaps there is also a chance this is related to the way the csv is being imported and prepared? I'm attaching the csv as well (as .txt since github does not support .csv).

```
              price(USD)  price(%)     % man       1 shift
2013-04-28    134.210000       NaN       NaN           NaN
2013-05-05    118.842857 -0.015728 -0.015728    121.457143
2013-05-12    113.925714 -0.000890 -0.000890    114.055714
2013-05-19    118.710000  0.008954  0.008954    117.711429
2013-05-26    127.732857  0.013101  0.013101    126.091429
2013-06-02    128.634286 -0.012134 -0.012134    130.232857
2013-06-09    114.727143 -0.027950 -0.027950    117.911429
2013-06-16    103.840000 -0.000162 -0.000162    103.910000
```


#### Expected Output
```
              price(USD)  price(%)     % man       1 shift
2013-04-28    134.210000       NaN       NaN           NaN
2013-05-05    118.842857 -0.1145     -0.1145    134.210000
2013-05-12    113.925714  -0.041       -0.041      118.842857
```


#### Output of ``pd.show_versions()``

<details>

[paste the output of ``pd.show_versions()`` here below this line]

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.2.final.0
python-bits: 64
OS: Darwin
OS-release: 17.2.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.20.3
pytest: None
pip: 9.0.1
setuptools: 36.4.0
Cython: None
numpy: 1.13.1
scipy: None
xarray: None
IPython: None
sphinx: None
patsy: None
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: None
s3fs: None
pandas_gbq: None
pandas_datareader: None

</details>
