Consistent columns naming for candlesticks
Resampling timeseries with Pandas resample and ohlc method and Pandas DataReader should output DataFrame with same columns name to provide a consistent columns naming.

Currently this is not consistent.

```python
In [1]: import pandas_datareader as pdr

In [2]: df = pdr.DataReader("IBM", "google")
In [2]: df
Out[2]:
              Open    High     Low   Close   Volume
Date
2010-01-04  131.18  132.97  130.85  132.45  6155846
2010-01-05  131.68  131.85  130.10  130.85  6842471
2010-01-06  130.68  131.49  129.81  130.00  5605290
2010-01-07  129.87  130.25  128.91  129.55  5840569
2010-01-08  129.07  130.92  129.05  130.85  4197105
...            ...     ...     ...     ...      ...
2016-11-02  152.48  153.34  151.67  151.95  3074438
2016-11-03  152.51  153.74  151.80  152.37  2878803
2016-11-04  152.40  153.64  151.87  152.43  2470368
2016-11-07  153.99  156.11  153.84  155.72  3706214
2016-11-08  154.56     NaN     NaN  155.17  3921944
```

Pandas DataReader uses `Open`, `High`, `Low`, `Close` column name for candlesticks

```python
In [3]: price = df["Close"]
In [4]: price.resample("W").ohlc()
Out[4]:
                  open        high         low       close
Date
2010-01-10  132.449997  132.449997  129.550003  130.850006
2010-01-17  129.479996  132.309998  129.479996  131.779999
2010-01-24  134.139999  134.139999  125.500000  125.500000
2010-01-31  126.120003  126.330002  122.389999  122.389999
2010-02-07  124.669998  125.660004  123.000000  123.519997
...                ...         ...         ...         ...
2016-10-16  157.020004  157.020004  153.720001  154.449997
2016-10-23  154.770004  154.770004  149.630005  149.630005
2016-10-30  150.570007  153.350006  150.570007  152.610001
2016-11-06  153.690002  153.690002  151.949997  152.429993
2016-11-13  155.720001  155.720001  155.720001  155.720001

[358 rows x 4 columns]
```

Pandas uses `open`, `high`, `low`, `close` column name for candlesticks

We should change this on pandas side or on pandas-datareader side.

PS: on pandas_datareader side
https://github.com/pydata/pandas-datareader/issues/260