Python Pandas - whole row overflow with value of one previous column

New in pandas development. How to forward filling the DataFrame with the value contained in one previously seen column?

Standalone example:

import pandas as pd
import numpy as np
O = [1, np.nan, 5, np.nan]
H = [5, np.nan, 5, np.nan]
L = [1, np.nan, 2, np.nan]
C = [5, np.nan, 2, np.nan]
timestamps = ["2017-07-23 03:13:00", "2017-07-23 03:14:00", "2017-07-23 03:15:00", "2017-07-23 03:16:00"]
dict = {'Open': O, 'High': H, 'Low': L, 'Close': C}
df = pd.DataFrame(index=timestamps, data=dict)
ohlc = df[['Open', 'High', 'Low', 'Close']]

      

        
        
        
      

    

This gives the following DataFrame:

print(ohlc)
                     Open  High  Low  Close
2017-07-23 03:13:00   1.0   5.0  1.0    5.0
2017-07-23 03:14:00   NaN   NaN  NaN    NaN
2017-07-23 03:15:00   5.0   5.0  2.0    2.0
2017-07-23 03:16:00   NaN   NaN  NaN    NaN

      

        
        
        
      

    

I want to go from the last DataFrame to something like this:

                     Open  High  Low  Close
2017-07-23 03:13:00   1.0   5.0  1.0    5.0
2017-07-23 03:14:00   5.0   5.0  5.0    5.0
2017-07-23 03:15:00   5.0   5.0  2.0    2.0
2017-07-23 03:16:00   2.0   2.0  2.0    2.0

      

        
        
        
      

    

To have the previous value in "Close" move all rows until a new filled row appears. It's easy enough to fill the Close column like this:

column2fill = 'Close'
ohlc[column2fill] = ohlc[column2fill].ffill()
print(ohlc)
                     Open  High  Low  Close
2017-07-23 03:13:00   1.0   5.0  1.0    5.0
2017-07-23 03:14:00   NaN   NaN  NaN    5.0
2017-07-23 03:15:00   5.0   5.0  2.0    2.0
2017-07-23 03:16:00   NaN   NaN  NaN    2.0

      

        
        
        
      

    

But is there a way to fill lines 03:14:00 and 03:16:00 with the Close value of these lines? And is there a way to do it in one step, using a single forward fill instead of filling the Close column first?