Pandas - fill NaN based on the previous value of another cell

I have some stocks data in a dataframe that I'm resampling, which results in some NaN values. Here's a section of the raw feed:

In [34]: feeddfOut[34]:                      open   high    low  close  volumedate2017-12-03 07:00:00  14.46  14.46  14.46  14.46   250002017-12-03 07:01:00  14.46  14.46  14.46  14.46   209172017-12-03 07:06:00  14.50  14.50  14.50  14.50    20002017-12-03 07:12:00  14.50  14.56  14.50  14.56   17000

The feed is supposed to be minute-by-minute, but when there's not data available, the row is skipped. When resampling the dataframe and aggregating for the opens, highs, lows, and closes, it looks like this:

In [35]: feeddf.resample('3Min').agg({'open': 'first', 'high': 'max',  'low': 'min',  'close': 'last'})Out[35]:                      open   high    low  closedate2017-12-03 07:00:00  14.46  14.46  14.46  14.462017-12-03 07:03:00    NaN    NaN    NaN    NaN2017-12-03 07:06:00  14.50  14.50  14.50  14.502017-12-03 07:09:00    NaN    NaN    NaN    NaN2017-12-03 07:12:00  14.50  14.56  14.50  14.56

My question: I want to forward-fill the missing data based on the last row's close value. df.fillna(method='ffill') is not helping because it fills it based on the last value on the same column. Any idea?