Python 如何在 pandas 上应用 ffill() groupby 和有条件

我想有条件地填写之前的值，比如ffill().

例如，如果[‘day’]列为‘None’，我想对Groupby应用[‘Close’]ffill().

我附上了下面的例子.

df = pd.DataFrame({'name' : ['AAPL','AAPL','AAPL','AAPL','AAPL','AAPL','MSFT','MSFT','MSFT','MSFT','MSFT','MSFT'],
                   'day' : [None,'Fri', None, None, 'Mon', 'Thue', None,'Fri', None, None, 'Mon', 'Thue',],
                   'close' : [np.nan, 174.49, np.nan, np.nan, 175.84, np.nan, np.nan, 128.11, np.nan, np.nan, 128.93, np.nan]
                   })

   # df
   # Out[46]: 
   # AAPL  None     NaN
   # AAPL   Fri  174.49
   # AAPL  None     NaN
   # AAPL  None     NaN
   # AAPL   Mon  175.84
   # AAPL  Thue     NaN
   # MSFT  None     NaN
   # MSFT   Fri  128.11
   # MSFT  None     NaN
   # MSFT  None     NaN
   # MSFT   Mon  128.93
   # MSFT  Thue     NaN



# What I wannt
#    name   day   close
#    AAPL  None     NaN
#    AAPL   Fri  174.49
#    AAPL  None  174.49 <- if 'day' is None then wnat to ffill() 
#    AAPL  None  174.49 <- if 'day' is None then wnat to ffill() 
#    AAPL   Mon  175.84
#    AAPL  Thue     NaN
#    MSFT  None     NaN
#    MSFT   Fri  128.11
#    MSFT  None  128.11 <- if 'day' is None then wnat to ffill() 
#    MSFT  None  128.11 <- if 'day' is None then wnat to ffill() 
#    MSFT   Mon  128.93
#    MSFT  Thue     NaN