Dataframe：比较列值和下面的一行

Question

我有一个带方向的数据框：

        Direction: 
2/01/19 None
1/31/19 Upward
1/30/19 None
1/29/19 None
1/28/19 Downward
1/27/19 None
1/26/19 None
1/25/19 Upward

我想根据以下条件（从 1/25/19 开始）创建一个 "Momentum" 列：
1. 如果相应日期的方向是 'Upward'，然后将值设置为 'Upward'
2. 如果 Momentum 下面的第一行是 "Upward" 将其设置为 'Upward'
3.如果对应日期的Direction为'Downward'，则设置为'None'
4.否则，设置为'None'

换句话说，一旦你达到 'Upward' 状态，它应该保持这种状态直到你达到 'Downward'

结果应如下所示：

        Direction:  Momentum:
2/01/19 None        Upward
1/31/19 Upward      Upward
1/30/19 None        None
1/29/19 None        None
1/28/19 Downward    None
1/27/19 None        Upward
1/26/19 None        Upward
1/25/19 Upward      Upward

有没有不用循环的方法？

Answer 1

这是一种方法。喝杯咖啡后我会尝试改进它...

df['Momentum:'] = None  # Base case.
df.loc[df['Direction:'].eq('Upward'), 'Momentum:'] = 'Upward'
df.loc[df['Direction:'].eq('Downward'), 'Momentum:'] = 1  # Temporary value.
df.loc[:, 'Momentum:'] = df['Momentum:'].bfill()
df.loc[df['Momentum:'].eq(1), 'Momentum:'] = None  # Set temporary value back to None.
>>> df
        Direction: Momentum:
2/01/19       None    Upward
1/31/19     Upward    Upward
1/30/19       None      None
1/29/19       None      None
1/28/19   Downward      None
1/27/19       None    Upward
1/26/19       None    Upward
1/25/19     Upward    Upward

Answer 2

通过新数据编辑的答案首先回填 None 值，然后将 Downward 替换为 Nones:

#first replace strings Nones to None type
df['Direction:'] = df['Direction:'].mask(df['Direction:'] == 'None', None)

df['Momentum:'] = df['Direction:'].bfill().mask(lambda x: x == 'Downward', None)

或：

s = df['Direction:'].bfill()
df['Momentum:'] = s.mask(s == 'Downward', None)

print (df)
        Direction:  Momentum:
2/01/19       None     Upward
1/31/19     Upward     Upward
1/30/19       None       None
1/29/19       None       None
1/28/19   Downward       None
1/27/19       None     Upward
1/26/19       None     Upward
1/25/19     Upward     Upward

旧答案：

使用 numpy.where 和链式布尔掩码比较移位值和 | 的原始值进行按位或：

mask = df['Direction:'].eq('Upward') | df['Direction:'].shift(-1).eq('Upward')
df['Momentum:'] = np.where(mask, 'Upward', None)
print (df)
        Direction: Momentum:
1/31/19       None    Upward
1/30/19     Upward    Upward
1/29/19       None      None
1/28/19       None      None
1/27/19   Downward      None
1/26/19       None    Upward
1/25/19     Upward    Upward

Dataframe：比较列值和下面的一行

Dataframe: compare column value and one row below

python

pandas

dataframe

np