Insert value 1 in pandas Dataframe till one condition is met [Python]-CodePudding

I have an Dataframe with columns below minus the position column and my goal is to create a new column with name position that equals 1 when signal equals 1 and the Closeprice from the row that signals equals 1 is larger than the ATR. When Closeprice falls below the value of the ATR where Signals equal 1 the position will be equal to Zero.

Do you have any tips how I can do this?

CodePudding user response：

We can do it using the select method from numpy :

>>> import numpy as np

>>> condlist = [(df['Signal'] == 1) & (df['Closeprice'] > df['ATR']), 
...             (df['Signal'] == 1) & (df['Closeprice'] < df['ATR'])]
>>> choicelist = [1, 0]            
>>> df['Position'] = np.select(condlist, choicelist, default=0)
>>> df
    Signal  Closeprice  ATR     Position
0   1       10           5      1
1   0       20          15      0
2   0       30          25      0
3   0       40          50      0

On the second line the Position is 0 since the Signal value is 0.

CodePudding user response：

Use boolean mask. Create masks for your 2 conditions:

import numpy as np

m1 = df['Signal'].eq(1) & df['Closeprice'].gt(df['ATR'])
m2 = m1.shift() & df['Closeprice'].gt(df['ATR'])

df['Position'] = np.where(m1|m2, 1, 0)

Output:

>>> df
   Signal  Closeprice  ATR  Position
0       1          10    5         1  # True for m1 mask
1       0          20   15         1  # True for m2 mask
2       0          30   25         0
3       0          40   50         0