How to conditionally select previous row's value in python?

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I want to select the previous row's value only if it meets a certain condition E.g.

df:
Value  Marker  
10  0  
12  0  
50  1  
42  1  
52  0  
23  1

I want to select the previous row's value where marker == 0if the current value marker == 1.

Result:

df:
Value  Marker  Prev_Value  
10  0  nan
12  0  nan
50  1  12
42  1  12
52  0  nan
23  1  52

I tried: df[prev_value] = np.where(df[marker] == 1, df[Value].shift(), np.nan) but that does not take conditional previous value like i want.

pandas numpy python
2 Answers
condition = (df.Marker.shift() == 0) & (df.Marker == 1)
df['Prev_Value'] = np.where(condition, df.Value.shift(), np.nan)

Output:

df
   Value  Marker  Prev_Value
0     10       0         NaN
1     12       0         NaN
2     50       1        12.0
3     42       1         NaN
4     52       0         NaN
5     23       1        52.0
user_37405450

You could try this:

df['Prev_Value']=np.where(dataframe['Marker'].diff()==1,dataframe['Value'].shift(1, axis = 0),np.nan)

Output:

df

   Value  Marker  Prev_Value
0     10       0   NaN
1     12       0   NaN
2     50       1  12.0
3     42       1   NaN
4     52       0   NaN
5     23       1  52.0

If you want to get the previous non-1 marker value, if marker==1, you could try this:

prevro=[]
for i in reversed(df.index):

    if df.iloc[i,1]==1:
        prevro_zero=df.iloc[0:i,0][df.iloc[0:i,1].eq(0)].tolist()
        if len(prevro_zero)>0:
            prevro.append(prevro_zero[len(prevro_zero)-1])
        else:
            prevro.append(np.nan)
    else:
        prevro.append(np.nan)
        
df['Prev_Value']=list(reversed(prevro))

print(df)

Output:

   Value  Marker  Prev_Value
0     10       0         NaN
1     12       0         NaN
2     50       1        12.0
3     42       1        12.0
4     52       0         NaN
5     23       1        52.0
user_136762020
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