python - ternary expression dependent on two columns -

say have data set similar to:

df = pd.dataframe({'time':[1,2,3,4,5,6,7,8,9,10],'value': [1,3,5,5,6,8,9,5,6,7]}) 

giving:

   time  value 0     1      1 1     2      3 2     3      5 3     4      5 4     5      6 5     6      8 6     7      9 7     8      4 8     9      6 9    10      7 

what want set values > 5 equal 0 in "values" when "time" > 5. end product be:

   time  value 0     1      1 1     2      3 2     3      5 3     4      5 4     5      6 5     6      0 6     7      0 7     8      4 8     9      0 9    10      0 

i have been using code:

 df.value = [0 if x > 5 else x x in df.value]  

which changes all values 0 if > 5. have tried adding things code such as:

  df.value = [0 if x > 5 in df.value , x > 5 in df.time else x x in df.value] 

but can't seem right combination of words/code yield want. suggestions? thank you.

i find easy use numpy.where in these situations:

import numpy np df['value'] = np.where((df.time > 5) & (df.value > 5),0,df.value) 

*to add answer, in case there more conditions want satisfy can add them above code like:

df['value'] = np.where((df.time > 500) & (df.value > 5) | (df.time > 5) & (df.value < 1),0,df.value) 

just add " | " , write next condition.