Pandas dataframe assign 0 with all the value after first non-nan value

Question

I have a dataframe with several columns and a series whose value are the index of the first non-nan value of the dataframe:

dataframe x:

    a    b    c    d    e     f    g    h 
1   nan  nan  2    nan  nan  nan  nan  nan
2   nan  2    nan  10   23   nan  nan  nan
3   3    nan  23   42   232  3    nan  5

series y:

a   3
b   2
c   1
d   2
e   2
f   3
g   nan
h   3

now I want to assign 0 with all the value after first non-nan value(include the first non-nan value) by the value of series(whose value are the index of the first non-nan value of the dataframe x)

result is

    a    b    c    d    e     f    g    h 
1   nan  nan  0    nan  nan  nan  nan  nan
2   nan  0    0    0    0    nan  nan  nan
3   0    0    0    0    0    0    nan  0

I use applymap to deal with it,but applymap seems not to deal with index information,here is my code:

def mycode(x,y)
if x.index<=Y:
        return 0
    else:
        return x

cal = x.applymap(lambda x: mycode(x,y))

Answer 1

You can use ffill ( fillna with method='ffill' ) with clip :

x = x.ffill().clip(0,0)

Alternative solutions with boolean mask and where or mask :

x = x.where(x.ffill().isnull(), 0)

x = x.mask(x.ffill().notnull(), 0)

---

print (x)
     a    b    c    d    e    f   g    h
1  NaN  NaN  0.0  NaN  NaN  NaN NaN  NaN
2  NaN  0.0  0.0  0.0  0.0  NaN NaN  NaN
3  0.0  0.0  0.0  0.0  0.0  0.0 NaN  0.0

Detail:

print (x.ffill())
     a    b     c     d      e    f   g    h
1  NaN  NaN   2.0   NaN    NaN  NaN NaN  NaN
2  NaN  2.0   2.0  10.0   23.0  NaN NaN  NaN
3  3.0  2.0  23.0  42.0  232.0  3.0 NaN  5.0

print (x.ffill().isnull())
       a      b      c      d      e      f     g      h
1   True   True  False   True   True   True  True   True
2   True  False  False  False  False   True  True   True
3  False  False  False  False  False  False  True  False