ID  | DEAD     | 2009-10 | ...    | 2016-10
 -----------------------------------------
  1   | 2018-11  | 5.4     | ...    | 6.5
  2   | 2014-01  | 0.5     | ...    | 5.2
  ...
  N   | 2008-11  | 8.6     | ...    | 1.3

ID  | DEAD     | 2009-10 | ...    | 2016-10
 -----------------------------------------
  1   | 2018-11  | 5.4     | ...    | 6.5
  2   | 2014-01  | 0.5     | ...    | NaN
  ...
  N   | 2008-11  | 8.6     | ...    | NaN

time = df.columns[2:] # take the header as an index
time = pd.DataFrame(time)
time.columns = ['Dummy']
time['Dummy'] = pd.to_datetime(time.Dummy) # Convert index argument to datetime

df['DEAD'] = pd.to_datetime(tore.DEAD) # Convert column 'DEAD' to datetime



lists = []
for i in range(397):
    row = []
    for j in range(20000):
        if time.iloc[i,0] <= df.iloc[j,0]:
            newlist = 1
        else:
            newlist = np.NaN
        row.append(newlist)
    lists.append(row)

lists = pd.DataFrame(lists)
lists = lists.transpose()