TypeError: 'function' object is not subscriptable[Python3]

i am calling the method build_feature_category like this

obt=ObliviousTree(data,"hello",True)#data is pandas.DataFrame
obt.load_tree() 
obt.build_feature_category()

but it is giving this error,i think it has to do with using instance variable before they get created but i am not quite sure where i am doing it wrong: this is the error i am getting after calling those method above on that class

   label  session  week  hour  category       item    dwell
      -1        1     0    10         0  214536502    0.000
      -1        1     0    10         0  214536500  180.591
      -1        1     0    10         0  214536506   37.130                               -1         1     0    10         0  214577561  133.308
      -1        2     0    13         0  214662742    0.000
      -1        2     0    13         0  214662742   41.759
      -1        2     0    13         0  214825110   78.073
      -1        2     0    13         0  214757390   73.264
      -1        2     0    14         0  214757407   47.537
      -1        2     0    14         0  214551617  118.642
['label', 'session', 'week', 'hour', 'category', 'item', 'dwell']
Traceback (most recent call last):
File "dataloader.py", line 39, in <module>
obt.build_feature_category()
File "/sdfs/challenge/odg/ObliviousTree.py",  line 24, in  build_feature_category
self.feature_name_values[feature_name]=np.unique[self.data[feature_name]]
TypeError: 'function' object is not subscriptable



import numpy as np
class ObliviousTree:

'This is an implementation of Oblvious Tree'

def __init__(self,data=[],func="C.45",autoload=False):
    self.data=data
    self.split_funct=func
    self.autoload=autoload
    self.feature_names=self.data.columns.tolist()
    self.feature_name_values={}


def load_tree(self):
    if not self.autoload:
        print("skipped autoloading")
    else:
        print(self.data)
        print(self.feature_names)


def build_feature_category(self):
    for feature_name in self.feature_names:
        self.feature_name_values[feature_name]=np.unique[self.data[feature_name]]
    print(self.feature_name_values)