Getting IndexError in pandas dataframe

This code is giving me the following error in Python 3.6 pandas 23.x

IndexError: only integers, slices (:), ellipsis (...), numpy.newaxis (None) and integer or boolean arrays are valid indices

on line

ostype[asset] = dfx.ostype(0) # get same error with [0]

I'm not clear why. Here is the entire code, running in Jupyter.

from collections import defaultdict
assets = defaultdict(list)
warnings = defaultdict(list)
result = defaultdict(list)
for asset in servers:
    result[asset] = 'Fail'
    # This filters to only the records for this asset
    dfx = df[df['server'] == asset]
    ostype[asset] = dfx.ostype(0) ### Error
    for ntp in dfx.source:
        if ntp in valid_ntp_servers:
            result[asset] = 'Pass'
            assets[asset].append(ntp)
        else:
            warnings[asset].append(ntp)

I put the code in a separate Jupyter cell and get exactly the expected result

test = dfx.ostype[0]
print(test)

linux

Additional testing

for asset in servers[:5]:
    dfx = df[df['server'] == asset]
    test = dfx.ostype[0]
    print(dfx)
    print(test)

Results in the following exception

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-388-010067e6d390> in <module>()
      2 for asset in servers[:5]:
      3     dfx = df[df['server'] == asset]
----> 4     test = dfx.ostype[0]
      5     print(dfx)
      6     print(test)

~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\series.py in __getitem__(self, key)
    765         key = com._apply_if_callable(key, self)
    766         try:
--> 767             result = self.index.get_value(self, key)
    768 
    769             if not is_scalar(result):

~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\indexes\base.py in get_value(self, series, key)
   3116         try:
   3117             return self._engine.get_value(s, k,
-> 3118                                           tz=getattr(series.dtype, 'tz', None))
   3119         except KeyError as e1:
   3120             if len(self) > 0 and self.inferred_type in ['integer', 'boolean']:

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_value()

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_value()

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.get_item()

pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.get_item()

KeyError: 0

The output from the loop looks like:

  ostype        date   server            source
0  linux  2018-08-14  abcde01  east.time.zzzzzz
1  linux  2018-08-14  abcde01       ntp7.zzzzzz
2  linux  2018-08-14  abcde01       ntp9.zzzzzz
3  linux  2018-08-14  abcde01       ntp0.zzzzzz
linux

Using .iloc[0] as suggested in the comments works in my test loop, but fails when I use it in my program.

IndexError                                Traceback (most recent call last)
<ipython-input-390-fce3c88d6e8e> in <module>()
      6     result[asset] = 'Fail'
      7     dfx = df[df['server'] == asset]
----> 8     ostype[asset] = dfx.ostype.iloc[0]
      9     for ntp in dfx.source:
     10         if ntp in valid_ntp_servers:

IndexError: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices