MatPlotLib Key Error: 0 When Annotating - python-3.x

Question

In this bit of code, I am trying to create a bar chart with one bar (as the "total" bar which will be placed next to other bars) with a slice of a data frame. It works for the other slice of the data frame, but for the "total" slice (which is just one row), I keep getting this "Key Error: 0":
x_4t = dfCOPN['Percent'][-1:]
y_4t = dfCOPN['index'][-1:]
ind4t = np.arange(len(y_4t))
...
for i, text in enumerate(ind4t):
if x_4t<72:
ax4t.annotate(str(x_4t)[:-2]+"%", xy=(x_4t+2,ind4t+0.4),fontsize=9, color='black', va='center', ha='left')
elif x_4t>=72:
ax4t.annotate(str(x_4t[i])[:-2]+"%", xy=(x_4t[i]-2,ind4t[i]+0.4),fontsize=9, color='white', va='center', ha='right')
Here's the error:
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-42-e192a1699cc5> in <module>()
174 # for i, text in enumerate(ind4t):
--> 175 if x_4t<72:
176 ax4t.annotate(str(x_4t)[:-2]+"%", xy=(x_4t+2,ind4t+0.4),fontsize=9, color='black', va='center', ha='left')
C:\Users\m\Anaconda3\lib\site-packages\pandas\core\generic.py in __nonzero__(self)
729 "Use a.empty, a.bool(), a.item(), a.any() or a.all()."
--> 730 .format(self.__class__.__name__))
731
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
During handling of the above exception, another exception occurred:
KeyError Traceback (most recent call last)
<ipython-input-42-e192a1699cc5> in <module>()
185 except:
186 for i, text in enumerate(ind4t):
--> 187 ax4t.annotate(str(x_4t[i])[:-2]+"%", xy=(x_4t[i]+2,ind4t[i]+0.4),fontsize=9, color='black', va='center', ha='left')
188 for i, text in enumerate(ind5t):
189 ax5t.annotate(str(x_5t[i])[:-2]+"%", xy=(x_5t[i]+2,ind5t[i]+0.4),fontsize=9, color='black', va='center', ha='left')
C:\Users\m\Anaconda3\lib\site-packages\pandas\core\series.py in __getitem__(self, key)
549 def __getitem__(self, key):
550 try:
--> 551 result = self.index.get_value(self, key)
552
553 if not np.isscalar(result):
C:\Users\m\Anaconda3\lib\site-packages\pandas\core\index.py in get_value(self, series, key)
1721
1722 try:
-> 1723 return self._engine.get_value(s, k)
1724 except KeyError as e1:
1725 if len(self) > 0 and self.inferred_type in ['integer','boolean']:
pandas\index.pyx in pandas.index.IndexEngine.get_value (pandas\index.c:3204)()
pandas\index.pyx in pandas.index.IndexEngine.get_value (pandas\index.c:2903)()
pandas\index.pyx in pandas.index.IndexEngine.get_loc (pandas\index.c:3843)()
pandas\hashtable.pyx in pandas.hashtable.Int64HashTable.get_item (pandas\hashtable.c:6525)()
pandas\hashtable.pyx in pandas.hashtable.Int64HashTable.get_item (pandas\hashtable.c:6463)()
KeyError: 0
I'll send a complete example if needed, but I just wanted to see if the answer is obvious enough to not do so.
Thanks in advance!

Answer 1

TL;DR; use iloc
x4t.iloc[0]
The problem is that pd.Series use index not position indexing via []. This is a powerful idea/bit of syntax as frequently when you are working with a Series the value of the index is the interesting thing, not the position in the Series (ex a date index), however if you expect that Series / DataFrames will behave exactly like a numpy array you will have issues (I speak from experience here).