Solution: Remove the duplicate indexes from the series (i.e. dicoprix) and keep them unique

You got it, the problem is in dicoprix[df.loc[x,'medicament1']]

There are duplicates in the indexes of the series dicoprix, which cannot be put as one value in the dataframe.

Below is the demonstration:

In [1]: 
import pandas as pd
dum_ser = pd.Series(index=['a','b','b','c'], data=['apple', 'balloon', 'ball', 'cat' ])

[Out 1]
a      apple
b    balloon
b       ball
c        cat
dtype: object


In [2]: 
df = pd.DataFrame({'letter':['a','b','c','d'], 'full_form':['aley', 'byue', 'case', 'cible']}, index=[0,1,2,3])
df

Out [2]:
    letter  full_form
0   a   aley
1   b   byue
2   c   case
3   d   cible

Following command will run fine as 'a' is not the duplicate index in dum_ser series

In [3]: 
df.loc[0,'full_form'] = dum_ser['a']
df

Out [3]:
    letter  full_form
0   a   apple
1   b   byue
2   c   case
3   d   apple

Error will occur when the command tries to insert two records from the series(as there are two records for the index b in dum_ser, to check run the command dum_ser['b']) into one value-space of the DataFrame. Refer below

In [4]:
df.loc[1,'full_form'] = dum_ser['b']

Out [4]:
    ---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-4-af11b9b3a776> in <module>()
----> 1 df.loc['b','full_form'] = dum_ser['b']

C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py in __setitem__(self, key, value)
    187             key = com._apply_if_callable(key, self.obj)
    188         indexer = self._get_setitem_indexer(key)
--> 189         self._setitem_with_indexer(indexer, value)
    190 
    191     def _validate_key(self, key, axis):

C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py in _setitem_with_indexer(self, indexer, value)
    635                 # setting for extensionarrays that store dicts. Need to decide
    636                 # if it's worth supporting that.
--> 637                 value = self._align_series(indexer, Series(value))
    638 
    639             elif isinstance(value, ABCDataFrame):

C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py in _align_series(self, indexer, ser, multiindex_indexer)
    775             return ser.reindex(ax)._values
    776 
--> 777         raise ValueError('Incompatible indexer with Series')
    778 
    779     def _align_frame(self, indexer, df):

ValueError: Incompatible indexer with Series

The above-written line of the code is the one of the iteration from the for loop i.e. for x=1

Solution: Remove the duplicate indexes from the series (i.e. dum_ser here) and keep them unique

I had a same problem, in

for i, (result, status) in enumerate(results):
    df.at[i, 'response'] = result

And this error, how I understand, can mean that type of value what you try assign does not match the column type in the dataframe
In my case result was a dict, because it response post request
Solution is easy - cast type to string:

for i, (result, status) in enumerate(results):
        df.at[i, 'response'] = str(result)

Use indexing like this:

dicoprix[df.loc[x,'medicament1']][0]

It did work for me.