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Description
Code Sample, a copy-pastable example if possible
>>> s = pandas.Series([{0: 'a', 1: 'b'}]) >>> s 0 {0: 'a', 1: 'b'} dtype: object >>> s.str.get(-1) Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/mgarcia/.anaconda3/lib/python3.6/site-packages/pandas/core/strings.py", line 1556, in get result = str_get(self._data, i) File "/home/mgarcia/.anaconda3/lib/python3.6/site-packages/pandas/core/strings.py", line 1264, in str_get return _na_map(f, arr) File "/home/mgarcia/.anaconda3/lib/python3.6/site-packages/pandas/core/strings.py", line 156, in _na_map return _map(f, arr, na_mask=True, na_value=na_result, dtype=dtype) File "/home/mgarcia/.anaconda3/lib/python3.6/site-packages/pandas/core/strings.py", line 171, in _map result = lib.map_infer_mask(arr, f, mask.view(np.uint8), convert) File "pandas/_libs/src/inference.pyx", line 1482, in pandas._libs.lib.map_infer_mask File "/home/mgarcia/.anaconda3/lib/python3.6/site-packages/pandas/core/strings.py", line 1263, in <lambda> f = lambda x: x[i] if len(x) > i >= -len(x) else np.nan KeyError: -1Problem description
str.get is designed for strings, but also useful with other structures like lists, for which works fine. When the values of the Series contain a dict, str.get tries to get the key provided as an index from the dictionary and fails with a KeyError.
I think it's more consistent with the rest of pandas to simply return numpy.nan when this happens.
Expected Output
>>> s = pandas.Series([{0: 'a', 1: 'b'}]) >>> s 0 {0: 'a', 1: 'b'} dtype: object >>> s.str.get(-1) 0 NaN Output of pd.show_versions()
INSTALLED VERSIONS
commit: fa231e8
python: 3.6.4.final.0
python-bits: 64
OS: Linux
OS-release: 4.8.13-100.fc23.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_GB.utf8
LOCALE: en_GB.UTF-8
pandas: 0.23.0.dev0+740.gfa231e8.dirty
pytest: 3.1.3
pip: 9.0.1
setuptools: 38.5.1
Cython: 0.27.3
numpy: 1.14.0
scipy: 1.0.0
pyarrow: 0.8.0
xarray: 0.10.0
IPython: 6.2.1
sphinx: 1.5
patsy: 0.5.0
dateutil: 2.6.1
pytz: 2018.3
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.4
feather: 0.4.0
matplotlib: 2.1.2
openpyxl: 2.5.0
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.2
lxml: 4.1.1
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: 1.2.1
pymysql: 0.8.0
psycopg2: None
jinja2: 2.10
s3fs: 0.1.3
fastparquet: 0.1.4
pandas_gbq: None
pandas_datareader: None