Just had something odd come up while trying to come up with something for this SO question.
If we use DataFrame.apply() to try and create dictionaries from the rows of a dataframe, it seems to return the dict.values() method rather than returning the dict itself.
df = pd.DataFrame({'k': ['a', 'b', 'c'], 'v': [1, 2, 3]})
df.apply(lambda row: {row['k']: row['v']}, axis=1)
Out[52]:
0 <built-in method values of dict object at 0x07...
1 <built-in method values of dict object at 0x03...
2 <built-in method values of dict object at 0x07...
dtype: object
Looks like it's probably something to do with trying to grab the values attribute when the output of the applied function is a Series or something similar.
Library versions:
pd.show_versions()
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.6.final.0
python-bits: 32
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 30 Stepping 5, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
pandas: 0.15.0
nose: 1.3.4
Cython: 0.21
numpy: 1.9.0
scipy: 0.14.0
statsmodels: 0.5.0
IPython: 2.3.0
sphinx: 1.2.3
patsy: 0.3.0
dateutil: 1.5
pytz: 2014.7
bottleneck: None
tables: 3.1.1
numexpr: 2.3.1
matplotlib: 1.4.2
openpyxl: 1.8.5
xlrd: 0.9.3
xlwt: 0.7.5
xlsxwriter: 0.5.7
lxml: 3.4.0
bs4: 4.3.2
html5lib: 0.999
httplib2: None
apiclient: None
rpy2: None
sqlalchemy: 0.9.7
pymysql: None
psycopg2: None
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