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import pandas c = pandas.Categorical(["A", "B", "C", "D"], categories=["A", "B", "C", "D"]) df = pandas.DataFrame({"x": c}) bytes = df.to_msgpack() pandas.read_msgpack(bytes)
<ipython-input-1-ec1dc8306f4c> in <module>() 1 import pandas 2 df = pandas.DataFrame({"x": pandas.Categorical(["A", "B", "C", "D"], categories=["A", "B", "C", "D"])}) ----> 3 pandas.read_msgpack(df.to_msgpack()) /home/pwaller/.local/lib/python3.4/site-packages/pandas/io/packers.py in read_msgpack(path_or_buf, encoding, iterator, **kwargs) 153 try: 154 fh = compat.BytesIO(path_or_buf) --> 155 return read(fh) 156 finally: 157 if fh is not None: /home/pwaller/.local/lib/python3.4/site-packages/pandas/io/packers.py in read(fh) 131 132 def read(fh): --> 133 l = list(unpack(fh, encoding=encoding, **kwargs)) 134 if len(l) == 1: 135 return l[0] pandas/msgpack/_unpacker.pyx in pandas.msgpack._unpacker.Unpacker.__next__ (pandas/msgpack/_unpacker.cpp:5277)() pandas/msgpack/_unpacker.pyx in pandas.msgpack._unpacker.Unpacker._unpack (pandas/msgpack/_unpacker.cpp:4268)() /home/pwaller/.local/lib/python3.4/site-packages/pandas/io/packers.py in decode(obj) 526 placement=placement) 527 --> 528 blocks = [create_block(b) for b in obj['blocks']] 529 return globals()[obj['klass']](BlockManager(blocks, axes)) 530 elif typ == 'datetime': /home/pwaller/.local/lib/python3.4/site-packages/pandas/io/packers.py in <listcomp>(.0) 526 placement=placement) 527 --> 528 blocks = [create_block(b) for b in obj['blocks']] 529 return globals()[obj['klass']](BlockManager(blocks, axes)) 530 elif typ == 'datetime': /home/pwaller/.local/lib/python3.4/site-packages/pandas/io/packers.py in create_block(b) 513 514 def create_block(b): --> 515 values = unconvert(b['values'], dtype_for(b['dtype']), 516 b['compress']).reshape(b['shape']) 517 /home/pwaller/.local/lib/python3.4/site-packages/pandas/io/packers.py in dtype_for(t) 181 if t in dtype_dict: 182 return dtype_dict[t] --> 183 return np.typeDict[t] 184 185 c2f_dict = {'complex': np.float64, KeyError: 'category'
A DataFrame containing a categorical variable x.
x
pd.show_versions()
Note I have also tested 0.18.0rc1.
INSTALLED VERSIONS ------------------ commit: None python: 3.4.3.final.0 python-bits: 64 OS: Linux OS-release: 4.2.0-30-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_GB.UTF-8 pandas: 0.17.1 nose: 1.3.6 pip: 8.1.0 setuptools: 20.0 Cython: 0.23.4 numpy: 1.10.2 scipy: 0.16.1 statsmodels: 0.6.1 IPython: 4.1.1 sphinx: None patsy: 0.4.1 dateutil: 2.5.0 pytz: 2015.7 blosc: None bottleneck: None tables: 3.2.2 numexpr: 2.4.6 matplotlib: 1.5.0 openpyxl: None xlrd: None xlwt: None xlsxwriter: 0.7.3 lxml: None bs4: 4.3.2 html5lib: 0.999 httplib2: 0.9 apiclient: None sqlalchemy: 1.0.11 pymysql: None psycopg2: None Jinja2: None
The text was updated successfully, but these errors were encountered:
dupe of #7621 being worked on in #12191
pull-requests are welcome!
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Ah, apologies, I searched issues but didn't see the pull request!
yeah that's the PR, I updated to include the original issue.
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A copy-pastable code sample
What happens
Expected Output
A DataFrame containing a categorical variable
x
.output of
pd.show_versions()
Note I have also tested 0.18.0rc1.
The text was updated successfully, but these errors were encountered: