def dshape_from_pandas_helper(col):
"""Return an object from datashape.coretypes given a column from a pandas
dataframe.
"""
if (isinstance(col.dtype, type(pd.Categorical.dtype)) or
isinstance(col.dtype, pd.api.types.CategoricalDtype) or
cudf and isinstance(col.dtype, cudf.core.dtypes.CategoricalDtype)):
# Compute category dtype
categories = np.array(col.cat.categories)
if categories.dtype.kind == 'U':
categories = categories.astype('object')
cat_dshape = datashape.dshape('{} * {}'.format(
len(col.cat.categories),
categories.dtype,
))
return datashape.Categorical(categories,
type=cat_dshape,
ordered=col.cat.ordered)
elif col.dtype.kind == 'M':
tz = getattr(col.dtype, 'tz', None)
if tz is not None:
# Pandas stores this as a pytz.tzinfo, but DataShape wants a string
tz = str(tz)
return datashape.Option(datashape.DateTime(tz=tz))
elif isinstance(col.dtype, RaggedDtype):
return col.dtype
dshape = datashape.CType.from_numpy_dtype(col.dtype)
dshape = datashape.string if dshape == datashape.object_ else dshape
if dshape in (datashape.string, datashape.datetime_):
return datashape.Option(dshape)
return dshape
def dshape_from_pandas_helper(col):
if isinstance(col.dtype, type(pd.Categorical.dtype)):
cat_dshape = datashape.dshape('{} * {}'.format(
len(col.cat.categories),
col.cat.categories.dtype,
))
return datashape.Categorical(col.cat.categories.values,
type=cat_dshape,
ordered=col.cat.categorical.ordered)
elif col.dtype.kind == 'M':
tz = getattr(col.dtype, 'tz', None)
if tz is not None:
# Pandas stores this as a pytz.tzinfo, but DataShape wants a string
tz = str(tz)
return datashape.Option(datashape.DateTime(tz=tz))
dshape = datashape.CType.from_numpy_dtype(col.dtype)
dshape = datashape.string if dshape == datashape.object_ else dshape
if dshape in (datashape.string, datashape.datetime_):
return datashape.Option(dshape)
return dshape
