def write_dataframe(df, path):
'''
Write a pandas.DataFrame to Feather format
'''
writer = ext.FeatherWriter(path)
# TODO(wesm): pipeline conversion to Arrow memory layout
for i, name in enumerate(df.columns):
col = df.iloc[:, i]
if not isinstance(name, six.string_types):
name = str(name)
writer.write_array(name, col)
writer.close()
def write_dataframe(df, path):
'''
Write a pandas.DataFrame to Feather format
'''
path = unicode(path)
writer = ext.FeatherWriter(path)
if isinstance(df, pd.SparseDataFrame):
df = df.to_dense()
if not df.columns.is_unique:
raise ValueError("cannot serialize duplicate column names")
# TODO(wesm): pipeline conversion to Arrow memory layout
for i, name in enumerate(df.columns):
col = df.iloc[:, i]
if pdapi.is_object_dtype(col):
inferred_type = pd.lib.infer_dtype(col)
msg = ("cannot serialize column {n} "
"named {name} with dtype {dtype}".format(
n=i, name=name, dtype=inferred_type))
if inferred_type in ['mixed']:
# allow columns with nulls + an inferable type
inferred_type = pd.lib.infer_dtype(col[col.notnull()])
if inferred_type in ['mixed']:
raise ValueError(msg)
elif inferred_type not in ['unicode', 'string']:
raise ValueError(msg)
if not isinstance(name, six.string_types):
name = str(name)
writer.write_array(name, col)
writer.close()