def read_metadata(*args, **kwargs):
meta, stats, parts, index = ArrowEngine.read_metadata(*args, **kwargs)
# If `strings_to_categorical==True`, convert objects to int32
strings_to_cats = kwargs.get("strings_to_categorical", False)
new_meta = cudf.DataFrame(index=meta.index)
for col in meta.columns:
if meta[col].dtype == "O":
new_meta[col] = as_column(
meta[col], dtype="int32" if strings_to_cats else "object")
else:
new_meta[col] = as_column(meta[col])
return (new_meta, stats, parts, index)
def read_metadata(*args, **kwargs):
meta, stats, parts = ArrowEngine.read_metadata(*args, **kwargs)
# If `strings_to_categorical==True`, convert objects to int32
strings_to_cats = kwargs.get("strings_to_categorical", False)
dtypes = {}
for col in meta.columns:
if meta[col].dtype == "O":
dtypes[col] = "int32" if strings_to_cats else "object"
meta = cudf.DataFrame.from_pandas(meta)
for col, dtype in dtypes.items():
meta[col] = meta[col].astype(dtype)
return (meta, stats, parts)