ni-todo-spot opened a new issue, #13353: URL: https://github.com/apache/arrow/issues/13353
Hey All, I was wondering what is the most elegant & efficient way of casting a decimal column of a table into a float type, when converting a table into a pandas dataframe? In the code I'm working on, I got to a situation which a `Table` instance has a column of a `decimal128(6, 5)` data type. I'd like to convert that into a `float` data type. I tried the following: (see [this](https://arrow.apache.org/docs/python/api/datatypes.html#type-checking) & [this](https://arrow.apache.org/docs/python/pandas.html#nullable-types) for reference) ```python import pandas as pd import pyarrow as pa def converter(data_type): if pa.types.is_decimal(data_type): return pd.Float64Dtype() return None table = ... # contains a decimal column df = table.to_pandas(types_mapper=converter) ``` But when I tried it I got the following error: `TypeError: Expected array of Float64 type, got decimal128(6, 5) instead` Can anyone please suggest a better way to cast such column into a float data type? Thanks in advance! -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
