Improve performance of pandas arrow extractor
MEMBER
Looks like this change
```
pa_table[pa_table.column_names[0]].to_pandas(types_mapper=pandas_types_mapper)
```
doesn't return a Series with the correct type.
This is related to https://issues.apache.org/jira/browse/ARROW-9664

Since the types_mapper isn't taken into account, the ArrayXD types are not converted to the correct pandas extension dtype
2021-06-18T14:46:18Z
https://github.com/huggingface/datasets/pull/2519#issuecomment-864091492
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2021-06-18T14:46:18Z
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@lhoestq I think I found a workaround... 😉 
2021-06-18T16:20:06Z
https://github.com/huggingface/datasets/pull/2519#issuecomment-864147802
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MEMBER
For some reason the benchmarks are not run Oo
2021-06-21T09:04:54Z
https://github.com/huggingface/datasets/pull/2519#issuecomment-864865384
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2021-06-21T09:04:54Z
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MEMBER
Anyway, merging.
We'll see on master how much speed ups we got
2021-06-21T09:06:00Z
https://github.com/huggingface/datasets/pull/2519#issuecomment-864866247
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While reviewing PR #2505, I noticed that pandas arrow extractor could be refactored to be faster.