| From: | Adrian Klaver <adrian(dot)klaver(at)aklaver(dot)com> |
|---|---|
| To: | Shaozhong SHI <shishaozhong(at)gmail(dot)com> |
| Cc: | pgsql-general <pgsql-general(at)lists(dot)postgresql(dot)org> |
| Subject: | Re: Testing of a fast method to bulk insert a Pandas DataFrame into Postgres |
| Date: | 2021-10-04 17:30:22 |
| Message-ID: | c00dacdc-b40b-29bf-85cd-149e0d0a9608@aklaver.com |
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| Lists: | pgsql-general pgsql-sql |
On 10/4/21 10:28 AM, Adrian Klaver wrote:
> On 10/4/21 10:10 AM, Shaozhong SHI wrote:
>> Hello, Adrian Klaver,
>> What is the robust way to upgrade Pandas?
>
> Carefully.
>
> The most recent version is 1.3.3, which is approximately 5 versions
> ahead of where you are now. The big jump is when Pandas went from 0.25
> to 1.0. See docs here:
>
> https://pandas.pydata.org/docs/whatsnew/v1.0.0.html?highlight=upgrade
>
> So the process should be 0.24 -> 0.25, verify, 0.25 -> 1.0, verify. Then
> on to wherever you want to end up a step at a time.
>
> Before each step spend time here:
>
> https://pandas.pydata.org/docs/whatsnew/
>
> to see what the gotcha's are.
Should have added:
If you are not already working in a virtualenv it would be a good idea
to do the above in one or more.
>
>
>> Regards,
>> David
>>
>
>
>
--
Adrian Klaver
adrian(dot)klaver(at)aklaver(dot)com
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