Send like a pretty standard optimization scenario. I'd recommend:

1. Find the bottleneck. Here if your suspect it's pandas dataframe vs lists, 
run a timing analysis using each.
2. Remove the bottleneck

On March 17, 2019 6:52:23 PM CDT, "Guillermo Yáñez Feliú" 
<gyanezfe...@gmail.com> wrote:
> 
>
>Hello,
>
>
>I’m working in a project that consists in converting a local postgresql
>
>database (that uses sqlalchemy as the ORM) into a web application, in
>which 
>I upload excel sheets, read them, do some small cleaning and then
>upload 
>selected data into a postgresql database using Django’s ORM. The idea
>is to 
>have the data in a server instead of in every user’s machine. 
>
>Everything is ok but data loading is taking too long since, I think, I
>am 
>using panda’s dataframes to easily structure, read and save the data.
>In 
>the local version of the library, I used lists and was way faster.
>
>
>I don’t if it’s related to Sqlalchemy, Django, lists or dataframes. Any
>
>suggestions on how to read spreadsheets data and upload it into a 
>postgresql database using Django?
>
>
>Thanks a lot.
>
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