Comments (5)
@akshowhini This is easy to do when the number and name of columns are the same, which doesn't happen very often. A robust way to do this would be to group multiple tables from different pages by partially matching the column names (based on some threshold) and concatenate them.
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The way I'm Doing this in my personal project is with
pd.concat(self.list_of_dfs)
The only problem I see is when tables have different column-names. So I just Rename them
names = self.list_of_dfs[0].columns.tolist() for df in self.list_of_dfs: df.columns = names
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This issue is low priority as there's no general way to merge tables spanning multiple pages across millions of different types of table structures.
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@vinayak-mehta I would like to contribute to this. However, I would like to know your expectations on the scenarios and how to handle those.
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Has this thread seen any progress. I was looking through the same issues haven't got any permanent solution to merge tables spanning multiple pages.
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