Problem Statement
Hello,
As of today, you can convert easily a string. But what I want to do, as a contribution to Amphi ETL is to interface it with Pandas.
Proposed Solution
Several use case, either to or form toon.
pandas_to_toon would be like an an aggregation, given a pandas string (the table represents a dataframe). Example :
| Customer |
Customer Country |
Customer question |
| 1 |
FR |
How do you do? |
| 2 |
UK |
How old are you? |
| 2 |
UK |
Are you hungry? |
could give, by row (here, I choose only Customer and question)
| Customer |
Customer Country |
Customer question |
Generated Toon |
| 1 |
FR |
How do you do? |
Customer: 1 "Customer Question": How do you do? |
| 2 |
UK |
How old are you? |
Customer: 2 "Customer Question": How old are you? |
| 2 |
UK |
Are you hungry? |
Customer: 2 "Customer Question": Are you hungry? |
But I can also have
| Customer |
Customer Question |
Generated Toon |
| 1 |
FR |
Customer: 1 "Customer Question": How do you do? |
| 2 |
UK |
Customer: 2 "Customer Question": mydataframe[3]{Customer,"Customer Question"}: 2,How old are you? 2,"Are you hungry? " |
or even
| Generated Toon |
[3]{Customer,"Customer Question"}: 1,How do you do? 2,How old are you? 2,"Are you hungry? " |
Alternatives Considered
None
SPEC Compliance
No response
Additional Context
I would like to use it on Amphi-ETL in addition with an LLM
Problem Statement
Hello,
As of today, you can convert easily a string. But what I want to do, as a contribution to Amphi ETL is to interface it with Pandas.
Proposed Solution
Several use case, either to or form toon.
pandas_to_toon would be like an an aggregation, given a pandas string (the table represents a dataframe). Example :
could give, by row (here, I choose only Customer and question)
"Customer Question": How do you do?
"Customer Question": How old are you?
"Customer Question": Are you hungry?
But I can also have
"Customer Question": How do you do?
"Customer Question": mydataframe[3]{Customer,"Customer Question"}:
2,How old are you?
2,"Are you hungry? "
or even
1,How do you do?
2,How old are you?
2,"Are you hungry? "
Alternatives Considered
None
SPEC Compliance
No response
Additional Context
I would like to use it on Amphi-ETL in addition with an LLM