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As this discussion shows, there are use cases where we want specific loadings indexed by (row, col) pairs to be set to specific values. Unlike using .loc, indexing a group of columns and a group of rows of the same length would return only the values at corresponding positions.
Feature Description
This shouldn't be difficult...
Alternative Solutions
In numpy or pytorch or any numerical packages this is the default.
Additional Context
No response
The text was updated successfully, but these errors were encountered:
pls look at prior discussions this is not a very common or useful operation in pandas
Hi Jeff, Thanks for the pointers. I checked the previous discussions and I think there are some people requesting this functionality of lookup (as shown in #40140) and the main reason for deprecation is more on the performance side. My feature request arises more out of the need to set values for specific loadings indexed by (row, col) pairs rather than just looking them up, which I agree can be easily done by the current factorize functionality. But setting values is a more delicate thing and would require mapping back and forth the columns & indices if doing manually by first transforming to NumPy then transform back. Having a Pandas-native functionality wrapping around this pipeline of operations would be extremely helpful.
Feature Type
Adding new functionality to pandas
Changing existing functionality in pandas
Removing existing functionality in pandas
Problem Description
As this discussion shows, there are use cases where we want specific loadings indexed by (row, col) pairs to be set to specific values. Unlike using
.loc
, indexing a group of columns and a group of rows of the same length would return only the values at corresponding positions.Feature Description
This shouldn't be difficult...
Alternative Solutions
In
numpy
orpytorch
or any numerical packages this is the default.Additional Context
No response
The text was updated successfully, but these errors were encountered: