3
votes
Accepted
Spatial Join Pandas Dataframes of Bounding Boxes (cross match)
Edited after comments in other answers:
Generally speaking, I would reframe this as a linear sum assignment problem.
This can be solved using a modified version of Munkres algorithm allowing a cost ...
- 449
2
votes
Spatial Join Pandas Dataframes of Bounding Boxes (cross match)
TL;DR: I would focus on a good measure first (described below, but IntOvUn is fine too) and then use KD-Tree in Scipy to speed up the computation if needed: https://docs.scipy.org/doc/scipy/reference/...
- 156
2
votes
Spatial Join Pandas Dataframes of Bounding Boxes (cross match)
One option is a brute-force approach.
Write a custom function that compares a single input box to a single template box and determines if they meet the criteria or not.
Then loop through the template ...
- 19.4k
1
vote
Understanding correlation - Machine Learning
Unfortunately, things are not as simple.
About Correlation
For some simple models (especially linear / logistic regression), the correlation between feature and target variable is a good indicator ...
- 523
1
vote
Accepted
Group rows partially [Python] [Pandas]
You can do this by making use of shift to create different groups based on consecutive values of the states column, after which ...
- 6,817
1
vote
Replacing rows of dataframe with rows of another dataframe that have the same index
pandas.DataFrame.update is what you are looking for. This modifies in place the provided DataFrame using non-NA values from another DataFrame. Use overwrite=True if ...
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