Reputation: 1
I encounter TypeError: 'DataFrame' object is not callable with the following. Anyone can help? Thanks.
%cd -
dataset_orig = df_data_1(protected_attribute_names=['Gender'],
privileged_classes=['Male'],
features_to_drop=[])
dataset_orig_train, dataset_orig_test = dataset_orig.split([0.7], shuffle=True)
privileged_groups = [{'Gender': 1}]
unprivileged_groups = [{'Gender': 0}]
/home/wsuser/work
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TypeError Traceback (most recent call last)
<ipython-input-59-8c624cfec261> in <module>
5 # consider in this evaluation
6 privileged_classes=['Male'], # male is considered privileged
----> 7 features_to_drop=[]) # ignore all other attributes
8
9 dataset_orig_train, dataset_orig_test = dataset_orig.split([0.7], shuffle=True)
TypeError: 'DataFrame' object is not callable
Upvotes: 0
Views: 967
Reputation: 4629
It appears that df_data_1
is your dataset dataframe, right? If it is, you would need to update your script to convert it to StandardDataset
:
from aif360.datasets import StandardDataset
dataset_orig = StandardDataset(df_data_1,
protected_attribute_names=['Gender'],
privileged_classes=['Male'],
features_to_drop=[],
favorable_classes=[1] # Update this with label values which are considered favorable in your dataset
)
I am not sure how your dataset looks like, but you can adapt the complete reproducible example here to do this process for your dataset.
Upvotes: 0