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Keep non-feature columns when encoding feature matrix #111

merged 5 commits into from Mar 14, 2018


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rwedge commented Mar 14, 2018

#78 added the option of including non-feature columns with the calculated feature matrix, but encode_features was not including them when creating an encoded feature matrix. This PR fixes encode_features so it includes non-feature columns in the encoded feature matrix.


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codecov-io commented Mar 14, 2018

Codecov Report

Merging #111 into master will increase coverage by 0.05%.
The diff coverage is 100%.

Impacted file tree graph

@@            Coverage Diff            @@
##           master    #111      +/-   ##
+ Coverage   88.24%   88.3%   +0.05%     
  Files          73      73              
  Lines        7412    7447      +35     
+ Hits         6541    6576      +35     
  Misses        871     871
Impacted Files Coverage Δ
...ests/computational_backend/ 100% <100%> (ø) ⬆️
featuretools/synthesis/ 94.54% <100%> (+0.92%) ⬆️

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@@ -65,6 +65,8 @@ def encode_features(feature_matrix, features, top_n=10, include_unknown=True,
X = feature_matrix.copy()
encoded = []
feature_names = [f.get_name() for f in features]
extra_columns = [col for col in X.columns if col not in feature_names]

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kmax12 Mar 14, 2018


to make this safer, can we add in a check that all the features you pass in are columns in the feature matrix? with this change, we might silence issues where the feature matrix and features don't match


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kmax12 commented Mar 14, 2018

looks good to me. merging in.

@kmax12 kmax12 merged commit 959069d into master Mar 14, 2018

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@rwedge rwedge referenced this pull request Mar 21, 2018


Release v0.1.19 #114

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