ml-pipeline
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1. ml_pipeline
1.1. src.ml_pipeline
1.1.1. src.ml_pipeline.ML_Feature
1.1.2. src.ml_pipeline.ML_Features
1.1.3. src.ml_pipeline.ML_Input_File
1.1.4. src.ml_pipeline.ML_Input_Files
1.1.5. src.ml_pipeline.ML_Model
1.1.6. src.ml_pipeline.ML_Models
1.1.7. src.ml_pipeline.ML_ParentClass
1.1.8. src.ml_pipeline.ML_params
1.1.9. src.ml_pipeline.ML_support
1.1.9.1. src.ml_pipeline.ML_support.create_unique_Path
1.1.9.2. src.ml_pipeline.ML_support.export_df
1.1.9.3. src.ml_pipeline.ML_support.export_df_to_Path
1.1.9.4. src.ml_pipeline.ML_support.gen_from_template
1.1.9.5. src.ml_pipeline.ML_support.generate_sample_df
1.1.9.6. src.ml_pipeline.ML_support.get_df_from_dict
1.1.9.7. src.ml_pipeline.ML_support.get_dict_from_df
1.1.9.8. src.ml_pipeline.ML_support.import_df
1.1.9.9. src.ml_pipeline.ML_support.import_df_from_Path
1.1.9.10. src.ml_pipeline.ML_support.join_nickname_and_col
1.1.9.11. src.ml_pipeline.ML_support.shap_importance
1.1.9.12. src.ml_pipeline.ML_support.split_ncol
1.1.10. src.ml_pipeline.Templates
ml-pipeline
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1.1.9.
src.ml_pipeline.ML_support
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1.1.9.6.
src.ml_pipeline.ML_support.get_df_from_dict
1.1.9.6.
src.ml_pipeline.ML_support.get_df_from_dict
¶
get_df_from_dict
(
dictionary
:
dict
,
key_col
:
str
=
'Key'
,
val_col
:
str
=
'Value'
)
→
pandas.core.frame.DataFrame
[source]
¶
Given a dictionary, turn it into a pandas DF with KEY and VALUE columns