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Spark and Jupyter notebooks to analyse data from the Norwegian Prescription Database

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examples
examples
 
 
html_notebooks_thesis
html_notebooks_thesis
 
 
src
src
 
 
.gitignore
.gitignore
 
 
20190219_general_statistics.ipynb
20190219_general_statistics.ipynb
 
 
LICENSE
LICENSE
 
 
README.md
README.md
 
 
example_load_datasets.ipynb
example_load_datasets.ipynb
 
 
example_spylon_kernel_usage.ipynb
example_spylon_kernel_usage.ipynb
 
 
init_repo.sh
init_repo.sh
 
 
preprocessing_NPR.ipynb
preprocessing_NPR.ipynb
 
 
preprocessing_hospitalization.ipynb
preprocessing_hospitalization.ipynb
 
 
preprocessing_hospitalization_ICD_ICPC.ipynb
preprocessing_hospitalization_ICD_ICPC.ipynb
 
 
preprocessing_prescription.ipynb
preprocessing_prescription.ipynb
 
 
requirements.txt
requirements.txt
 
 
tsk_20181001_analysis_prescriptions_and_patients_distr_by_birthyear.ipynb
tsk_20181001_analysis_prescriptions_and_patients_distr_by_birthyear.ipynb
 
 
tsk_20181102_analysis_hospitalization_compare_drug_consumption_of_live_and_dead_patients_logplot.ipynb
tsk_20181102_analysis_hospitalization_compare_drug_consumption_of_live_and_dead_patients_logplot.ipynb
 
 
tsk_20181106_analysis_hospitalization_bucketing_relative_to_death_time.ipynb
tsk_20181106_analysis_hospitalization_bucketing_relative_to_death_time.ipynb
 
 
tsk_20181119_analyses_prescriptions_count_by_week.ipynb
tsk_20181119_analyses_prescriptions_count_by_week.ipynb
 
 
tsk_20181121_population_distribution.ipynb
tsk_20181121_population_distribution.ipynb
 
 
tsk_20181208_hosp_count_no_id.ipynb
tsk_20181208_hosp_count_no_id.ipynb
 
 
tsk_20181213_hosp_aggregates.ipynb
tsk_20181213_hosp_aggregates.ipynb
 
 
tsk_20190122_preprocessing_onehot_ATC_4level.ipynb
tsk_20190122_preprocessing_onehot_ATC_4level.ipynb
 
 
tsk_20190211_experiment1-p1-patient-selection.ipynb
tsk_20190211_experiment1-p1-patient-selection.ipynb
 
 
tsk_20190219_experiment1-p2-preprocessing_modeling_assessment.ipynb
tsk_20190219_experiment1-p2-preprocessing_modeling_assessment.ipynb
 
 
tsk_20190219_experiment1-p3-unfinished.ipynb
tsk_20190219_experiment1-p3-unfinished.ipynb
 
 
tsk_20190313_experiment2-p1-patient-selection.ipynb
tsk_20190313_experiment2-p1-patient-selection.ipynb
 
 
tsk_20190318_experiment2-p2-preprocessing+bootstrap_logistic_regression.ipynb
tsk_20190318_experiment2-p2-preprocessing+bootstrap_logistic_regression.ipynb
 
 
tsk_20190318_experiment2-p3-interpret_results.ipynb
tsk_20190318_experiment2-p3-interpret_results.ipynb
 
 
tsk_20190527_experiment2_bootstrap_time_graph.ipynb
tsk_20190527_experiment2_bootstrap_time_graph.ipynb
 
 

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Prescription analyses

This repository contains a set of jupyter notebooks with analyses of prescription data

Requirements

Spark related

  • Java 8
  • Scala
  • Apache Spark

Python/Jupyter

  • Python 3.6.7 (the version used)
  • Ipython
  • Jupyter notebook
  • Scikit learn (sklearn)
  • Numpy
  • Pandas
  • Spylon-kernel (Spark+Scala/Pyspark kernel for jupyter)

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Spark and Jupyter notebooks to analyse data from the Norwegian Prescription Database

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