About the dataset

The dataset contains the patient records collected from a hospital in Greenland. The "Survived_1_year" column is a target variable which has binary entries (0 or 1).

Survived_1_year == 0, implies that the patient did not survive after 1 year of treatment
Survived_1_year == 1, implies that the patient survived after 1 year of treatment

To load the dataset in your jupyter notebook, use the below command:

import pandas as pd
pharma_data = pd.read_csv('https://raw.githubusercontent.com/dphi-official/Datasets/master/pharma_data/Training_set_begs.csv')

Data Description:

ID_Patient_Care_Situation: Care situation of a patient during treatment
Diagnosed_Condition: The diagnosed condition of the patient
ID_Patient: Patient identifier number
Treatment_with_drugs: Class of drugs used during treatment
Survived_1_year: If the patient survived after one year (0 means did not survive; 1 means survived)
Patient_Age: Age of the patient
Patient_Body_Mass_Index: A calculated value based on the patient’s weight, height, etc.
Patient_Smoker: If the patient was a smoker or not
Patient_Rural_Urban: If the patient stayed in Rural or Urban part of the country
Previous_Condition: Condition of the patient before the start of the treatment ( This variable is splitted into 8 columns - A, B, C, D, E, F, Z and Number_of_prev_cond. A, B, C, D, E, F and Z are the previous conditions of the patient. Suppose for one patient, if the entry in column A is 1, it means that the previous condition of the patient was A. If the patient didn't have that condition, it is 0 and same for other conditions. If a patient has previous condition as A and C , columns A and C will have entries as 1 and 1 respectively while the other column B, D, E, F, Z will have entries 0, 0, 0, 0, 0 respectively. The column Number_of_prev_cond will have entry as 2 i.e. 1 + 0 + 1 + 0 + 0 + 0 + 0 + 0 = 2 in this case. )

Feel free to google 'Diagnose' and 'Body Mass Index' if you don't know about these terms.

To load the test dataset in your jupyter notebook, use the below command:


test_data = pd.read_csv('https://raw.githubusercontent.com/dphi-official/Datasets/master/pharma_data/Testing_set_begs.csv')

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