Docker zadanie 2

Dockerfile

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+FROM ubuntu:latest
+RUN apt-get update -y
+RUN apt-get install -y python3 python3-pip
+
+RUN python3 -m pip install --user kaggle
+RUN pip install --user pandas
+RUN pip install --user scikit-learn
+
+WORKDIR app
+
+ARG CUTOFF
+ENV CUTOFF=${CUTOFF}
+
+COPY main_docker.py ./
+COPY heart_2020_cleaned.csv ./
+
+
+CMD ["python3", "./main_docker.py"]

main_docker.py

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+import pandas as pd
+from sklearn.model_selection import train_test_split
+import os
+
+dataset = pd.read_csv("heart_2020_cleaned.csv")
+print(dataset.describe(include='all'))
+dataset = dataset.dropna()
+
+print(dataset.describe(include='all'))
+
+dataset_train, dataset_test = train_test_split(dataset, test_size=.2, train_size=.8, random_state=1)
+
+print(dataset_train.describe(include='all'))
+
+print("Wielkości:")
+
+print("Zbiór uczący:", dataset_train.shape[0])
+print("Zbiór testowy:", dataset_test.shape[0])
+print("Łącznie: ", dataset.shape[0])
+
+print(dataset["GenHealth"].value_counts())
+print(dataset_train["GenHealth"].value_counts())
+print("Średnia BMI -łącznie: ", dataset["BMI"].mean())
+print("Odchylenie standardowe BMI - uczący:", dataset_train["BMI"].std())
+print("Odchylenie standardowe BMI - łącznie:", dataset["BMI"].std())
+
+print("Mediana BMI:", dataset_test["BMI"].median())
+
+max_bmi = dataset_train["BMI"].max()
+
+print(max_bmi)
+dataset_train["BMI"] = dataset_train["BMI"].apply(lambda x: x/max_bmi)
+dataset_test["BMI"] = dataset_test["BMI"].apply(lambda x: x/max_bmi)
+print(dataset_train["AgeCategory"].value_counts())
+print(dataset_train["BMI"])