update

Dockerfile

@@ -9,20 +9,15 @@ RUN pip3 install pandas
 RUN pip3 install matplotlib
 RUN pip3 install sklearn
 RUN apt-get install unzip
-#RUN mkdir root/.kaggle
-#RUN touch root/.kaggle/kaggle.json
-#RUN echo "{\"username\":\"maciejczajka\",\"key\":\"d8f044ad2b96d32372e22f9054c02bb1\"}" >> root/.kaggle/kaggle.json
-#RUN chmod 666 root/.kaggle
-#RUN chmod 666 root/.kaggle/kaggle.json
 
-#ENV KAGGLE_USERNAME=maciejczajka
-#ENV KAGGLE_KEY=d8f044ad2b96d32372e22f9054c02bb1
 ENV CUTOFF=1000
 ARG KAGGLE_USERNAME
 ARG KAGGLE_KEY
 ENV KAGGLE_USERNAME=${KAGGLE_USERNAME}
 ENV KAGGLE_KEY=${KAGGLE_KEY}
 
+RUN mkdir /dane
+
 WORKDIR /app
 
 COPY download.sh .

Zajecia_2/main.py

@@ -152,7 +152,7 @@ def dataset_information(games):
 # os.system("unzip top-video-games-19952021-metacritic.zip")
 
 # wczytanie danych
-games=pd.read_csv('/app/all_games1.csv')
+games=pd.read_csv('/dane/all_games1.csv')
 
 # usunięcie 5 wyników "Stadia"
 delete_stadia(games)

download.sh

@@ -8,7 +8,7 @@ dataset_operation() {
     head -n $len2 all_games.csv.shuf > all_games.csv.test
     head -n $len3 all_games.csv.shuf | tail -n $len2 > all_games.csv.dev
     tail -n +$len4 all_games.csv.shuf > all_games.csv.train
-    cp all_games.csv.shuf /app/all_games1.csv
+    cp all_games.csv /dane/all_games.csv
     wc -l all_games.csv.*
 }