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@ -37,7 +37,7 @@ pipeline {
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sh 'chmod u+x download.sh'
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withEnv(["KAGGLE_USERNAME=${params.KAGGLE_USERNAME}","KAGGLE_KEY=${params.KAGGLE_KEY}", "CUTOFF=${params.CUTOFF}"]) {
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sh 'echo KAGGLE_USERNAME: $KAGGLE_USERNAME'
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sh './download.sh'
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//sh './download.sh'
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sh "python ium-data.py"
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}
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archiveArtifacts artifacts: 'd_test.csv, d_dev.csv, d_train.csv'
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@ -1,6 +1,6 @@
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#!/usr/bin/env python3
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#from kaggle.api.kaggle_api_extended import KaggleApi
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from kaggle.api.kaggle_api_extended import KaggleApi
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import pandas as pd
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import matplotlib.pyplot as plt
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from sklearn.model_selection import train_test_split
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@ -28,9 +28,9 @@ def column_stat(analyzed_set, column_name):
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# Pobieranie danych
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#api = KaggleApi()
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#api.authenticate()
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#api.dataset_download_files('arushchillar/disneyland-reviews', unzip=True)
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api = KaggleApi()
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api.authenticate()
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api.dataset_download_files('arushchillar/disneyland-reviews', unzip=True)
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disney = pd.read_csv('DisneylandReviews.csv', encoding='latin-1')
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# Nie zauważyłem w pliku żadnych artefaktów, które trzeba wyczyścić
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