Merge remote-tracking branch 'origin/master'
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f2f21bc120
7
Jenkinsfile
vendored
7
Jenkinsfile
vendored
@ -26,7 +26,8 @@ pipeline{
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steps{
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withEnv(["CUTOFF=${params.CUTOFF}"]) {
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sh "chmod 777 ./script.sh"
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sh "./script.sh"
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}
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}}
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stage('Archive artifacts'){
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@ -34,7 +35,7 @@ pipeline{
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archiveArtifacts 'test.csv'
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archiveArtifacts 'dev.csv'
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archiveArtifacts 'train.csv'
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}
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}
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}
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}
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}}
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33
script2.py
33
script2.py
@ -21,15 +21,26 @@ movies_data.dropna(inplace=True)
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# Remove not interesting columns
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drop_columns = ["title_id", "certificate", "title", "plot"]
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drop_columns2 = [
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"original_title",
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"countries",
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"genres",
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"director",
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"cast",
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"release_date",
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]
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drop_columns = drop_columns + drop_columns2
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movies_data.drop(labels=drop_columns, axis=1, inplace=True)
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# Normalize data, lowercase str
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for column_name in ["original_title", "countries", "genres", "director", "cast"]:
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movies_data[column_name] = (
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movies_data[column_name]
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.str.translate(str.maketrans("", "", string.punctuation))
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.str.lower()
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)
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# for column_name in ["original_title", "countries", "genres", "director", "cast"]:
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# movies_data[column_name] = (
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# movies_data[column_name]
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# .str.translate(str.maketrans("", "", string.punctuation))
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# .str.lower()
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# )
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# Remove ',' from votes number and change type to int
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movies_data["votes_number"] = (movies_data["votes_number"].str.replace(",", "")).astype(
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@ -42,17 +53,9 @@ movies_data[["votes_number", "year", "runtime"]] = scaler.fit_transform(
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movies_data[["votes_number", "year", "runtime"]]
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)
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drop_columns = [
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"original_title",
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"countries",
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"genres",
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"director",
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"cast",
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"release_date",
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]
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movies_data.drop(labels=drop_columns, axis=1, inplace=True)
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#movies_data.drop(labels=drop_columns, axis=1, inplace=True)
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# Split set to train/dev/test 6:2:2 ratio and save to .csv file
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train, dev = train_test_split(movies_data, train_size=0.6, test_size=0.4, shuffle=True)
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