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import csv |
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import random |
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import pandas as pd |
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def read_train_data(): |
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rows = [] |
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with open( |
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"Gungor_2018_VictorianAuthorAttribution_data-train.csv", "r", encoding="latin1" |
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) as f: |
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csv_reader = csv.reader(f) |
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header = next(csv_reader) |
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for row in csv_reader: |
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rows.append({"text": row[0], "author": int(row[1]) - 1}) |
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return rows |
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def read_test_data(): |
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with open("test_labels.txt", "r") as f: |
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labels = [label.strip() for label in f.readlines()] |
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with open( |
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"Gungor_2018_VictorianAuthorAttribution_data.csv", "r", encoding="latin1" |
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) as f: |
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lines = f.readlines() |
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texts = [line.strip() for line in lines[1:]] |
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rows = [] |
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for text, label in zip(texts, labels): |
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rows.append({"text": text, "author": int(label) - 1}) |
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return rows |
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def run(): |
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train_rows = read_train_data() |
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test_rows = read_test_data() |
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all_rows = train_rows + test_rows |
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random.shuffle(all_rows) |
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pd.DataFrame(train_rows).to_parquet("train.parquet") |
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pd.DataFrame(test_rows).to_parquet("test.parquet") |
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pd.DataFrame(all_rows).to_parquet("complete.parquet") |
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if __name__ == "__main__": |
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run() |
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