30 lines
798 B
Python
30 lines
798 B
Python
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import subprocess
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import pandas as pd
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import numpy as np
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import subprocess
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rc = subprocess.call("./process_data.sh")
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# import kaggle
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# kaggle.api.authenticate()
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# kaggle.api.dataset_download_files('shivamb/real-or-fake-fake-jobposting-prediction', path='fake_job_postings.csv', unzip=True)
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data=pd.read_csv('fake_job_postings.csv')
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data = data.replace(np.nan, '', regex=True)
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print("="*20)
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print('Ilość wierszy w zbiorze: ',len(data))
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print("="*10, ' data["department"].value_counts() ', 10*'=')
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print(data["department"].value_counts())
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print("="*10, ' data.median() ', 10*'=')
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print(data.median())
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print("="*10, ' data.describe(include="all") ', 10*'=')
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print(data.describe(include='all'))
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data.describe(include="all").to_csv(r'stats.txt', header=None, index=None, sep='\t', mode='a')
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