In [2]:
import pandas as pd
# Column names based on the dataset description
columns = ['Label', 'Alcohol', 'Malic_Acid', 'Ash', 'Alkalinity_of_Ash', 'Magnesium',
'Total_phenoids', 'Flavanoids', 'Nonflavanoid_Phenols', 'Proanthocyanins',
'Color_Intensity', 'Hue', '0D280/0315ofdiluted_wines', 'Proline']
# Load the wine dataset from UCI repository
url = "https://archive.ics.uci.edu/ml/machine-learning-databases/wine/wine.data"
wine_data = pd.read_csv(url, header=None, names=columns)
# Save as CSV and Excel locally
csv_file_path = 'wine_data.csv'
excel_file_path = 'wine_data.xlsx'
# Save as CSV
wine_data.to_csv(csv_file_path, index=False)
# Save as Excel
wine_data.to_excel(excel_file_path, index=False)
(csv_file_path, excel_file_path)
Out[2]:
('wine_data.csv', 'wine_data.xlsx')
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