91 lines
2.7 KiB
Python
91 lines
2.7 KiB
Python
import os
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import pandas as pd
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STATIC_PATH = './Static'
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def dLoader(folder, label_names=None):
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"""
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Load data from Excel files in a specified folder.
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Args:
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folder (str): Name of the folder containing Excel files.
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label_names (list): Optional list of label names. If not provided, file names will be used.
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Returns:
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pandas.DataFrame: Loaded and processed data.
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"""
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folder_path = os.path.join(STATIC_PATH, folder)
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file_names = [f for f in os.listdir(folder_path) if f.endswith('.xlsx')]
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if not label_names:
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label_names = [f.split('.')[0] for f in file_names]
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max_row_length = get_max_row_len(folder_path, file_names)
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all_features = []
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for i, file_name in enumerate(file_names):
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features = load_xlsx(os.path.join(folder_path, file_name), label_names[i], max_row_length)
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all_features.append(features)
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return pd.concat(all_features, ignore_index=True)
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def load_xlsx(file_name, label_name, max_row_length, fill_rule='mean'):
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"""
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Load and process data from a single Excel file.
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Args:
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file_name (str): Path to the Excel file.
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label_name (str): Label for the data in this file.
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max_row_length (int): Maximum number of rows to consider.
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fill_rule (str): Rule for filling missing values ('min', 'mean', or None).
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Returns:
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pandas.DataFrame: Processed data from the Excel file.
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"""
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df = pd.read_excel(file_name)
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features = df.iloc[0:, 1::2]
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features.dropna(inplace=True)
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features.reset_index(drop=True, inplace=True)
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features = features.T
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features = features.apply(lambda row: fill_to_len(row, max_row_length, fill_rule), axis=1)
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features['label'] = label_name
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features.columns = [f'feature{i+1}' for i in range(max_row_length)] + ['label']
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return features
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def fill_to_len(row, length=1000, rule=None):
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"""
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Fill a row to a specified length.
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Args:
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row (pandas.Series): Row to fill.
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length (int): Desired length of the row.
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rule (str): Rule for filling ('min', 'mean', or None).
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Returns:
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pandas.Series: Filled row.
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"""
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fill_value = 0
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if rule == 'min':
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fill_value = row.min()
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elif rule == 'mean':
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fill_value = row.mean()
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fill_values = pd.Series([fill_value] * (length - len(row)))
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return pd.concat([row, fill_values], ignore_index=True)
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def get_max_row_len(folder, filenames):
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"""
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Get the maximum row length across all Excel files in a folder.
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Args:
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folder (str): Path to the folder containing Excel files.
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filenames (list): List of Excel file names.
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Returns:
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int: Maximum row length.
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"""
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return max(pd.read_excel(os.path.join(folder, filename)).shape[0] for filename in filenames) |