60 lines
2.1 KiB
Python
60 lines
2.1 KiB
Python
import os
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import pandas as pd
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from sqlalchemy import create_engine
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from dotenv import load_dotenv
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# Load environment variables from .env file
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load_dotenv()
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# Get DB connection parameters from environment
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DB_USER = os.getenv('DB_USER')
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DB_PASSWORD = os.getenv('DB_PASSWORD')
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DB_HOST = os.getenv('DB_HOST')
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DB_PORT = os.getenv('DB_PORT')
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DB_NAME = os.getenv('DB_NAME')
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# Create a connection string
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connection_string = f"mariadb+pymysql://{DB_USER}:{DB_PASSWORD}@{DB_HOST}:{DB_PORT}/{DB_NAME}"
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# Create the SQLAlchemy engine
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engine = create_engine(connection_string)
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# Define a list of file paths and corresponding table names
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file_paths = [
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('sec_data/2015q1/sub.txt', 'sub'),
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('sec_data/2015q1/tag.txt', 'tag'),
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('sec_data/2015q1/num.txt', 'num'),
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('sec_data/2015q1/pre.txt', 'pre')
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]
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# Loop through each file and write the data to the database
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for i, (file_path, table_name) in enumerate(file_paths):
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print(f"\nAnalyzing {file_path} (File {i+1}/4)...")
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# Read the data into a Pandas DataFrame
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df = pd.read_csv(file_path, sep='\t')
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# Inspect the DataFrame
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print("First rows of the DataFrame:")
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print(df.head(10))
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# Get the DataFrame Information
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print("\nSummary Information:")
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print(df.info())
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# Check if there are any missing values in the DataFrame
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missing_values = df.isnull().sum()
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print("\nMissing Values:")
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print(missing_values)
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# If the file being processed is 'num.txt', fix the `coreg` column
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if table_name == 'num':
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df['coreg'] = df['coreg'].fillna('nocoreg')
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print("\nUpdated 'coreg' column (NaN values replaced with 'nocoreg'):")
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print(df[['coreg']].head(10)) # Display first 10 rows of the 'coreg' column for verification
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# Write the DataFrame to the corresponding table in the MariaDB database
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df.to_sql(table_name, con=engine, if_exists='append', index=False)
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print(f"\nData from {file_path} written to the '{table_name}' table in the database.")
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print("\nAll files have been processed and written to the database.") |